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Sample records for binding mode prediction

  1. Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design.

    Science.gov (United States)

    Grebner, Christoph; Iegre, Jessica; Ulander, Johan; Edman, Karl; Hogner, Anders; Tyrchan, Christian

    2016-04-25

    Computer-aided drug design plays an important role in medicinal chemistry to obtain insights into molecular mechanisms and to prioritize design strategies. Although significant improvement has been made in structure based design, it still remains a key challenge to accurately model and predict induced fit mechanisms. Most of the current available techniques either do not provide sufficient protein conformational sampling or are too computationally demanding to fit an industrial setting. The current study presents a systematic and exhaustive investigation of predicting binding modes for a range of systems using PELE (Protein Energy Landscape Exploration), an efficient and fast protein-ligand sampling algorithm. The systems analyzed (cytochrome P, kinase, protease, and nuclear hormone receptor) exhibit different complexities of ligand induced fit mechanisms and protein dynamics. The results are compared with results from classical molecular dynamics simulations and (induced fit) docking. This study shows that ligand induced side chain rearrangements and smaller to medium backbone movements are captured well in PELE. Large secondary structure rearrangements, however, remain challenging for all employed techniques. Relevant binding modes (ligand heavy atom RMSD PELE method within a few hours of simulation, positioning PELE as a tool applicable for rapid drug design cycles.

  2. Binding mode and free energy prediction of fisetin/β-cyclodextrin inclusion complexes

    Directory of Open Access Journals (Sweden)

    Bodee Nutho

    2014-11-01

    Full Text Available In the present study, our aim is to investigate the preferential binding mode and encapsulation of the flavonoid fisetin in the nano-pore of β-cyclodextrin (β-CD at the molecular level using various theoretical approaches: molecular docking, molecular dynamics (MD simulations and binding free energy calculations. The molecular docking suggested four possible fisetin orientations in the cavity through its chromone or phenyl ring with two different geometries of fisetin due to the rotatable bond between the two rings. From the multiple MD results, the phenyl ring of fisetin favours its inclusion into the β-CD cavity, whilst less binding or even unbinding preference was observed in the complexes where the larger chromone ring is located in the cavity. All MM- and QM-PBSA/GBSA free energy predictions supported the more stable fisetin/β-CD complex of the bound phenyl ring. Van der Waals interaction is the key force in forming the complexes. In addition, the quantum mechanics calculations with M06-2X/6-31G(d,p clearly showed that both solvation effect and BSSE correction cannot be neglected for the energy determination of the chosen system.

  3. Prediction of consensus binding mode geometries for related chemical series of positive allosteric modulators of adenosine and muscarinic acetylcholine receptors.

    Science.gov (United States)

    Sakkal, Leon A; Rajkowski, Kyle Z; Armen, Roger S

    2017-06-05

    Following insights from recent crystal structures of the muscarinic acetylcholine receptor, binding modes of Positive Allosteric Modulators (PAMs) were predicted under the assumption that PAMs should bind to the extracellular surface of the active state. A series of well-characterized PAMs for adenosine (A 1 R, A 2A R, A 3 R) and muscarinic acetylcholine (M 1 R, M 5 R) receptors were modeled using both rigid and flexible receptor CHARMM-based molecular docking. Studies of adenosine receptors investigated the molecular basis of the probe-dependence of PAM activity by modeling in complex with specific agonist radioligands. Consensus binding modes map common pharmacophore features of several chemical series to specific binding interactions. These models provide a rationalization of how PAM binding slows agonist radioligand dissociation kinetics. M 1 R PAMs were predicted to bind in the analogous M 2 R PAM LY2119620 binding site. The M 5 R NAM (ML-375) was predicted to bind in the PAM (ML-380) binding site with a unique induced-fit receptor conformation. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  4. Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

    Science.gov (United States)

    Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

    2017-08-01

    The growing number of protein-ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein-ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein-ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein-ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein-ligand complex structures available to improve predictions on binding.

  5. Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR.

    Science.gov (United States)

    Westermaier, Yvonne; Ruiz-Carmona, Sergio; Theret, Isabelle; Perron-Sierra, Françoise; Poissonnet, Guillaume; Dacquet, Catherine; Boutin, Jean A; Ducrot, Pierre; Barril, Xavier

    2017-08-01

    The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

  6. Binding Mode Prediction of 5-Hydroxytryptamine 2C Receptor Ligands by Homology Modeling and Molecular Docking Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, Asif; Nagarajan, Shanthi; Doddareddy, Munikumar Reddy; Cho, Yong Seo; Pae, Ae Nim [Korea Institute of Science and Technology, Seoul (Korea, Republic of)

    2011-06-15

    Serotonin or 5-hydroxytryptamine subtype 2C (5-HT{sub 2C}) receptor belongs to class A amine subfamily of Gprotein- coupled receptor (GPCR) super family and its ligands has therapeutic promise as anti-depressant and -obesity agents. So far, bovine rhodopsin from class A opsin subfamily was the mostly used X-ray crystal template to model this receptor. Here, we explained homology model using beta 2 adrenergic receptor (β2AR), the model was energetically minimized and validated by flexible ligand docking with known agonists and antagonists. In the active site Asp134, Ser138 of transmembrane 3 (TM3), Arg195 of extracellular loop 2 (ECL2) and Tyr358 of TM7 were found as important residues to interact with agonists. In addition to these, V208 of ECL2 and N351 of TM7 was found to interact with antagonists. Several conserved residues including Trp324, Phe327 and Phe328 were also found to contribute hydrophobic interaction. The predicted ligand binding mode is in good agreement with published mutagenesis and homology model data. This new template derived homology model can be useful for further virtual screening based lead identification.

  7. Prediction of the binding mode and resistance profile for a dual-target pyrrolyl diketo acid scaffold against HIV-1 integrase and reverse-transcriptase-associated ribonuclease H.

    Science.gov (United States)

    Yang, Fengyuan; Zheng, Guoxun; Fu, Tingting; Li, Xiaofeng; Tu, Gao; Li, Ying Hong; Yao, Xiaojun; Xue, Weiwei; Zhu, Feng

    2018-06-27

    The rapid emergence of drug-resistant variants is one of the most common causes of highly active antiretroviral therapeutic (HAART) failure in patients infected with HIV-1. Compared with the existing HAART, the recently developed pyrrolyl diketo acid scaffold targeting both HIV-1 integrase (IN) and reverse transcriptase-associated ribonuclease H (RNase H) is an efficient approach to counteract the failure of anti-HIV treatment due to drug resistance. However, the binding mode and potential resistance profile of these inhibitors with important mechanistic principles remain poorly understood. To address this issue, an integrated computational method was employed to investigate the binding mode of inhibitor JMC6F with HIV-1 IN and RNase H. By using per-residue binding free energy decomposition analysis, the following residues: Asp64, Thr66, Leu68, Asp116, Tyr143, Gln148 and Glu152 in IN, Asp443, Glu478, Trp536, Lys541 and Asp549 in RNase H were identified as key residues for JMC6F binding. And then computational alanine scanning was carried to further verify the key residues. Moreover, the resistance profile of the currently known major mutations in HIV-1 IN and 2 mutations in RNase H against JMC6F was predicted by in silico mutagenesis studies. The results demonstrated that only three mutations in HIV-1 IN (Y143C, Q148R and N155H) and two mutations in HIV-1 RNase H (Y501R and Y501W) resulted in a reduction of JMC6F potency, thus indicating their potential role in providing resistance to JMC6F. These data provided important insights into the binding mode and resistance profile of the inhibitors with a pyrrolyl diketo acid scaffold in HIV-1 IN and RNase H, which would be helpful for the development of more effective dual HIV-1 IN and RNase H inhibitors.

  8. Multiple binding modes of ibuprofen in human serum albumin identified by absolute binding free energy calculations

    KAUST Repository

    Evoli, Stefania

    2016-11-10

    Human serum albumin possesses multiple binding sites and transports a wide range of ligands that include the anti-inflammatory drug ibuprofen. A complete map of the binding sites of ibuprofen in albumin is difficult to obtain in traditional experiments, because of the structural adaptability of this protein in accommodating small ligands. In this work, we provide a set of predictions covering the geometry, affinity of binding and protonation state for the pharmaceutically most active form (S-isomer) of ibuprofen to albumin, by using absolute binding free energy calculations in combination with classical molecular dynamics (MD) simulations and molecular docking. The most favorable binding modes correctly reproduce several experimentally identified binding locations, which include the two Sudlow\\'s drug sites (DS2 and DS1) and the fatty acid binding sites 6 and 2 (FA6 and FA2). Previously unknown details of the binding conformations were revealed for some of them, and formerly undetected binding modes were found in other protein sites. The calculated binding affinities exhibit trends which seem to agree with the available experimental data, and drastically degrade when the ligand is modeled in a protonated (neutral) state, indicating that ibuprofen associates with albumin preferentially in its charged form. These findings provide a detailed description of the binding of ibuprofen, help to explain a wide range of results reported in the literature in the last decades, and demonstrate the possibility of using simulation methods to predict ligand binding to albumin.

  9. Effect of cobratoxin binding on the normal mode vibration within acetylcholine binding protein.

    Science.gov (United States)

    Bertaccini, Edward J; Lindahl, Erik; Sixma, Titia; Trudell, James R

    2008-04-01

    Recent crystal structures of the acetylcholine binding protein (AChBP) have revealed surprisingly small structural alterations upon ligand binding. Here we investigate the extent to which ligand binding may affect receptor dynamics. AChBP is a homologue of the extracellular component of ligand-gated ion channels (LGICs). We have previously used an elastic network normal-mode analysis to propose a gating mechanism for the LGICs and to suggest the effects of various ligands on such motions. However, the difficulties with elastic network methods lie in their inability to account for the modest effects of a small ligand or mutation on ion channel motion. Here, we report the successful application of an elastic network normal mode technique to measure the effects of large ligand binding on receptor dynamics. The present calculations demonstrate a clear alteration in the native symmetric motions of a protein due to the presence of large protein cobratoxin ligands. In particular, normal-mode analysis revealed that cobratoxin binding to this protein significantly dampened the axially symmetric motion of the AChBP that may be associated with channel gating in the full nAChR. The results suggest that alterations in receptor dynamics could be a general feature of ligand binding.

  10. Multiple binding modes of ibuprofen in human serum albumin identified by absolute binding free energy calculations

    KAUST Repository

    Evoli, Stefania; Mobley, David L.; Guzzi, Rita; Rizzuti, Bruno

    2016-01-01

    experiments, because of the structural adaptability of this protein in accommodating small ligands. In this work, we provide a set of predictions covering the geometry, affinity of binding and protonation state for the pharmaceutically most active form (S

  11. Binding of ethidium to the nucleosome core particle. 2. Internal and external binding modes

    International Nuclear Information System (INIS)

    McMurray, C.T.; Small, E.W.; van Holde, K.E.

    1991-01-01

    The authors have previously reported that the binding of ethidium bromide to the nucleosome core particle results in a stepwise dissociation of the structure which involves the initial release of one copy each of H2A and H2B. In this report, they have examined the absorbance and fluorescence properties of intercalated and outside bound forms of ethidium bromide. From these properties, they have measured the extent of external, electrostatic binding of the dye versus internal, intercalation binding to the core particle, free from contribution by linker DNA. They have established that dissociation is induced by the intercalation mode of binding to DNA within the core particle DNA, and not by binding to the histones or by nonintercalative binding to DNA. The covalent binding of [ 3 H]-8-azidoethidium to the core particle clearly shows that < 1.0 adduct is formed per histone octamer over a wide range of input ratios. Simultaneously, analyses of steady-state fluorescence enhancement and fluorescence lifetime data from bound ethidium complexes demonstrate extensive intercalation binding. Combined analyses from steady-state fluorescence intensity with equilibrium dialysis or fluorescence lifetime data revealed that dissociation began when ∼14 ethidium molecules are bound by intercalation to each core particle and < 1.0 nonintercalated ion pair was formed per core particle

  12. Knowledge-based Fragment Binding Prediction

    Science.gov (United States)

    Tang, Grace W.; Altman, Russ B.

    2014-01-01

    Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

  13. CW EPR parameters reveal cytochrome P450 ligand binding modes.

    Science.gov (United States)

    Lockart, Molly M; Rodriguez, Carlo A; Atkins, William M; Bowman, Michael K

    2018-06-01

    Cytochrome P450 (CYP) monoxygenses utilize heme cofactors to catalyze oxidation reactions. They play a critical role in metabolism of many classes of drugs, are an attractive target for drug development, and mediate several prominent drug interactions. Many substrates and inhibitors alter the spin state of the ferric heme by displacing the heme's axial water ligand in the resting enzyme to yield a five-coordinate iron complex, or they replace the axial water to yield a nitrogen-ligated six-coordinate iron complex, which are traditionally assigned by UV-vis spectroscopy. However, crystal structures and recent pulsed electron paramagnetic resonance (EPR) studies find a few cases where molecules hydrogen bond to the axial water. The water-bridged drug-H 2 O-heme has UV-vis spectra similar to nitrogen-ligated, six-coordinate complexes, but are closer to "reverse type I" complexes described in older liteature. Here, pulsed and continuous wave (CW) EPR demonstrate that water-bridged complexes are remarkably common among a range of nitrogenous drugs or drug fragments that bind to CYP3A4 or CYP2C9. Principal component analysis reveals a distinct clustering of CW EPR spectral parameters for water-bridged complexes. CW EPR reveals heterogeneous mixtures of ligated states, including multiple directly-coordinated complexes and water-bridged complexes. These results suggest that water-bridged complexes are under-represented in CYP structural databases and can have energies similar to other ligation modes. The data indicates that water-bridged binding modes can be identified and distinguished from directly-coordinated binding by CW EPR. Copyright © 2018 Elsevier Inc. All rights reserved.

  14. Nonspecific DNA Binding and Bending by HUαβ: Interfaces of the Three Binding Modes Characterized by Salt Dependent Thermodynamics

    Science.gov (United States)

    Koh, Junseock; Shkel, Irina; Saecker, Ruth M.; Record, M. Thomas

    2011-01-01

    Previous ITC and FRET studies demonstrated that Escherichia coli HUαβ binds nonspecifically to duplex DNA in three different binding modes: a tighter-binding 34 bp mode which interacts with DNA in large (>34 bp) gaps between bound proteins, reversibly bending it 140° and thereby increasing its flexibility, and two weaker, modestly cooperative small-site-size modes (10 bp, 6 bp) useful for filling gaps between bound proteins shorter than 34 bp. Here we use ITC to determine the thermodynamics of these binding modes as a function of salt concentration, and deduce that DNA in the 34 bp mode is bent around but not wrapped on the body of HU, in contrast to specific binding of IHF. Analyses of binding isotherms (8, 15, 34 bp DNA) and initial binding heats (34, 38, 160 bp DNA) reveal that all three modes have similar log-log salt concentration derivatives of the binding constants (Ski) even though their binding site sizes differ greatly; most probable values of Ski on 34 bp or larger DNA are − 7.5 ± 0.5. From the similarity of Ski values, we conclude that binding interfaces of all three modes involve the same region of the arms and saddle of HU. All modes are entropy-driven, as expected for nonspecific binding driven by the polyelectrolyte effect. The bent-DNA 34 bp mode is most endothermic, presumably because of the cost of HU-induced DNA bending, while the 6 bp mode is modestly exothermic at all salt concentrations examined. Structural models consistent with the observed Ski values are proposed. PMID:21513716

  15. Prediction of binding modes between protein L-isoaspartyl (D-aspartyl) O-methyltransferase and peptide substrates including isomerized aspartic acid residues using in silico analytic methods for the substrate screening.

    Science.gov (United States)

    Oda, Akifumi; Noji, Ikuhiko; Fukuyoshi, Shuichi; Takahashi, Ohgi

    2015-12-10

    Because the aspartic acid (Asp) residues in proteins are occasionally isomerized in the human body, not only l-α-Asp but also l-β-Asp, D-α-Asp and D-β-Asp are found in human proteins. In these isomerized aspartic acids, the proportion of D-β-Asp is the largest and the proportions of l-β-Asp and D-α-Asp found in human proteins are comparatively small. To explain the proportions of aspartic acid isomers, the possibility of an enzyme able to repair l-β-Asp and D-α-Asp is frequently considered. The protein L-isoaspartyl (D-aspartyl) O-methyltransferase (PIMT) is considered one of the possible repair enzymes for l-β-Asp and D-α-Asp. Human PIMT is an enzyme that recognizes both l-β-Asp and D-α-Asp, and catalyzes the methylation of their side chains. In this study, the binding modes between PIMT and peptide substrates containing l-β-Asp or D-α-Asp residues were investigated using computational protein-ligand docking and molecular dynamics simulations. The results indicate that carboxyl groups of both l-β-Asp and D-α-Asp were recognized in similar modes by PIMT and that the C-terminal regions of substrate peptides were located in similar positions on PIMT for both the l-β-Asp and D-α-Asp peptides. In contrast, for peptides containing l-α-Asp or D-β-Asp residues, which are not substrates of PIMT, the computationally constructed binding modes between PIMT and peptides greatly differed from those between PIMT and substrates. In the nonsubstrate peptides, not inter- but intra-molecular hydrogen bonds were observed, and the conformations of peptides were more rigid than those of substrates. Thus, the in silico analytical methods were able to distinguish substrates from nonsubstrates and the computational methods are expected to complement experimental analytical methods. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Fluoroquinolone-gyrase-DNA complexes: two modes of drug binding.

    Science.gov (United States)

    Mustaev, Arkady; Malik, Muhammad; Zhao, Xilin; Kurepina, Natalia; Luan, Gan; Oppegard, Lisa M; Hiasa, Hiroshi; Marks, Kevin R; Kerns, Robert J; Berger, James M; Drlica, Karl

    2014-05-02

    DNA gyrase and topoisomerase IV control bacterial DNA topology by breaking DNA, passing duplex DNA through the break, and then resealing the break. This process is subject to reversible corruption by fluoroquinolones, antibacterials that form drug-enzyme-DNA complexes in which the DNA is broken. The complexes, called cleaved complexes because of the presence of DNA breaks, have been crystallized and found to have the fluoroquinolone C-7 ring system facing the GyrB/ParE subunits. As expected from x-ray crystallography, a thiol-reactive, C-7-modified chloroacetyl derivative of ciprofloxacin (Cip-AcCl) formed cross-linked cleaved complexes with mutant GyrB-Cys(466) gyrase as evidenced by resistance to reversal by both EDTA and thermal treatments. Surprisingly, cross-linking was also readily seen with complexes formed by mutant GyrA-G81C gyrase, thereby revealing a novel drug-gyrase interaction not observed in crystal structures. The cross-link between fluoroquinolone and GyrA-G81C gyrase correlated with exceptional bacteriostatic activity for Cip-AcCl with a quinolone-resistant GyrA-G81C variant of Escherichia coli and its Mycobacterium smegmatis equivalent (GyrA-G89C). Cip-AcCl-mediated, irreversible inhibition of DNA replication provided further evidence for a GyrA-drug cross-link. Collectively these data establish the existence of interactions between the fluoroquinolone C-7 ring and both GyrA and GyrB. Because the GyrA-Gly(81) and GyrB-Glu(466) residues are far apart (17 Å) in the crystal structure of cleaved complexes, two modes of quinolone binding must exist. The presence of two binding modes raises the possibility that multiple quinolone-enzyme-DNA complexes can form, a discovery that opens new avenues for exploring and exploiting relationships between drug structure and activity with type II DNA topoisomerases.

  17. Molecular Dynamics Insights into Polyamine-DNA Binding Modes: Implications for Cross-Link Selectivity.

    Science.gov (United States)

    Bignon, Emmanuelle; Chan, Chen-Hui; Morell, Christophe; Monari, Antonio; Ravanat, Jean-Luc; Dumont, Elise

    2017-09-18

    Biogenic polyamines, which play a role in DNA condensation and stabilization, are ubiquitous and are found at millimolar concentration in the nucleus of eukaryotic cells. The interaction modes of three polyamines-putrescine (Put), spermine (Spm), and spermidine (Spd)-with a self-complementary 16 base pair (bp) duplex, are investigated by all-atom explicit-solvent molecular dynamics. The length of the amine aliphatic chain leads to a change of the interaction mode from minor groove binding to major groove binding. Through all-atom dynamics, noncovalent interactions that stabilize the polyamine-DNA complex and prefigure the reactivity, leading to the low-barrier formation of deleterious DNA-polyamine cross-links, after one-electron oxidation of a guanine nucleobase, are unraveled. The binding strength is quantified from the obtained trajectories by molecular mechanics generalized Born surface area post-processing (MM-GBSA). The values of binding free energies provide the same affinity order, Putpredictions. The binding modes and carbon-nitrogen distances along the series of polyamines illustrate the selectivity towards deleterious DNA-polyamine cross-link formation through the extraction of average approaching distances between the C8 atom of guanines and the ammonium group. These results imply that the formation of DNA-polyamine cross-links involves deprotonation of the guanine radical cation to attack the polyamines, which must be positively charged to lie in the vicinity of the B-helix. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Predicting the Diversity of Foreign Entry Modes

    DEFF Research Database (Denmark)

    Hashai, Niron; Geisler Asmussen, Christian; Benito, Gabriel

    2007-01-01

    diversity across value chain activities and host markets. Analyzing a sample of Israeli based firms we show that larger firms exhibit a higher degree of entry mode diversity both across value chain activities and across host markets. Higher levels of knowledge intensity are also associated with more......This paper expands entry mode literature by referring to multiple modes exerted in different value chain activities within and across host markets, rather than to a single entry mode at the host market level. Scale of operations and knowledge intensity are argued to affect firms' entry mode...... diversity in firms' entry modes across both dimensions....

  19. A novel hypothesis for the binding mode of HERG channel blockers

    International Nuclear Information System (INIS)

    Choe, Han; Nah, Kwang Hoon; Lee, Soo Nam; Lee, Han Sam; Lee, Hui Sun; Jo, Su Hyun; Leem, Chae Hun; Jang, Yeon Jin

    2006-01-01

    We present a new docking model for HERG channel blockade. Our new model suggests three key interactions such that (1) a protonated nitrogen of the channel blocker forms a hydrogen bond with the carbonyl oxygen of HERG residue T623; (2) an aromatic moiety of the channel blocker makes a π-π interaction with the aromatic ring of HERG residue Y652; and (3) a hydrophobic group of the channel blocker forms a hydrophobic interaction with the benzene ring of HERG residue F656. The previous model assumes two interactions such that (1) a protonated nitrogen of the channel blocker forms a cation-π interaction with the aromatic ring of HERG residue Y652; and (2) a hydrophobic group of the channel blocker forms a hydrophobic interaction with the benzene ring of HERG residue F656. To test these models, we classified 69 known HERG channel blockers into eight binding types based on their plausible binding modes, and further categorized them into two groups based on the number of interactions our model would predict with the HERG channel (two or three). We then compared the pIC 5 value distributions between these two groups. If the old hypothesis is correct, the distributions should not differ between the two groups (i.e., both groups show only two binding interactions). If our novel hypothesis is correct, the distributions should differ between Groups 1 and 2. Consistent with our hypothesis, the two groups differed with regard to pIC 5 , and the group having more predicted interactions with the HERG channel had a higher mean pIC 5 value. Although additional work will be required to further validate our hypothesis, this improved understanding of the HERG channel blocker binding mode may help promote the development of in silico predictions methods for identifying potential HERG channel blockers

  20. Machine Learning Reveals a Non-Canonical Mode of Peptide Binding to MHC class II Molecules

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Jurtz, Vanessa Isabell; Kaever, Thomas

    2017-01-01

    binding motif with a non-canonical binding core of length different from nine. This previously undescribed mode of peptide binding to MHCII molecules gives a more complete picture of peptide presentation by MHCII and allows us to model more accurately this event. This article is protected by copyright...

  1. Predicting DNA-binding proteins and binding residues by complex structure prediction and application to human proteome.

    Directory of Open Access Journals (Sweden)

    Huiying Zhao

    Full Text Available As more and more protein sequences are uncovered from increasingly inexpensive sequencing techniques, an urgent task is to find their functions. This work presents a highly reliable computational technique for predicting DNA-binding function at the level of protein-DNA complex structures, rather than low-resolution two-state prediction of DNA-binding as most existing techniques do. The method first predicts protein-DNA complex structure by utilizing the template-based structure prediction technique HHblits, followed by binding affinity prediction based on a knowledge-based energy function (Distance-scaled finite ideal-gas reference state for protein-DNA interactions. A leave-one-out cross validation of the method based on 179 DNA-binding and 3797 non-binding protein domains achieves a Matthews correlation coefficient (MCC of 0.77 with high precision (94% and high sensitivity (65%. We further found 51% sensitivity for 82 newly determined structures of DNA-binding proteins and 56% sensitivity for the human proteome. In addition, the method provides a reasonably accurate prediction of DNA-binding residues in proteins based on predicted DNA-binding complex structures. Its application to human proteome leads to more than 300 novel DNA-binding proteins; some of these predicted structures were validated by known structures of homologous proteins in APO forms. The method [SPOT-Seq (DNA] is available as an on-line server at http://sparks-lab.org.

  2. Binding modes and functional surface of anti-mammalian scorpion α-toxins to sodium channels.

    Science.gov (United States)

    Chen, Rong; Chung, Shin-Ho

    2012-10-02

    Scorpion α-toxins bind to the voltage-sensing domains of voltage-gated sodium (Na(V)) channels and interfere with the inactivation mechanisms. The functional surface of α-toxins has been shown to contain an NC-domain consisting of the five-residue turn (positions 8-12) and the C-terminus (positions 56-64) and a core-domain centered on the residue 18. The NC- and core-domains are interconnected by the linker-domain (positions 8-18). Here with atomistic molecular dynamics simulations, we examine the binding modes between two α-toxins, the anti-mammalian AahII and the anti-insect LqhαIT, and the voltage-sensing domain of rat Na(V)1.2, a subtype of Na(V) channels expressed in nerve cells. Both toxins are docked to the extracellular side of the voltage-sensing domain of Na(V)1.2 using molecular dynamics simulations, with the linker-domain assumed to wedge into the binding pocket. Several salt bridges and hydrophobic clusters are observed to form between the NC- and core-domains of the toxins and Na(V)1.2 and stabilize the toxin-channel complexes. The binding modes predicted are consistent with available mutagenesis data and can readily explain the relative affinities of AahII and LqhαIT for Na(V)1.2. The dissociation constants for the two toxin-channel complexes are derived, which compare favorably with experiment. Our models demonstrate that the functional surface of anti-mammalian scorpion α-toxins is centered on the linker-domain, similar to that of β-toxins.

  3. The binding cavity of mouse major urinary protein is optimised for a variety of ligand binding modes

    Energy Technology Data Exchange (ETDEWEB)

    Pertinhez, Thelma A.; Ferrari, Elena; Casali, Emanuela [Department of Experimental Medicine, University of Parma, Via Volturno, 39, 43100 Parma (Italy); Patel, Jital A. [Department of Chemistry, University of Oxford, Inorganic Chemistry Laboratory, South Parks Road, Oxford OX1 3QR (United Kingdom); Spisni, Alberto, E-mail: alberto.spisni@unipr.it [Department of Experimental Medicine, University of Parma, Via Volturno, 39, 43100 Parma (Italy); Smith, Lorna J., E-mail: lorna.smith@chem.ox.ac.uk [Department of Chemistry, University of Oxford, Inorganic Chemistry Laboratory, South Parks Road, Oxford OX1 3QR (United Kingdom)

    2009-12-25

    {sup 15}N and {sup 1}HN chemical shift data and {sup 15}N relaxation studies have been used to characterise the binding of N-phenyl-naphthylamine (NPN) to mouse major urinary protein (MUP). NPN binds in the {beta}-barrel cavity of MUP, hydrogen bonding to Tyr120 and making extensive non-bonded contacts with hydrophobic side chains. In contrast to the natural pheromone 2-sec-butyl-4,5-dihydrothiazole, NPN binding gives no change to the overall mobility of the protein backbone of MUP. Comparison with 11 different ligands that bind to MUP shows a range of binding modes involving 16 different residues in the {beta}-barrel cavity. These finding justify why MUP is able to adapt to allow for many successful binding partners.

  4. CaMELS: In silico prediction of calmodulin binding proteins and their binding sites.

    Science.gov (United States)

    Abbasi, Wajid Arshad; Asif, Amina; Andleeb, Saiqa; Minhas, Fayyaz Ul Amir Afsar

    2017-09-01

    Due to Ca 2+ -dependent binding and the sequence diversity of Calmodulin (CaM) binding proteins, identifying CaM interactions and binding sites in the wet-lab is tedious and costly. Therefore, computational methods for this purpose are crucial to the design of such wet-lab experiments. We present an algorithm suite called CaMELS (CalModulin intEraction Learning System) for predicting proteins that interact with CaM as well as their binding sites using sequence information alone. CaMELS offers state of the art accuracy for both CaM interaction and binding site prediction and can aid biologists in studying CaM binding proteins. For CaM interaction prediction, CaMELS uses protein sequence features coupled with a large-margin classifier. CaMELS models the binding site prediction problem using multiple instance machine learning with a custom optimization algorithm which allows more effective learning over imprecisely annotated CaM-binding sites during training. CaMELS has been extensively benchmarked using a variety of data sets, mutagenic studies, proteome-wide Gene Ontology enrichment analyses and protein structures. Our experiments indicate that CaMELS outperforms simple motif-based search and other existing methods for interaction and binding site prediction. We have also found that the whole sequence of a protein, rather than just its binding site, is important for predicting its interaction with CaM. Using the machine learning model in CaMELS, we have identified important features of protein sequences for CaM interaction prediction as well as characteristic amino acid sub-sequences and their relative position for identifying CaM binding sites. Python code for training and evaluating CaMELS together with a webserver implementation is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#camels. © 2017 Wiley Periodicals, Inc.

  5. Prediction of failure modes for concrete nuclear-containment buildings

    International Nuclear Information System (INIS)

    Butler, T.A.

    1982-01-01

    The failure modes and associated failure pressures for two common generic types of PWR containments are predicted. One building type is a lightly reinforced, posttensioned structure represented by the Zion nuclear reactor containment. The other is the normally reinforced Indian Point containment. Two-dimensional models of the buildings developed using the finite element method are used to predict the failure modes and failure pressures. Predicted failure modes for both containments involve loss of structural integrity at the intersection of the cylindrical sidewall with the base slab

  6. An in silico analysis of the binding modes and binding affinities of small molecule modulators of PDZ-peptide interactions.

    Directory of Open Access Journals (Sweden)

    Garima Tiwari

    Full Text Available Inhibitors of PDZ-peptide interactions have important implications in a variety of biological processes including treatment of cancer and Parkinson's disease. Even though experimental studies have reported characterization of peptidomimetic inhibitors of PDZ-peptide interactions, the binding modes for most of them have not been characterized by structural studies. In this study we have attempted to understand the structural basis of the small molecule-PDZ interactions by in silico analysis of the binding modes and binding affinities of a set of 38 small molecules with known K(i or K(d values for PDZ2 and PDZ3 domains of PSD-95 protein. These two PDZ domains show differential selectivity for these compounds despite having a high degree of sequence similarity and almost identical peptide binding pockets. Optimum binding modes for these ligands for PDZ2 and PDZ3 domains were identified by using a novel combination of semi-flexible docking and explicit solvent molecular dynamics (MD simulations. Analysis of the binding modes revealed most of the peptidomimectic ligands which had high K(i or K(d moved away from the peptide binding pocket, while ligands with high binding affinities remained in the peptide binding pocket. The differential specificities of the PDZ2 and PDZ3 domains primarily arise from differences in the conformation of the loop connecting βB and βC strands, because this loop interacts with the N-terminal chemical moieties of the ligands. We have also computed the MM/PBSA binding free energy values for these 38 compounds with both the PDZ domains from multiple 5 ns MD trajectories on each complex i.e. a total of 228 MD trajectories of 5 ns length each. Interestingly, computational binding free energies show good agreement with experimental binding free energies with a correlation coefficient of approximately 0.6. Thus our study demonstrates that combined use of docking and MD simulations can help in identification of potent inhibitors

  7. Cytotoxic protein from the mushroom Coprinus comatus possesses a unique mode for glycan binding and specificity

    Science.gov (United States)

    Zhang, Peilan; Yang, Guang; Xia, Changqing; Polston, Jane E.; Li, Gengnan; Li, Shiwu; Lin, Zhao; Yang, Li-jun; Bruner, Steven D.

    2017-01-01

    Glycans possess significant chemical diversity; glycan binding proteins (GBPs) recognize specific glycans to translate their structures to functions in various physiological and pathological processes. Therefore, the discovery and characterization of novel GBPs and characterization of glycan–GBP interactions are significant to provide potential targets for therapeutic intervention of many diseases. Here, we report the biochemical, functional, and structural characterization of a 130-amino-acid protein, Y3, from the mushroom Coprinus comatus. Biochemical studies of recombinant Y3 from a yeast expression system demonstrated the protein is a unique GBP. Additionally, we show that Y3 exhibits selective and potent cytotoxicity toward human T-cell leukemia Jurkat cells compared with a panel of cancer cell lines via inducing caspase-dependent apoptosis. Screening of a glycan array demonstrated GalNAcβ1–4(Fucα1–3)GlcNAc (LDNF) as a specific Y3-binding ligand. To provide a structural basis for function, the crystal structure was solved to a resolution of 1.2 Å, revealing a single-domain αβα-sandwich motif. Two monomers were dimerized to form a large 10-stranded, antiparallel β-sheet flanked by α-helices on each side, representing a unique oligomerization mode among GBPs. A large glycan binding pocket extends into the dimeric interface, and docking of LDNF identified key residues for glycan interactions. Disruption of residues predicted to be involved in LDNF/Y3 interactions resulted in the significant loss of binding to Jurkat T-cells and severely impaired their cytotoxicity. Collectively, these results demonstrate Y3 to be a GBP with selective cytotoxicity toward human T-cell leukemia cells and indicate its potential use in cancer diagnosis and treatment. PMID:28784797

  8. Cytotoxic protein from the mushroom Coprinus comatus possesses a unique mode for glycan binding and specificity.

    Science.gov (United States)

    Zhang, Peilan; Li, Kunhua; Yang, Guang; Xia, Changqing; Polston, Jane E; Li, Gengnan; Li, Shiwu; Lin, Zhao; Yang, Li-Jun; Bruner, Steven D; Ding, Yousong

    2017-08-22

    Glycans possess significant chemical diversity; glycan binding proteins (GBPs) recognize specific glycans to translate their structures to functions in various physiological and pathological processes. Therefore, the discovery and characterization of novel GBPs and characterization of glycan-GBP interactions are significant to provide potential targets for therapeutic intervention of many diseases. Here, we report the biochemical, functional, and structural characterization of a 130-amino-acid protein, Y3, from the mushroom Coprinus comatus Biochemical studies of recombinant Y3 from a yeast expression system demonstrated the protein is a unique GBP. Additionally, we show that Y3 exhibits selective and potent cytotoxicity toward human T-cell leukemia Jurkat cells compared with a panel of cancer cell lines via inducing caspase-dependent apoptosis. Screening of a glycan array demonstrated GalNAcβ1-4(Fucα1-3)GlcNAc (LDNF) as a specific Y3-binding ligand. To provide a structural basis for function, the crystal structure was solved to a resolution of 1.2 Å, revealing a single-domain αβα-sandwich motif. Two monomers were dimerized to form a large 10-stranded, antiparallel β-sheet flanked by α-helices on each side, representing a unique oligomerization mode among GBPs. A large glycan binding pocket extends into the dimeric interface, and docking of LDNF identified key residues for glycan interactions. Disruption of residues predicted to be involved in LDNF/Y3 interactions resulted in the significant loss of binding to Jurkat T-cells and severely impaired their cytotoxicity. Collectively, these results demonstrate Y3 to be a GBP with selective cytotoxicity toward human T-cell leukemia cells and indicate its potential use in cancer diagnosis and treatment.

  9. Structural insights into Cydia pomonella pheromone binding protein 2 mediated prediction of potentially active semiochemicals

    Science.gov (United States)

    Tian, Zhen; Liu, Jiyuan; Zhang, Yalin

    2016-03-01

    Given the advantages of behavioral disruption application in pest control and the damage of Cydia pomonella, due progresses have not been made in searching active semiochemicals for codling moth. In this research, 31 candidate semiochemicals were ranked for their binding potential to Cydia pomonella pheromone binding protein 2 (CpomPBP2) by simulated docking, and this sorted result was confirmed by competitive binding assay. This high predicting accuracy of virtual screening led to the construction of a rapid and viable method for semiochemicals searching. By reference to binding mode analyses, hydrogen bond and hydrophobic interaction were suggested to be two key factors in determining ligand affinity, so is the length of molecule chain. So it is concluded that semiochemicals of appropriate chain length with hydroxyl group or carbonyl group at one head tended to be favored by CpomPBP2. Residues involved in binding with each ligand were pointed out as well, which were verified by computational alanine scanning mutagenesis. Progress made in the present study helps establish an efficient method for predicting potentially active compounds and prepares for the application of high-throughput virtual screening in searching semiochemicals by taking insights into binding mode analyses.

  10. Predicting protein-binding RNA nucleotides with consideration of binding partners.

    Science.gov (United States)

    Tuvshinjargal, Narankhuu; Lee, Wook; Park, Byungkyu; Han, Kyungsook

    2015-06-01

    In recent years several computational methods have been developed to predict RNA-binding sites in protein. Most of these methods do not consider interacting partners of a protein, so they predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNAs. Unlike the problem of predicting RNA-binding sites in protein, the problem of predicting protein-binding sites in RNA has received little attention mainly because it is much more difficult and shows a lower accuracy on average. In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence. In an effort to improve the prediction accuracy and usefulness of the previous method, we developed a new method that uses both RNA and protein sequence data. In this study, we identified effective features of RNA and protein molecules and developed a new support vector machine (SVM) model to predict protein-binding nucleotides from RNA and protein sequence data. The new model that used both protein and RNA sequence data achieved a sensitivity of 86.5%, a specificity of 86.2%, a positive predictive value (PPV) of 72.6%, a negative predictive value (NPV) of 93.8% and Matthews correlation coefficient (MCC) of 0.69 in a 10-fold cross validation; it achieved a sensitivity of 58.8%, a specificity of 87.4%, a PPV of 65.1%, a NPV of 84.2% and MCC of 0.48 in independent testing. For comparative purpose, we built another prediction model that used RNA sequence data alone and ran it on the same dataset. In a 10 fold-cross validation it achieved a sensitivity of 85.7%, a specificity of 80.5%, a PPV of 67.7%, a NPV of 92.2% and MCC of 0.63; in independent testing it achieved a sensitivity of 67.7%, a specificity of 78.8%, a PPV of 57.6%, a NPV of 85.2% and MCC of 0.45. In both cross-validations and independent testing, the new model that used both RNA and protein sequences showed a better performance than the model that used RNA sequence data alone in

  11. Transcription factor binding sites prediction based on modified nucleosomes.

    Directory of Open Access Journals (Sweden)

    Mohammad Talebzadeh

    Full Text Available In computational methods, position weight matrices (PWMs are commonly applied for transcription factor binding site (TFBS prediction. Although these matrices are more accurate than simple consensus sequences to predict actual binding sites, they usually produce a large number of false positive (FP predictions and so are impoverished sources of information. Several studies have employed additional sources of information such as sequence conservation or the vicinity to transcription start sites to distinguish true binding regions from random ones. Recently, the spatial distribution of modified nucleosomes has been shown to be associated with different promoter architectures. These aligned patterns can facilitate DNA accessibility for transcription factors. We hypothesize that using data from these aligned and periodic patterns can improve the performance of binding region prediction. In this study, we propose two effective features, "modified nucleosomes neighboring" and "modified nucleosomes occupancy", to decrease FP in binding site discovery. Based on these features, we designed a logistic regression classifier which estimates the probability of a region as a TFBS. Our model learned each feature based on Sp1 binding sites on Chromosome 1 and was tested on the other chromosomes in human CD4+T cells. In this work, we investigated 21 histone modifications and found that only 8 out of 21 marks are strongly correlated with transcription factor binding regions. To prove that these features are not specific to Sp1, we combined the logistic regression classifier with the PWM, and created a new model to search TFBSs on the genome. We tested the model using transcription factors MAZ, PU.1 and ELF1 and compared the results to those using only the PWM. The results show that our model can predict Transcription factor binding regions more successfully. The relative simplicity of the model and capability of integrating other features make it a superior method

  12. Binding Mode of Insulin Receptor and Agonist Peptide

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Insulin is a protein hormone secreted by pancreatic β cells. One of its main functions is to keep the balance of glucose inside the body by regulating the absorption and metabolism of glucose in the periphery tissue, as well as the production and storage of hepatic glycogen. The insulin receptor is a transmembrane glycoprotein in which two α subunits with a molecular weight of 135 kD and twoβ subunits with a molecular weight of 95 kD are joined by a disulfide bond to form a β-α-α-β structure. The extracellular α subunit, especially, its three domains near the N-terminal are partially responsible for signal transduction or ligand-binding, as indicated by the experiments. The extracellular α subunits are involved in binding the ligands. The experimental results indicate that the three domains of the N-terminal of the α subunits are the main determinative parts of the insulin receptor to bind the insulin or mimetic peptide.We employed the extracellular domain (PDBID: 1IGR) of the insulin-like growth factor-1 receptor (IGF-1 R ) as the template to simulate and optimize the spatial structures of the three domains in the extracellular domain of the insulin receptor, which includes 468 residues. The work was accomplished by making use of the homology program in the Insight Ⅱ package on an Origin3800 server. The docking calculations of the insulin receptor obtained by homology with hexapeptides were carried out by means of the program Affinity. The analysis indicated that there were hydrogen bonding, and electrostatic and hydrophobic effects in the docking complex of the insulin receptor with hexapeptides.Moreover, we described the spatial orientation of a mimetic peptide with agonist activity in the docking complex. We obtained a rough model of binding of DLAPSQ or STIVYS with the insulin receptor, which provides the powerful theoretical support for designing the minimal insulin mimetic peptide with agonist activity, making it possible to develop oral small

  13. Solar g-modes? Comparison of detected asymptotic g-mode frequencies with solar model predictions

    Science.gov (United States)

    Wood, Suzannah Rebecca; Guzik, Joyce Ann; Mussack, Katie; Bradley, Paul A.

    2018-06-01

    After many years of searching for solar gravity modes, Fossat et al. (2017) reported detection of the nearly equally spaced high-order g-modes periods using a 15-year time series of GOLF data from the SOHO spacecraft. Here we report progress towards and challenges associated with calculating and comparing g-mode period predictions for several previously published standard solar models using various abundance mixtures and opacities, as well as the predictions for some non-standard models incorporating early mass loss, and compare with the periods reported by Fossat et al (2017). Additionally, we have a side-by-side comparison of results of different stellar pulsation codes for calculating g-mode predictions. These comparisons will allow for testing of nonstandard physics input that affect the core, including an early more massive Sun and dynamic electron screening.

  14. Predicting nucleic acid binding interfaces from structural models of proteins.

    Science.gov (United States)

    Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

    2012-02-01

    The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

  15. Predicting binding within disordered protein regions to structurally characterised peptide-binding domains.

    Directory of Open Access Journals (Sweden)

    Waqasuddin Khan

    Full Text Available Disordered regions of proteins often bind to structured domains, mediating interactions within and between proteins. However, it is difficult to identify a priori the short disordered regions involved in binding. We set out to determine if docking such peptide regions to peptide binding domains would assist in these predictions.We assembled a redundancy reduced dataset of SLiM (Short Linear Motif containing proteins from the ELM database. We selected 84 sequences which had an associated PDB structures showing the SLiM bound to a protein receptor, where the SLiM was found within a 50 residue region of the protein sequence which was predicted to be disordered. First, we investigated the Vina docking scores of overlapping tripeptides from the 50 residue SLiM containing disordered regions of the protein sequence to the corresponding PDB domain. We found only weak discrimination of docking scores between peptides involved in binding and adjacent non-binding peptides in this context (AUC 0.58.Next, we trained a bidirectional recurrent neural network (BRNN using as input the protein sequence, predicted secondary structure, Vina docking score and predicted disorder score. The results were very promising (AUC 0.72 showing that multiple sources of information can be combined to produce results which are clearly superior to any single source.We conclude that the Vina docking score alone has only modest power to define the location of a peptide within a larger protein region known to contain it. However, combining this information with other knowledge (using machine learning methods clearly improves the identification of peptide binding regions within a protein sequence. This approach combining docking with machine learning is primarily a predictor of binding to peptide-binding sites, and is not intended as a predictor of specificity of binding to particular receptors.

  16. Prediction of GPCR-Ligand Binding Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Sangmin Seo

    2018-01-01

    Full Text Available We propose a novel method that predicts binding of G-protein coupled receptors (GPCRs and ligands. The proposed method uses hub and cycle structures of ligands and amino acid motif sequences of GPCRs, rather than the 3D structure of a receptor or similarity of receptors or ligands. The experimental results show that these new features can be effective in predicting GPCR-ligand binding (average area under the curve [AUC] of 0.944, because they are thought to include hidden properties of good ligand-receptor binding. Using the proposed method, we were able to identify novel ligand-GPCR bindings, some of which are supported by several studies.

  17. A systems biology approach to transcription factor binding site prediction.

    Directory of Open Access Journals (Sweden)

    Xiang Zhou

    2010-03-01

    Full Text Available The elucidation of mammalian transcriptional regulatory networks holds great promise for both basic and translational research and remains one the greatest challenges to systems biology. Recent reverse engineering methods deduce regulatory interactions from large-scale mRNA expression profiles and cross-species conserved regulatory regions in DNA. Technical challenges faced by these methods include distinguishing between direct and indirect interactions, associating transcription regulators with predicted transcription factor binding sites (TFBSs, identifying non-linearly conserved binding sites across species, and providing realistic accuracy estimates.We address these challenges by closely integrating proven methods for regulatory network reverse engineering from mRNA expression data, linearly and non-linearly conserved regulatory region discovery, and TFBS evaluation and discovery. Using an extensive test set of high-likelihood interactions, which we collected in order to provide realistic prediction-accuracy estimates, we show that a careful integration of these methods leads to significant improvements in prediction accuracy. To verify our methods, we biochemically validated TFBS predictions made for both transcription factors (TFs and co-factors; we validated binding site predictions made using a known E2F1 DNA-binding motif on E2F1 predicted promoter targets, known E2F1 and JUND motifs on JUND predicted promoter targets, and a de novo discovered motif for BCL6 on BCL6 predicted promoter targets. Finally, to demonstrate accuracy of prediction using an external dataset, we showed that sites matching predicted motifs for ZNF263 are significantly enriched in recent ZNF263 ChIP-seq data.Using an integrative framework, we were able to address technical challenges faced by state of the art network reverse engineering methods, leading to significant improvement in direct-interaction detection and TFBS-discovery accuracy. We estimated the accuracy

  18. Automated benchmarking of peptide-MHC class I binding predictions

    Science.gov (United States)

    Trolle, Thomas; Metushi, Imir G.; Greenbaum, Jason A.; Kim, Yohan; Sidney, John; Lund, Ole; Sette, Alessandro; Peters, Bjoern; Nielsen, Morten

    2015-01-01

    Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility complex (MHC) class I molecules have been developed over the last decades. However, the multitude of available prediction tools makes it non-trivial for the end-user to select which tool to use for a given task. To provide a solid basis on which to compare different prediction tools, we here describe a framework for the automated benchmarking of peptide-MHC class I binding prediction tools. The framework runs weekly benchmarks on data that are newly entered into the Immune Epitope Database (IEDB), giving the public access to frequent, up-to-date performance evaluations of all participating tools. To overcome potential selection bias in the data included in the IEDB, a strategy was implemented that suggests a set of peptides for which different prediction methods give divergent predictions as to their binding capability. Upon experimental binding validation, these peptides entered the benchmark study. Results: The benchmark has run for 15 weeks and includes evaluation of 44 datasets covering 17 MHC alleles and more than 4000 peptide-MHC binding measurements. Inspection of the results allows the end-user to make educated selections between participating tools. Of the four participating servers, NetMHCpan performed the best, followed by ANN, SMM and finally ARB. Availability and implementation: Up-to-date performance evaluations of each server can be found online at http://tools.iedb.org/auto_bench/mhci/weekly. All prediction tool developers are invited to participate in the benchmark. Sign-up instructions are available at http://tools.iedb.org/auto_bench/mhci/join. Contact: mniel@cbs.dtu.dk or bpeters@liai.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25717196

  19. The structure and binding mode of citrate in the stabilization of gold nanoparticles

    KAUST Repository

    Al-Johani, Hind

    2017-03-27

    Elucidating the binding mode of carboxylate-containing ligands to gold nanoparticles (AuNPs) is crucial to understand their stabilizing role. A detailed picture of the three-dimensional structure and coordination modes of citrate, acetate, succinate and glutarate to AuNPs is obtained by 13C and 23Na solid-state NMR in combination with computational modelling and electron microscopy. The binding between the carboxylates and the AuNP surface is found to occur in three different modes. These three modes are simultaneously present at low citrate to gold ratios, while a monocarboxylate monodentate (1κO1) mode is favoured at high citrate:gold ratios. The surface AuNP atoms are found to be predominantly in the zero oxidation state after citrate coordination, although trace amounts of Auδ+ are observed. 23Na NMR experiments show that Na+ ions are present near the gold surface, indicating that carboxylate binding occurs as a 2e− L-type interaction for each oxygen atom involved. This approach has broad potential to probe the binding of a variety of ligands to metal nanoparticles.

  20. The structure and binding mode of citrate in the stabilization of gold nanoparticles

    KAUST Repository

    Al-Johani, Hind; Abou-Hamad, Edy; Jedidi, Abdesslem; Widdifield, Cory M.; Viger-Gravel, Jasmine; Sangaru, Shiv; Gajan, David; Anjum, Dalaver H.; Ould-Chikh, Samy; Hedhili, Mohamed N.; Gurinov, Andrei; Kelly, Michael J.; El Eter, Mohamad; Cavallo, Luigi; Basset, Jean-Marie; Basset, Jean-Marie

    2017-01-01

    Elucidating the binding mode of carboxylate-containing ligands to gold nanoparticles (AuNPs) is crucial to understand their stabilizing role. A detailed picture of the three-dimensional structure and coordination modes of citrate, acetate, succinate and glutarate to AuNPs is obtained by 13C and 23Na solid-state NMR in combination with computational modelling and electron microscopy. The binding between the carboxylates and the AuNP surface is found to occur in three different modes. These three modes are simultaneously present at low citrate to gold ratios, while a monocarboxylate monodentate (1κO1) mode is favoured at high citrate:gold ratios. The surface AuNP atoms are found to be predominantly in the zero oxidation state after citrate coordination, although trace amounts of Auδ+ are observed. 23Na NMR experiments show that Na+ ions are present near the gold surface, indicating that carboxylate binding occurs as a 2e− L-type interaction for each oxygen atom involved. This approach has broad potential to probe the binding of a variety of ligands to metal nanoparticles.

  1. Distinct ubiquitin binding modes exhibited by SH3 domains: molecular determinants and functional implications.

    Directory of Open Access Journals (Sweden)

    Jose L Ortega Roldan

    Full Text Available SH3 domains constitute a new type of ubiquitin-binding domains. We previously showed that the third SH3 domain (SH3-C of CD2AP binds ubiquitin in an alternative orientation. We have determined the structure of the complex between first CD2AP SH3 domain and ubiquitin and performed a structural and mutational analysis to decipher the determinants of the SH3-C binding mode to ubiquitin. We found that the Phe-to-Tyr mutation in CD2AP and in the homologous CIN85 SH3-C domain does not abrogate ubiquitin binding, in contrast to previous hypothesis and our findings for the first two CD2AP SH3 domains. The similar alternative binding mode of the SH3-C domains of these related adaptor proteins is characterised by a higher affinity to C-terminal extended ubiquitin molecules. We conclude that CD2AP/CIN85 SH3-C domain interaction with ubiquitin constitutes a new ubiquitin-binding mode involved in a different cellular function and thus changes the previously established mechanism of EGF-dependent CD2AP/CIN85 mono-ubiquitination.

  2. Peptide binding predictions for HLA DR, DP and DQ molecules

    DEFF Research Database (Denmark)

    Wang, P.; Sidney, J.; Kim, Y.

    2010-01-01

    a significant gap in knowledge as HLA DP and DQ molecules are presumably equally important, and have only been studied less because they are more difficult to handle experimentally. RESULTS: In this study, we aimed to narrow this gap by providing a large scale dataset of over 17,000 HLA-peptide binding...... affinities for a set of 11 HLA DP and DQ alleles. We also expanded our dataset for HLA DR alleles resulting in a total of 40,000 MHC class II binding affinities covering 26 allelic variants. Utilizing this dataset, we generated prediction tools utilizing several machine learning algorithms and evaluated...... include all training data for maximum performance. 4) The recently developed NN-align prediction method significantly outperformed all other algorithms, including a naïve consensus based on all prediction methods. A new consensus method dropping the comparably weak ARB prediction method could outperform...

  3. The Binding Mode of the Sonic Hedgehog Inhibitor Robotnikinin, a Combined Docking and QM/MM MD Study

    Directory of Open Access Journals (Sweden)

    Manuel Hitzenberger

    2017-10-01

    Full Text Available Erroneous activation of the Hedgehog pathway has been linked to a great amount of cancerous diseases and therefore a large number of studies aiming at its inhibition have been carried out. One leverage point for novel therapeutic strategies targeting the proteins involved, is the prevention of complex formation between the extracellular signaling protein Sonic Hedgehog and the transmembrane protein Patched 1. In 2009 robotnikinin, a small molecule capable of binding to and inhibiting the activity of Sonic Hedgehog has been identified, however in the absence of X-ray structures of the Sonic Hedgehog-robotnikinin complex, the binding mode of this inhibitor remains unknown. In order to aid with the identification of novel Sonic Hedgehog inhibitors, the presented investigation elucidates the binding mode of robotnikinin by performing an extensive docking study, including subsequent molecular mechanical as well as quantum mechanical/molecular mechanical molecular dynamics simulations. The attained configurations enabled the identification of a number of key protein-ligand interactions, aiding complex formation and providing stabilizing contributions to the binding of the ligand. The predicted structure of the Sonic Hedgehog-robotnikinin complex is provided via a PDB file as Supplementary Material and can be used for further reference.

  4. Using physics-based pose predictions and free energy perturbation calculations to predict binding poses and relative binding affinities for FXR ligands in the D3R Grand Challenge 2

    Science.gov (United States)

    Athanasiou, Christina; Vasilakaki, Sofia; Dellis, Dimitris; Cournia, Zoe

    2018-01-01

    Computer-aided drug design has become an integral part of drug discovery and development in the pharmaceutical and biotechnology industry, and is nowadays extensively used in the lead identification and lead optimization phases. The drug design data resource (D3R) organizes challenges against blinded experimental data to prospectively test computational methodologies as an opportunity for improved methods and algorithms to emerge. We participated in Grand Challenge 2 to predict the crystallographic poses of 36 Farnesoid X Receptor (FXR)-bound ligands and the relative binding affinities for two designated subsets of 18 and 15 FXR-bound ligands. Here, we present our methodology for pose and affinity predictions and its evaluation after the release of the experimental data. For predicting the crystallographic poses, we used docking and physics-based pose prediction methods guided by the binding poses of native ligands. For FXR ligands with known chemotypes in the PDB, we accurately predicted their binding modes, while for those with unknown chemotypes the predictions were more challenging. Our group ranked #1st (based on the median RMSD) out of 46 groups, which submitted complete entries for the binding pose prediction challenge. For the relative binding affinity prediction challenge, we performed free energy perturbation (FEP) calculations coupled with molecular dynamics (MD) simulations. FEP/MD calculations displayed a high success rate in identifying compounds with better or worse binding affinity than the reference (parent) compound. Our studies suggest that when ligands with chemical precedent are available in the literature, binding pose predictions using docking and physics-based methods are reliable; however, predictions are challenging for ligands with completely unknown chemotypes. We also show that FEP/MD calculations hold predictive value and can nowadays be used in a high throughput mode in a lead optimization project provided that crystal structures of

  5. Conditional mode regression: Application to functional time series prediction

    OpenAIRE

    Dabo-Niang, Sophie; Laksaci, Ali

    2008-01-01

    We consider $\\alpha$-mixing observations and deal with the estimation of the conditional mode of a scalar response variable $Y$ given a random variable $X$ taking values in a semi-metric space. We provide a convergence rate in $L^p$ norm of the estimator. A useful and typical application to functional times series prediction is given.

  6. Predicting accurate absolute binding energies in aqueous solution

    DEFF Research Database (Denmark)

    Jensen, Jan Halborg

    2015-01-01

    Recent predictions of absolute binding free energies of host-guest complexes in aqueous solution using electronic structure theory have been encouraging for some systems, while other systems remain problematic. In this paper I summarize some of the many factors that could easily contribute 1-3 kcal......-represented by continuum models. While I focus on binding free energies in aqueous solution the approach also applies (with minor adjustments) to any free energy difference such as conformational or reaction free energy differences or activation free energies in any solvent....

  7. Prediction of chloride ingress and binding in cement paste

    DEFF Research Database (Denmark)

    Geiker, Mette Rica; Nielsen, Erik Pram; Herforth, Duncan

    2007-01-01

    This paper summarizes recent work on an analytical model for predicting the ingress rate of chlorides in cement-based materials. An integral part of this is a thermodynamic model for predicting the phase equilibria in hydrated Portland cement. The model’s ability to predict chloride binding...... in Portland cement pastes at any content of chloride, alkalis, sulfates and carbonate was verified experimentally and found to be equally valid when applied to other data in the literature. The thermodynamic model for predicting the phase equilibria in hydrated Portland cement was introduced into an existing...... Finite Difference Model for the ingress of chlorides into concrete which takes into account its multi-component nature. The “composite theory” was then used to predict the diffusivity of each ion based on the phase assemblage present in the hydrated Portland cement paste. Agreement was found between...

  8. Nonlinear Predictive Sliding Mode Control for Active Suspension System

    Directory of Open Access Journals (Sweden)

    Dazhuang Wang

    2018-01-01

    Full Text Available An active suspension system is important in meeting the requirements of the ride comfort and handling stability for vehicles. In this work, a nonlinear model of active suspension system and a corresponding nonlinear robust predictive sliding mode control are established for the control problem of active suspension. Firstly, a seven-degree-of-freedom active suspension model is established considering the nonlinear effects of springs and dampers; and secondly, the dynamic model is expanded in the time domain, and the corresponding predictive sliding mode control is established. The uncertainties in the controller are approximated by the fuzzy logic system, and the adaptive controller reduces the approximation error to increase the robustness of the control system. Finally, the simulation results show that the ride comfort and handling stability performance of the active suspension system is better than that of the passive suspension system and the Skyhook active suspension. Thus, the system can obviously improve the shock absorption performance of vehicles.

  9. Tube Model Predictive Control with an Auxiliary Sliding Mode Controller

    Directory of Open Access Journals (Sweden)

    Miodrag Spasic

    2016-07-01

    Full Text Available This paper studies Tube Model Predictive Control (MPC with a Sliding Mode Controller (SMC as an auxiliary controller. It is shown how to calculate the tube widths under SMC control, and thus how much the constraints of the nominal MPC have to be tightened in order to achieve robust stability and constraint fulfillment. The analysis avoids the assumption of infinitely fast switching in the SMC controller.

  10. Improved Wind Speed Prediction Using Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    ZHANG, Y.

    2018-05-01

    Full Text Available Wind power industry plays an important role in promoting the development of low-carbon economic and energy transformation in the world. However, the randomness and volatility of wind speed series restrict the healthy development of the wind power industry. Accurate wind speed prediction is the key to realize the stability of wind power integration and to guarantee the safe operation of the power system. In this paper, combined with the Empirical Mode Decomposition (EMD, the Radial Basis Function Neural Network (RBF and the Least Square Support Vector Machine (SVM, an improved wind speed prediction model based on Empirical Mode Decomposition (EMD-RBF-LS-SVM is proposed. The prediction result indicates that compared with the traditional prediction model (RBF, LS-SVM, the EMD-RBF-LS-SVM model can weaken the random fluctuation to a certain extent and improve the short-term accuracy of wind speed prediction significantly. In a word, this research will significantly reduce the impact of wind power instability on the power grid, ensure the power grid supply and demand balance, reduce the operating costs in the grid-connected systems, and enhance the market competitiveness of the wind power.

  11. DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues.

    Science.gov (United States)

    Ma, Xin; Guo, Jing; Sun, Xiao

    2016-01-01

    DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. However, insufficient work has been done on the prediction of DNA-binding proteins from protein sequence information. In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. The hybrid feature contains two types of novel sequence features, which reflect information about the conservation of physicochemical properties of the amino acids, and the binding propensity of DNA-binding residues and non-binding propensities of non-binding residues. The comparisons with each feature demonstrated that these two novel features contributed most to the improvement in predictive ability. Furthermore, to improve the prediction performance of the DNABP model, feature selection using the minimum redundancy maximum relevance (mRMR) method combined with incremental feature selection (IFS) was carried out during the model construction. The results showed that the DNABP model could achieve 86.90% accuracy, 83.76% sensitivity, 90.03% specificity and a Matthews correlation coefficient of 0.727. High prediction accuracy and performance comparisons with previous research suggested that DNABP could be a useful approach to identify DNA-binding proteins from sequence information. The DNABP web server system is freely available at http://www.cbi.seu.edu.cn/DNABP/.

  12. Prediction of Nucleotide Binding Peptides Using Star Graph Topological Indices.

    Science.gov (United States)

    Liu, Yong; Munteanu, Cristian R; Fernández Blanco, Enrique; Tan, Zhiliang; Santos Del Riego, Antonino; Pazos, Alejandro

    2015-11-01

    The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this biological function is an important research topic. The current study proposes a mixed methodology to obtain the first classification model that is able to predict new nucleotide binding peptides, using only the amino acid sequence. Thus, the methodology uses a Star graph molecular descriptor of the peptide sequences and the Machine Learning technique for the best classifier. The best model represents a Random Forest classifier based on two features of the embedded and non-embedded graphs. The performance of the model is excellent, considering similar models in the field, with an Area Under the Receiver Operating Characteristic Curve (AUROC) value of 0.938 and true positive rate (TPR) of 0.886 (test subset). The prediction of new nucleotide binding peptides with this model could be useful for drug target studies in drug development. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations

    Science.gov (United States)

    Mey, Antonia S. J. S.; Jiménez, Jordi Juárez; Michel, Julien

    2018-01-01

    The Drug Design Data Resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of Farsenoid X Receptor (FXR) inhibitors with a semi-automated alchemical free energy calculation workflow featuring FESetup and SOMD software tools. Reasonable performance was observed in retrospective analyses of literature datasets. Nevertheless, blinded predictions on the full D3R datasets were poor due to difficulties encountered with the ranking of compounds that vary in their net-charge. Performance increased for predictions that were restricted to subsets of compounds carrying the same net-charge. Disclosure of X-ray crystallography derived binding modes maintained or improved the correlation with experiment in a subsequent rounds of predictions. The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature structure activity relationships (SAR)s only, and comparable or slightly inferior, to the best submissions from other groups.

  14. Half-life predictions for decay modes of superheavy nuclei

    International Nuclear Information System (INIS)

    Duarte, S.B.; Tavares, O.A.P.; Goncalves, M.; Rodriguez, O.; Guzman, F.; Barbosa, T.N.; Garcia, F.; Dimarco, A.

    2004-09-01

    We applied the Effective Liquid Drop Model (ELDM) to predict the alpha-decay, cluster emission and cold fission half-life-values of nuclei in the region of Superheavy Elements (SHE). The present calculations have been made in the region of the ZN-plane defined by 155 <=N <=220 and 110<=Z<=135. Shell effects are included via the Q-value of the corresponding decay case. We report the results of a systematic calculation of the half-life for the three nuclear decay modes in a region of the ZN-plane where superheavy elements are expected to be found. Results have shown that, among the decay modes investigated here, the alpha decay is the dominant one. i.e, the decay mode of smallest half-lives. Half-life predictions for alpha decay, cluster emission and cold fission for the isotopic family of the most recent SHE detected of Z=115 and for the isotopic family of the already consolidated SHE of Z=111 are presented. (author)

  15. Estrogen Receptor Folding Modulates cSrc Kinase SH2 Interaction via a Helical Binding Mode.

    Science.gov (United States)

    Nieto, Lidia; Tharun, Inga M; Balk, Mark; Wienk, Hans; Boelens, Rolf; Ottmann, Christian; Milroy, Lech-Gustav; Brunsveld, Luc

    2015-11-20

    The estrogen receptors (ERs) feature, next to their transcriptional role, important nongenomic signaling actions, with emerging clinical relevance. The Src Homology 2 (SH2) domain mediated interaction between cSrc kinase and ER plays a key role in this; however the molecular determinants of this interaction have not been elucidated. Here, we used phosphorylated ER peptide and semisynthetic protein constructs in a combined biochemical and structural study to, for the first time, provide a quantitative and structural characterization of the cSrc SH2-ER interaction. Fluorescence polarization experiments delineated the SH2 binding motif in the ER sequence. Chemical shift perturbation analysis by nuclear magnetic resonance (NMR) together with molecular dynamics (MD) simulations allowed us to put forward a 3D model of the ER-SH2 interaction. The structural basis of this protein-protein interaction has been compared with that of the high affinity SH2 binding sequence GpYEEI. The ER features a different binding mode from that of the "two-pronged plug two-hole socket" model in the so-called specificity determining region. This alternative binding mode is modulated via the folding of ER helix 12, a structural element directly C-terminal of the key phosphorylated tyrosine. The present findings provide novel molecular entries for understanding nongenomic ER signaling and targeting the corresponding disease states.

  16. Predicting "Hot" and "Warm" Spots for Fragment Binding.

    Science.gov (United States)

    Rathi, Prakash Chandra; Ludlow, R Frederick; Hall, Richard J; Murray, Christopher W; Mortenson, Paul N; Verdonk, Marcel L

    2017-05-11

    Computational fragment mapping methods aim to predict hotspots on protein surfaces where small fragments will bind. Such methods are popular for druggability assessment as well as structure-based design. However, to date researchers developing or using such tools have had no clear way of assessing the performance of these methods. Here, we introduce the first diverse, high quality validation set for computational fragment mapping. The set contains 52 diverse examples of fragment binding "hot" and "warm" spots from the Protein Data Bank (PDB). Additionally, we describe PLImap, a novel protocol for fragment mapping based on the Protein-Ligand Informatics force field (PLIff). We evaluate PLImap against the new fragment mapping test set, and compare its performance to that of simple shape-based algorithms and fragment docking using GOLD. PLImap is made publicly available from https://bitbucket.org/AstexUK/pli .

  17. Predicting plasticity with soft vibrational modes: from dislocations to glasses.

    Science.gov (United States)

    Rottler, Jörg; Schoenholz, Samuel S; Liu, Andrea J

    2014-04-01

    We show that quasilocalized low-frequency modes in the vibrational spectrum can be used to construct soft spots, or regions vulnerable to rearrangement, which serve as a universal tool for the identification of flow defects in solids. We show that soft spots not only encode spatial information, via their location, but also directional information, via directors for particles within each soft spot. Single crystals with isolated dislocations exhibit low-frequency phonon modes that localize at the core, and their polarization pattern predicts the motion of atoms during elementary dislocation glide in two and three dimensions in exquisite detail. Even in polycrystals and disordered solids, we find that the directors associated with particles in soft spots are highly correlated with the direction of particle displacements in rearrangements.

  18. A Combined Molecular Docking/Dynamics Approach to Probe the Binding Mode of Cancer Drugs with Cytochrome P450 3A4

    Directory of Open Access Journals (Sweden)

    Suresh Panneerselvam

    2015-08-01

    Full Text Available Cytarabine, daunorubicin, doxorubicin and vincristine are clinically used for combinatorial therapies of cancers in different combinations. However, the knowledge about the interaction of these drugs with the metabolizing enzyme cytochrome P450 is limited. Therefore, we utilized computational methods to predict and assess the drug-binding modes. In this study, we performed docking, MD simulations and free energy landscape analysis to understand the drug-enzyme interactions, protein domain motions and the most populated free energy minimum conformations of the docked protein-drug complexes, respectively. The outcome of docking and MD simulations predicted the productive, as well as the non-productive binding modes of the selected drugs. Based on these interaction studies, we observed that S119, R212 and R372 are the major drug-binding residues in CYP3A4. The molecular mechanics Poisson–Boltzmann surface area analysis revealed the dominance of hydrophobic forces in the CYP3A4-drug association. Further analyses predicted the residues that may contain favorable drug-specific interactions. The probable binding modes of the cancer drugs from this study may extend the knowledge of the protein-drug interaction and pave the way to design analogs with reduced toxicity. In addition, they also provide valuable insights into the metabolism of the cancer drugs.

  19. Memory Binding Test Predicts Incident Amnestic Mild Cognitive Impairment.

    Science.gov (United States)

    Mowrey, Wenzhu B; Lipton, Richard B; Katz, Mindy J; Ramratan, Wendy S; Loewenstein, David A; Zimmerman, Molly E; Buschke, Herman

    2016-07-14

    The Memory Binding Test (MBT), previously known as Memory Capacity Test, has demonstrated discriminative validity for distinguishing persons with amnestic mild cognitive impairment (aMCI) and dementia from cognitively normal elderly. We aimed to assess the predictive validity of the MBT for incident aMCI. In a longitudinal, community-based study of adults aged 70+, we administered the MBT to 246 cognitively normal elderly adults at baseline and followed them annually. Based on previous work, a subtle reduction in memory binding at baseline was defined by a Total Items in the Paired (TIP) condition score of ≤22 on the MBT. Cox proportional hazards models were used to assess the predictive validity of the MBT for incident aMCI accounting for the effects of covariates. The hazard ratio of incident aMCI was also assessed for different prediction time windows ranging from 4 to 7 years of follow-up, separately. Among 246 controls who were cognitively normal at baseline, 48 developed incident aMCI during follow-up. A baseline MBT reduction was associated with an increased risk for developing incident aMCI (hazard ratio (HR) = 2.44, 95% confidence interval: 1.30-4.56, p = 0.005). When varying the prediction window from 4-7 years, the MBT reduction remained significant for predicting incident aMCI (HR range: 2.33-3.12, p: 0.0007-0.04). Persons with poor performance on the MBT are at significantly greater risk for developing incident aMCI. High hazard ratios up to seven years of follow-up suggest that the MBT is sensitive to early disease.

  20. Crystal structure of glucose isomerase in complex with xylitol inhibitor in one metal binding mode.

    Science.gov (United States)

    Bae, Ji-Eun; Kim, In Jung; Nam, Ki Hyun

    2017-11-04

    Glucose isomerase (GI) is an intramolecular oxidoreductase that interconverts aldoses and ketoses. These characteristics are widely used in the food, detergent, and pharmaceutical industries. In order to obtain an efficient GI, identification of novel GI genes and substrate binding/inhibition have been studied. Xylitol is a well-known inhibitor of GI. In Streptomyces rubiginosus, two crystal structures have been reported for GI in complex with xylitol inhibitor. However, a structural comparison showed that xylitol can have variable conformation at the substrate binding site, e.g., a nonspecific binding mode. In this study, we report the crystal structure of S. rubiginosus GI in a complex with xylitol and glycerol. Our crystal structure showed one metal binding mode in GI, which we presumed to represent the inactive form of the GI. The metal ion was found only at the M1 site, which was involved in substrate binding, and was not present at the M2 site, which was involved in catalytic function. The O 2 and O 4 atoms of xylitol molecules contributed to the stable octahedral coordination of the metal in M1. Although there was no metal at the M2 site, no large conformational change was observed for the conserved residues coordinating M2. Our structural analysis showed that the metal at the M2 site was not important when a xylitol inhibitor was bound to the M1 site in GI. Thus, these findings provided important information for elucidation or engineering of GI functions. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Validation of tautomeric and protomeric binding modes by free energy calculations. A case study for the structure based optimization of d-amino acid oxidase inhibitors

    Science.gov (United States)

    Orgován, Zoltán; Ferenczy, György G.; Steinbrecher, Thomas; Szilágyi, Bence; Bajusz, Dávid; Keserű, György M.

    2018-02-01

    Optimization of fragment size d-amino acid oxidase (DAAO) inhibitors was investigated using a combination of computational and experimental methods. Retrospective free energy perturbation (FEP) calculations were performed for benzo[d]isoxazole derivatives, a series of known inhibitors with two potential binding modes derived from X-ray structures of other DAAO inhibitors. The good agreement between experimental and computed binding free energies in only one of the hypothesized binding modes strongly support this bioactive conformation. Then, a series of 1-H-indazol-3-ol derivatives formerly not described as DAAO inhibitors was investigated. Binding geometries could be reliably identified by structural similarity to benzo[d]isoxazole and other well characterized series and FEP calculations were performed for several tautomers of the deprotonated and protonated compounds since all these forms are potentially present owing to the experimental pKa values of representative compounds in the series. Deprotonated compounds are proposed to be the most important bound species owing to the significantly better agreement between their calculated and measured affinities compared to the protonated forms. FEP calculations were also used for the prediction of the affinities of compounds not previously tested as DAAO inhibitors and for a comparative structure-activity relationship study of the benzo[d]isoxazole and indazole series. Selected indazole derivatives were synthesized and their measured binding affinity towards DAAO was in good agreement with FEP predictions.

  2. Convolutional neural network architectures for predicting DNA–protein binding

    Science.gov (United States)

    Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

    2016-01-01

    Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

  3. AgI -Induced Switching of DNA Binding Modes via Formation of a Supramolecular Metallacycle.

    Science.gov (United States)

    Basak, Shibaji; Léon, J Christian; Ferranco, Annaleizle; Sharma, Renu; Hebenbrock, Marian; Lough, Alan; Müller, Jens; Kraatz, Heinz-Bernhard

    2018-03-12

    The histidine derivative L1 of the DNA intercalator naphthalenediimide (NDI) forms a triangular Ag I complex (C2). The interactions of L1 and of C2 with DNA were studied by circular dichroism (CD) and UV/Vis spectroscopy and by viscosity studies. Different binding modes were observed for L1 and for C2, as the Ag I complex C2 is too large in size to act as an intercalator. If Ag I is added to the NDI molecule that is already intercalated into a duplex, higher order complexes are formed within the DNA duplex and cause disruptions in the helical duplex structure, which leads to a significant decrease in the characteristic CD features of B-DNA. Thus, via addition of a metal we show how a classic and well-known organic intercalator unit can be turned into a partial metallo insertor. We also show how electrochemical impedance spectroscopy (EIS) can be used to probe DNA binding modes on DNA films that are immobilized on gold surfaces. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots

    Science.gov (United States)

    2014-01-01

    Background Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results This work proposes a new method, βACV ASA , to predict the change of binding free energy after alanine mutations. βACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector (ACV). A β contact between two atoms is a direct contact without being interrupted by any other atom between them. A β contact’s potential contribution to protein binding is also supposed to be inversely proportional to its ASA to follow the water exclusion hypothesis of binding hot spots. Tested on a dataset of 396 alanine mutations, our method is found to be superior in classification performance to many other methods, including Robetta, FoldX, HotPOINT, an ACV method of β contacts without ASA integration, and ACV ASA methods (similar to βACV ASA but based on distance-cutoff contacts). Based on our data analysis and results, we can draw conclusions that: (i) our method is powerful in the prediction of binding free energy change after alanine mutation; (ii) β contacts are better than distance-cutoff contacts for modeling the well-organized protein-binding interfaces; (iii) β contacts usually are only a small fraction number of the distance-based contacts; and (iv) water exclusion is a necessary condition for a residue to become a binding hot spot. Conclusions βACV ASA is designed using the advantages of both β contacts and water exclusion. It is an excellent tool to predict binding free energy changes and binding hot spots after alanine mutation. PMID:24568581

  5. A novel cofactor-binding mode in bacterial IMP dehydrogenases explains inhibitor selectivity.

    Science.gov (United States)

    Makowska-Grzyska, Magdalena; Kim, Youngchang; Maltseva, Natalia; Osipiuk, Jerzy; Gu, Minyi; Zhang, Minjia; Mandapati, Kavitha; Gollapalli, Deviprasad R; Gorla, Suresh Kumar; Hedstrom, Lizbeth; Joachimiak, Andrzej

    2015-02-27

    The steadily rising frequency of emerging diseases and antibiotic resistance creates an urgent need for new drugs and targets. Inosine 5'-monophosphate dehydrogenase (IMP dehydrogenase or IMPDH) is a promising target for the development of new antimicrobial agents. IMPDH catalyzes the oxidation of IMP to XMP with the concomitant reduction of NAD(+), which is the pivotal step in the biosynthesis of guanine nucleotides. Potent inhibitors of bacterial IMPDHs have been identified that bind in a structurally distinct pocket that is absent in eukaryotic IMPDHs. The physiological role of this pocket was not understood. Here, we report the structures of complexes with different classes of inhibitors of Bacillus anthracis, Campylobacter jejuni, and Clostridium perfringens IMPDHs. These structures in combination with inhibition studies provide important insights into the interactions that modulate selectivity and potency. We also present two structures of the Vibrio cholerae IMPDH in complex with IMP/NAD(+) and XMP/NAD(+). In both structures, the cofactor assumes a dramatically different conformation than reported previously for eukaryotic IMPDHs and other dehydrogenases, with the major change observed for the position of the NAD(+) adenosine moiety. More importantly, this new NAD(+)-binding site involves the same pocket that is utilized by the inhibitors. Thus, the bacterial IMPDH-specific NAD(+)-binding mode helps to rationalize the conformation adopted by several classes of prokaryotic IMPDH inhibitors. These findings offer a potential strategy for further ligand optimization. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  6. A Novel Cofactor-binding Mode in Bacterial IMP Dehydrogenases Explains Inhibitor Selectivity*

    Science.gov (United States)

    Makowska-Grzyska, Magdalena; Kim, Youngchang; Maltseva, Natalia; Osipiuk, Jerzy; Gu, Minyi; Zhang, Minjia; Mandapati, Kavitha; Gollapalli, Deviprasad R.; Gorla, Suresh Kumar; Hedstrom, Lizbeth; Joachimiak, Andrzej

    2015-01-01

    The steadily rising frequency of emerging diseases and antibiotic resistance creates an urgent need for new drugs and targets. Inosine 5′-monophosphate dehydrogenase (IMP dehydrogenase or IMPDH) is a promising target for the development of new antimicrobial agents. IMPDH catalyzes the oxidation of IMP to XMP with the concomitant reduction of NAD+, which is the pivotal step in the biosynthesis of guanine nucleotides. Potent inhibitors of bacterial IMPDHs have been identified that bind in a structurally distinct pocket that is absent in eukaryotic IMPDHs. The physiological role of this pocket was not understood. Here, we report the structures of complexes with different classes of inhibitors of Bacillus anthracis, Campylobacter jejuni, and Clostridium perfringens IMPDHs. These structures in combination with inhibition studies provide important insights into the interactions that modulate selectivity and potency. We also present two structures of the Vibrio cholerae IMPDH in complex with IMP/NAD+ and XMP/NAD+. In both structures, the cofactor assumes a dramatically different conformation than reported previously for eukaryotic IMPDHs and other dehydrogenases, with the major change observed for the position of the NAD+ adenosine moiety. More importantly, this new NAD+-binding site involves the same pocket that is utilized by the inhibitors. Thus, the bacterial IMPDH-specific NAD+-binding mode helps to rationalize the conformation adopted by several classes of prokaryotic IMPDH inhibitors. These findings offer a potential strategy for further ligand optimization. PMID:25572472

  7. Absolute analytical prediction of photonic crystal guided mode resonance wavelengths

    International Nuclear Information System (INIS)

    Hermannsson, Pétur Gordon; Vannahme, Christoph; Smith, Cameron L. C.; Kristensen, Anders

    2014-01-01

    A class of photonic crystal resonant reflectors known as guided mode resonant filters are optical structures that are widely used in the field of refractive index sensing, particularly in biosensing. For the purposes of understanding and design, their behavior has traditionally been modeled numerically with methods such as rigorous coupled wave analysis. Here it is demonstrated how the absolute resonance wavelengths of such structures can be predicted by analytically modeling them as slab waveguides in which the propagation constant is determined by a phase matching condition. The model is experimentally verified to be capable of predicting the absolute resonance wavelengths to an accuracy of within 0.75 nm, as well as resonance wavelength shifts due to changes in cladding index within an accuracy of 0.45 nm across the visible wavelength regime in the case where material dispersion is taken into account. Furthermore, it is demonstrated that the model is valid beyond the limit of low grating modulation, for periodically discontinuous waveguide layers, high refractive index contrasts, and highly dispersive media.

  8. Prediction of RNA-Binding Proteins by Voting Systems

    Directory of Open Access Journals (Sweden)

    C. R. Peng

    2011-01-01

    Full Text Available It is important to identify which proteins can interact with RNA for the purpose of protein annotation, since interactions between RNA and proteins influence the structure of the ribosome and play important roles in gene expression. This paper tries to identify proteins that can interact with RNA using voting systems. Firstly through Weka, 34 learning algorithms are chosen for investigation. Then simple majority voting system (SMVS is used for the prediction of RNA-binding proteins, achieving average ACC (overall prediction accuracy value of 79.72% and MCC (Matthew’s correlation coefficient value of 59.77% for the independent testing dataset. Then mRMR (minimum redundancy maximum relevance strategy is used, which is transferred into algorithm selection. In addition, the MCC value of each classifier is assigned to be the weight of the classifier’s vote. As a result, best average MCC values are attained when 22 algorithms are selected and integrated through weighted votes, which are 64.70% for the independent testing dataset, and ACC value is 82.04% at this moment.

  9. Mechanisms of Intentional Binding and Sensory Attenuation: The Role of Temporal Prediction, Temporal Control, Identity Prediction, and Motor Prediction

    Science.gov (United States)

    Hughes, Gethin; Desantis, Andrea; Waszak, Florian

    2013-01-01

    Sensory processing of action effects has been shown to differ from that of externally triggered stimuli, with respect both to the perceived timing of their occurrence (intentional binding) and to their intensity (sensory attenuation). These phenomena are normally attributed to forward action models, such that when action prediction is consistent…

  10. Mutation analysis and molecular modeling for the investigation of ligand-binding modes of GPR84.

    Science.gov (United States)

    Nikaido, Yoshiaki; Koyama, Yuuta; Yoshikawa, Yasushi; Furuya, Toshio; Takeda, Shigeki

    2015-05-01

    GPR84 is a G protein-coupled receptor for medium-chain fatty acids. Capric acid and 3,3'-diindolylmethane are specific agonists for GPR84. We built a homology model of a GPR84-capric acid complex to investigate the ligand-binding mode using the crystal structure of human active-state β2-adrenergic receptor. We performed site-directed mutagenesis to subject ligand-binding sites to our model using GPR84-Giα fusion proteins and a [(35)S]GTPγS-binding assay. We compared the activity of the wild type and mutated forms of GPR84 by [(35)S]GTPγS binding to capric acid and diindolylmethane. The mutations L100D `Ballesteros-Weinstein numbering: 3.32), F101Y (3.33) and N104Q (3.36) in the transmembrane helix III and N357D (7.39) in the transmembrane helix VII resulted in reduced capric acid activity but maintained the diindolylmethane responses. Y186F (5.46) and Y186H (5.46) mutations had no characteristic effect on capric acid but with diindolylmethane they significantly affected the G protein activation efficiency. The L100D (3.32) mutant responded to decylamine, a fatty amine, instead of a natural agonist, the fatty acid capric acid, suggesting that we have identified a mutated G protein-coupled receptor-artificial ligand pairing. Our molecular model provides an explanation for these results and interactions between GPR84 and capric acid. Further, from the results of a double stimulation assay, we concluded that diindolylmethane was a positive allosteric modulator for GPR84. © The Authors 2014. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

  11. Development of estrogen receptor beta binding prediction model using large sets of chemicals.

    Science.gov (United States)

    Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Gong, Ping; Zhang, Chaoyang; Tong, Weida; Hong, Huixiao

    2017-11-03

    We developed an ER β binding prediction model to facilitate identification of chemicals specifically bind ER β or ER α together with our previously developed ER α binding model. Decision Forest was used to train ER β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations were conducted to assess the chance correlation. The average accuracy of 5-fold cross validations was 93.14% with a standard deviation of 0.64%. Prediction confidence analysis indicated that the higher the prediction confidence the more accurate the predictions. Permutation testing results revealed that the prediction model is unlikely generated by chance. Eighteen informative descriptors were identified to be important to ER β binding prediction. Application of the prediction model to the data from ToxCast project yielded very high sensitivity of 90-92%. Our results demonstrated ER β binding of chemicals could be accurately predicted using the developed model. Coupling with our previously developed ER α prediction model, this model could be expected to facilitate drug development through identification of chemicals that specifically bind ER β or ER α .

  12. Prediction of nucleosome positioning based on transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Xianfu Yi

    Full Text Available BACKGROUND: The DNA of all eukaryotic organisms is packaged into nucleosomes, the basic repeating units of chromatin. The nucleosome consists of a histone octamer around which a DNA core is wrapped and the linker histone H1, which is associated with linker DNA. By altering the accessibility of DNA sequences, the nucleosome has profound effects on all DNA-dependent processes. Understanding the factors that influence nucleosome positioning is of great importance for the study of genomic control mechanisms. Transcription factors (TFs have been suggested to play a role in nucleosome positioning in vivo. PRINCIPAL FINDINGS: Here, the minimum redundancy maximum relevance (mRMR feature selection algorithm, the nearest neighbor algorithm (NNA, and the incremental feature selection (IFS method were used to identify the most important TFs that either favor or inhibit nucleosome positioning by analyzing the numbers of transcription factor binding sites (TFBSs in 53,021 nucleosomal DNA sequences and 50,299 linker DNA sequences. A total of nine important families of TFs were extracted from 35 families, and the overall prediction accuracy was 87.4% as evaluated by the jackknife cross-validation test. CONCLUSIONS: Our results are consistent with the notion that TFs are more likely to bind linker DNA sequences than the sequences in the nucleosomes. In addition, our results imply that there may be some TFs that are important for nucleosome positioning but that play an insignificant role in discriminating nucleosome-forming DNA sequences from nucleosome-inhibiting DNA sequences. The hypothesis that TFs play a role in nucleosome positioning is, thus, confirmed by the results of this study.

  13. HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information

    Directory of Open Access Journals (Sweden)

    Hu Jianjun

    2011-05-01

    Full Text Available Abstract Background Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues. Results Here we introduced an efficient algorithm HemeBIND for predicting heme binding residues by integrating structural and sequence information. We systematically investigated the characteristics of binding interfaces based on a non-redundant dataset of heme-protein complexes. It was found that several sequence and structural attributes such as evolutionary conservation, solvent accessibility, depth and protrusion clearly illustrate the differences between heme binding and non-binding residues. These features can then be separately used or combined to build the structure-based classifiers using support vector machine (SVM. The results showed that the information contained in these features is largely complementary and their combination achieved the best performance. To further improve the performance, an attempt has been made to develop a post-processing procedure to reduce the number of false positives. In addition, we built a sequence-based classifier based on SVM and sequence profile as an alternative when only sequence information can be used. Finally, we employed a voting method to combine the outputs of structure-based and sequence-based classifiers, which demonstrated remarkably better performance than the individual classifier alone

  14. Probable mode prediction for H.264 advanced video coding P slices using removable SKIP mode distortion estimation

    Science.gov (United States)

    You, Jongmin; Jeong, Jechang

    2010-02-01

    The H.264/AVC (advanced video coding) is used in a wide variety of applications including digital broadcasting and mobile applications, because of its high compression efficiency. The variable block mode scheme in H.264/AVC contributes much to its high compression efficiency but causes a selection problem. In general, rate-distortion optimization (RDO) is the optimal mode selection strategy, but it is computationally intensive. For this reason, the H.264/AVC encoder requires a fast mode selection algorithm for use in applications that require low-power and real-time processing. A probable mode prediction algorithm for the H.264/AVC encoder is proposed. To reduce the computational complexity of RDO, the proposed method selects probable modes among all allowed block modes using removable SKIP mode distortion estimation. Removable SKIP mode distortion is used to estimate whether or not a further divided block mode is appropriate for a macroblock. It is calculated using a no-motion reference block with a few computations. Then the proposed method reduces complexity by performing the RDO process only for probable modes. Experimental results show that the proposed algorithm can reduce encoding time by an average of 55.22% without significant visual quality degradation and increased bit rate.

  15. Mode of bindings of zinc oxide nanoparticles to myoglobin and horseradish peroxidase: A spectroscopic investigations

    Science.gov (United States)

    Mandal, Gopa; Bhattacharya, Sudeshna; Ganguly, Tapan

    2011-07-01

    The interactions between two heme proteins myoglobin (HMb) and horseradish peroxidase (HRP) with zinc oxide (ZnO) nanoparticles are investigated by using UV-vis absorption, steady state fluorescence, synchronous fluorescence, time-resolved fluorescence, FT-IR, atomic force microscopy (AFM) and circular dichroism (CD) techniques under physiological condition of pH˜7.4. The presence of mainly static mode in fluorescence quenching mechanism of HMb and HRP by ZnO nanoparticle indicates the possibility of formation of ground state complex. The processes of bindings of ZnO nanoparticles with the two proteins are spontaneous molecular interaction procedures. In both cases hydrogen bonding plays a major role. The circular dichroism (CD) spectra reveal that a helicity of the proteins is reduced by increasing ZnO nanoparticle concentration although the α-helical structures of HMb and HRP retain their identity. On binding to the ZnO nanoparticles the secondary structure of HRP molecules (or HMb molecules) remains unchanged while there is a substantial change in the environment of the tyrosin active site in case of HRP molecules and tryptophan active site in case of HMb molecules. Tapping mode atomic force microscopy (AFM) was applied for the investigation the structure of HRP adsorbed in the environment of nanoparticles on the silicon and on the bare silicon. HRP molecules adsorb and aggregate on the mica with ZnO nanoparticle. The aggregation indicates an attractive interaction among the adsorbed molecules. The molecules are randomly distributed on the bare silicon wafer. The adsorption of HRP in the environment of ZnO nanoparticle changes drastically the domains due to a strong interaction between HRP and ZnO nanoparticles. Similar situation is observed in case of HMb molecules. These findings demonstrate the efficacy of biomedical applications of ZnO nanoparticles as well as in elucidating their mechanisms of action as drugs in both human and plant systems.

  16. Machine learning competition in immunology – Prediction of HLA class I binding peptides

    DEFF Research Database (Denmark)

    Zhang, Guang Lan; Ansari, Hifzur Rahman; Bradley, Phil

    2011-01-01

    of peptide binding, therefore, determines the accuracy of the overall method. Computational predictions of peptide binding to HLA, both class I and class II, use a variety of algorithms ranging from binding motifs to advanced machine learning techniques ( [Brusic et al., 2004] and [Lafuente and Reche, 2009...

  17. Prediction of DNA-binding specificity in zinc finger proteins

    Indian Academy of Sciences (India)

    2012-06-25

    Jun 25, 2012 ... Support Vector Machine (SVM) is a state-of-the-art classifica- tion technique. Using canonical binding model, the C2H2 zinc finger protein–DNA interaction interface is modelled by the pairwise amino acid–base interactions. Using a classification framework, known examples of non-binding ZF–DNA pairs.

  18. NetMHCpan, a method for MHC class I binding prediction beyond humans

    DEFF Research Database (Denmark)

    Hoof, Ilka; Peters, B; Sidney, J

    2009-01-01

    molecules. We show that the NetMHCpan-2.0 method can accurately predict binding to uncharacterized HLA molecules, including HLA-C and HLA-G. Moreover, NetMHCpan-2.0 is demonstrated to accurately predict peptide binding to chimpanzee and macaque MHC class I molecules. The power of NetMHCpan-2.0 to guide...

  19. New insight into the binding modes of TNP-AMP to human liver fructose-1,6-bisphosphatase.

    Science.gov (United States)

    Han, Xinya; Huang, Yunyuan; Zhang, Rui; Xiao, San; Zhu, Shuaihuan; Qin, Nian; Hong, Zongqin; Wei, Lin; Feng, Jiangtao; Ren, Yanliang; Feng, Lingling; Wan, Jian

    2016-08-05

    Human liver fructose-1,6-bisphosphatase (FBPase) contains two binding sites, a substrate fructose-1,6-bisphosphate (FBP) active site and an adenosine monophosphate (AMP) allosteric site. The FBP active site works by stabilizing the FBPase, and the allosteric site impairs the activity of FBPase through its binding of a nonsubstrate molecule. The fluorescent AMP analogue, 2',3'-O-(2,4,6-trinitrophenyl)adenosine 5'-monophosphate (TNP-AMP) has been used as a fluorescent probe as it is able to competitively inhibit AMP binding to the AMP allosteric site and, therefore, could be used for exploring the binding modes of inhibitors targeted on the allosteric site. In this study, we have re-examined the binding modes of TNP-AMP to FBPase. However, our present enzyme kinetic assays show that AMP and FBP both can reduce the fluorescence from the bound TNP-AMP through competition for FBPase, suggesting that TNP-AMP binds not only to the AMP allosteric site but also to the FBP active site. Mutagenesis assays of K274L (located in the FBP active site) show that the residue K274 is very important for TNP-AMP to bind to the active site of FBPase. The results further prove that TNP-AMP is able to bind individually to the both sites. Our present study provides a new insight into the binding mechanism of TNP-AMP to the FBPase. The TNP-AMP fluorescent probe can be used to exam the binding site of an inhibitor (the active site or the allosteric site) using FBPase saturated by AMP and FBP, respectively, or the K247L mutant FBPase. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Structure prediction and binding sites analysis of curcin protein of Jatropha curcas using computational approaches.

    Science.gov (United States)

    Srivastava, Mugdha; Gupta, Shishir K; Abhilash, P C; Singh, Nandita

    2012-07-01

    Ribosome inactivating proteins (RIPs) are defense proteins in a number of higher-plant species that are directly targeted toward herbivores. Jatropha curcas is one of the biodiesel plants having RIPs. The Jatropha seed meal, after extraction of oil, is rich in curcin, a highly toxic RIP similar to ricin, which makes it unsuitable for animal feed. Although the toxicity of curcin is well documented in the literature, the detailed toxic properties and the 3D structure of curcin has not been determined by X-ray crystallography, NMR spectroscopy or any in silico techniques to date. In this pursuit, the structure of curcin was modeled by a composite approach of 3D structure prediction using threading and ab initio modeling. Assessment of model quality was assessed by methods which include Ramachandran plot analysis and Qmean score estimation. Further, we applied the protein-ligand docking approach to identify the r-RNA binding residue of curcin. The present work provides the first structural insight into the binding mode of r-RNA adenine to the curcin protein and forms the basis for designing future inhibitors of curcin. Cloning of a future peptide inhibitor within J. curcas can produce non-toxic varieties of J. curcas, which would make the seed-cake suitable as animal feed without curcin detoxification.

  1. A computational analysis of the binding mode of closantel as inhibitor of the Onchocerca volvulus chitinase: insights on macrofilaricidal drug design

    Science.gov (United States)

    Segura-Cabrera, Aldo; Bocanegra-García, Virgilio; Lizarazo-Ortega, Cristian; Guo, Xianwu; Correa-Basurto, José; Rodríguez-Pérez, Mario A.

    2011-12-01

    Onchocerciasis is a leading cause of blindness with at least 37 million people infected and more than 120 million people at risk of contracting the disease; most (99%) of this population, threatened by infection, live in Africa. The drug of choice for mass treatment is the microfilaricidal Mectizan® (ivermectin); it does not kill the adult stages of the parasite at the standard dose which is a single annual dose aimed at disease control. However, multiple treatments a year with ivermectin have effects on adult worms. The discovery of new therapeutic targets and drugs directed towards the killing of the adult parasites are thus urgently needed. The chitinase of filarial nematodes is a new drug target due to its essential function in the metabolism and molting of the parasite. Closantel is a potent and specific inhibitor of chitinase of Onchocerca volvulus (OvCHT1) and other filarial chitinases. However, the binding mode and specificity of closantel towards OvCHT1 remain unknown. In the absence of a crystallographic structure of OvCHT1, we developed a homology model of OvCHT1 using the currently available X-ray structures of human chitinases as templates. Energy minimization and molecular dynamics (MD) simulation of the model led to a high quality of 3D structure of OvCHIT1. A flexible docking study using closantel as the ligand on the binding site of OvCHIT1 and human chitinases was performed and demonstrated the differences in the closantel binding mode between OvCHIT1 and human chitinase. Furthermore, molecular dynamics simulations and free-energy calculation were employed to determine and compare the detailed binding mode of closantel with OvCHT1 and the structure of human chitinase. This comparative study allowed identification of structural features and properties responsible for differences in the computationally predicted closantel binding modes. The homology model and the closantel binding mode reported herein might help guide the rational development of

  2. Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015.

    Science.gov (United States)

    Deng, Nanjie; Flynn, William F; Xia, Junchao; Vijayan, R S K; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M

    2016-09-01

    binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.

  3. DRD2 genotype-based variation of default mode network activity and of its relationship with striatal DAT binding.

    Science.gov (United States)

    Sambataro, Fabio; Fazio, Leonardo; Taurisano, Paolo; Gelao, Barbara; Porcelli, Annamaria; Mancini, Marina; Sinibaldi, Lorenzo; Ursini, Gianluca; Masellis, Rita; Caforio, Grazia; Di Giorgio, Annabella; Niccoli-Asabella, Artor; Popolizio, Teresa; Blasi, Giuseppe; Bertolino, Alessandro

    2013-01-01

    The default mode network (DMN) comprises a set of brain regions with "increased" activity during rest relative to cognitive processing. Activity in the DMN is associated with functional connections with the striatum and dopamine (DA) levels in this brain region. A functional single-nucleotide polymorphism within the dopamine D2 receptor gene (DRD2, rs1076560 G > T) shifts splicing of the 2 D2 isoforms, D2 short and D2 long, and has been associated with striatal DA signaling as well as with cognitive processing. However, the effects of this polymorphism on DMN have not been explored. The aim of this study was to evaluate the effects of rs1076560 on DMN and striatal connectivity and on their relationship with striatal DA signaling. Twenty-eight subjects genotyped for rs1076560 underwent functional magnetic resonance imaging during a working memory task and 123 55 I-Fluoropropyl-2-beta-carbomethoxy-3-beta(4-iodophenyl) nortropan Single Photon Emission Computed Tomography ([(123)I]-FP-CIT SPECT) imaging (a measure of dopamine transporter [DAT] binding). Spatial group-independent component (IC) analysis was used to identify DMN and striatal ICs. Within the anterior DMN IC, GG subjects had relatively greater connectivity in medial prefrontal cortex (MPFC), which was directly correlated with striatal DAT binding. Within the posterior DMN IC, GG subjects had reduced connectivity in posterior cingulate relative to T carriers. Additionally, rs1076560 genotype predicted connectivity differences within a striatal network, and these changes were correlated with connectivity in MPFC and posterior cingulate within the DMN. These results suggest that genetically determined D2 receptor signaling is associated with DMN connectivity and that these changes are correlated with striatal function and presynaptic DA signaling.

  4. A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

    KAUST Repository

    Chen, Peng

    2015-12-03

    Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

  5. A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

    KAUST Repository

    Chen, Peng; Hu, ShanShan; Zhang, Jun; Gao, Xin; Li, Jinyan; Xia, Junfeng; Wang, Bing

    2015-01-01

    Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

  6. Structural Dynamics Investigation of Human Family 1 & 2 Cystatin-Cathepsin L1 Interaction: A Comparison of Binding Modes.

    Directory of Open Access Journals (Sweden)

    Suman Kumar Nandy

    Full Text Available Cystatin superfamily is a large group of evolutionarily related proteins involved in numerous physiological activities through their inhibitory activity towards cysteine proteases. Despite sharing the same cystatin fold, and inhibiting cysteine proteases through the same tripartite edge involving highly conserved N-terminal region, L1 and L2 loop; cystatins differ widely in their inhibitory affinity towards C1 family of cysteine proteases and molecular details of these interactions are still elusive. In this study, inhibitory interactions of human family 1 & 2 cystatins with cathepsin L1 are predicted and their stability and viability are verified through protein docking & comparative molecular dynamics. An overall stabilization effect is observed in all cystatins on complex formation. Complexes are mostly dominated by van der Waals interaction but the relative participation of the conserved regions varied extensively. While van der Waals contacts prevail in L1 and L2 loop, N-terminal segment chiefly acts as electrostatic interaction site. In fact the comparative dynamics study points towards the instrumental role of L1 loop in directing the total interaction profile of the complex either towards electrostatic or van der Waals contacts. The key amino acid residues surfaced via interaction energy, hydrogen bonding and solvent accessible surface area analysis for each cystatin-cathepsin L1 complex influence the mode of binding and thus control the diverse inhibitory affinity of cystatins towards cysteine proteases.

  7. Asymmetry of 3H- imipramine binding may predict psychiatric illness

    International Nuclear Information System (INIS)

    Demeter, E.; Tekes, K.; Majorossy, K.; Palkovits, M.; Soos, M.; Magyar, K.; Somogyl, E.

    1989-01-01

    The B/sub max/ and Kd values for 3 H-imipramine binding were measured in post-mortem human brains from drug-free selected psychiatric subject homicide victims and normal controls. The two groups were comparable in age and gender. The number of imipramine binding sites in the frontal cortices of psychiatric subjects had significantly higher B/sub max/ values in the left hemisphere than in the right hemisphere. Inversely, the number of imipramine binding sites in the frontal cortices of normal controls were significantly higher in the right brain than in the left brain. It was postulated that the inhibiting effect of central serotonin has weakened in psychiatric cases, therefore the changes of presynaptic serotonergic activity might be associated with psychiatric illness in the left hemisphere of human brain

  8. Neural Network Prediction of Disruptions Caused by Locked Modes on J-TEXT Tokamak

    International Nuclear Information System (INIS)

    Ding Yonghua; Jin Xuesong; Chen Zhenzhen; Zhuang Ge

    2013-01-01

    Prediction of disruptions caused by locked modes using the Back-Propagation (BP) neural network is completed on J-TEXT tokamak. The network, which is based on the BP neural network, uses Mirnov coils and locked mode coils signals as input data, and outputs a signal including information of prediction of locked mode. The rate of successful prediction of locked modes is more than 90%. For intrinsic locked mode disruptions, the network can give a prewarning signal about 1 ms ahead of the locking-time. For the disruption caused by resonant magnetic perturbation (RMPs) locked modes, the network can give a prewarning signal about 10 ms ahead of the locking-time

  9. A Deep Learning Prediction Model Based on Extreme-Point Symmetric Mode Decomposition and Cluster Analysis

    OpenAIRE

    Li, Guohui; Zhang, Songling; Yang, Hong

    2017-01-01

    Aiming at the irregularity of nonlinear signal and its predicting difficulty, a deep learning prediction model based on extreme-point symmetric mode decomposition (ESMD) and clustering analysis is proposed. Firstly, the original data is decomposed by ESMD to obtain the finite number of intrinsic mode functions (IMFs) and residuals. Secondly, the fuzzy c-means is used to cluster the decomposed components, and then the deep belief network (DBN) is used to predict it. Finally, the reconstructed ...

  10. Friction stress effects on mode I crack growth predictions

    NARCIS (Netherlands)

    Chen, Q.; Deshpande, V.S.; Giessen, E. van der; Needleman, A.

    2003-01-01

    The effect of a lattice friction stress on the monotonic growth of a plane strain mode I crack under small-scale yielding conditions is analyzed using discrete dislocation plasticity. When the friction stress is increased from zero to half the dislocation nucleation stress, the crack tip stress

  11. Prediction of the binding affinities of peptides to class II MHC using a regularized thermodynamic model

    Directory of Open Access Journals (Sweden)

    Mittelmann Hans D

    2010-01-01

    Full Text Available Abstract Background The binding of peptide fragments of extracellular peptides to class II MHC is a crucial event in the adaptive immune response. Each MHC allotype generally binds a distinct subset of peptides and the enormous number of possible peptide epitopes prevents their complete experimental characterization. Computational methods can utilize the limited experimental data to predict the binding affinities of peptides to class II MHC. Results We have developed the Regularized Thermodynamic Average, or RTA, method for predicting the affinities of peptides binding to class II MHC. RTA accounts for all possible peptide binding conformations using a thermodynamic average and includes a parameter constraint for regularization to improve accuracy on novel data. RTA was shown to achieve higher accuracy, as measured by AUC, than SMM-align on the same data for all 17 MHC allotypes examined. RTA also gave the highest accuracy on all but three allotypes when compared with results from 9 different prediction methods applied to the same data. In addition, the method correctly predicted the peptide binding register of 17 out of 18 peptide-MHC complexes. Finally, we found that suboptimal peptide binding registers, which are often ignored in other prediction methods, made significant contributions of at least 50% of the total binding energy for approximately 20% of the peptides. Conclusions The RTA method accurately predicts peptide binding affinities to class II MHC and accounts for multiple peptide binding registers while reducing overfitting through regularization. The method has potential applications in vaccine design and in understanding autoimmune disorders. A web server implementing the RTA prediction method is available at http://bordnerlab.org/RTA/.

  12. An Overview of the Prediction of Protein DNA-Binding Sites

    Directory of Open Access Journals (Sweden)

    Jingna Si

    2015-03-01

    Full Text Available Interactions between proteins and DNA play an important role in many essential biological processes such as DNA replication, transcription, splicing, and repair. The identification of amino acid residues involved in DNA-binding sites is critical for understanding the mechanism of these biological activities. In the last decade, numerous computational approaches have been developed to predict protein DNA-binding sites based on protein sequence and/or structural information, which play an important role in complementing experimental strategies. At this time, approaches can be divided into three categories: sequence-based DNA-binding site prediction, structure-based DNA-binding site prediction, and homology modeling and threading. In this article, we review existing research on computational methods to predict protein DNA-binding sites, which includes data sets, various residue sequence/structural features, machine learning methods for comparison and selection, evaluation methods, performance comparison of different tools, and future directions in protein DNA-binding site prediction. In particular, we detail the meta-analysis of protein DNA-binding sites. We also propose specific implications that are likely to result in novel prediction methods, increased performance, or practical applications.

  13. An overview of the prediction of protein DNA-binding sites.

    Science.gov (United States)

    Si, Jingna; Zhao, Rui; Wu, Rongling

    2015-03-06

    Interactions between proteins and DNA play an important role in many essential biological processes such as DNA replication, transcription, splicing, and repair. The identification of amino acid residues involved in DNA-binding sites is critical for understanding the mechanism of these biological activities. In the last decade, numerous computational approaches have been developed to predict protein DNA-binding sites based on protein sequence and/or structural information, which play an important role in complementing experimental strategies. At this time, approaches can be divided into three categories: sequence-based DNA-binding site prediction, structure-based DNA-binding site prediction, and homology modeling and threading. In this article, we review existing research on computational methods to predict protein DNA-binding sites, which includes data sets, various residue sequence/structural features, machine learning methods for comparison and selection, evaluation methods, performance comparison of different tools, and future directions in protein DNA-binding site prediction. In particular, we detail the meta-analysis of protein DNA-binding sites. We also propose specific implications that are likely to result in novel prediction methods, increased performance, or practical applications.

  14. Binding Mode and Structure-Activity Relationships of ITE as an Aryl Hydrocarbon Receptor (AhR) Agonist.

    Science.gov (United States)

    Dolciami, Daniela; Gargaro, Marco; Cerra, Bruno; Scalisi, Giulia; Bagnoli, Luana; Servillo, Giuseppe; Fazia, Maria Agnese Della; Puccetti, Paolo; Quintana, Francisco J; Fallarino, Francesca; Macchiarulo, Antonio

    2018-02-06

    Discovered as a modulator of the toxic response to environmental pollutants, aryl hydrocarbon receptor (AhR) has recently gained attention for its involvement in various physiological and pathological pathways. AhR is a ligand-dependent transcription factor activated by a large array of chemical compounds, which include metabolites of l-tryptophan (l-Trp) catabolism as endogenous ligands of the receptor. Among these, 2-(1'H-indole-3'-carbonyl)thiazole-4-carboxylic acid methyl ester (ITE) has attracted interest in the scientific community, being endowed with nontoxic, immunomodulatory, and anticancer AhR-mediated functions. So far, no information about the binding mode and interactions of ITE with AhR is available. In this study, we used docking and molecular dynamics to propose a putative binding mode of ITE into the ligand binding pocket of AhR. Mutagenesis studies were then instrumental in validating the proposed binding mode, identifying His 285 and Tyr 316 as important key residues for ligand-dependent receptor activation. Finally, a set of ITE analogues was synthesized and tested to further probe molecular interactions of ITE to AhR and characterize the relevance of specific functional groups in the chemical structure for receptor activity. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Homology modeling of Homo sapiens lipoic acid synthase: Substrate docking and insights on its binding mode.

    Science.gov (United States)

    Krishnamoorthy, Ezhilarasi; Hassan, Sameer; Hanna, Luke Elizabeth; Padmalayam, Indira; Rajaram, Rama; Viswanathan, Vijay

    2017-05-07

    Lipoic acid synthase (LIAS) is an iron-sulfur cluster mitochondrial enzyme which catalyzes the final step in the de novo pathway for the biosynthesis of lipoic acid, a potent antioxidant. Recently there has been significant interest in its role in metabolic diseases and its deficiency in LIAS expression has been linked to conditions such as diabetes, atherosclerosis and neonatal-onset epilepsy, suggesting a strong inverse correlation between LIAS reduction and disease status. In this study we use a bioinformatics approach to predict its structure, which would be helpful to understanding its role. A homology model for LIAS protein was generated using X-ray crystallographic structure of Thermosynechococcus elongatus BP-1 (PDB ID: 4U0P). The predicted structure has 93% of the residues in the most favour region of Ramachandran plot. The active site of LIAS protein was mapped and docked with S-Adenosyl Methionine (SAM) using GOLD software. The LIAS-SAM complex was further refined using molecular dynamics simulation within the subsite 1 and subsite 3 of the active site. To the best of our knowledge, this is the first study to report a reliable homology model of LIAS protein. This study will facilitate a better understanding mode of action of the enzyme-substrate complex for future studies in designing drugs that can target LIAS protein. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Structure-based Understanding of Binding Affinity and Mode of Estrogen Receptor α Agonists and Antagonists.

    Science.gov (United States)

    The flexible hydrophobic ligand binding pocket (LBP) of estrogen receptor α (ERα) allows the binding of a wide variety of endocrine disruptors. Upon ligand binding, the LBP reshapes around the contours of the ligand and stabilizes the complex by complementary hydrophobic interact...

  17. Multiple ligand-binding modes in bacterial R67 dihydrofolate reductase

    Science.gov (United States)

    Alonso, Hernán; Gillies, Malcolm B.; Cummins, Peter L.; Bliznyuk, Andrey A.; Gready, Jill E.

    2005-03-01

    R67 dihydrofolate reductase (DHFR), a bacterial plasmid-encoded enzyme associated with resistance to the drug trimethoprim, shows neither sequence nor structural homology with the chromosomal DHFR. It presents a highly symmetrical toroidal structure, where four identical monomers contribute to the unique central active-site pore. Two reactants (dihydrofolate, DHF), two cofactors (NADPH) or one of each (R67•DHF•NADPH) can be found simultaneously within the active site, the last one being the reactive ternary complex. As the positioning of the ligands has proven elusive to empirical determination, we addressed the problem from a theoretical perspective. Several potential structures of the ternary complex were generated using the docking programs AutoDock and FlexX. The variability among the final poses, many of which conformed to experimental data, prompted us to perform a comparative scoring analysis and molecular dynamics simulations to assess the stability of the complexes. Analysis of ligand-ligand and ligand-protein interactions along the 4 ns trajectories of eight different structures allowed us to identify important inter-ligand contacts and key protein residues. Our results, combined with published empirical data, clearly suggest that multipe binding modes of the ligands are possible within R67 DHFR. While the pterin ring of DHF and the nicotinamide ring of NADPH assume a stacked endo-conformation at the centre of the pore, probably assisted by V66, Q67 and I68, the tails of the molecules extend towards opposite ends of the cavity, adopting multiple configurations in a solvent rich-environment where hydrogen-bond interactions with K32 and Y69 may play important roles.

  18. Expression, purification and DNA-binding activities of two putative ModE proteins of Herbaspirillum seropedicae (Burkholderiales, Oxalobacteraceae

    Directory of Open Access Journals (Sweden)

    André L.F. Souza

    2008-01-01

    Full Text Available In prokaryotes molybdenum is taken up by a high-affinity ABC-type transporter system encoded by the modABC genes. The endophyte β-Proteobacterium Herbaspirillum seropedicae has two modABC gene clusters and two genes encoding putative Mo-dependent regulator proteins (ModE1 and ModE2. Analysis of the amino acid sequence of the ModE1 protein of H. seropedicae revealed the presence of an N-terminal domain containing a DNA-binding helix-turn-helix motif (HTH and a C-terminal domain with a molybdate-binding motif. The second putative regulator protein, ModE2, contains only the helix-turn-helix motif, similar to that observed in some sequenced genomes. We cloned the modE1 (810 bp and modE2 (372 bp genes and expressed them in Escherichia coli as His-tagged fusion proteins, which we subsequently purified. The over-expressed recombinant His-ModE1 was insoluble and was purified after solubilization with urea and then on-column refolded during affinity chromatography. The His-ModE2 was expressed as a soluble protein and purified by affinity chromatography. These purified proteins were analyzed by DNA band-shift assays using the modA2 promoter region as probe. Our results indicate that His-ModE1 and His-ModE2 are able to bind to the modA2 promoter region, suggesting that both proteins may play a role in the regulation of molybdenum uptake and metabolism in H. seropedicae.

  19. Probe the Binding Mode of Aristololactam-β-D-glucoside to Phenylalanine Transfer RNA in Silico

    DEFF Research Database (Denmark)

    Xiao, Xingqing; Zhao, Binwu; Yang, Li

    2016-01-01

    Understanding the interactions of drug molecules with biomacromolecules at a micro-scale level is essential to design potent drugs for the treatments of human genome diseases. To unravel the mechanism of binding of aristololactam-β-D-glucoside (ADG) and phenylalanine transfer RNA (t...... on the tRNAPhe, and atomistic MD simulations were conducted to examine the thermal stability of five predicted binding poses for the complex of ADG and the tRNAPhe. The binding free energies of the five complexes were then calculated using the molecular mechanics/generalized born surface area approach...

  20. MAPPIN: a method for annotating, predicting pathogenicity and mode of inheritance for nonsynonymous variants.

    Science.gov (United States)

    Gosalia, Nehal; Economides, Aris N; Dewey, Frederick E; Balasubramanian, Suganthi

    2017-10-13

    Nonsynonymous single nucleotide variants (nsSNVs) constitute about 50% of known disease-causing mutations and understanding their functional impact is an area of active research. Existing algorithms predict pathogenicity of nsSNVs; however, they are unable to differentiate heterozygous, dominant disease-causing variants from heterozygous carrier variants that lead to disease only in the homozygous state. Here, we present MAPPIN (Method for Annotating, Predicting Pathogenicity, and mode of Inheritance for Nonsynonymous variants), a prediction method which utilizes a random forest algorithm to distinguish between nsSNVs with dominant, recessive, and benign effects. We apply MAPPIN to a set of Mendelian disease-causing mutations and accurately predict pathogenicity for all mutations. Furthermore, MAPPIN predicts mode of inheritance correctly for 70.3% of nsSNVs. MAPPIN also correctly predicts pathogenicity for 87.3% of mutations from the Deciphering Developmental Disorders Study with a 78.5% accuracy for mode of inheritance. When tested on a larger collection of mutations from the Human Gene Mutation Database, MAPPIN is able to significantly discriminate between mutations in known dominant and recessive genes. Finally, we demonstrate that MAPPIN outperforms CADD and Eigen in predicting disease inheritance modes for all validation datasets. To our knowledge, MAPPIN is the first nsSNV pathogenicity prediction algorithm that provides mode of inheritance predictions, adding another layer of information for variant prioritization. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  1. Predicting Flavin and Nicotinamide Adenine Dinucleotide-Binding Sites in Proteins Using the Fragment Transformation Method

    Directory of Open Access Journals (Sweden)

    Chih-Hao Lu

    2015-01-01

    Full Text Available We developed a computational method to identify NAD- and FAD-binding sites in proteins. First, we extracted from the Protein Data Bank structures of proteins that bind to at least one of these ligands. NAD-/FAD-binding residue templates were then constructed by identifying binding residues through the ligand-binding database BioLiP. The fragment transformation method was used to identify structures within query proteins that resembled the ligand-binding templates. By comparing residue types and their relative spatial positions, potential binding sites were identified and a ligand-binding potential for each residue was calculated. Setting the false positive rate at 5%, our method predicted NAD- and FAD-binding sites at true positive rates of 67.1% and 68.4%, respectively. Our method provides excellent results for identifying FAD- and NAD-binding sites in proteins, and the most important is that the requirement of conservation of residue types and local structures in the FAD- and NAD-binding sites can be verified.

  2. Computational Studies of Difference in Binding Modes of Peptide and Non-Peptide Inhibitors to MDM2/MDMX Based on Molecular Dynamics Simulations

    Directory of Open Access Journals (Sweden)

    Yuxin Zhang

    2012-02-01

    Full Text Available Inhibition of p53-MDM2/MDMX interaction is considered to be a promising strategy for anticancer drug design to activate wild-type p53 in tumors. We carry out molecular dynamics (MD simulations to study the binding mechanisms of peptide and non-peptide inhibitors to MDM2/MDMX. The rank of binding free energies calculated by molecular mechanics generalized Born surface area (MM-GBSA method agrees with one of the experimental values. The results suggest that van der Waals energy drives two kinds of inhibitors to MDM2/MDMX. We also find that the peptide inhibitors can produce more interaction contacts with MDM2/MDMX than the non-peptide inhibitors. Binding mode predictions based on the inhibitor-residue interactions show that the π–π, CH–π and CH–CH interactions dominated by shape complimentarity, govern the binding of the inhibitors in the hydrophobic cleft of MDM2/MDMX. Our studies confirm the residue Tyr99 in MDMX can generate a steric clash with the inhibitors due to energy and structure. This finding may theoretically provide help to develop potent dual-specific or MDMX inhibitors.

  3. Absolute analytical prediction of photonic crystal guided mode resonance wavelengths

    DEFF Research Database (Denmark)

    Hermannsson, Pétur Gordon; Vannahme, Christoph; Smith, Cameron

    2014-01-01

    numerically with methods such as rigorous coupled wave analysis. Here it is demonstrated how the absolute resonance wavelengths of such structures can be predicted by analytically modeling them as slab waveguides in which the propagation constant is determined by a phase matching condition. The model...... is experimentally verified to be capable of predicting the absolute resonance wavelengths to an accuracy of within 0.75 nm, as well as resonance wavelength shifts due to changes in cladding index within an accuracy of 0.45 nm across the visible wavelength regime in the case where material dispersion is taken...

  4. Discovery of a Potent Class of PI3Kα Inhibitors with Unique Binding Mode via Encoded Library Technology (ELT).

    Science.gov (United States)

    Yang, Hongfang; Medeiros, Patricia F; Raha, Kaushik; Elkins, Patricia; Lind, Kenneth E; Lehr, Ruth; Adams, Nicholas D; Burgess, Joelle L; Schmidt, Stanley J; Knight, Steven D; Auger, Kurt R; Schaber, Michael D; Franklin, G Joseph; Ding, Yun; DeLorey, Jennifer L; Centrella, Paolo A; Mataruse, Sibongile; Skinner, Steven R; Clark, Matthew A; Cuozzo, John W; Evindar, Ghotas

    2015-05-14

    In the search of PI3K p110α wild type and H1047R mutant selective small molecule leads, an encoded library technology (ELT) campaign against the desired target proteins was performed which led to the discovery of a selective chemotype for PI3K isoforms from a three-cycle DNA encoded library. An X-ray crystal structure of a representative inhibitor from this chemotype demonstrated a unique binding mode in the p110α protein.

  5. Assessing the model transferability for prediction of transcription factor binding sites based on chromatin accessibility.

    Science.gov (United States)

    Liu, Sheng; Zibetti, Cristina; Wan, Jun; Wang, Guohua; Blackshaw, Seth; Qian, Jiang

    2017-07-27

    Computational prediction of transcription factor (TF) binding sites in different cell types is challenging. Recent technology development allows us to determine the genome-wide chromatin accessibility in various cellular and developmental contexts. The chromatin accessibility profiles provide useful information in prediction of TF binding events in various physiological conditions. Furthermore, ChIP-Seq analysis was used to determine genome-wide binding sites for a range of different TFs in multiple cell types. Integration of these two types of genomic information can improve the prediction of TF binding events. We assessed to what extent a model built upon on other TFs and/or other cell types could be used to predict the binding sites of TFs of interest. A random forest model was built using a set of cell type-independent features such as specific sequences recognized by the TFs and evolutionary conservation, as well as cell type-specific features derived from chromatin accessibility data. Our analysis suggested that the models learned from other TFs and/or cell lines performed almost as well as the model learned from the target TF in the cell type of interest. Interestingly, models based on multiple TFs performed better than single-TF models. Finally, we proposed a universal model, BPAC, which was generated using ChIP-Seq data from multiple TFs in various cell types. Integrating chromatin accessibility information with sequence information improves prediction of TF binding.The prediction of TF binding is transferable across TFs and/or cell lines suggesting there are a set of universal "rules". A computational tool was developed to predict TF binding sites based on the universal "rules".

  6. Using TESS to predict transcription factor binding sites in DNA sequence.

    Science.gov (United States)

    Schug, Jonathan

    2008-03-01

    This unit describes how to use the Transcription Element Search System (TESS). This Web site predicts transcription factor binding sites (TFBS) in DNA sequence using two different kinds of models of sites, strings and positional weight matrices. The binding of transcription factors to DNA is a major part of the control of gene expression. Transcription factors exhibit sequence-specific binding; they form stronger bonds to some DNA sequences than to others. Identification of a good binding site in the promoter for a gene suggests the possibility that the corresponding factor may play a role in the regulation of that gene. However, the sequences transcription factors recognize are typically short and allow for some amount of mismatch. Because of this, binding sites for a factor can typically be found at random every few hundred to a thousand base pairs. TESS has features to help sort through and evaluate the significance of predicted sites.

  7. Binding Ligand Prediction for Proteins Using Partial Matching of Local Surface Patches

    Directory of Open Access Journals (Sweden)

    Lee Sael

    2010-12-01

    Full Text Available Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

  8. Binding ligand prediction for proteins using partial matching of local surface patches.

    Science.gov (United States)

    Sael, Lee; Kihara, Daisuke

    2010-01-01

    Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

  9. Towards Automated Binding Affinity Prediction Using an Iterative Linear Interaction Energy Approach

    Directory of Open Access Journals (Sweden)

    C. Ruben Vosmeer

    2014-01-01

    Full Text Available Binding affinity prediction of potential drugs to target and off-target proteins is an essential asset in drug development. These predictions require the calculation of binding free energies. In such calculations, it is a major challenge to properly account for both the dynamic nature of the protein and the possible variety of ligand-binding orientations, while keeping computational costs tractable. Recently, an iterative Linear Interaction Energy (LIE approach was introduced, in which results from multiple simulations of a protein-ligand complex are combined into a single binding free energy using a Boltzmann weighting-based scheme. This method was shown to reach experimental accuracy for flexible proteins while retaining the computational efficiency of the general LIE approach. Here, we show that the iterative LIE approach can be used to predict binding affinities in an automated way. A workflow was designed using preselected protein conformations, automated ligand docking and clustering, and a (semi-automated molecular dynamics simulation setup. We show that using this workflow, binding affinities of aryloxypropanolamines to the malleable Cytochrome P450 2D6 enzyme can be predicted without a priori knowledge of dominant protein-ligand conformations. In addition, we provide an outlook for an approach to assess the quality of the LIE predictions, based on simulation outcomes only.

  10. Prediction of small molecule binding property of protein domains with Bayesian classifiers based on Markov chains.

    Science.gov (United States)

    Bulashevska, Alla; Stein, Martin; Jackson, David; Eils, Roland

    2009-12-01

    Accurate computational methods that can help to predict biological function of a protein from its sequence are of great interest to research biologists and pharmaceutical companies. One approach to assume the function of proteins is to predict the interactions between proteins and other molecules. In this work, we propose a machine learning method that uses a primary sequence of a domain to predict its propensity for interaction with small molecules. By curating the Pfam database with respect to the small molecule binding ability of its component domains, we have constructed a dataset of small molecule binding and non-binding domains. This dataset was then used as training set to learn a Bayesian classifier, which should distinguish members of each class. The domain sequences of both classes are modelled with Markov chains. In a Jack-knife test, our classification procedure achieved the predictive accuracies of 77.2% and 66.7% for binding and non-binding classes respectively. We demonstrate the applicability of our classifier by using it to identify previously unknown small molecule binding domains. Our predictions are available as supplementary material and can provide very useful information to drug discovery specialists. Given the ubiquitous and essential role small molecules play in biological processes, our method is important for identifying pharmaceutically relevant components of complete proteomes. The software is available from the author upon request.

  11. Adaboost Ensemble with Simple Genetic Algorithm for Student Prediction Mode

    OpenAIRE

    AhmedSharaf ElDen; ElDen1Malaka A. Moustafa2Hany; M. Harb; AbdelH.Emara

    2013-01-01

    Predicting the student performance is a great concern to the higher education managements.Thisprediction helps to identify and to improve students' performance.Several factors may improve thisperformance.In the present study, we employ the data mining processes, particularly classification, toenhance the quality of the higher educational system. Recently, a new direction is used for the improvementof the classification accuracy by combining classifiers.In thispaper, we design and evaluate a f...

  12. SABinder: A Web Service for Predicting Streptavidin-Binding Peptides.

    Science.gov (United States)

    He, Bifang; Kang, Juanjuan; Ru, Beibei; Ding, Hui; Zhou, Peng; Huang, Jian

    2016-01-01

    Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p binders. In either case, it will be helpful and can benefit related scientific community.

  13. Predictable and unpredictable modes of seasonal mean precipitation over Northeast China

    Science.gov (United States)

    Ying, Kairan; Frederiksen, Carsten S.; Zhao, Tianbao; Zheng, Xiaogu; Xiong, Zhe; Yi, Xue; Li, Chunxiang

    2018-04-01

    This study investigates the patterns of interannual variability that arise from the potentially predictable (slow) and unpredictable (intraseasonal) components of seasonal mean precipitation over Northeast (NE) China, using observations from a network of 162 meteorological stations for the period 1961-2014. A variance decomposition method is applied to identify the sources of predictability, as well as the sources of prediction uncertainty, for January-February-March (JFM), April-May-June (AMJ), July-August-September (JAS) and October-November-December (OND). The averaged potential predictability (ratio of slow to total variance) of NE China precipitation has the highest value of 0.32 during JAS and lowest value of 0.1 in AMJ. Possible sources of seasonal prediction for the leading predictable precipitation EOF modes come from the SST anomalies in the Japan Sea, as well as the North Atlantic during JFM, the Indian Ocean SST in AMJ, and the eastern tropical Pacific SST in JAS and OND. The prolonged linear trend, which is seen in the principal component time series of the leading predictable mode in JFM and OND, may also serve as a source of predictability. The Polar-Eurasia and Northern Annular Mode atmospheric teleconnection patterns are closely connected with the leading and the second predictable mode of JAS, respectively. The Hadley cell circulation is closely related to the leading predictable mode of OND. The leading/second unpredictable precipitation modes for all these four seasons show a similar monopole/dipole structure, and can be largely attributed to the intraseasonal variabilities of the atmosphere.

  14. Predicting peptides binding to MHC class II molecules using multi-objective evolutionary algorithms

    Directory of Open Access Journals (Sweden)

    Feng Lin

    2007-11-01

    Full Text Available Abstract Background Peptides binding to Major Histocompatibility Complex (MHC class II molecules are crucial for initiation and regulation of immune responses. Predicting peptides that bind to a specific MHC molecule plays an important role in determining potential candidates for vaccines. The binding groove in class II MHC is open at both ends, allowing peptides longer than 9-mer to bind. Finding the consensus motif facilitating the binding of peptides to a MHC class II molecule is difficult because of different lengths of binding peptides and varying location of 9-mer binding core. The level of difficulty increases when the molecule is promiscuous and binds to a large number of low affinity peptides. In this paper, we propose two approaches using multi-objective evolutionary algorithms (MOEA for predicting peptides binding to MHC class II molecules. One uses the information from both binders and non-binders for self-discovery of motifs. The other, in addition, uses information from experimentally determined motifs for guided-discovery of motifs. Results The proposed methods are intended for finding peptides binding to MHC class II I-Ag7 molecule – a promiscuous binder to a large number of low affinity peptides. Cross-validation results across experiments on two motifs derived for I-Ag7 datasets demonstrate better generalization abilities and accuracies of the present method over earlier approaches. Further, the proposed method was validated and compared on two publicly available benchmark datasets: (1 an ensemble of qualitative HLA-DRB1*0401 peptide data obtained from five different sources, and (2 quantitative peptide data obtained for sixteen different alleles comprising of three mouse alleles and thirteen HLA alleles. The proposed method outperformed earlier methods on most datasets, indicating that it is well suited for finding peptides binding to MHC class II molecules. Conclusion We present two MOEA-based algorithms for finding motifs

  15. Using sequence-specific chemical and structural properties of DNA to predict transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Amy L Bauer

    2010-11-01

    Full Text Available An important step in understanding gene regulation is to identify the DNA binding sites recognized by each transcription factor (TF. Conventional approaches to prediction of TF binding sites involve the definition of consensus sequences or position-specific weight matrices and rely on statistical analysis of DNA sequences of known binding sites. Here, we present a method called SiteSleuth in which DNA structure prediction, computational chemistry, and machine learning are applied to develop models for TF binding sites. In this approach, binary classifiers are trained to discriminate between true and false binding sites based on the sequence-specific chemical and structural features of DNA. These features are determined via molecular dynamics calculations in which we consider each base in different local neighborhoods. For each of 54 TFs in Escherichia coli, for which at least five DNA binding sites are documented in RegulonDB, the TF binding sites and portions of the non-coding genome sequence are mapped to feature vectors and used in training. According to cross-validation analysis and a comparison of computational predictions against ChIP-chip data available for the TF Fis, SiteSleuth outperforms three conventional approaches: Match, MATRIX SEARCH, and the method of Berg and von Hippel. SiteSleuth also outperforms QPMEME, a method similar to SiteSleuth in that it involves a learning algorithm. The main advantage of SiteSleuth is a lower false positive rate.

  16. Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.

    Science.gov (United States)

    Tsai, Zing Tsung-Yeh; Shiu, Shin-Han; Tsai, Huai-Kuang

    2015-08-01

    Transcription factor (TF) binding is determined by the presence of specific sequence motifs (SM) and chromatin accessibility, where the latter is influenced by both chromatin state (CS) and DNA structure (DS) properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a "TF-agnostic" predictive model based on three DNA "intrinsic properties" (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy) that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome.

  17. Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.

    Directory of Open Access Journals (Sweden)

    Zing Tsung-Yeh Tsai

    2015-08-01

    Full Text Available Transcription factor (TF binding is determined by the presence of specific sequence motifs (SM and chromatin accessibility, where the latter is influenced by both chromatin state (CS and DNA structure (DS properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a "TF-agnostic" predictive model based on three DNA "intrinsic properties" (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome.

  18. Deep convolutional neural networks for pan-specific peptide-MHC class I binding prediction.

    Science.gov (United States)

    Han, Youngmahn; Kim, Dongsup

    2017-12-28

    Computational scanning of peptide candidates that bind to a specific major histocompatibility complex (MHC) can speed up the peptide-based vaccine development process and therefore various methods are being actively developed. Recently, machine-learning-based methods have generated successful results by training large amounts of experimental data. However, many machine learning-based methods are generally less sensitive in recognizing locally-clustered interactions, which can synergistically stabilize peptide binding. Deep convolutional neural network (DCNN) is a deep learning method inspired by visual recognition process of animal brain and it is known to be able to capture meaningful local patterns from 2D images. Once the peptide-MHC interactions can be encoded into image-like array(ILA) data, DCNN can be employed to build a predictive model for peptide-MHC binding prediction. In this study, we demonstrated that DCNN is able to not only reliably predict peptide-MHC binding, but also sensitively detect locally-clustered interactions. Nonapeptide-HLA-A and -B binding data were encoded into ILA data. A DCNN, as a pan-specific prediction model, was trained on the ILA data. The DCNN showed higher performance than other prediction tools for the latest benchmark datasets, which consist of 43 datasets for 15 HLA-A alleles and 25 datasets for 10 HLA-B alleles. In particular, the DCNN outperformed other tools for alleles belonging to the HLA-A3 supertype. The F1 scores of the DCNN were 0.86, 0.94, and 0.67 for HLA-A*31:01, HLA-A*03:01, and HLA-A*68:01 alleles, respectively, which were significantly higher than those of other tools. We found that the DCNN was able to recognize locally-clustered interactions that could synergistically stabilize peptide binding. We developed ConvMHC, a web server to provide user-friendly web interfaces for peptide-MHC class I binding predictions using the DCNN. ConvMHC web server can be accessible via http://jumong.kaist.ac.kr:8080/convmhc

  19. Glycosaminoglycans are interactants of Langerin: comparison with gp120 highlights an unexpected calcium-independent binding mode.

    Science.gov (United States)

    Chabrol, Eric; Nurisso, Alessandra; Daina, Antoine; Vassal-Stermann, Emilie; Thepaut, Michel; Girard, Eric; Vivès, Romain R; Fieschi, Franck

    2012-01-01

    Langerin is a C-type lectin specifically expressed in Langerhans cells. As recently shown for HIV, Langerin is thought to capture pathogens and mediate their internalisation into Birbeck Granules for elimination. However, the precise functions of Langerin remain elusive, mostly because of the lack of information on its binding properties and physiological ligands. Based on recent reports that Langerin binds to sulfated sugars, we conducted here a comparative analysis of Langerin interaction with mannose-rich HIV glycoprotein gp120 and glycosaminoglycan (GAGs), a family of sulfated polysaccharides expressed at the surface of most mammalian cells. Our results first revealed that Langerin bound to these different glycans through very distinct mechanisms and led to the identification of a novel, GAG-specific binding mode within Langerin. In contrast to the canonical lectin domain, this new binding site showed no Ca(2+)-dependency, and could only be detected in entire, trimeric extracellular domains of Langerin. Interestingly binding to GAGs, did not simply rely on a net charge effect, but rather on more discrete saccharide features, such as 6-O-sulfation, or iduronic acid content. Using molecular modelling simulations, we proposed a model of Langerin/heparin complex, which located the GAG binding site at the interface of two of the three Carbohydrate-recognition domains of the protein, at the edge of the a-helix coiled-coil. To our knowledge, the binding properties that we have highlighted here for Langerin, have never been reported for C-type lectins before. These findings provide new insights towards the understanding of Langerin biological functions.

  20. Glycosaminoglycans are interactants of Langerin: comparison with gp120 highlights an unexpected calcium-independent binding mode.

    Directory of Open Access Journals (Sweden)

    Eric Chabrol

    Full Text Available Langerin is a C-type lectin specifically expressed in Langerhans cells. As recently shown for HIV, Langerin is thought to capture pathogens and mediate their internalisation into Birbeck Granules for elimination. However, the precise functions of Langerin remain elusive, mostly because of the lack of information on its binding properties and physiological ligands. Based on recent reports that Langerin binds to sulfated sugars, we conducted here a comparative analysis of Langerin interaction with mannose-rich HIV glycoprotein gp120 and glycosaminoglycan (GAGs, a family of sulfated polysaccharides expressed at the surface of most mammalian cells. Our results first revealed that Langerin bound to these different glycans through very distinct mechanisms and led to the identification of a novel, GAG-specific binding mode within Langerin. In contrast to the canonical lectin domain, this new binding site showed no Ca(2+-dependency, and could only be detected in entire, trimeric extracellular domains of Langerin. Interestingly binding to GAGs, did not simply rely on a net charge effect, but rather on more discrete saccharide features, such as 6-O-sulfation, or iduronic acid content. Using molecular modelling simulations, we proposed a model of Langerin/heparin complex, which located the GAG binding site at the interface of two of the three Carbohydrate-recognition domains of the protein, at the edge of the a-helix coiled-coil. To our knowledge, the binding properties that we have highlighted here for Langerin, have never been reported for C-type lectins before. These findings provide new insights towards the understanding of Langerin biological functions.

  1. PatchSurfers: Two methods for local molecular property-based binding ligand prediction.

    Science.gov (United States)

    Shin, Woong-Hee; Bures, Mark Gregory; Kihara, Daisuke

    2016-01-15

    Protein function prediction is an active area of research in computational biology. Function prediction can help biologists make hypotheses for characterization of genes and help interpret biological assays, and thus is a productive area for collaboration between experimental and computational biologists. Among various function prediction methods, predicting binding ligand molecules for a target protein is an important class because ligand binding events for a protein are usually closely intertwined with the proteins' biological function, and also because predicted binding ligands can often be directly tested by biochemical assays. Binding ligand prediction methods can be classified into two types: those which are based on protein-protein (or pocket-pocket) comparison, and those that compare a target pocket directly to ligands. Recently, our group proposed two computational binding ligand prediction methods, Patch-Surfer, which is a pocket-pocket comparison method, and PL-PatchSurfer, which compares a pocket to ligand molecules. The two programs apply surface patch-based descriptions to calculate similarity or complementarity between molecules. A surface patch is characterized by physicochemical properties such as shape, hydrophobicity, and electrostatic potentials. These properties on the surface are represented using three-dimensional Zernike descriptors (3DZD), which are based on a series expansion of a 3 dimensional function. Utilizing 3DZD for describing the physicochemical properties has two main advantages: (1) rotational invariance and (2) fast comparison. Here, we introduce Patch-Surfer and PL-PatchSurfer with an emphasis on PL-PatchSurfer, which is more recently developed. Illustrative examples of PL-PatchSurfer performance on binding ligand prediction as well as virtual drug screening are also provided. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. A community resource benchmarking predictions of peptide binding to MHC-I molecules.

    Science.gov (United States)

    Peters, Bjoern; Bui, Huynh-Hoa; Frankild, Sune; Nielson, Morten; Lundegaard, Claus; Kostem, Emrah; Basch, Derek; Lamberth, Kasper; Harndahl, Mikkel; Fleri, Ward; Wilson, Stephen S; Sidney, John; Lund, Ole; Buus, Soren; Sette, Alessandro

    2006-06-09

    Recognition of peptides bound to major histocompatibility complex (MHC) class I molecules by T lymphocytes is an essential part of immune surveillance. Each MHC allele has a characteristic peptide binding preference, which can be captured in prediction algorithms, allowing for the rapid scan of entire pathogen proteomes for peptide likely to bind MHC. Here we make public a large set of 48,828 quantitative peptide-binding affinity measurements relating to 48 different mouse, human, macaque, and chimpanzee MHC class I alleles. We use this data to establish a set of benchmark predictions with one neural network method and two matrix-based prediction methods extensively utilized in our groups. In general, the neural network outperforms the matrix-based predictions mainly due to its ability to generalize even on a small amount of data. We also retrieved predictions from tools publicly available on the internet. While differences in the data used to generate these predictions hamper direct comparisons, we do conclude that tools based on combinatorial peptide libraries perform remarkably well. The transparent prediction evaluation on this dataset provides tool developers with a benchmark for comparison of newly developed prediction methods. In addition, to generate and evaluate our own prediction methods, we have established an easily extensible web-based prediction framework that allows automated side-by-side comparisons of prediction methods implemented by experts. This is an advance over the current practice of tool developers having to generate reference predictions themselves, which can lead to underestimating the performance of prediction methods they are not as familiar with as their own. The overall goal of this effort is to provide a transparent prediction evaluation allowing bioinformaticians to identify promising features of prediction methods and providing guidance to immunologists regarding the reliability of prediction tools.

  3. SAAMBE: Webserver to Predict the Charge of Binding Free Energy Caused by Amino Acids Mutations.

    Science.gov (United States)

    Petukh, Marharyta; Dai, Luogeng; Alexov, Emil

    2016-04-12

    Predicting the effect of amino acid substitutions on protein-protein affinity (typically evaluated via the change of protein binding free energy) is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver, the Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) webserver, which addresses the demand for tools for predicting the change of protein binding free energy. SAAMBE is an easy to use webserver, which only requires that a coordinate file be inputted and the user is provided with various, but easy to navigate, options. The user specifies the mutation position, wild type residue and type of mutation to be made. The server predicts the binding free energy change, the changes of the corresponding energy components and provides the energy minimized 3D structure of the wild type and mutant proteins for download. The SAAMBE protocol performance was tested by benchmarking the predictions against over 1300 experimentally determined changes of binding free energy and a Pearson correlation coefficient of 0.62 was obtained. How the predictions can be used for discriminating disease-causing from harmless mutations is discussed. The webserver can be accessed via http://compbio.clemson.edu/saambe_webserver/.

  4. Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions

    DEFF Research Database (Denmark)

    Kim, Yohan; Sidney, John; Buus, Søren

    2014-01-01

    Background: It is important to accurately determine the performance of peptide: MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected error rate. Two common approaches to determine prediction performance...... are cross-validation, in which all available data are iteratively split into training and testing data, and the use of blind sets generated separately from the data used to construct the predictive method. In the present study, we have compared cross-validated prediction performances generated on our last...

  5. A web server for analysis, comparison and prediction of protein ligand binding sites.

    Science.gov (United States)

    Singh, Harinder; Srivastava, Hemant Kumar; Raghava, Gajendra P S

    2016-03-25

    One of the major challenges in the field of system biology is to understand the interaction between a wide range of proteins and ligands. In the past, methods have been developed for predicting binding sites in a protein for a limited number of ligands. In order to address this problem, we developed a web server named 'LPIcom' to facilitate users in understanding protein-ligand interaction. Analysis, comparison and prediction modules are available in the "LPIcom' server to predict protein-ligand interacting residues for 824 ligands. Each ligand must have at least 30 protein binding sites in PDB. Analysis module of the server can identify residues preferred in interaction and binding motif for a given ligand; for example residues glycine, lysine and arginine are preferred in ATP binding sites. Comparison module of the server allows comparing protein-binding sites of multiple ligands to understand the similarity between ligands based on their binding site. This module indicates that ATP, ADP and GTP ligands are in the same cluster and thus their binding sites or interacting residues exhibit a high level of similarity. Propensity-based prediction module has been developed for predicting ligand-interacting residues in a protein for more than 800 ligands. In addition, a number of web-based tools have been integrated to facilitate users in creating web logo and two-sample between ligand interacting and non-interacting residues. In summary, this manuscript presents a web-server for analysis of ligand interacting residue. This server is available for public use from URL http://crdd.osdd.net/raghava/lpicom .

  6. A comprehensive approach to ascertain the binding mode of curcumin with DNA

    Science.gov (United States)

    Haris, P.; Mary, Varughese; Aparna, P.; Dileep, K. V.; Sudarsanakumar, C.

    2017-03-01

    Curcumin is a natural phytochemical from the rhizoma of Curcuma longa, the popular Indian spice that exhibits a wide range of pharmacological properties like antioxidant, anticancer, anti-inflammatory, antitumor, and antiviral activities. In the published literatures we can see different studies and arguments on the interaction of curcumin with DNA. The intercalative binding, groove binding and no binding of curcumin with DNA were reported. In this context, we conducted a detailed study to understand the mechanism of recognition of dimethylsulfoxide-solubilized curcumin by DNA. The interaction of curcumin with calf thymus DNA (ctDNA) was confirmed by agarose gel electrophoresis. The nature of binding and energetics of interaction were studied by Isothermal Titration Calorimetry (ITC), Differential Scanning Calorimetry (DSC), UV-visible, fluorescence and melting temperature (Tm) analysis. The experimental data were compared with molecular modeling studies. Our investigation confirmed that dimethylsulfoxide-solubilized curcumin binds in the minor groove of the ctDNA without causing significant structural alteration to the DNA.

  7. Binding modes of dihydroquinoxalinones in a homology model of bradykinin receptor 1.

    Science.gov (United States)

    Ha, Sookhee N; Hey, Pat J; Ransom, Rick W; Harrell, C Meacham; Murphy, Kathryn L; Chang, Ray; Chen, Tsing-Bau; Su, Dai-Shi; Markowitz, M Kristine; Bock, Mark G; Freidinger, Roger M; Hess, Fred J

    2005-05-27

    We report the first homology model of human bradykinin receptor B1 generated from the crystal structure of bovine rhodopsin as a template. Using an automated docking procedure, two B1 receptor antagonists of the dihydroquinoxalinone structural class were docked into the receptor model. Site-directed mutagenesis data of the amino acid residues in TM1, TM3, TM6, and TM7 were incorporated to place the compounds in the binding site of the homology model of the human B1 bradykinin receptor. The best pose in agreement with the mutation data was selected for detailed study of the receptor-antagonist interaction. To test the model, the calculated antagonist-receptor binding energy was correlated with the experimentally measured binding affinity (K(i)) for nine dihydroquinoxalinone analogs. The model was used to gain insight into the molecular mechanism for receptor function and to optimize the dihydroquinoxalinone analogs.

  8. Analysis and Prediction of Sea Ice Evolution using Koopman Mode Decomposition Techniques

    Science.gov (United States)

    2018-04-30

    Resources: N/A TOTAL: $18,687 2 TECHNICAL STATUS REPORT Abstract The program goal is analysis of sea ice dynamical behavior using Koopman Mode Decompo...Title: Analysis and Prediction of Sea Ice Evolution using Koopman Mode Decomposition Techniques Subject: Monthly Progress Report Period of...Attn: Code 5596 4555 Overlook Avenue, SW Washington, D.C. 20375-5320 E-mail: reports@library.nrl.navy.mil Defense Technical Information Center

  9. Binding modes and pathway of RHPS4 to human telomeric G-quadruplex and duplex DNA probed by all-atom molecular dynamics simulations with explicit solvent.

    Science.gov (United States)

    Mulholland, Kelly; Siddiquei, Farzana; Wu, Chun

    2017-07-19

    RHPS4, a potent binder to human telomeric DNA G-quadruplex, shows high efficacy in tumor cell growth inhibition. However, it's preferential binding to DNA G-quadruplex over DNA duplex (about 10 fold) remains to be improved toward its clinical application. A high resolution structure of the single-stranded telomeric DNA G-quadruplexes, or B-DNA duplex, in complex with RHPS4 is not available yet, and the binding nature of this ligand to these DNA forms remains to be elusive. In this study, we carried out 40 μs molecular dynamics binding simulations with a free ligand to decipher the binding pathway of RHPS4 to a DNA duplex and three G-quadruplex folders (parallel, antiparallel and hybrid) of the human telomeric DNA sequence. The most stable binding mode identified for the duplex, parallel, antiparallel and hybrid G-quadruplexes is an intercalation, bottom stacking, top intercalation and bottom intercalation mode, respectively. The intercalation mode with similar binding strength to both the duplex and the G-quadruplexes, explains the lack of binding selectivity of RHPS4 to the G-quadruplex form. Therefore, a ligand modification that destabilizes the duplex intercalation mode but stabilizes the G-quadruplex intercalation mode will improve the binding selectivity toward G-quadruplex. The intercalation mode of RHPS4 to both the duplex and the antiparallel and the hybrid G-quadruplex follows a base flipping-insertion mechanism rather than an open-insertion mechanism. The groove binding, the side binding and the intercalation with flipping out of base were observed to be intermediate states before the full intercalation state with paired bases.

  10. Bridging Binding Modes of Phosphine-Stabilized Nitrous Oxide to Zn(C6F5)2

    NARCIS (Netherlands)

    Neu, Rebecca C.; Otten, Edwin; Stephan, Douglas W.

    2009-01-01

    Reaction of [tBu3PN2O(B(C6H4F)3)] with 1, 1.5, or 2 equivalents of Zn(C6F5)2 affords the species [{tBu3PN2OZn(C6F5)2}2], [{tBu3PN2OZn(C6F5)2}2Zn(C6F5)2], and [tBu3PN2O{Zn(C6F5)2}2] displaying unique binding modes of Zn to the phosphine-stabilized N2O fragment.

  11. Cell-type specificity of ChIP-predicted transcription factor binding sites

    Directory of Open Access Journals (Sweden)

    Håndstad Tony

    2012-08-01

    Full Text Available Abstract Background Context-dependent transcription factor (TF binding is one reason for differences in gene expression patterns between different cellular states. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq identifies genome-wide TF binding sites for one particular context—the cells used in the experiment. But can such ChIP-seq data predict TF binding in other cellular contexts and is it possible to distinguish context-dependent from ubiquitous TF binding? Results We compared ChIP-seq data on TF binding for multiple TFs in two different cell types and found that on average only a third of ChIP-seq peak regions are common to both cell types. Expectedly, common peaks occur more frequently in certain genomic contexts, such as CpG-rich promoters, whereas chromatin differences characterize cell-type specific TF binding. We also find, however, that genotype differences between the cell types can explain differences in binding. Moreover, ChIP-seq signal intensity and peak clustering are the strongest predictors of common peaks. Compared with strong peaks located in regions containing peaks for multiple transcription factors, weak and isolated peaks are less common between the cell types and are less associated with data that indicate regulatory activity. Conclusions Together, the results suggest that experimental noise is prevalent among weak peaks, whereas strong and clustered peaks represent high-confidence binding events that often occur in other cellular contexts. Nevertheless, 30-40% of the strongest and most clustered peaks show context-dependent regulation. We show that by combining signal intensity with additional data—ranging from context independent information such as binding site conservation and position weight matrix scores to context dependent chromatin structure—we can predict whether a ChIP-seq peak is likely to be present in other cellular contexts.

  12. Structure of Bacillus subtilis γ-glutamyltranspeptidase in complex with acivicin: diversity of the binding mode of a classical and electrophilic active-site-directed glutamate analogue

    International Nuclear Information System (INIS)

    Ida, Tomoyo; Suzuki, Hideyuki; Fukuyama, Keiichi; Hiratake, Jun; Wada, Kei

    2014-01-01

    The binding modes of acivicin, a classical and an electrophilic active-site-directed glutamate analogue, to bacterial γ-glutamyltranspeptidases were found to be diverse. γ-Glutamyltranspeptidase (GGT) is an enzyme that plays a central role in glutathione metabolism, and acivicin is a classical inhibitor of GGT. Here, the structure of acivicin bound to Bacillus subtilis GGT determined by X-ray crystallography to 1.8 Å resolution is presented, in which it binds to the active site in a similar manner to that in Helicobacter pylori GGT, but in a different binding mode to that in Escherichia coli GGT. In B. subtilis GGT, acivicin is bound covalently through its C3 atom with sp 2 hybridization to Thr403 O γ , the catalytic nucleophile of the enzyme. The results show that acivicin-binding sites are common, but the binding manners and orientations of its five-membered dihydroisoxazole ring are diverse in the binding pockets of GGTs

  13. Studies on Aryl-Substituted Phenylalanines: Synthesis, Activity, and Different Binding Modes at AMPA Receptors

    DEFF Research Database (Denmark)

    Szymanska, Ewa; Frydenvang, Karla Andrea; Pickering, Darryl S

    2016-01-01

    , not previously seen for amino acid-based AMPA receptor antagonists, X-ray crystal structures of both eutomers in complex with the GluA2 ligand binding domain were solved. The cocrystal structures of (S)-37 and (R)-38 showed similar interactions of the amino acid parts but unexpected and different orientations...

  14. Determination of Vanadium Binding Mode on Seawater-Contacted Polyamidoxime Adsorbents

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Zhicheng [Lawrence Berkeley National Laboratory (LBNL); Rao, Linfeng [Lawrence Berkeley National Laboratory (LBNL); Abney, Carter W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bryantsev, Vyacheslav [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ivanov, Aleksandr [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-09-01

    Adsorbents developed for the recovery of uranium from seawater display poor selectivity over other transition metals present in the ocean, with vanadium particularly problematic. To improve selectivity, an indispensable step is the positive identification of metal binding environments following actual seawater deployment. In this work we apply x-ray absorption fine structure (XAFS) spectroscopy to directly investigate the vanadium binding environment on seawater-deployed polyamidoxime adsorbents. Comparison of the x-ray absorption near edge spectra (XANES) reveal marked similarities to recently a reported non-oxido vanadium (V) structure formed upon binding with cyclic imidedioxime, a byproduct of generating amidoxime functionalities. Density functional theory (DFT) calculations provided a series of putative vanadium binding environments for both vanadium (IV) and vanadium (V) oxidation states, and with both amidoxime and cyclic imidedioxime. Fits of the extended XAFS (EXAFS) data confirmed vanadium (V) is bound exclusively by the cyclic imidedioxime moiety in a 1:2 metal:ligand fashion, though a modest structural distortion is also observed compared to crystal structure data and computationally optimized geometries which is attributed to morphology effects from the polymer graft chain and the absence of crystal packing interactions. These results demonstrate that improved selectivity for uranium over vanadium can be achieved by suppressing the formation of cyclic imidedioxime during preparation of polyamidoxime adsorbents for seawater uranium recovery.

  15. MHC2NNZ: A novel peptide binding prediction approach for HLA DQ molecules

    Science.gov (United States)

    Xie, Jiang; Zeng, Xu; Lu, Dongfang; Liu, Zhixiang; Wang, Jiao

    2017-07-01

    The major histocompatibility complex class II (MHC-II) molecule plays a crucial role in immunology. Computational prediction of MHC-II binding peptides can help researchers understand the mechanism of immune systems and design vaccines. Most of the prediction algorithms for MHC-II to date have made large efforts in human leukocyte antigen (HLA, the name of MHC in Human) molecules encoded in the DR locus. However, HLA DQ molecules are equally important and have only been made less progress because it is more difficult to handle them experimentally. In this study, we propose an artificial neural network-based approach called MHC2NNZ to predict peptides binding to HLA DQ molecules. Unlike previous artificial neural network-based methods, MHC2NNZ not only considers sequence similarity features but also captures the chemical and physical properties, and a novel method incorporating these properties is proposed to represent peptide flanking regions (PFR). Furthermore, MHC2NNZ improves the prediction accuracy by combining with amino acid preference at more specific positions of the peptides binding core. By evaluating on 3549 peptides binding to six most frequent HLA DQ molecules, MHC2NNZ is demonstrated to outperform other state-of-the-art MHC-II prediction methods.

  16. Effect of B-ring substitution pattern on binding mode of propionamide selective androgen receptor modulators.

    Science.gov (United States)

    Bohl, Casey E; Wu, Zengru; Chen, Jiyun; Mohler, Michael L; Yang, Jun; Hwang, Dong Jin; Mustafa, Suni; Miller, Duane D; Bell, Charles E; Dalton, James T

    2008-10-15

    Selective androgen receptor modulators (SARMs) are essentially prostate sparing androgens, which provide therapeutic potential in osteoporosis, male hormone replacement, and muscle wasting. Herein we report crystal structures of the androgen receptor (AR) ligand-binding domain (LBD) complexed to a series of potent synthetic nonsteroidal SARMs with a substituted pendant arene referred to as the B-ring. We found that hydrophilic B-ring para-substituted analogs exhibit an additional region of hydrogen bonding not seen with steroidal compounds and that multiple halogen substitutions affect the B-ring conformation and aromatic interactions with Trp741. This information elucidates interactions important for high AR binding affinity and provides new insight for structure-based drug design.

  17. HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.

    Science.gov (United States)

    Zaman, Rianon; Chowdhury, Shahana Yasmin; Rashid, Mahmood A; Sharma, Alok; Dehzangi, Abdollah; Shatabda, Swakkhar

    2017-01-01

    DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

  18. HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features

    Directory of Open Access Journals (Sweden)

    Rianon Zaman

    2017-01-01

    Full Text Available DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

  19. A Novel, “Double-Clamp” Binding Mode for Human Heme Oxygenase-1 Inhibition

    Science.gov (United States)

    Rahman, Mona N.; Vlahakis, Jason Z.; Vukomanovic, Dragic; Lee, Wallace; Szarek, Walter A.; Nakatsu, Kanji; Jia, Zongchao

    2012-01-01

    The development of heme oxygenase (HO) inhibitors is critical in dissecting and understanding the HO system and for potential therapeutic applications. We have established a program to design and optimize HO inhibitors using structure-activity relationships in conjunction with X-ray crystallographic analyses. One of our previous complex crystal structures revealed a putative secondary hydrophobic binding pocket which could be exploited for a new design strategy by introducing a functional group that would fit into this potential site. To test this hypothesis and gain further insights into the structural basis of inhibitor binding, we have synthesized and characterized 1-(1H-imidazol-1-yl)-4,4-diphenyl-2-butanone (QC-308). Using a carbon monoxide (CO) formation assay on rat spleen microsomes, the compound was found to be ∼15 times more potent (IC50 = 0.27±0.07 µM) than its monophenyl analogue, which is already a potent compound in its own right (QC-65; IC50 = 4.0±1.8 µM). The crystal structure of hHO-1 with QC-308 revealed that the second phenyl group in the western region of the compound is indeed accommodated by a definitive secondary proximal hydrophobic pocket. Thus, the two phenyl moieties are each stabilized by distinct hydrophobic pockets. This “double-clamp” binding offers additional inhibitor stabilization and provides a new route for improvement of human heme oxygenase inhibitors. PMID:22276118

  20. A novel, "double-clamp" binding mode for human heme oxygenase-1 inhibition.

    Directory of Open Access Journals (Sweden)

    Mona N Rahman

    Full Text Available The development of heme oxygenase (HO inhibitors is critical in dissecting and understanding the HO system and for potential therapeutic applications. We have established a program to design and optimize HO inhibitors using structure-activity relationships in conjunction with X-ray crystallographic analyses. One of our previous complex crystal structures revealed a putative secondary hydrophobic binding pocket which could be exploited for a new design strategy by introducing a functional group that would fit into this potential site. To test this hypothesis and gain further insights into the structural basis of inhibitor binding, we have synthesized and characterized 1-(1H-imidazol-1-yl-4,4-diphenyl-2-butanone (QC-308. Using a carbon monoxide (CO formation assay on rat spleen microsomes, the compound was found to be ∼15 times more potent (IC(50 = 0.27±0.07 µM than its monophenyl analogue, which is already a potent compound in its own right (QC-65; IC(50 = 4.0±1.8 µM. The crystal structure of hHO-1 with QC-308 revealed that the second phenyl group in the western region of the compound is indeed accommodated by a definitive secondary proximal hydrophobic pocket. Thus, the two phenyl moieties are each stabilized by distinct hydrophobic pockets. This "double-clamp" binding offers additional inhibitor stabilization and provides a new route for improvement of human heme oxygenase inhibitors.

  1. A novel, "double-clamp" binding mode for human heme oxygenase-1 inhibition.

    Science.gov (United States)

    Rahman, Mona N; Vlahakis, Jason Z; Vukomanovic, Dragic; Lee, Wallace; Szarek, Walter A; Nakatsu, Kanji; Jia, Zongchao

    2012-01-01

    The development of heme oxygenase (HO) inhibitors is critical in dissecting and understanding the HO system and for potential therapeutic applications. We have established a program to design and optimize HO inhibitors using structure-activity relationships in conjunction with X-ray crystallographic analyses. One of our previous complex crystal structures revealed a putative secondary hydrophobic binding pocket which could be exploited for a new design strategy by introducing a functional group that would fit into this potential site. To test this hypothesis and gain further insights into the structural basis of inhibitor binding, we have synthesized and characterized 1-(1H-imidazol-1-yl)-4,4-diphenyl-2-butanone (QC-308). Using a carbon monoxide (CO) formation assay on rat spleen microsomes, the compound was found to be ∼15 times more potent (IC(50) = 0.27±0.07 µM) than its monophenyl analogue, which is already a potent compound in its own right (QC-65; IC(50) = 4.0±1.8 µM). The crystal structure of hHO-1 with QC-308 revealed that the second phenyl group in the western region of the compound is indeed accommodated by a definitive secondary proximal hydrophobic pocket. Thus, the two phenyl moieties are each stabilized by distinct hydrophobic pockets. This "double-clamp" binding offers additional inhibitor stabilization and provides a new route for improvement of human heme oxygenase inhibitors.

  2. PRODIGY : a web server for predicting the binding affinity of protein-protein complexes

    NARCIS (Netherlands)

    Xue, Li; Garcia Lopes Maia Rodrigues, João; Kastritis, Panagiotis L; Bonvin, Alexandre Mjj; Vangone, Anna

    2016-01-01

    Gaining insights into the structural determinants of protein-protein interactions holds the key for a deeper understanding of biological functions, diseases and development of therapeutics. An important aspect of this is the ability to accurately predict the binding strength for a given

  3. Electrostatics, structure prediction, and the energy landscapes for protein folding and binding.

    Science.gov (United States)

    Tsai, Min-Yeh; Zheng, Weihua; Balamurugan, D; Schafer, Nicholas P; Kim, Bobby L; Cheung, Margaret S; Wolynes, Peter G

    2016-01-01

    While being long in range and therefore weakly specific, electrostatic interactions are able to modulate the stability and folding landscapes of some proteins. The relevance of electrostatic forces for steering the docking of proteins to each other is widely acknowledged, however, the role of electrostatics in establishing specifically funneled landscapes and their relevance for protein structure prediction are still not clear. By introducing Debye-Hückel potentials that mimic long-range electrostatic forces into the Associative memory, Water mediated, Structure, and Energy Model (AWSEM), a transferable protein model capable of predicting tertiary structures, we assess the effects of electrostatics on the landscapes of thirteen monomeric proteins and four dimers. For the monomers, we find that adding electrostatic interactions does not improve structure prediction. Simulations of ribosomal protein S6 show, however, that folding stability depends monotonically on electrostatic strength. The trend in predicted melting temperatures of the S6 variants agrees with experimental observations. Electrostatic effects can play a range of roles in binding. The binding of the protein complex KIX-pKID is largely assisted by electrostatic interactions, which provide direct charge-charge stabilization of the native state and contribute to the funneling of the binding landscape. In contrast, for several other proteins, including the DNA-binding protein FIS, electrostatics causes frustration in the DNA-binding region, which favors its binding with DNA but not with its protein partner. This study highlights the importance of long-range electrostatics in functional responses to problems where proteins interact with their charged partners, such as DNA, RNA, as well as membranes. © 2015 The Protein Society.

  4. Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

    Science.gov (United States)

    Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

    2016-01-01

    Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

  5. A novel method for improved accuracy of transcription factor binding site prediction

    KAUST Repository

    Khamis, Abdullah M.; Motwalli, Olaa Amin; Oliva, Romina; Jankovic, Boris R.; Medvedeva, Yulia; Ashoor, Haitham; Essack, Magbubah; Gao, Xin; Bajic, Vladimir B.

    2018-01-01

    Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

  6. A novel method for improved accuracy of transcription factor binding site prediction

    KAUST Repository

    Khamis, Abdullah M.

    2018-03-20

    Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

  7. Molecular Dynamics Simulations to Investigate the Binding Mode of the Natural Product Liphagal with Phosphoinositide 3-Kinase α

    Directory of Open Access Journals (Sweden)

    Yanjuan Gao

    2016-06-01

    Full Text Available Phosphatidylinositol 3-kinase α (PI3Kα is an attractive target for anticancer drug design. Liphagal, isolated from the marine sponge Aka coralliphaga, possesses the special “liphagane” meroterpenoid carbon skeleton and has been demonstrated as a PI3Kα inhibitor. Molecular docking and molecular dynamics simulations were performed to explore the dynamic behaviors of PI3Kα binding with liphagal, and free energy calculations and energy decomposition analysis were carried out by use of molecular mechanics/Poisson-Boltzmann (generalized Born surface area (MM/PB(GBSA methods. The results reveal that the heteroatom rich aromatic D-ring of liphagal extends towards the polar region of the binding site, and the D-ring 15-hydroxyl and 16-hydroxyl form three hydrogen bonds with Asp810 and Tyr836. The cyclohexyl A-ring projects up into the upper pocket of the lipophilic region, and the hydrophobic/van der Waals interactions with the residues Met772, Trp780, Ile800, Ile848, Val850, Met922, Phe930, Ile932 could be the key interactions for the affinity of liphagal to PI3Kα. Thus, a new strategy for the rational design of more potent analogs of liphagal against PI3Kα is provided. Our proposed PI3Kα/liphagal binding mode would be beneficial for the discovery of new active analogs of liphagal against PI3Kα.

  8. Prediction of mean monthly river discharges in Colombia through Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    A. M. Carmona

    2015-04-01

    Full Text Available The hydro-climatology of Colombia exhibits strong natural variability at a broad range of time scales including: inter-decadal, decadal, inter-annual, annual, intra-annual, intra-seasonal, and diurnal. Diverse applied sectors rely on quantitative predictions of river discharges for operational purposes including hydropower generation, agriculture, human health, fluvial navigation, territorial planning and management, risk preparedness and mitigation, among others. Various methodologies have been used to predict monthly mean river discharges that are based on "Predictive Analytics", an area of statistical analysis that studies the extraction of information from historical data to infer future trends and patterns. Our study couples the Empirical Mode Decomposition (EMD with traditional methods, e.g. Autoregressive Model of Order 1 (AR1 and Neural Networks (NN, to predict mean monthly river discharges in Colombia, South America. The EMD allows us to decompose the historical time series of river discharges into a finite number of intrinsic mode functions (IMF that capture the different oscillatory modes of different frequencies associated with the inherent time scales coexisting simultaneously in the signal (Huang et al. 1998, Huang and Wu 2008, Rao and Hsu, 2008. Our predictive method states that it is easier and simpler to predict each IMF at a time and then add them up together to obtain the predicted river discharge for a certain month, than predicting the full signal. This method is applied to 10 series of monthly mean river discharges in Colombia, using calibration periods of more than 25 years, and validation periods of about 12 years. Predictions are performed for time horizons spanning from 1 to 12 months. Our results show that predictions obtained through the traditional methods improve when the EMD is used as a previous step, since errors decrease by up to 13% when the AR1 model is used, and by up to 18% when using Neural Networks is

  9. Precise Ab-initio prediction of terahertz vibrational modes in crystalline systems

    DEFF Research Database (Denmark)

    Jepsen, Peter Uhd; Clark, Stewart J.

    2007-01-01

    We use a combination of experimental THz time-domain spectroscopy and ab-initio density functional perturbative theory to accurately predict the terahertz vibrational spectrum of molecules in the crystalline phase. Our calculations show that distinct vibrational modes found in solid-state materials...

  10. Diverse modes of binding in structures of Leishmania majorN-myristoyltransferase with selective inhibitors

    Directory of Open Access Journals (Sweden)

    James A. Brannigan

    2014-07-01

    Full Text Available The leishmaniases are a spectrum of global diseases of poverty associated with immune dysfunction and are the cause of high morbidity. Despite the long history of these diseases, no effective vaccine is available and the currently used drugs are variously compromised by moderate efficacy, complex side effects and the emergence of resistance. It is therefore widely accepted that new therapies are needed. N-Myristoyltransferase (NMT has been validated pre-clinically as a target for the treatment of fungal and parasitic infections. In a previously reported high-throughput screening program, a number of hit compounds with activity against NMT from Leishmania donovani have been identified. Here, high-resolution crystal structures of representative compounds from four hit series in ternary complexes with myristoyl-CoA and NMT from the closely related L. major are reported. The structures reveal that the inhibitors associate with the peptide-binding groove at a site adjacent to the bound myristoyl-CoA and the catalytic α-carboxylate of Leu421. Each inhibitor makes extensive apolar contacts as well as a small number of polar contacts with the protein. Remarkably, the compounds exploit different features of the peptide-binding groove and collectively occupy a substantial volume of this pocket, suggesting that there is potential for the design of chimaeric inhibitors with significantly enhanced binding. Despite the high conservation of the active sites of the parasite and human NMTs, the inhibitors act selectively over the host enzyme. The role of conformational flexibility in the side chain of Tyr217 in conferring selectivity is discussed.

  11. Fatigue crack growth and life prediction under mixed-mode loading

    Science.gov (United States)

    Sajith, S.; Murthy, K. S. R. K.; Robi, P. S.

    2018-04-01

    Fatigue crack growth life as a function of crack length is essential for the prevention of catastrophic failures from damage tolerance perspective. In damage tolerance design approach, principles of fracture mechanics are usually applied to predict the fatigue life of structural components. Numerical prediction of crack growth versus number of cycles is essential in damage tolerance design. For cracks under mixed mode I/II loading, modified Paris law (d/a d N =C (ΔKe q ) m ) along with different equivalent stress intensity factor (ΔKeq) model is used for fatigue crack growth rate prediction. There are a large number of ΔKeq models available for the mixed mode I/II loading, the selection of proper ΔKeq model has significant impact on fatigue life prediction. In the present investigation, the performance of ΔKeq models in fatigue life prediction is compared with respect to the experimental findings as there are no guidelines/suggestions available on the selection of these models for accurate and/or conservative predictions of fatigue life. Within the limitations of availability of experimental data and currently available numerical simulation techniques, the results of present study attempt to outline models that would provide accurate and conservative life predictions. Such a study aid the numerical analysts or engineers in the proper selection of the model for numerical simulation of the fatigue life. Moreover, the present investigation also suggests a procedure to enhance the accuracy of life prediction using Paris law.

  12. Automatic generation of bioinformatics tools for predicting protein-ligand binding sites.

    Science.gov (United States)

    Komiyama, Yusuke; Banno, Masaki; Ueki, Kokoro; Saad, Gul; Shimizu, Kentaro

    2016-03-15

    Predictive tools that model protein-ligand binding on demand are needed to promote ligand research in an innovative drug-design environment. However, it takes considerable time and effort to develop predictive tools that can be applied to individual ligands. An automated production pipeline that can rapidly and efficiently develop user-friendly protein-ligand binding predictive tools would be useful. We developed a system for automatically generating protein-ligand binding predictions. Implementation of this system in a pipeline of Semantic Web technique-based web tools will allow users to specify a ligand and receive the tool within 0.5-1 day. We demonstrated high prediction accuracy for three machine learning algorithms and eight ligands. The source code and web application are freely available for download at http://utprot.net They are implemented in Python and supported on Linux. shimizu@bi.a.u-tokyo.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  13. Analysis of electric moments of RNA-binding proteins: implications for mechanism and prediction

    Directory of Open Access Journals (Sweden)

    Sarai Akinori

    2011-02-01

    Full Text Available Abstract Background Protein-RNA interactions play important role in many biological processes such as gene regulation, replication, protein synthesis and virus assembly. Although many structures of various types of protein-RNA complexes have been determined, the mechanism of protein-RNA recognition remains elusive. We have earlier shown that the simplest electrostatic properties viz. charge, dipole and quadrupole moments, calculated from backbone atomic coordinates of proteins are biased relative to other proteins, and these quantities can be used to identify DNA-binding proteins. Closely related, RNA-binding proteins are investigated in this study. In particular, discrimination between various types of RNA-binding proteins, evolutionary conservation of these bulk electrostatic features and effect of conformational changes by complex formation are investigated. Basic binding mechanism of a putative RNA-binding protein (HI1333 from Haemophilus influenza is suggested as a potential application of this study. Results We found that similar to DNA-binding proteins (DBPs, RNA-binding proteins (RBPs also show significantly higher values of electric moments. However, higher moments in RBPs are found to strongly depend on their functional class: proteins binding to ribosomal RNA (rRNA constitute the only class with all three of the properties (charge, dipole and quadrupole moments being higher than control proteins. Neural networks were trained using leave-one-out cross-validation to predict RBPs from control data as well as pair-wise classification capacity between proteins binding to various RNA types. RBPs and control proteins reached up to 78% accuracy measured by the area under the ROC curve. Proteins binding to rRNA are found to be best distinguished (AUC = 79%. Changes in dipole and quadrupole moments between unbound and bound structures were small and these properties are found to be robust under complex formation. Conclusions Bulk electric

  14. Multiband Prediction Model for Financial Time Series with Multivariate Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Md. Rabiul Islam

    2012-01-01

    Full Text Available This paper presents a subband approach to financial time series prediction. Multivariate empirical mode decomposition (MEMD is employed here for multiband representation of multichannel financial time series together. Autoregressive moving average (ARMA model is used in prediction of individual subband of any time series data. Then all the predicted subband signals are summed up to obtain the overall prediction. The ARMA model works better for stationary signal. With multiband representation, each subband becomes a band-limited (narrow band signal and hence better prediction is achieved. The performance of the proposed MEMD-ARMA model is compared with classical EMD, discrete wavelet transform (DWT, and with full band ARMA model in terms of signal-to-noise ratio (SNR and mean square error (MSE between the original and predicted time series. The simulation results show that the MEMD-ARMA-based method performs better than the other methods.

  15. Prediction of Carbohydrate-Binding Proteins from Sequences Using Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Seizi Someya

    2010-01-01

    Full Text Available Carbohydrate-binding proteins are proteins that can interact with sugar chains but do not modify them. They are involved in many physiological functions, and we have developed a method for predicting them from their amino acid sequences. Our method is based on support vector machines (SVMs. We first clarified the definition of carbohydrate-binding proteins and then constructed positive and negative datasets with which the SVMs were trained. By applying the leave-one-out test to these datasets, our method delivered 0.92 of the area under the receiver operating characteristic (ROC curve. We also examined two amino acid grouping methods that enable effective learning of sequence patterns and evaluated the performance of these methods. When we applied our method in combination with the homology-based prediction method to the annotated human genome database, H-invDB, we found that the true positive rate of prediction was improved.

  16. Unveiling a novel transient druggable pocket in BACE-1 through molecular simulations: Conformational analysis and binding mode of multisite inhibitors

    Science.gov (United States)

    Di Pietro, Ornella; Laughton, Charles A.

    2017-01-01

    The critical role of BACE-1 in the formation of neurotoxic ß-amyloid peptides in the brain makes it an attractive target for an efficacious treatment of Alzheimer’s disease. However, the development of clinically useful BACE-1 inhibitors has proven to be extremely challenging. In this study we examine the binding mode of a novel potent inhibitor (compound 1, with IC50 80 nM) designed by synergistic combination of two fragments—huprine and rhein—that individually are endowed with very low activity against BACE-1. Examination of crystal structures reveals no appropriate binding site large enough to accommodate 1. Therefore we have examined the conformational flexibility of BACE-1 through extended molecular dynamics simulations, paying attention to the highly flexible region shaped by loops 8–14, 154–169 and 307–318. The analysis of the protein dynamics, together with studies of pocket druggability, has allowed us to detect the transient formation of a secondary binding site, which contains Arg307 as a key residue for the interaction with small molecules, at the edge of the catalytic cleft. The formation of this druggable “floppy” pocket would enable the binding of multisite inhibitors targeting both catalytic and secondary sites. Molecular dynamics simulations of BACE-1 bound to huprine-rhein hybrid compounds support the feasibility of this hypothesis. The results provide a basis to explain the high inhibitory potency of the two enantiomeric forms of 1, together with the large dependence on the length of the oligomethylenic linker. Furthermore, the multisite hypothesis has allowed us to rationalize the inhibitory potency of a series of tacrine-chromene hybrid compounds, specifically regarding the apparent lack of sensitivity of the inhibition constant to the chemical modifications introduced in the chromene unit. Overall, these findings pave the way for the exploration of novel functionalities in the design of optimized BACE-1 multisite inhibitors

  17. Determination of ligand binding modes in weak protein–ligand complexes using sparse NMR data

    Energy Technology Data Exchange (ETDEWEB)

    Mohanty, Biswaranjan; Williams, Martin L.; Doak, Bradley C.; Vazirani, Mansha; Ilyichova, Olga [Monash University, Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences (Australia); Wang, Geqing [La Trobe University, La Trobe Institute for Molecular Bioscience (Australia); Bermel, Wolfgang [Bruker Biospin GmbH (Germany); Simpson, Jamie S.; Chalmers, David K. [Monash University, Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences (Australia); King, Glenn F. [The University of Queensland, Institute for Molecular Bioscience (Australia); Mobli, Mehdi, E-mail: m.mobli@uq.edu.au [The University of Queensland, Centre for Advanced Imaging (Australia); Scanlon, Martin J., E-mail: martin.scanlon@monash.edu [Monash University, Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences (Australia)

    2016-11-15

    We describe a general approach to determine the binding pose of small molecules in weakly bound protein–ligand complexes by deriving distance constraints between the ligand and methyl groups from all methyl-containing residues of the protein. We demonstrate that using a single sample, which can be prepared without the use of expensive precursors, it is possible to generate high-resolution data rapidly and obtain the resonance assignments of Ile, Leu, Val, Ala and Thr methyl groups using triple resonance scalar correlation data. The same sample may be used to obtain Met {sup ε}CH{sub 3} assignments using NOESY-based methods, although the superior sensitivity of NOESY using [U-{sup 13}C,{sup 15}N]-labeled protein makes the use of this second sample more efficient. We describe a structural model for a weakly binding ligand bound to its target protein, DsbA, derived from intermolecular methyl-to-ligand nuclear Overhauser enhancements, and demonstrate that the ability to assign all methyl resonances in the spectrum is essential to derive an accurate model of the structure. Once the methyl assignments have been obtained, this approach provides a rapid means to generate structural models for weakly bound protein–ligand complexes. Such weak complexes are often found at the beginning of programs of fragment based drug design and can be challenging to characterize using X-ray crystallography.

  18. Salmonella Enterica Serovar Typhimurium BipA Exhibits Two Distinct Ribosome Binding Modes

    Energy Technology Data Exchange (ETDEWEB)

    deLivron, M.; Robinson, V

    2008-01-01

    BipA is a highly conserved prokaryotic GTPase that functions to influence numerous cellular processes in bacteria. In Escherichia coli and Salmonella enterica serovar Typhimurium, BipA has been implicated in controlling bacterial motility, modulating attachment and effacement processes, and upregulating the expression of virulence genes and is also responsible for avoidance of host defense mechanisms. In addition, BipA is thought to be involved in bacterial stress responses, such as those associated with virulence, temperature, and symbiosis. Thus, BipA is necessary for securing bacterial survival and successful invasion of the host. Steady-state kinetic analysis and pelleting assays were used to assess the GTPase and ribosome-binding properties of S. enterica BipA. Under normal bacterial growth, BipA associates with the ribosome in the GTP-bound state. However, using sucrose density gradients, we demonstrate that the association of BipA and the ribosome is altered under stress conditions in bacteria similar to those experienced during virulence. The data show that this differential binding is brought about by the presence of ppGpp, an alarmone that signals the onset of stress-related events in bacteria.

  19. Interaction of the N-(3-Methylpyridin-2-ylamide Derivatives of Flurbiprofen and Ibuprofen with FAAH: Enantiomeric Selectivity and Binding Mode.

    Directory of Open Access Journals (Sweden)

    Jessica Karlsson

    Full Text Available Combined fatty acid amide hydrolase (FAAH and cyclooxygenase (COX inhibition is a promising approach for pain-relief. The Flu-AM1 and Ibu-AM5 derivatives of flurbiprofen and ibuprofen retain similar COX-inhibitory properties and are more potent inhibitors of FAAH than the parent compounds. However, little is known as to the nature of their interaction with FAAH, or to the importance of their chirality. This has been explored here.FAAH inhibitory activity was measured in rat brain homogenates and in lysates expressing either wild-type or FAAH(T488A-mutated enzyme. Molecular modelling was undertaken using both docking and molecular dynamics. The (R- and (S-enantiomers of Flu-AM1 inhibited rat FAAH with similar potencies (IC50 values of 0.74 and 0.99 μM, respectively, whereas the (S-enantiomer of Ibu-AM5 (IC50 0.59 μM was more potent than the (R-enantiomer (IC50 5.7 μM. Multiple inhibition experiments indicated that both (R-Flu-AM1 and (S-Ibu-AM5 inhibited FAAH in a manner mutually exclusive to carprofen. Computational studies indicated that the binding site for the Flu-AM1 and Ibu-AM5 enantiomers was located between the acyl chain binding channel and the membrane access channel, in a site overlapping the carprofen binding site, and showed a binding mode in line with that proposed for carprofen and other non-covalent ligands. The potency of (R-Flu-AM1 was lower towards lysates expressing FAAH mutated at the proposed carprofen binding area than in lysates expressing wild-type FAAH.The study provides kinetic and structural evidence that the enantiomers of Flu-AM1 and Ibu-AM5 bind in the substrate channel of FAAH. This information will be useful in aiding the design of novel dual-action FAAH: COX inhibitors.

  20. Degradation mode analysis: An approach to establish effective predictive maintenance tasks

    International Nuclear Information System (INIS)

    Sonnett, D.E.; Douglass, P.T.; Barnard, D.D.

    1991-01-01

    A significant number of nuclear generating stations have been employing Reliability Centered Maintenance methodology to arrive at applicable and effective maintenance tasks for their plant equipment. The resultant endpoint of most programs has been an increased emphasis on predictive maintenance as the task of choice for monitoring and trending plant equipment condition to address failure mechanisms of the analyses. Many of these plants have spent several years conducting reliability centered analysis before they seriously begin implementing predictive program improvements. In this paper we present another methodology, entitled Degradation Mode Analysis, which provides a more direct method to quickly and economically achieve the major benefit of reliability centered analysis, namely predictive maintenance. (author)

  1. Interaction and Binding Modes of bis-Ruthenium(II Complex to Synthetic DNAs

    Directory of Open Access Journals (Sweden)

    Hasi Rani Barai

    2016-06-01

    Full Text Available [μ-(linkerL2(dipyrido[3,2-a:2′,3′-c]phenazine2(phenanthroline2Ru(II2]2+ with linker: 1,3-bis-(4-pyridyl-propane, L: PF6 (bis-Ru-bpp was synthesized and their binding properties to a various polynucleotides were investigated by spectroscopy, including normal absorption, circular dichroism(CD, linear dichroism(LD, and luminescence techniques in this study. On binding to polynucleotides, the bis-Ru-bpp complex with poly[d(A-T2], and poly[d(I-C2] exhibited a negative LDr signal whose intensity was as large as that in the DNA absorption region, followed by a complicated LDr signal in the metal-to-ligand charge transfer region. Also, the emission intensity and equilibrium constant of the bis-Ru-bpp complex with poly[d(A-T2], and poly[d(I-C2] were enhanced. It was reported that both of dppz ligand of the bis-Ru-bpp complex intercalated between DNA base-pairs when bound to native, mixed sequence DNA. Observed spectral properties resemble to those observed for poly[d(A-T2] and poly[d(I-C2], led us to be concluded that both dppz ligands intercalate between alternated AT and IC bases-pairs In contrast when bis-Ru-bpp complex was bound to poly[d(G-C2], the magnitude of the LDr in the dppz absorption region, as well as the emission intensity, was half in comparison to that of bound to poly[d(A-T2], and poly[d(I-C2]. Therefore the spectral properties of the bis-Ru-bpp-poly[d(G-C2] complex suggested deviation from bis-intercalation model in the poly[d(G-C2] case. These results can be explained by a model whereby one of the dppz ligands is intercalated while the other is exposed to solvent or may exist near to phosphate. Also it is indicative that the amine group of guanine in the minor groove provides the steric hindrance for incoming intercalation binder and it also takes an important role in a difference in binding of bis-Ru-bpp bound to poly[d(A-T2] and poly[d(I-C2].

  2. Predictive simulations of radio frequency heated plasmas of Tore Supra using the Multi-Mode model

    International Nuclear Information System (INIS)

    Voitsekhovitch, Irina; Bateman, Glenn; Kritz, Arnold H.; Pankin, Alexei

    2002-01-01

    Multichannel integrated predictive simulations using the Multi-Mode transport model are carried out for radio frequency heated Tore Supra tokamak discharges in which helium is the primary ion component. Lower hybrid heated discharges in which the total current is driven noninductively [X. Litaudon et al., Plasma Phys. Controlled Fusion 43, 677 (2001)] and a discharge with ion cyclotron radio frequency heating of the hydrogen minority ions [G. T. Hoang et al., Nucl. Fusion 38, 117 (1998)] are simulated. The simulations of these discharges represent the first test of the Multi-Mode model in helium plasmas with dominant electron heating. Also for the first time, the particle transport in Tore Supra discharges is computed and the density profiles are predicted self-consistently with other transport channels. It is found in these simulations that the anomalous transport driven by trapped electron mode turbulence is dominant compared to the transport driven by the ion temperature gradient turbulence. The feature of the Multi-Mode model to calculate the impurity transport self-consistently with other transport channels is used in this study to predict the influence of carbon impurity influx on the discharge evolution

  3. Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach

    DEFF Research Database (Denmark)

    Buus, S.; Lauemoller, S.L.; Worning, Peder

    2003-01-01

    We have generated Artificial Neural Networks (ANN) capable of performing sensitive, quantitative predictions of peptide binding to the MHC class I molecule, HLA-A*0204. We have shown that such quantitative ANN are superior to conventional classification ANN, that have been trained to predict bind...... of an iterative feedback loop whereby advanced, computational bioinformatics optimize experimental strategy, and vice versa....

  4. Comparisons of theoretically predicted transport from ion temperature gradient instabilities to L-mode tokamak experiments

    International Nuclear Information System (INIS)

    Kotschenreuther, M.; Wong, H.V.; Lyster, P.L.; Berk, H.L.; Denton, R.; Miner, W.H.; Valanju, P.

    1991-12-01

    The theoretical transport from kinetic micro-instabilities driven by ion temperature gradients is a sheared slab is compared to experimentally inferred transport in L-mode tokamaks. Low noise gyrokinetic simulation techniques are used to obtain the ion thermal transport coefficient X. This X is much smaller than in experiments, and so cannot explain L-mode confinement. Previous predictions based on fluid models gave much greater X than experiments. Linear and nonlinear comparisons with the fluid model show that it greatly overestimates transport for experimental parameters. In addition, disagreements among previous analytic and simulation calculations of X in the fluid model are reconciled

  5. SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

    Science.gov (United States)

    Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong

    2015-01-01

    Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

  6. Computational prediction of cAMP receptor protein (CRP binding sites in cyanobacterial genomes

    Directory of Open Access Journals (Sweden)

    Su Zhengchang

    2009-01-01

    Full Text Available Abstract Background Cyclic AMP receptor protein (CRP, also known as catabolite gene activator protein (CAP, is an important transcriptional regulator widely distributed in many bacteria. The biological processes under the regulation of CRP are highly diverse among different groups of bacterial species. Elucidation of CRP regulons in cyanobacteria will further our understanding of the physiology and ecology of this important group of microorganisms. Previously, CRP has been experimentally studied in only two cyanobacterial strains: Synechocystis sp. PCC 6803 and Anabaena sp. PCC 7120; therefore, a systematic genome-scale study of the potential CRP target genes and binding sites in cyanobacterial genomes is urgently needed. Results We have predicted and analyzed the CRP binding sites and regulons in 12 sequenced cyanobacterial genomes using a highly effective cis-regulatory binding site scanning algorithm. Our results show that cyanobacterial CRP binding sites are very similar to those in E. coli; however, the regulons are very different from that of E. coli. Furthermore, CRP regulons in different cyanobacterial species/ecotypes are also highly diversified, ranging from photosynthesis, carbon fixation and nitrogen assimilation, to chemotaxis and signal transduction. In addition, our prediction indicates that crp genes in modern cyanobacteria are likely inherited from a common ancestral gene in their last common ancestor, and have adapted various cellular functions in different environments, while some cyanobacteria lost their crp genes as well as CRP binding sites during the course of evolution. Conclusion The CRP regulons in cyanobacteria are highly diversified, probably as a result of divergent evolution to adapt to various ecological niches. Cyanobacterial CRPs may function as lineage-specific regulators participating in various cellular processes, and are important in some lineages. However, they are dispensable in some other lineages. The

  7. Deep learning and model predictive control for self-tuning mode-locked lasers

    Science.gov (United States)

    Baumeister, Thomas; Brunton, Steven L.; Nathan Kutz, J.

    2018-03-01

    Self-tuning optical systems are of growing importance in technological applications such as mode-locked fiber lasers. Such self-tuning paradigms require {\\em intelligent} algorithms capable of inferring approximate models of the underlying physics and discovering appropriate control laws in order to maintain robust performance for a given objective. In this work, we demonstrate the first integration of a {\\em deep learning} (DL) architecture with {\\em model predictive control} (MPC) in order to self-tune a mode-locked fiber laser. Not only can our DL-MPC algorithmic architecture approximate the unknown fiber birefringence, it also builds a dynamical model of the laser and appropriate control law for maintaining robust, high-energy pulses despite a stochastically drifting birefringence. We demonstrate the effectiveness of this method on a fiber laser which is mode-locked by nonlinear polarization rotation. The method advocated can be broadly applied to a variety of optical systems that require robust controllers.

  8. Evolutionary Limitation and Opportunities for Developing tRNA Synthetase Inhibitors with 5-Binding-Mode Classification

    Directory of Open Access Journals (Sweden)

    Pengfei Fang

    2015-12-01

    Full Text Available Aminoacyl-tRNA synthetases (aaRSs are enzymes that catalyze the transfer of amino acids to their cognate tRNAs as building blocks for translation. Each of the aaRS families plays a pivotal role in protein biosynthesis and is indispensable for cell growth and survival. In addition, aaRSs in higher species have evolved important non-translational functions. These translational and non-translational functions of aaRS are attractive for developing antibacterial, antifungal, and antiparasitic agents and for treating other human diseases. The interplay between amino acids, tRNA, ATP, EF-Tu and non-canonical binding partners, had shaped each family with distinct pattern of key sites for regulation, with characters varying among species across the path of evolution. These sporadic variations in the aaRSs offer great opportunity to target these essential enzymes for therapy. Up to this day, growing numbers of aaRS inhibitors have been discovered and developed. Here, we summarize the latest developments and structural studies of aaRS inhibitors, and classify them with distinct binding modes into five categories.

  9. Ligand binding modes from low resolution GPCR models and mutagenesis: chicken bitter taste receptor as a test-case.

    Science.gov (United States)

    Di Pizio, Antonella; Kruetzfeldt, Louisa-Marie; Cheled-Shoval, Shira; Meyerhof, Wolfgang; Behrens, Maik; Niv, Masha Y

    2017-08-15

    Bitter taste is one of the basic taste modalities, warning against consuming potential poisons. Bitter compounds activate members of the bitter taste receptor (Tas2r) subfamily of G protein-coupled receptors (GPCRs). The number of functional Tas2rs is species-dependent. Chickens represent an intriguing minimalistic model, because they detect the bitter taste of structurally different molecules with merely three bitter taste receptor subtypes. We investigated the binding modes of several known agonists of a representative chicken bitter taste receptor, ggTas2r1. Because of low sequence similarity between ggTas2r1 and crystallized GPCRs (~10% identity, ~30% similarity at most), the combination of computational approaches with site-directed mutagenesis was used to characterize the agonist-bound conformation of ggTas2r1 binding site between TMs 3, 5, 6 and 7. We found that the ligand interactions with N93 in TM3 and/or N247 in TM5, combined with hydrophobic contacts, are typically involved in agonist recognition. Next, the ggTas2r1 structural model was successfully used to identify three quinine analogues (epiquinidine, ethylhydrocupreine, quinidine) as new ggTas2r1 agonists. The integrated approach validated here may be applicable to additional cases where the sequence identity of the GPCR of interest and the existing experimental structures is low.

  10. A unique binding mode enables MCM2 to chaperone histones H3-H4 at replication forks

    DEFF Research Database (Denmark)

    Huang, Hongda; Strømme, Caroline B; Saredi, Giulia

    2015-01-01

    During DNA replication, chromatin is reassembled by recycling of modified old histones and deposition of new ones. How histone dynamics integrates with DNA replication to maintain genome and epigenome information remains unclear. Here, we reveal how human MCM2, part of the replicative helicase......, chaperones histones H3-H4. Our first structure shows an H3-H4 tetramer bound by two MCM2 histone-binding domains (HBDs), which hijack interaction sites used by nucleosomal DNA. Our second structure reveals MCM2 and ASF1 cochaperoning an H3-H4 dimer. Mutational analyses show that the MCM2 HBD is required...... for MCM2-7 histone-chaperone function and normal cell proliferation. Further, we show that MCM2 can chaperone both new and old canonical histones H3-H4 as well as H3.3 and CENPA variants. The unique histone-binding mode of MCM2 thus endows the replicative helicase with ideal properties for recycling...

  11. A unique binding mode enables MCM2 to chaperone histones H3-H4 at replication forks.

    Science.gov (United States)

    Huang, Hongda; Strømme, Caroline B; Saredi, Giulia; Hödl, Martina; Strandsby, Anne; González-Aguilera, Cristina; Chen, Shoudeng; Groth, Anja; Patel, Dinshaw J

    2015-08-01

    During DNA replication, chromatin is reassembled by recycling of modified old histones and deposition of new ones. How histone dynamics integrates with DNA replication to maintain genome and epigenome information remains unclear. Here, we reveal how human MCM2, part of the replicative helicase, chaperones histones H3-H4. Our first structure shows an H3-H4 tetramer bound by two MCM2 histone-binding domains (HBDs), which hijack interaction sites used by nucleosomal DNA. Our second structure reveals MCM2 and ASF1 cochaperoning an H3-H4 dimer. Mutational analyses show that the MCM2 HBD is required for MCM2-7 histone-chaperone function and normal cell proliferation. Further, we show that MCM2 can chaperone both new and old canonical histones H3-H4 as well as H3.3 and CENPA variants. The unique histone-binding mode of MCM2 thus endows the replicative helicase with ideal properties for recycling histones genome wide during DNA replication.

  12. Structure-based prediction of free energy changes of binding of PTP1B inhibitors

    Science.gov (United States)

    Wang, Jing; Ling Chan, Shek; Ramnarayan, Kal

    2003-08-01

    The goals were (1) to understand the driving forces in the binding of small molecule inhibitors to the active site of PTP1B and (2) to develop a molecular mechanics-based empirical free energy function for compound potency prediction. A set of compounds with known activities was docked onto the active site. The related energy components and molecular surface areas were calculated. The bridging water molecules were identified and their contributions were considered. Linear relationships were explored between the above terms and the binding free energies of compounds derived based on experimental inhibition constants. We found that minimally three terms are required to give rise to a good correlation (0.86) with predictive power in five-group cross-validation test (q2 = 0.70). The dominant terms are the electrostatic energy and non-electrostatic energy stemming from the intra- and intermolecular interactions of solutes and from those of bridging water molecules in complexes.

  13. Cloud computing approaches for prediction of ligand binding poses and pathways.

    Science.gov (United States)

    Lawrenz, Morgan; Shukla, Diwakar; Pande, Vijay S

    2015-01-22

    We describe an innovative protocol for ab initio prediction of ligand crystallographic binding poses and highly effective analysis of large datasets generated for protein-ligand dynamics. We include a procedure for setup and performance of distributed molecular dynamics simulations on cloud computing architectures, a model for efficient analysis of simulation data, and a metric for evaluation of model convergence. We give accurate binding pose predictions for five ligands ranging in affinity from 7 nM to > 200 μM for the immunophilin protein FKBP12, for expedited results in cases where experimental structures are difficult to produce. Our approach goes beyond single, low energy ligand poses to give quantitative kinetic information that can inform protein engineering and ligand design.

  14. Determination of the binding mode for anti-inflammatory natural product xanthohumol with myeloid differentiation protein 2

    Directory of Open Access Journals (Sweden)

    Fu W

    2016-01-01

    Full Text Available Weitao Fu,1,* Lingfeng Chen,1,* Zhe Wang,1 Chengwei Zhao,1 Gaozhi Chen,1 Xing Liu,1 Yuanrong Dai,2 Yuepiao Cai,1 Chenglong Li,1,3 Jianmin Zhou,1 Guang Liang1 1Chemical Biology Research Center, School of Pharmaceutical Sciences, 2Department of Respiratory Medicine, the Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of China; 3Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, Ohio State University, Columbus, OH, USA *These authors contributed equally to this work Abstract: It is recognized that myeloid differentiation protein 2 (MD-2, a coreceptor of toll-like receptor 4 (TLR4 for innate immunity, plays an essential role in activation of the lipopolysaccharide signaling pathway. MD-2 is known as a neoteric and suitable therapeutical target. Therefore, there is great interest in the development of a potent MD-2 inhibitor for anti-inflammatory therapeutics. Several studies have reported that xanthohumol (XN, an anti-inflammatory natural product from hops and beer, can block the TLR4 signaling by binding to MD-2 directly. However, the interaction between MD-2 and XN remains unknown. Herein, our work aims at characterizing interactions between MD-2 and XN. Using a combination of experimental and theoretical modeling analysis, we found that XN can embed into the hydrophobic pocket of MD-2 and form two stable hydrogen bonds with residues ARG-90 and TYR-102 of MD-2. Moreover, we confirmed that ARG-90 and TYR-102 were two necessary residues during the recognition process of XN binding to MD-2. Results from this study identified the atomic interactions between the MD-2 and XN, which will contribute to future structural design of novel MD-2-targeting molecules for the treatment of inflammatory diseases. Keywords: myeloid differentiation 2, xanthohumol, binding mode, inflammation, molecular dynamics simulation 

  15. 'In-Crystallo' Capture of a Michaelis Complex And Product Binding Modes of a Bacterial Phosphotriesterase

    Energy Technology Data Exchange (ETDEWEB)

    Jackson, C.J.; Foo, J.-L.; Kim, H.-K.; Carr, P.D.; Liu, J.-W.; Salem, G.; Ollis, D.L.

    2009-05-18

    The mechanism by which the binuclear metallophosphotriesterases (PTEs, E.C. 3.1.8.1) catalyse substrate hydrolysis has been extensively studied. The {mu}-hydroxo bridge between the metal ions has been proposed to be the initiating nucleophile in the hydrolytic reaction. In contrast, analysis of some biomimetic systems has indicated that {mu}-hydroxo bridges are often not themselves nucleophiles, but act as general bases for freely exchangeable nucleophilic water molecules. Herein, we present crystallographic analyses of a bacterial PTE from Agrobacterium radiobacter, OpdA, capturing the enzyme-substrate complex during hydrolysis. This model of the Michaelis complex suggests the alignment of the substrate will favor attack from a solvent molecule terminally coordinated to the {alpha}-metal ion. The bridging of both metal ions by the product, without disruption of the {mu}-hydroxo bridge, is also consistent with nucleophilic attack occurring from the terminal position. When phosphodiesters are soaked into crystals of OpdA, they coordinate bidentately to the {beta}-metal ion, displacing the {mu}-hydroxo bridge. Thus, alternative product-binding modes exist for the PTEs, and it is the bridging mode that appears to result from phosphotriester hydrolysis. Kinetic analysis of the PTE and promiscuous phosphodiesterase activities confirms that the presence of a {mu}-hydroxo bridge during phosphotriester hydrolysis is correlated with a lower pK{sub a} for the nucleophile, consistent with a general base function during catalysis.

  16. The calcium binding properties and structure prediction of the Hax-1 protein.

    Science.gov (United States)

    Balcerak, Anna; Rowinski, Sebastian; Szafron, Lukasz M; Grzybowska, Ewa A

    2017-01-01

    Hax-1 is a protein involved in regulation of different cellular processes, but its properties and exact mechanisms of action remain unknown. In this work, using purified, recombinant Hax-1 and by applying an in vitro autoradiography assay we have shown that this protein binds Ca 2+ . Additionally, we performed structure prediction analysis which shows that Hax-1 displays definitive structural features, such as two α-helices, short β-strands and four disordered segments.

  17. Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

    Science.gov (United States)

    Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

    2015-10-01

    A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM.

  18. Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

    International Nuclear Information System (INIS)

    Setiadi, A C; Brunsell, P R; Frassinetti, L

    2015-01-01

    A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM. (paper)

  19. Fault Tolerant Flight Control Using Sliding Modes and Subspace Identification-Based Predictive Control

    KAUST Repository

    Siddiqui, Bilal A.; El-Ferik, Sami; Abdelkader, Mohamed

    2016-01-01

    In this work, a cascade structure of a time-scale separated integral sliding mode and model predictive control is proposed as a viable alternative for fault-tolerant control. A multi-variable sliding mode control law is designed as the inner loop of the flight control system. Subspace identification is carried out on the aircraft in closed loop. The identified plant is then used for model predictive controllers in the outer loop. The overall control law demonstrates improved robustness to measurement noise, modeling uncertainties, multiple faults and severe wind turbulence and gusts. In addition, the flight control system employs filters and dead-zone nonlinear elements to reduce chattering and improve handling quality. Simulation results demonstrate the efficiency of the proposed controller using conventional fighter aircraft without control redundancy.

  20. Predictive Sliding Mode Control for Attitude Tracking of Hypersonic Vehicles Using Fuzzy Disturbance Observer

    Directory of Open Access Journals (Sweden)

    Xianlei Cheng

    2015-01-01

    Full Text Available We propose a predictive sliding mode control (PSMC scheme for attitude control of hypersonic vehicle (HV with system uncertainties and external disturbances based on an improved fuzzy disturbance observer (IFDO. First, for a class of uncertain affine nonlinear systems with system uncertainties and external disturbances, we propose a predictive sliding mode control based on fuzzy disturbance observer (FDO-PSMC, which is used to estimate the composite disturbances containing system uncertainties and external disturbances. Afterward, to enhance the composite disturbances rejection performance, an improved FDO-PSMC (IFDO-PSMC is proposed by incorporating a hyperbolic tangent function with FDO to compensate for the approximate error of FDO. Finally, considering the actuator dynamics, the proposed IFDO-PSMC is applied to attitude control system design for HV to track the guidance commands with high precision and strong robustness. Simulation results demonstrate the effectiveness and robustness of the proposed attitude control scheme.

  1. Fault Tolerant Flight Control Using Sliding Modes and Subspace Identification-Based Predictive Control

    KAUST Repository

    Siddiqui, Bilal A.

    2016-07-26

    In this work, a cascade structure of a time-scale separated integral sliding mode and model predictive control is proposed as a viable alternative for fault-tolerant control. A multi-variable sliding mode control law is designed as the inner loop of the flight control system. Subspace identification is carried out on the aircraft in closed loop. The identified plant is then used for model predictive controllers in the outer loop. The overall control law demonstrates improved robustness to measurement noise, modeling uncertainties, multiple faults and severe wind turbulence and gusts. In addition, the flight control system employs filters and dead-zone nonlinear elements to reduce chattering and improve handling quality. Simulation results demonstrate the efficiency of the proposed controller using conventional fighter aircraft without control redundancy.

  2. Prediction of multipactor in the iris region of rf deflecting mode cavities

    Directory of Open Access Journals (Sweden)

    G. Burt

    2011-12-01

    Full Text Available Multipactor is a major cause of field limitation in many superconducting rf cavities. Multipacting is a particular issue for deflecting mode cavities as the typical behavior is not well studied, understood, or parametrized. In this paper an approximate analytical model for the prediction of multipactor in the iris region of deflecting mode cavities is developed. This new but simple model yields a clear explanation on the broad range of rf field levels over which the multipactor can occur. The principle multipactors under investigation here are two-point multipactors associated with cyclotron motion in the cavity’s rf magnetic field. The predictions from the model are compared to numerical simulations and good agreement is obtained. The results are also compared to experimental results previously reported by KEK and are also found in good agreement.

  3. Models for Predicting Boundary Conditions in L-Mode Tokamak Plasma

    International Nuclear Information System (INIS)

    Siriwitpreecha, A.; Onjun, T.; Suwanna, S.; Poolyarat, N.; Picha, R.

    2009-07-01

    Full text: The models for predicting temperature and density of ions and electrons at boundary conditions in L-mode tokamak plasma are developed using an empirical approach and optimized against the experimental data obtained from the latest public version of the International Pedestal Database (version 3.2). It is assumed that the temperature and density at boundary of L-mode plasma are functions of engineering parameters such as plasma current, toroidal magnetic field, total heating power, line averaged density, hydrogenic particle mass (A H ), major radius, minor radius, and elongation at the separatrix. Multiple regression analysis is carried out for these parameters with 86 data points in L-mode from Aug (61) and JT60U (25). The RMSE of temperature and density at boundary of L-mode plasma are found to be 24.41% and 18.81%, respectively. These boundary models are implemented in BALDUR code, which will be used to simulate the L-mode plasma in the tokamak

  4. Rapid and accurate prediction and scoring of water molecules in protein binding sites.

    Directory of Open Access Journals (Sweden)

    Gregory A Ross

    Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

  5. Surface-enhanced Raman Scattering Study of the Binding Modes of a Dibenzotetraaza[14]annulene Derivative with DNA/RNA Polynucleotides

    OpenAIRE

    Miljanić, Snežana; Dijanošić, Adriana; Kalac, Matea; Radić Stojković, Marijana; Piantanida, Ivo; Pawlica, Dariusz; Eilmes, Julita

    2012-01-01

    Binding modes of a dibenzotetraaza14annulene (DBTAA) derivative with synthetic nucleic acids were studied using surface-enhanced Raman spectroscopy (SERS). Changes in SERS intensity and appearance of new bands in spectra were attributed to different complexes formed between the DBTAA molecules and DNA/RNA polynucleotides. A decrease in intensity pointed to intercalation as the dominant binding mode of the annulene derivative with poly dGdC-poly dGdC and poly rA-poly rU, whereas new bands in...

  6. Prediction of Accurate Mixed Mode Fatigue Crack Growth Curves using the Paris' Law

    Science.gov (United States)

    Sajith, S.; Krishna Murthy, K. S. R.; Robi, P. S.

    2017-12-01

    Accurate information regarding crack growth times and structural strength as a function of the crack size is mandatory in damage tolerance analysis. Various equivalent stress intensity factor (SIF) models are available for prediction of mixed mode fatigue life using the Paris' law. In the present investigation these models have been compared to assess their efficacy in prediction of the life close to the experimental findings as there are no guidelines/suggestions available on selection of these models for accurate and/or conservative predictions of fatigue life. Within the limitations of availability of experimental data and currently available numerical simulation techniques, the results of present study attempts to outline models that would provide accurate and conservative life predictions.

  7. Improved Prediction of Preterm Delivery Using Empirical Mode Decomposition Analysis of Uterine Electromyography Signals.

    Directory of Open Access Journals (Sweden)

    Peng Ren

    Full Text Available Preterm delivery increases the risk of infant mortality and morbidity, and therefore developing reliable methods for predicting its likelihood are of great importance. Previous work using uterine electromyography (EMG recordings has shown that they may provide a promising and objective way for predicting risk of preterm delivery. However, to date attempts at utilizing computational approaches to achieve sufficient predictive confidence, in terms of area under the curve (AUC values, have not achieved the high discrimination accuracy that a clinical application requires. In our study, we propose a new analytical approach for assessing the risk of preterm delivery using EMG recordings which firstly employs Empirical Mode Decomposition (EMD to obtain their Intrinsic Mode Functions (IMF. Next, the entropy values of both instantaneous amplitude and instantaneous frequency of the first ten IMF components are computed in order to derive ratios of these two distinct components as features. Discrimination accuracy of this approach compared to those proposed previously was then calculated using six differently representative classifiers. Finally, three different electrode positions were analyzed for their prediction accuracy of preterm delivery in order to establish which uterine EMG recording location was optimal signal data. Overall, our results show a clear improvement in prediction accuracy of preterm delivery risk compared with previous approaches, achieving an impressive maximum AUC value of 0.986 when using signals from an electrode positioned below the navel. In sum, this provides a promising new method for analyzing uterine EMG signals to permit accurate clinical assessment of preterm delivery risk.

  8. The Drosophila hnRNP F/H Homolog Glorund Uses Two Distinct RNA-Binding Modes to Diversify Target Recognition.

    Science.gov (United States)

    Tamayo, Joel V; Teramoto, Takamasa; Chatterjee, Seema; Hall, Traci M Tanaka; Gavis, Elizabeth R

    2017-04-04

    The Drosophila hnRNP F/H homolog, Glorund (Glo), regulates nanos mRNA translation by interacting with a structured UA-rich motif in the nanos 3' untranslated region. Glo regulates additional RNAs, however, and mammalian homologs bind G-tract sequences to regulate alternative splicing, suggesting that Glo also recognizes G-tract RNA. To gain insight into how Glo recognizes both structured UA-rich and G-tract RNAs, we used mutational analysis guided by crystal structures of Glo's RNA-binding domains and identified two discrete RNA-binding surfaces that allow Glo to recognize both RNA motifs. By engineering Glo variants that favor a single RNA-binding mode, we show that a subset of Glo's functions in vivo is mediated solely by the G-tract binding mode, whereas regulation of nanos requires both recognition modes. Our findings suggest a molecular mechanism for the evolution of dual RNA motif recognition in Glo that may be applied to understanding the functional diversity of other RNA-binding proteins. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  9. The Drosophila hnRNP F/H Homolog Glorund Uses Two Distinct RNA-Binding Modes to Diversify Target Recognition

    Directory of Open Access Journals (Sweden)

    Joel V. Tamayo

    2017-04-01

    Full Text Available The Drosophila hnRNP F/H homolog, Glorund (Glo, regulates nanos mRNA translation by interacting with a structured UA-rich motif in the nanos 3′ untranslated region. Glo regulates additional RNAs, however, and mammalian homologs bind G-tract sequences to regulate alternative splicing, suggesting that Glo also recognizes G-tract RNA. To gain insight into how Glo recognizes both structured UA-rich and G-tract RNAs, we used mutational analysis guided by crystal structures of Glo’s RNA-binding domains and identified two discrete RNA-binding surfaces that allow Glo to recognize both RNA motifs. By engineering Glo variants that favor a single RNA-binding mode, we show that a subset of Glo’s functions in vivo is mediated solely by the G-tract binding mode, whereas regulation of nanos requires both recognition modes. Our findings suggest a molecular mechanism for the evolution of dual RNA motif recognition in Glo that may be applied to understanding the functional diversity of other RNA-binding proteins.

  10. Investigation of the binding mode of a novel cruzain inhibitor by docking, molecular dynamics, ab initio and MM/PBSA calculations

    Science.gov (United States)

    Martins, Luan Carvalho; Torres, Pedro Henrique Monteiro; de Oliveira, Renata Barbosa; Pascutti, Pedro Geraldo; Cino, Elio A.; Ferreira, Rafaela Salgado

    2018-05-01

    Chagas disease remains a major health problem in South America, and throughout the world. The two drugs clinically available for its treatment have limited efficacy and cause serious adverse effects. Cruzain is an established therapeutic target of Trypanosoma cruzi, the protozoan that causes Chagas disease. Our group recently identified a competitive cruzain inhibitor (compound 1) with an IC50 = 15 µM that is also more synthetically accessible than the previously reported lead, compound 2. Prior studies, however, did not propose a binding mode for compound 1, hindering understanding of the structure-activity relationship and optimization. Here, the cruzain binding mode of compound 1 was investigated using docking, molecular dynamics (MD) simulations with ab initio derived parameters, ab initio calculations, and MM/PBSA. Two ligand protonation states and four binding poses were evaluated. A careful ligand parameterization method was employed to derive more physically meaningful parameters than those obtained by automated tools. The poses of unprotonated 1 were unstable in MD, showing large conformational changes and diffusing away from the binding site, whereas the protonated form showed higher stability and interaction with negatively charged residues Asp161 and Cys25. MM/PBSA also suggested that these two residues contribute favorably to binding of compound 1. By combining results from MD, ab initio calculations, and MM/PBSA, a binding mode of 1 is proposed. The results also provide insights for further optimization of 1, an interesting lead compound for the development of new cruzain inhibitors.

  11. The Drosophila hnRNP F/H Homolog Glorund Uses Two Distinct RNA-Binding Modes to Diversify Target Recognition

    Energy Technology Data Exchange (ETDEWEB)

    Tamayo, Joel V.; Teramoto, Takamasa; Chatterjee, Seema; Hall, Traci M. Tanaka; Gavis, Elizabeth R. (Princeton); (NIH)

    2017-04-01

    The Drosophila hnRNP F/H homolog, Glorund (Glo), regulates nanos mRNA translation by interacting with a structured UA-rich motif in the nanos 3' untranslated region. Glo regulates additional RNAs, however, and mammalian homologs bind G-tract sequences to regulate alternative splicing, suggesting that Glo also recognizes G-tract RNA. To gain insight into how Glo recognizes both structured UA-rich and G-tract RNAs, we used mutational analysis guided by crystal structures of Glo’s RNA-binding domains and identified two discrete RNA-binding surfaces that allow Glo to recognize both RNA motifs. By engineering Glo variants that favor a single RNA-binding mode, we show that a subset of Glo’s functions in vivo is mediated solely by the G-tract binding mode, whereas regulation of nanos requires both recognition modes. Our findings suggest a molecular mechanism for the evolution of dual RNA motif recognition in Glo that may be applied to understanding the functional diversity of other RNA-binding proteins.

  12. Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screening.

    Science.gov (United States)

    Ain, Qurrat Ul; Aleksandrova, Antoniya; Roessler, Florian D; Ballester, Pedro J

    2015-01-01

    Docking tools to predict whether and how a small molecule binds to a target can be applied if a structural model of such target is available. The reliability of docking depends, however, on the accuracy of the adopted scoring function (SF). Despite intense research over the years, improving the accuracy of SFs for structure-based binding affinity prediction or virtual screening has proven to be a challenging task for any class of method. New SFs based on modern machine-learning regression models, which do not impose a predetermined functional form and thus are able to exploit effectively much larger amounts of experimental data, have recently been introduced. These machine-learning SFs have been shown to outperform a wide range of classical SFs at both binding affinity prediction and virtual screening. The emerging picture from these studies is that the classical approach of using linear regression with a small number of expert-selected structural features can be strongly improved by a machine-learning approach based on nonlinear regression allied with comprehensive data-driven feature selection. Furthermore, the performance of classical SFs does not grow with larger training datasets and hence this performance gap is expected to widen as more training data becomes available in the future. Other topics covered in this review include predicting the reliability of a SF on a particular target class, generating synthetic data to improve predictive performance and modeling guidelines for SF development. WIREs Comput Mol Sci 2015, 5:405-424. doi: 10.1002/wcms.1225 For further resources related to this article, please visit the WIREs website.

  13. Structural analysis of substrate recognition by glucose isomerase in Mn2+ binding mode at M2 site in S. rubiginosus.

    Science.gov (United States)

    Bae, Ji-Eun; Hwang, Kwang Yeon; Nam, Ki Hyun

    2018-06-16

    Glucose isomerase (GI) catalyzes the reversible enzymatic isomerization of d-glucose and d-xylose to d-fructose and d-xylulose, respectively. This is one of the most important enzymes in the production of high-fructose corn syrup (HFCS) and biofuel. We recently determined the crystal structure of GI from S. rubiginosus (SruGI) complexed with a xylitol inhibitor in one metal binding mode. Although we assessed inhibitor binding at the M1 site, the metal binding at the M2 site and the substrate recognition mechanism for SruGI remains the unclear. Here, we report the crystal structure of the two metal binding modes of SruGI and its complex with glucose. This study provides a snapshot of metal binding at the SruGI M2 site in the presence of Mn 2+ , but not in the presence of Mg 2+ . Metal binding at the M2 site elicits a configuration change at the M1 site. Glucose molecule can only bind to the M1 site in presence of Mn 2+ at the M2 site. Glucose and Mn 2+ at the M2 site were bridged by water molecules using a hydrogen bonding network. The metal binding geometry of the M2 site indicates a distorted octahedral coordination with an angle of 55-110°, whereas the M1 site has a relatively stable octahedral coordination with an angle of 85-95°. We suggest a two-step sequential process for SruGI substrate recognition, in Mn 2+ binding mode, at the M2 site. Our results provide a better understanding of the molecular role of the M2 site in GI substrate recognition. Copyright © 2018. Published by Elsevier Inc.

  14. Predicting the binding patterns of hub proteins: a study using yeast protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Carson M Andorf

    Full Text Available Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Of particular interest are hub proteins that can interact with large numbers of partners and often play essential roles in cellular control. Depending on the number of binding sites, protein hubs can be classified at a structural level as singlish-interface hubs (SIH with one or two binding sites, or multiple-interface hubs (MIH with three or more binding sites. In terms of kinetics, hub proteins can be classified as date hubs (i.e., interact with different partners at different times or locations or party hubs (i.e., simultaneously interact with multiple partners.Our approach works in 3 phases: Phase I classifies if a protein is likely to bind with another protein. Phase II determines if a protein-binding (PB protein is a hub. Phase III classifies PB proteins as singlish-interface versus multiple-interface hubs and date versus party hubs. At each stage, we use sequence-based predictors trained using several standard machine learning techniques.Our method is able to predict whether a protein is a protein-binding protein with an accuracy of 94% and a correlation coefficient of 0.87; identify hubs from non-hubs with 100% accuracy for 30% of the data; distinguish date hubs/party hubs with 69% accuracy and area under ROC curve of 0.68; and SIH/MIH with 89% accuracy and area under ROC curve of 0.84. Because our method is based on sequence information alone, it can be used even in settings where reliable protein-protein interaction data or structures of protein-protein complexes are unavailable to obtain useful insights into the functional and evolutionary characteristics of proteins and their interactions.We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu.

  15. Predictive modelling of edge transport phenomena in ELMy H-mode tokamak fusion plasmas

    International Nuclear Information System (INIS)

    Loennroth, J.-S.

    2009-01-01

    This thesis discusses a range of work dealing with edge plasma transport in magnetically confined fusion plasmas by means of predictive transport modelling, a technique in which qualitative predictions and explanations are sought by running transport codes equipped with models for plasma transport and other relevant phenomena. The focus is on high confinement mode (H-mode) tokamak plasmas, which feature improved performance thanks to the formation of an edge transport barrier. H-mode plasmas are generally characterized by the occurrence of edge localized modes (ELMs), periodic eruptions of particles and energy, which limit confinement and may turn out to be seriously damaging in future tokamaks. The thesis introduces schemes and models for qualitative study of the ELM phenomenon in predictive transport modelling. It aims to shed new light on the dynamics of ELMs using these models. It tries to explain various experimental observations related to the performance and ELM-behaviour of H-mode plasmas. Finally, it also tries to establish more generally the potential effects of ripple-induced thermal ion losses on H-mode plasma performance and ELMs. It is demonstrated that the proposed ELM modelling schemes can qualitatively reproduce the experimental dynamics of a number of ELM regimes. Using a theory-motivated ELM model based on a linear instability model, the dynamics of combined ballooning-peeling mode ELMs is studied. It is shown that the ELMs are most often triggered by a ballooning mode instability, which renders the plasma peeling mode unstable, causing the ELM to continue in a peeling mode phase. Understanding the dynamics of ELMs will be a key issue when it comes to controlling and mitigating the ELMs in future large tokamaks. By means of integrated modelling, it is shown that an experimentally observed increase in the ELM frequency and deterioration of plasma confinement triggered by external neutral gas puffing might be due to a transition from the second to

  16. Prediction of trypsin/molecular fragment binding affinities by free energy decomposition and empirical scores

    Science.gov (United States)

    Benson, Mark L.; Faver, John C.; Ucisik, Melek N.; Dashti, Danial S.; Zheng, Zheng; Merz, Kenneth M.

    2012-05-01

    Two families of binding affinity estimation methodologies are described which were utilized in the SAMPL3 trypsin/fragment binding affinity challenge. The first is a free energy decomposition scheme based on a thermodynamic cycle, which included separate contributions from enthalpy and entropy of binding as well as a solvent contribution. Enthalpic contributions were estimated with PM6-DH2 semiempirical quantum mechanical interaction energies, which were modified with a statistical error correction procedure. Entropic contributions were estimated with the rigid-rotor harmonic approximation, and solvent contributions to the free energy were estimated with several different methods. The second general methodology is the empirical score LISA, which contains several physics-based terms trained with the large PDBBind database of protein/ligand complexes. Here we also introduce LISA+, an updated version of LISA which, prior to scoring, classifies systems into one of four classes based on a ligand's hydrophobicity and molecular weight. Each version of the two methodologies (a total of 11 methods) was trained against a compiled set of known trypsin binders available in the Protein Data Bank to yield scaling parameters for linear regression models. Both raw and scaled scores were submitted to SAMPL3. Variants of LISA showed relatively low absolute errors but also low correlation with experiment, while the free energy decomposition methods had modest success when scaling factors were included. Nonetheless, re-scaled LISA yielded the best predictions in the challenge in terms of RMS error, and six of these models placed in the top ten best predictions by RMS error. This work highlights some of the difficulties of predicting binding affinities of small molecular fragments to protein receptors as well as the benefit of using training data.

  17. The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

    Science.gov (United States)

    Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

    2011-07-01

    The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

  18. Predicting binding affinities of protein ligands from three-dimensional models: application to peptide binding to class I major histocompatibility proteins

    DEFF Research Database (Denmark)

    Rognan, D; Lauemoller, S L; Holm, A

    1999-01-01

    A simple and fast free energy scoring function (Fresno) has been developed to predict the binding free energy of peptides to class I major histocompatibility (MHC) proteins. It differs from existing scoring functions mainly by the explicit treatment of ligand desolvation and of unfavorable protein...... coordinates of the MHC-bound peptide have first been determined with an accuracy of about 1-1.5 A. Furthermore, it may be easily recalibrated for any protein-ligand complex.......) and of a series of 16 peptides to H-2K(k). Predictions were more accurate for HLA-A2-binding peptides as the training set had been built from experimentally determined structures. The average error in predicting the binding free energy of the test peptides was 3.1 kJ/mol. For the homology model-derived equation...

  19. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Lund, Ole

    2007-01-01

    the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance...... of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles. RESULTS: The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation...... between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR), we demonstrate a consistent gain in predictive performance...

  20. Low-Quality Structural and Interaction Data Improves Binding Affinity Prediction via Random Forest.

    Science.gov (United States)

    Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J

    2015-06-12

    Docking scoring functions can be used to predict the strength of protein-ligand binding. It is widely believed that training a scoring function with low-quality data is detrimental for its predictive performance. Nevertheless, there is a surprising lack of systematic validation experiments in support of this hypothesis. In this study, we investigated to which extent training a scoring function with data containing low-quality structural and binding data is detrimental for predictive performance. We actually found that low-quality data is not only non-detrimental, but beneficial for the predictive performance of machine-learning scoring functions, though the improvement is less important than that coming from high-quality data. Furthermore, we observed that classical scoring functions are not able to effectively exploit data beyond an early threshold, regardless of its quality. This demonstrates that exploiting a larger data volume is more important for the performance of machine-learning scoring functions than restricting to a smaller set of higher data quality.

  1. G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

    Science.gov (United States)

    Lee, Hui Sun; Im, Wonpil

    2017-01-01

    Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

  2. Improved methods for predicting peptide binding affinity to MHC class II molecules.

    Science.gov (United States)

    Jensen, Kamilla Kjaergaard; Andreatta, Massimo; Marcatili, Paolo; Buus, Søren; Greenbaum, Jason A; Yan, Zhen; Sette, Alessandro; Peters, Bjoern; Nielsen, Morten

    2018-01-06

    Major histocompatibility complex class II (MHC-II) molecules are expressed on the surface of professional antigen-presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC-II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T-cell epitopes. We here present updated versions of two MHC-II-peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC-peptide binding affinity data obtained from the Immune Epitope Database covering HLA-DR, HLA-DQ, HLA-DP and H-2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at www.cbs.dtu.dk/services/NetMHCII-2.3 and www.cbs.dtu.dk/services/NetMHCIIpan-3.2. © 2018 John Wiley & Sons Ltd.

  3. Accurate and Reliable Prediction of the Binding Affinities of Macrocycles to Their Protein Targets.

    Science.gov (United States)

    Yu, Haoyu S; Deng, Yuqing; Wu, Yujie; Sindhikara, Dan; Rask, Amy R; Kimura, Takayuki; Abel, Robert; Wang, Lingle

    2017-12-12

    Macrocycles have been emerging as a very important drug class in the past few decades largely due to their expanded chemical diversity benefiting from advances in synthetic methods. Macrocyclization has been recognized as an effective way to restrict the conformational space of acyclic small molecule inhibitors with the hope of improving potency, selectivity, and metabolic stability. Because of their relatively larger size as compared to typical small molecule drugs and the complexity of the structures, efficient sampling of the accessible macrocycle conformational space and accurate prediction of their binding affinities to their target protein receptors poses a great challenge of central importance in computational macrocycle drug design. In this article, we present a novel method for relative binding free energy calculations between macrocycles with different ring sizes and between the macrocycles and their corresponding acyclic counterparts. We have applied the method to seven pharmaceutically interesting data sets taken from recent drug discovery projects including 33 macrocyclic ligands covering a diverse chemical space. The predicted binding free energies are in good agreement with experimental data with an overall root-mean-square error (RMSE) of 0.94 kcal/mol. This is to our knowledge the first time where the free energy of the macrocyclization of linear molecules has been directly calculated with rigorous physics-based free energy calculation methods, and we anticipate the outstanding accuracy demonstrated here across a broad range of target classes may have significant implications for macrocycle drug discovery.

  4. SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

    Directory of Open Access Journals (Sweden)

    Xiaoxia Yang

    Full Text Available Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

  5. Predictions and observations of global beta-induced Alfven-acoustic modes in JET and NSTX

    Energy Technology Data Exchange (ETDEWEB)

    Gorelenkov, N N [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Berk, H L [Institute for Fusion Studies, University of Texas, Austin, TX 78712 (United States); Crocker, N A [Institute of Plasma and Fusion Research, University of California, Los Angeles, CA 90095-1354 (United States); Fredrickson, E D [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Kaye, S [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Kubota, S [Institute of Plasma and Fusion Research, University of California, Los Angeles, CA 90095-1354 (United States); Park, H [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Peebles, W [Institute of Plasma and Fusion Research, University of California, Los Angeles, CA 90095-1354 (United States); Sabbagh, S A [Department of Applied Physics, Columbia University, New York, NY 10027-6902 (United States); Sharapov, S E [Euroatom/UKAEA Fusion Association, Culham Science Centre, Abingdon, Oxfordshire OX14 3DB (United Kingdom); Stutmat, D [Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States); Tritz, K [Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States); Levinton, F M [Nova Photonics, One Oak Place, Princeton, NJ 08540 (United States); Yuh, H [Nova Photonics, One Oak Place, Princeton, NJ 08540 (United States)

    2007-12-15

    In this paper we report on observations and interpretations of a new class of global MHD eigenmode solutions arising in gaps in the low frequency Alfven-acoustic continuum below the geodesic acoustic mode frequency. These modes have been just reported (Gorelenkov et al 2007 Phys. Lett. 370 70-7) where preliminary comparisons indicate qualitative agreement between theory and experiment. Here we show a more quantitative comparison emphasizing recent NSTX experiments on the observations of the global eigenmodes, referred to as beta-induced Alfven-acoustic eigenmodes (BAAEs), which exist near the extrema of the Alfven-acoustic continuum. In accordance to the linear dispersion relations, the frequency of these modes may shift as the safety factor, q, profile relaxes. We show that BAAEs can be responsible for observations in JET plasmas at relatively low beta <2% as well as in NSTX plasmas at relatively high beta >20%. In NSTX plasma observed magnetic activity has the same properties as predicted by theory for the mode structure and the frequency. Found numerically in NOVA simulations BAAEs are used to explain the observed properties of relatively low frequency experimental signals seen in NSTX and JET tokamaks.

  6. Generalized Predictive Control of Dynamic Systems with Rigid-Body Modes

    Science.gov (United States)

    Kvaternik, Raymond G.

    2013-01-01

    Numerical simulations to assess the effectiveness of Generalized Predictive Control (GPC) for active control of dynamic systems having rigid-body modes are presented. GPC is a linear, time-invariant, multi-input/multi-output predictive control method that uses an ARX model to characterize the system and to design the controller. Although the method can accommodate both embedded (implicit) and explicit feedforward paths for incorporation of disturbance effects, only the case of embedded feedforward in which the disturbances are assumed to be unknown is considered here. Results from numerical simulations using mathematical models of both a free-free three-degree-of-freedom mass-spring-dashpot system and the XV-15 tiltrotor research aircraft are presented. In regulation mode operation, which calls for zero system response in the presence of disturbances, the simulations showed reductions of nearly 100%. In tracking mode operations, where the system is commanded to follow a specified path, the GPC controllers produced the desired responses, even in the presence of disturbances.

  7. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Karosiene, Edita; Rasmussen, Michael

    2015-01-01

    with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped...

  8. Neighbourhood, Route and Workplace-Related Environmental Characteristics Predict Adults' Mode of Travel to Work.

    Science.gov (United States)

    Dalton, Alice M; Jones, Andrew P; Panter, Jenna R; Ogilvie, David

    2013-01-01

    Commuting provides opportunities for regular physical activity which can reduce the risk of chronic disease. Commuters' mode of travel may be shaped by their environment, but understanding of which specific environmental characteristics are most important and might form targets for intervention is limited. This study investigated associations between mode choice and a range of objectively assessed environmental characteristics. Participants in the Commuting and Health in Cambridge study reported where they lived and worked, their usual mode of travel to work and a variety of socio-demographic characteristics. Using geographic information system (GIS) software, 30 exposure variables were produced capturing characteristics of areas around participants' homes and workplaces and their shortest modelled routes to work. Associations between usual mode of travel to work and personal and environmental characteristics were investigated using multinomial logistic regression. Of the 1124 respondents, 50% reported cycling or walking as their usual mode of travel to work. In adjusted analyses, home-work distance was strongly associated with mode choice, particularly for walking. Lower odds of walking or cycling rather than driving were associated with a less frequent bus service (highest versus lowest tertile: walking OR 0.61 [95% CI 0.20-1.85]; cycling OR 0.43 [95% CI 0.23-0.83]), low street connectivity (OR 0.22, [0.07-0.67]; OR 0.48 [0.26-0.90]) and free car parking at work (OR 0.24 [0.10-0.59]; OR 0.55 [0.32-0.95]). Participants were less likely to cycle if they had access to fewer destinations (leisure facilities, shops and schools) close to work (OR 0.36 [0.21-0.62]) and a railway station further from home (OR 0.53 [0.30-0.93]). Covariates strongly predicted travel mode (pseudo r-squared 0.74). Potentially modifiable environmental characteristics, including workplace car parking, street connectivity and access to public transport, are associated with travel mode choice

  9. Neighbourhood, Route and Workplace-Related Environmental Characteristics Predict Adults' Mode of Travel to Work.

    Directory of Open Access Journals (Sweden)

    Alice M Dalton

    Full Text Available Commuting provides opportunities for regular physical activity which can reduce the risk of chronic disease. Commuters' mode of travel may be shaped by their environment, but understanding of which specific environmental characteristics are most important and might form targets for intervention is limited. This study investigated associations between mode choice and a range of objectively assessed environmental characteristics.Participants in the Commuting and Health in Cambridge study reported where they lived and worked, their usual mode of travel to work and a variety of socio-demographic characteristics. Using geographic information system (GIS software, 30 exposure variables were produced capturing characteristics of areas around participants' homes and workplaces and their shortest modelled routes to work. Associations between usual mode of travel to work and personal and environmental characteristics were investigated using multinomial logistic regression.Of the 1124 respondents, 50% reported cycling or walking as their usual mode of travel to work. In adjusted analyses, home-work distance was strongly associated with mode choice, particularly for walking. Lower odds of walking or cycling rather than driving were associated with a less frequent bus service (highest versus lowest tertile: walking OR 0.61 [95% CI 0.20-1.85]; cycling OR 0.43 [95% CI 0.23-0.83], low street connectivity (OR 0.22, [0.07-0.67]; OR 0.48 [0.26-0.90] and free car parking at work (OR 0.24 [0.10-0.59]; OR 0.55 [0.32-0.95]. Participants were less likely to cycle if they had access to fewer destinations (leisure facilities, shops and schools close to work (OR 0.36 [0.21-0.62] and a railway station further from home (OR 0.53 [0.30-0.93]. Covariates strongly predicted travel mode (pseudo r-squared 0.74.Potentially modifiable environmental characteristics, including workplace car parking, street connectivity and access to public transport, are associated with travel mode

  10. Probing ligand binding modes of Mycobacterium tuberculosis MurC ligase by molecular modeling, dynamics simulation and docking.

    Science.gov (United States)

    Anuradha, C M; Mulakayala, Chaitanya; Babajan, Banaganapalli; Naveen, M; Rajasekhar, Chikati; Kumar, Chitta Suresh

    2010-01-01

    Multi drug resistance capacity for Mycobacterium tuberculosis (MDR-Mtb) demands the profound need for developing new anti-tuberculosis drugs. The present work is on Mtb-MurC ligase, which is an enzyme involved in biosynthesis of peptidoglycan, a component of Mtb cell wall. In this paper the 3-D structure of Mtb-MurC has been constructed using the templates 1GQQ and 1P31. Structural refinement and energy minimization of the predicted Mtb-MurC ligase model has been carried out by molecular dynamics. The streochemical check failures in the energy minimized model have been evaluated through Procheck, Whatif ProSA, and Verify 3D. Further torsion angles for the side chains of amino acid residues of the developed model were determined using Predictor. Docking analysis of Mtb-MurC model with ligands and natural substrates enabled us to identify specific residues viz. Gly125, Lys126, Arg331, and Arg332, within the Mtb-MurC binding pocket to play an important role in ligand and substrate binding affinity and selectivity. The availability of Mtb-MurC ligase built model, together with insights gained from docking analysis will promote the rational design of potent and selective Mtb-MurC ligase inhibitors as antituberculosis therapeutics.

  11. Tris-amidoximate uranyl complexes via η2 binding mode coordinated in aqueous solution shown by X-ray absorption spectroscopy and density functional theory methods.

    Science.gov (United States)

    Zhang, Linjuan; Qie, Meiying; Su, Jing; Zhang, Shuo; Zhou, Jing; Li, Jiong; Wang, Yu; Yang, Shitong; Wang, Shuao; Li, Jingye; Wu, Guozhong; Wang, Jian Qiang

    2018-03-01

    The present study sheds some light on the long-standing debate concerning the coordination properties between uranyl ions and the amidoxime ligand, which is a key ingredient for achieving efficient extraction of uranium. Using X-ray absorption fine structure combined with theoretical simulation methods, the binding mode and bonding nature of a uranyl-amidoxime complex in aqueous solution were determined for the first time. The results show that in a highly concentrated amidoxime solution the preferred binding mode between UO 2 2+ and the amidoxime ligand is η 2 coordination with tris-amidoximate species. In such a uranyl-amidoximate complex with η 2 binding motif, strong covalent interaction and orbital hybridization between U 5f/6d and (N, O) 2p should be responsible for the excellent binding ability of the amidoximate ligand to uranyl. The study was performed directly in aqueous solution to avoid the possible binding mode differences caused by crystallization of a single-crystal sample. This work also is an example of the simultaneous study of local structure and electronic structure in solution systems using combined diagnostic tools.

  12. LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation

    Directory of Open Access Journals (Sweden)

    Schroeder Michael

    2006-09-01

    Full Text Available Abstract Background Identifying pockets on protein surfaces is of great importance for many structure-based drug design applications and protein-ligand docking algorithms. Over the last ten years, many geometric methods for the prediction of ligand-binding sites have been developed. Results We present LIGSITEcsc, an extension and implementation of the LIGSITE algorithm. LIGSITEcsc is based on the notion of surface-solvent-surface events and the degree of conservation of the involved surface residues. We compare our algorithm to four other approaches, LIGSITE, CAST, PASS, and SURFNET, and evaluate all on a dataset of 48 unbound/bound structures and 210 bound-structures. LIGSITEcsc performs slightly better than the other tools and achieves a success rate of 71% and 75%, respectively. Conclusion The use of the Connolly surface leads to slight improvements, the prediction re-ranking by conservation to significant improvements of the binding site predictions. A web server for LIGSITEcsc and its source code is available at scoppi.biotec.tu-dresden.de/pocket.

  13. CaFE: a tool for binding affinity prediction using end-point free energy methods.

    Science.gov (United States)

    Liu, Hui; Hou, Tingjun

    2016-07-15

    Accurate prediction of binding free energy is of particular importance to computational biology and structure-based drug design. Among those methods for binding affinity predictions, the end-point approaches, such as MM/PBSA and LIE, have been widely used because they can achieve a good balance between prediction accuracy and computational cost. Here we present an easy-to-use pipeline tool named Calculation of Free Energy (CaFE) to conduct MM/PBSA and LIE calculations. Powered by the VMD and NAMD programs, CaFE is able to handle numerous static coordinate and molecular dynamics trajectory file formats generated by different molecular simulation packages and supports various force field parameters. CaFE source code and documentation are freely available under the GNU General Public License via GitHub at https://github.com/huiliucode/cafe_plugin It is a VMD plugin written in Tcl and the usage is platform-independent. tingjunhou@zju.edu.cn. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Determination of the binding mode for the cyclopentapeptide CXCR4 antagonist FC131 using a dual approach of ligand modifications and receptor mutagenesis

    DEFF Research Database (Denmark)

    Thiele, Stefanie; Mungalpara, J; Steen, A

    2014-01-01

    have previously been suggested based on molecular docking guided by structure-activity relationship (SAR) data; however, none of these have been verified by in vitro experiments. EXPERIMENTAL APPROACH: Heterologous (125) I-12G5-competition binding and functional assays (inhibition of CXCL12-mediated...... activation) of FC131 and three analogues were performed on wild-type CXCR4 and 25 receptor mutants. Computational modelling was used to rationalize the experimental data. KEY RESULTS: The Arg(2) and 2-Nal(3) side chains of FC131 interact with residues in TM-3 (His(113) , Asp(171) ) and TM-5 (hydrophobic......-bond in CXCR4 crystal structures and mutation of either residue to Ala abolishes CXCR4 activity. CONCLUSIONS AND IMPLICATIONS: Ligand modification, receptor mutagenesis and computational modelling approaches were used to identify the binding mode of FC131 in CXCR4, which was in agreement with binding modes...

  15. The DNA-recognition mode shared by archaeal feast/famine-regulatory proteins revealed by the DNA-binding specificities of TvFL3, FL10, FL11 and Ss-LrpB

    Science.gov (United States)

    Yokoyama, Katsushi; Nogami, Hideki; Kabasawa, Mamiko; Ebihara, Sonomi; Shimowasa, Ai; Hashimoto, Keiko; Kawashima, Tsuyoshi; Ishijima, Sanae A.; Suzuki, Masashi

    2009-01-01

    The DNA-binding mode of archaeal feast/famine-regulatory proteins (FFRPs), i.e. paralogs of the Esherichia coli leucine-responsive regulatory protein (Lrp), was studied. Using the method of systematic evolution of ligands by exponential enrichment (SELEX), optimal DNA duplexes for interacting with TvFL3, FL10, FL11 and Ss-LrpB were identified as TACGA[AAT/ATT]TCGTA, GTTCGA[AAT/ATT]TCGAAC, CCGAAA[AAT/ATT]TTTCGG and TTGCAA[AAT/ATT]TTGCAA, respectively, all fitting into the form abcdeWWWedcba. Here W is A or T, and e.g. a and a are bases complementary to each other. Apparent equilibrium binding constants of the FFRPs and various DNA duplexes were determined, thereby confirming the DNA-binding specificities of the FFRPs. It is likely that these FFRPs recognize DNA in essentially the same way, since their DNA-binding specificities were all explained by the same pattern of relationship between amino-acid positions and base positions to form chemical interactions. As predicted from this relationship, when Gly36 of TvFL3 was replaced by Thr, the b base in the optimal DNA duplex changed from A to T, and, when Thr36 of FL10 was replaced by Ser, the b base changed from T to G/A. DNA-binding characteristics of other archaeal FFRPs, Ptr1, Ptr2, Ss-Lrp and LysM, are also consistent with the relationship. PMID:19468044

  16. An adaptive mode-driven spatiotemporal motion vector prediction for wavelet video coding

    Science.gov (United States)

    Zhao, Fan; Liu, Guizhong; Qi, Yong

    2010-07-01

    The three-dimensional subband/wavelet codecs use 5/3 filters rather than Haar filters for the motion compensation temporal filtering (MCTF) to improve the coding gain. In order to curb the increased motion vector rate, an adaptive motion mode driven spatiotemporal motion vector prediction (AMDST-MVP) scheme is proposed. First, by making use of the direction histograms of four motion vector fields resulting from the initial spatial motion vector prediction (SMVP), the motion mode of the current GOP is determined according to whether the fast or complex motion exists in the current GOP. Then the GOP-level MVP scheme is thereby determined by either the S-MVP or the AMDST-MVP, namely, AMDST-MVP is the combination of S-MVP and temporal-MVP (T-MVP). If the latter is adopted, the motion vector difference (MVD) between the neighboring MV fields and the S-MVP resulting MV of the current block is employed to decide whether or not the MV of co-located block in the previous frame is used for prediction the current block. Experimental results show that AMDST-MVP not only can improve the coding efficiency but also reduce the number of computation complexity.

  17. Reliability analysis and prediction of mixed mode load using Markov Chain Model

    International Nuclear Information System (INIS)

    Nikabdullah, N.; Singh, S. S. K.; Alebrahim, R.; Azizi, M. A.; K, Elwaleed A.; Noorani, M. S. M.

    2014-01-01

    The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading

  18. Binding mode dependent signaling for the detection of Cu2 +: An experimental and theoretical approach with practical applications

    Science.gov (United States)

    Ghosh, Soumen; Khan, Mehebub Ali; Ganguly, Aniruddha; Masum, Abdulla Al; Alam, Md. Akhtarul; Guchhait, Nikhil

    2018-02-01

    Two amido-schiff bases (3-Hydroxy-naphthalene-2-carboxylic acid pyren-1-ylmethylene-hydrazide and Naphthalene-2-carboxylic acid pyren-1-ylmethylene-hydrazide) have been synthesized having a common structural unit and only differs by a -OH group in the naphthalene ring. Both of them can detect Cu2 + ion selectively in semi-aqueous medium in distinctly different output modes (one detects Cu2 + by naked-eye color change where as the other detects Cu2 + by fluorescence enhancement). The difference in the binding of Cu 2 + with the compounds is the reason for this observation. The detection limit is found to be micromolar region for compound which contains -OH group whereas the compound without -OH group detects copper in nano-molar region. DFT calculations have been performed in order to demonstrate the structure of the compounds and their copper complexes. Practical utility has been explored by successful paper strip response of both the compounds. The biological applications have been evaluated in RAW 264.7.

  19. Structure of Bacillus subtilis γ-glutamyltranspeptidase in complex with acivicin: diversity of the binding mode of a classical and electrophilic active-site-directed glutamate analogue

    Energy Technology Data Exchange (ETDEWEB)

    Ida, Tomoyo [Osaka University, Toyonaka, Osaka 560-0043 (Japan); Suzuki, Hideyuki [Kyoto Institute of Technology, Goshokaido-cho, Matsugasaki, Sakyo-ku, Kyoto 606-8585 (Japan); Fukuyama, Keiichi [Osaka University, Toyonaka, Osaka 560-0043 (Japan); Hiratake, Jun [Kyoto University, Uji, Kyoto 611-0011 (Japan); Wada, Kei, E-mail: keiwada@med.miyazaki-u.ac.jp [University of Miyazaki, Miyazaki 889-1692 (Japan); Osaka University, Toyonaka, Osaka 560-0043 (Japan)

    2014-02-01

    The binding modes of acivicin, a classical and an electrophilic active-site-directed glutamate analogue, to bacterial γ-glutamyltranspeptidases were found to be diverse. γ-Glutamyltranspeptidase (GGT) is an enzyme that plays a central role in glutathione metabolism, and acivicin is a classical inhibitor of GGT. Here, the structure of acivicin bound to Bacillus subtilis GGT determined by X-ray crystallography to 1.8 Å resolution is presented, in which it binds to the active site in a similar manner to that in Helicobacter pylori GGT, but in a different binding mode to that in Escherichia coli GGT. In B. subtilis GGT, acivicin is bound covalently through its C3 atom with sp{sup 2} hybridization to Thr403 O{sup γ}, the catalytic nucleophile of the enzyme. The results show that acivicin-binding sites are common, but the binding manners and orientations of its five-membered dihydroisoxazole ring are diverse in the binding pockets of GGTs.

  20. Principal component analysis for predicting transcription-factor binding motifs from array-derived data

    Directory of Open Access Journals (Sweden)

    Vincenti Matthew P

    2005-11-01

    Full Text Available Abstract Background The responses to interleukin 1 (IL-1 in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to transcription-factor binding motifs (TFBMs. In order to select a critical set of TFBMs from genomic DNA information and an array-derived data, an efficient algorithm to solve a combinatorial optimization problem is required. Although computational approaches based on evolutionary algorithms are commonly employed, an analytical algorithm would be useful to predict TFBMs at nearly no computational cost and evaluate varying modelling conditions. Singular value decomposition (SVD is a powerful method to derive primary components of a given matrix. Applying SVD to a promoter matrix defined from regulatory DNA sequences, we derived a novel method to predict the critical set of TFBMs. Results The promoter matrix was defined to establish a quantitative relationship between the IL-1-driven mRNA alteration and genomic DNA sequences of the IL-1 responsive genes. The matrix was decomposed with SVD, and the effects of 8 potential TFBMs (5'-CAGGC-3', 5'-CGCCC-3', 5'-CCGCC-3', 5'-ATGGG-3', 5'-GGGAA-3', 5'-CGTCC-3', 5'-AAAGG-3', and 5'-ACCCA-3' were predicted from a pool of 512 random DNA sequences. The prediction included matches to the core binding motifs of biologically known TFBMs such as AP2, SP1, EGR1, KROX, GC-BOX, ABI4, ETF, E2F, SRF, STAT, IK-1, PPARγ, STAF, ROAZ, and NFκB, and their significance was evaluated numerically using Monte Carlo simulation and genetic algorithm. Conclusion The described SVD-based prediction is an analytical method to provide a set of potential TFBMs involved in transcriptional regulation. The results would be useful to evaluate analytically a contribution of individual DNA sequences.

  1. Reliability prediction of engineering systems with competing failure modes due to component degradation

    International Nuclear Information System (INIS)

    Son, Young Kap

    2011-01-01

    Reliability of an engineering system depends on two reliability metrics: the mechanical reliability, considering component failures, that a functional system topology is maintained and the performance reliability of adequate system performance in each functional configuration. Component degradation explains not only the component aging processes leading to failure in function, but also system performance change over time. Multiple competing failure modes for systems with degrading components in terms of system functionality and system performance are considered in this paper with the assumption that system functionality is not independent of system performance. To reduce errors in system reliability prediction, this paper tries to extend system performance reliability prediction methods in open literature through combining system mechanical reliability from component reliabilities and system performance reliability. The extended reliability prediction method provides a useful way to compare designs as well as to determine effective maintenance policy for efficient reliability growth. Application of the method to an electro-mechanical system, as an illustrative example, is explained in detail, and the prediction results are discussed. Both mechanical reliability and performance reliability are compared to total system reliability in terms of reliability prediction errors

  2. Cost Function Network-based Design of Protein-Protein Interactions: predicting changes in binding affinity.

    Science.gov (United States)

    Viricel, Clément; de Givry, Simon; Schiex, Thomas; Barbe, Sophie

    2018-02-20

    Accurate and economic methods to predict change in protein binding free energy upon mutation are imperative to accelerate the design of proteins for a wide range of applications. Free energy is defined by enthalpic and entropic contributions. Following the recent progresses of Artificial Intelligence-based algorithms for guaranteed NP-hard energy optimization and partition function computation, it becomes possible to quickly compute minimum energy conformations and to reliably estimate the entropic contribution of side-chains in the change of free energy of large protein interfaces. Using guaranteed Cost Function Network algorithms, Rosetta energy functions and Dunbrack's rotamer library, we developed and assessed EasyE and JayZ, two methods for binding affinity estimation that ignore or include conformational entropic contributions on a large benchmark of binding affinity experimental measures. If both approaches outperform most established tools, we observe that side-chain conformational entropy brings little or no improvement on most systems but becomes crucial in some rare cases. as open-source Python/C ++ code at sourcesup.renater.fr/projects/easy-jayz. thomas.schiex@inra.fr and sophie.barbe@insa-toulouse.fr. Supplementary data are available at Bioinformatics online.

  3. Predicting DNA binding proteins using support vector machine with hybrid fractal features.

    Science.gov (United States)

    Niu, Xiao-Hui; Hu, Xue-Hai; Shi, Feng; Xia, Jing-Bo

    2014-02-21

    DNA-binding proteins play a vitally important role in many biological processes. Prediction of DNA-binding proteins from amino acid sequence is a significant but not fairly resolved scientific problem. Chaos game representation (CGR) investigates the patterns hidden in protein sequences, and visually reveals previously unknown structure. Fractal dimensions (FD) are good tools to measure sizes of complex, highly irregular geometric objects. In order to extract the intrinsic correlation with DNA-binding property from protein sequences, CGR algorithm, fractal dimension and amino acid composition are applied to formulate the numerical features of protein samples in this paper. Seven groups of features are extracted, which can be computed directly from the primary sequence, and each group is evaluated by the 10-fold cross-validation test and Jackknife test. Comparing the results of numerical experiments, the group of amino acid composition and fractal dimension (21-dimension vector) gets the best result, the average accuracy is 81.82% and average Matthew's correlation coefficient (MCC) is 0.6017. This resulting predictor is also compared with existing method DNA-Prot and shows better performances. © 2013 The Authors. Published by Elsevier Ltd All rights reserved.

  4. NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction

    Directory of Open Access Journals (Sweden)

    Lund Ole

    2009-09-01

    Full Text Available Abstract Background The major histocompatibility complex (MHC molecule plays a central role in controlling the adaptive immune response to infections. MHC class I molecules present peptides derived from intracellular proteins to cytotoxic T cells, whereas MHC class II molecules stimulate cellular and humoral immunity through presentation of extracellularly derived peptides to helper T cells. Identification of which peptides will bind a given MHC molecule is thus of great importance for the understanding of host-pathogen interactions, and large efforts have been placed in developing algorithms capable of predicting this binding event. Results Here, we present a novel artificial neural network-based method, NN-align that allows for simultaneous identification of the MHC class II binding core and binding affinity. NN-align is trained using a novel training algorithm that allows for correction of bias in the training data due to redundant binding core representation. Incorporation of information about the residues flanking the peptide-binding core is shown to significantly improve the prediction accuracy. The method is evaluated on a large-scale benchmark consisting of six independent data sets covering 14 human MHC class II alleles, and is demonstrated to outperform other state-of-the-art MHC class II prediction methods. Conclusion The NN-align method is competitive with the state-of-the-art MHC class II peptide binding prediction algorithms. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCII-2.0.

  5. Prediction of Water Binding to Protein Hydration Sites with a Discrete, Semiexplicit Solvent Model.

    Science.gov (United States)

    Setny, Piotr

    2015-12-08

    Buried water molecules are ubiquitous in protein structures and are found at the interface of most protein-ligand complexes. Determining their distribution and thermodynamic effect is a challenging yet important task, of great of practical value for the modeling of biomolecular structures and their interactions. In this study, we present a novel method aimed at the prediction of buried water molecules in protein structures and estimation of their binding free energies. It is based on a semiexplicit, discrete solvation model, which we previously introduced in the context of small molecule hydration. The method is applicable to all macromolecular structures described by a standard all-atom force field, and predicts complete solvent distribution within a single run with modest computational cost. We demonstrate that it indicates positions of buried hydration sites, including those filled by more than one water molecule, and accurately differentiates them from sterically accessible to water but void regions. The obtained estimates of water binding free energies are in fair agreement with reference results determined with the double decoupling method.

  6. Two modes of interaction of the single-stranded DNA-binding protein of bacteriophage T7 with the DNA polymerase-thioredoxin complex

    KAUST Repository

    Ghosh, Sharmistha; Hamdan, Samir; Richardson, Charles C.

    2010-01-01

    The DNA polymerase encoded by bacteriophage T7 has low processivity. Escherichia coli thioredoxin binds to a segment of 76 residues in the thumb subdomain of the polymerase and increases the processivity. The binding of thioredoxin leads to the formation of two basic loops, loops A and B, located within the thioredoxin-binding domain (TBD). Both loops interact with the acidic C terminus of the T7 helicase. A relatively weak electrostatic mode involves the C-terminal tail of the helicase and the TBD, whereas a high affinity interaction that does not involve the C-terminal tail occurs when the polymerase is in a polymerization mode. T7 gene 2.5 single-stranded DNA-binding protein (gp2.5) also has an acidic C-terminal tail. gp2.5 also has two modes of interaction with the polymerase, but both involve the C-terminal tail of gp2.5. An electrostatic interaction requires the basic residues in loops A and B, and gp2.5 binds to both loops with similar affinity as measured by surface plasmon resonance. When the polymerase is in a polymerization mode, the C terminus of gene 2.5 protein interacts with the polymerase in regions outside the TBD.gp2.5 increases the processivity of the polymerase-helicase complex during leading strand synthesis. When loop B of the TBD is altered, abortive DNA products are observed during leading strand synthesis. Loop B appears to play an important role in communication with the helicase and gp2.5, whereas loop A plays a stabilizing role in these interactions. © 2010 by The American Society for Biochemistry and Molecular Biology, Inc.

  7. Two modes of interaction of the single-stranded DNA-binding protein of bacteriophage T7 with the DNA polymerase-thioredoxin complex

    KAUST Repository

    Ghosh, Sharmistha

    2010-04-06

    The DNA polymerase encoded by bacteriophage T7 has low processivity. Escherichia coli thioredoxin binds to a segment of 76 residues in the thumb subdomain of the polymerase and increases the processivity. The binding of thioredoxin leads to the formation of two basic loops, loops A and B, located within the thioredoxin-binding domain (TBD). Both loops interact with the acidic C terminus of the T7 helicase. A relatively weak electrostatic mode involves the C-terminal tail of the helicase and the TBD, whereas a high affinity interaction that does not involve the C-terminal tail occurs when the polymerase is in a polymerization mode. T7 gene 2.5 single-stranded DNA-binding protein (gp2.5) also has an acidic C-terminal tail. gp2.5 also has two modes of interaction with the polymerase, but both involve the C-terminal tail of gp2.5. An electrostatic interaction requires the basic residues in loops A and B, and gp2.5 binds to both loops with similar affinity as measured by surface plasmon resonance. When the polymerase is in a polymerization mode, the C terminus of gene 2.5 protein interacts with the polymerase in regions outside the TBD.gp2.5 increases the processivity of the polymerase-helicase complex during leading strand synthesis. When loop B of the TBD is altered, abortive DNA products are observed during leading strand synthesis. Loop B appears to play an important role in communication with the helicase and gp2.5, whereas loop A plays a stabilizing role in these interactions. © 2010 by The American Society for Biochemistry and Molecular Biology, Inc.

  8. Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis.

    Science.gov (United States)

    Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X

    2016-09-01

    The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.

  9. Proteochemometric model for predicting the inhibition of penicillin-binding proteins

    Science.gov (United States)

    Nabu, Sunanta; Nantasenamat, Chanin; Owasirikul, Wiwat; Lawung, Ratana; Isarankura-Na-Ayudhya, Chartchalerm; Lapins, Maris; Wikberg, Jarl E. S.; Prachayasittikul, Virapong

    2015-02-01

    Neisseria gonorrhoeae infection threatens to become an untreatable sexually transmitted disease in the near future owing to the increasing emergence of N. gonorrhoeae strains with reduced susceptibility and resistance to the extended-spectrum cephalosporins (ESCs), i.e. ceftriaxone and cefixime, which are the last remaining option for first-line treatment of gonorrhea. Alteration of the penA gene, encoding penicillin-binding protein 2 (PBP2), is the main mechanism conferring penicillin resistance including reduced susceptibility and resistance to ESCs. To predict and investigate putative amino acid mutations causing β-lactam resistance particularly for ESCs, we applied proteochemometric modeling to generalize N. gonorrhoeae susceptibility data for predicting the interaction of PBP2 with therapeutic β-lactam antibiotics. This was afforded by correlating publicly available data on antimicrobial susceptibility of wild-type and mutant N. gonorrhoeae strains for penicillin-G, cefixime and ceftriaxone with 50 PBP2 protein sequence data using partial least-squares projections to latent structures. The generated model revealed excellent predictability ( R 2 = 0.91, Q 2 = 0.77, Q Ext 2 = 0.78). Moreover, our model identified amino acid mutations in PBP2 with the highest impact on antimicrobial susceptibility and provided information on physicochemical properties of amino acid mutations affecting antimicrobial susceptibility. Our model thus provided insight into the physicochemical basis for resistance development in PBP2 suggesting its use for predicting and monitoring novel PBP2 mutations that may emerge in the future.

  10. Rupture prediction for induction bends under opening mode bending with emphasis on strain localization

    International Nuclear Information System (INIS)

    Mitsuya, Masaki; Sakanoue, Takashi

    2015-01-01

    This study focuses on the opening mode of induction bends; this mode represents the deformation outside a bend. Bending experiments on induction bends are shown and the manner of failure of these bends was investigated. Ruptures occur at the intrados of the bends, which undergo tensile stress, and accompany the local reduction of wall thickness, i.e., necking that indicates strain localization. By implementing finite element analysis (FEA), it was shown that the rupture is dominated not by the fracture criterion of material but by the initiation of strain localization that is a deformation characteristic of the material. These ruptures are due to the rapid increase of local strain after the initiation of strain localization and suddenly reach the fracture criterion. For the evaluation of the deformability of the bends, a method based on FEA that can predict the displacement at the rupture is proposed. We show that the yield surface shape and the true stress–strain relationship after uniform elongation have to be defined on the basis of the actual properties of the bend material. The von Mises yield criterion, which is commonly used in cases of elastic–plastic FEA, could not predict the rupture and overestimated the deformability. In contrast, a yield surface obtained by performing tensile tests on a biaxial specimen could predict the rupture. The prediction of the rupture was accomplished by an inverse calibration method that determined the true stress-strain relationship after uniform elongation. As an alternative to the inverse calibration, a simple extrapolation method of the true stress-strain relationship after uniform elongation which can predict the rupture is proposed. - Highlights: • A method based on FEA that can predict the displacement at the rupture is proposed. • The yield surface shape and the true stress–strain have to be defined precisely. • The von Mises yield criterion overestimated the deformability. • The ruptures are due to the

  11. In silico predictive studies of mAHR congener binding using homology modelling and molecular docking.

    Science.gov (United States)

    Panda, Roshni; Cleave, A Suneetha Susan; Suresh, P K

    2014-09-01

    The aryl hydrocarbon receptor (AHR) is one of the principal xenobiotic, nuclear receptor that is responsible for the early events involved in the transcription of a complex set of genes comprising the CYP450 gene family. In the present computational study, homology modelling and molecular docking were carried out with the objective of predicting the relationship between the binding efficiency and the lipophilicity of different polychlorinated biphenyl (PCB) congeners and the AHR in silico. Homology model of the murine AHR was constructed by several automated servers and assessed by PROCHECK, ERRAT, VERIFY3D and WHAT IF. The resulting model of the AHR by MODWEB was used to carry out molecular docking of 36 PCB congeners using PatchDock server. The lipophilicity of the congeners was predicted using the XLOGP3 tool. The results suggest that the lipophilicity influences binding energy scores and is positively correlated with the same. Score and Log P were correlated with r = +0.506 at p = 0.01 level. In addition, the number of chlorine (Cl) atoms and Log P were highly correlated with r = +0.900 at p = 0.01 level. The number of Cl atoms and scores also showed a moderate positive correlation of r = +0.481 at p = 0.01 level. To the best of our knowledge, this is the first study employing PatchDock in the docking of AHR to the environmentally deleterious congeners and attempting to correlate structural features of the AHR with its biochemical properties with regards to PCBs. The result of this study are consistent with those of other computational studies reported in the previous literature that suggests that a combination of docking, scoring and ranking organic pollutants could be a possible predictive tool for investigating ligand-mediated toxicity, for their subsequent validation using wet lab-based studies. © The Author(s) 2012.

  12. Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach

    DEFF Research Database (Denmark)

    Buus, S.; Lauemoller, S.L.; Worning, Peder

    2003-01-01

    We have generated Artificial Neural Networks (ANN) capable of performing sensitive, quantitative predictions of peptide binding to the MHC class I molecule, HLA-A*0204. We have shown that such quantitative ANN are superior to conventional classification ANN, that have been trained to predict...

  13. Interaction of the amyloid precursor protein-like protein 1 (APLP1) E2 domain with heparan sulfate involves two distinct binding modes

    Energy Technology Data Exchange (ETDEWEB)

    Dahms, Sven O., E-mail: sdahms@fli-leibniz.de [Leibniz Institute for Age Research (FLI), Beutenbergstrasse 11, 07745 Jena (Germany); Mayer, Magnus C. [Freie Universität Berlin, Thielallee 63, 14195 Berlin (Germany); Miltenyi Biotec GmbH, Robert-Koch-Strasse 1, 17166 Teterow (Germany); Roeser, Dirk [Leibniz Institute for Age Research (FLI), Beutenbergstrasse 11, 07745 Jena (Germany); Multhaup, Gerd [McGill University Montreal, Montreal, Quebec H3G 1Y6 (Canada); Than, Manuel E., E-mail: sdahms@fli-leibniz.de [Leibniz Institute for Age Research (FLI), Beutenbergstrasse 11, 07745 Jena (Germany)

    2015-03-01

    Two X-ray structures of APLP1 E2 with and without a heparin dodecasaccharide are presented, revealing two distinct binding modes of the protein to heparan sulfate. The data provide a mechanistic explanation of how APP-like proteins bind to heparan sulfates and how they specifically recognize nonreducing structures of heparan sulfates. Beyond the pathology of Alzheimer’s disease, the members of the amyloid precursor protein (APP) family are essential for neuronal development and cell homeostasis in mammals. APP and its paralogues APP-like protein 1 (APLP1) and APP-like protein 2 (APLP2) contain the highly conserved heparan sulfate (HS) binding domain E2, which effects various (patho)physiological functions. Here, two crystal structures of the E2 domain of APLP1 are presented in the apo form and in complex with a heparin dodecasaccharide at 2.5 Å resolution. The apo structure of APLP1 E2 revealed an unfolded and hence flexible N-terminal helix αA. The (APLP1 E2){sub 2}–(heparin){sub 2} complex structure revealed two distinct binding modes, with APLP1 E2 explicitly recognizing the heparin terminus but also interacting with a continuous heparin chain. The latter only requires a certain register of the sugar moieties that fits to a positively charged surface patch and contributes to the general heparin-binding capability of APP-family proteins. Terminal binding of APLP1 E2 to heparin specifically involves a structure of the nonreducing end that is very similar to heparanase-processed HS chains. These data reveal a conserved mechanism for the binding of APP-family proteins to HS and imply a specific regulatory role of HS modifications in the biology of APP and APP-like proteins.

  14. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method.

    Science.gov (United States)

    Nielsen, Morten; Lundegaard, Claus; Lund, Ole

    2007-07-04

    Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles. The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR), we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors. The SMM-align method was shown to outperform other

  15. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

    Directory of Open Access Journals (Sweden)

    Lund Ole

    2007-07-01

    Full Text Available Abstract Background Antigen presenting cells (APCs sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC and three mouse H2-IA alleles. Results The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR, we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors. Conclusion

  16. Neuronal Calcium Sensor-1 Binds the D2 Dopamine Receptor and G-protein-coupled Receptor Kinase 1 (GRK1) Peptides Using Different Modes of Interactions.

    Science.gov (United States)

    Pandalaneni, Sravan; Karuppiah, Vijaykumar; Saleem, Muhammad; Haynes, Lee P; Burgoyne, Robert D; Mayans, Olga; Derrick, Jeremy P; Lian, Lu-Yun

    2015-07-24

    Neuronal calcium sensor-1 (NCS-1) is the primordial member of the neuronal calcium sensor family of EF-hand Ca(2+)-binding proteins. It interacts with both the G-protein-coupled receptor (GPCR) dopamine D2 receptor (D2R), regulating its internalization and surface expression, and the cognate kinases GRK1 and GRK2. Determination of the crystal structures of Ca(2+)/NCS-1 alone and in complex with peptides derived from D2R and GRK1 reveals that the differential recognition is facilitated by the conformational flexibility of the C-lobe-binding site. We find that two copies of the D2R peptide bind within the hydrophobic crevice on Ca(2+)/NCS-1, but only one copy of the GRK1 peptide binds. The different binding modes are made possible by the C-lobe-binding site of NCS-1, which adopts alternative conformations in each complex. C-terminal residues Ser-178-Val-190 act in concert with the flexible EF3/EF4 loop region to effectively form different peptide-binding sites. In the Ca(2+)/NCS-1·D2R peptide complex, the C-terminal region adopts a 310 helix-turn-310 helix, whereas in the GRK1 peptide complex it forms an α-helix. Removal of Ser-178-Val-190 generated a C-terminal truncation mutant that formed a dimer, indicating that the NCS-1 C-terminal region prevents NCS-1 oligomerization. We propose that the flexible nature of the C-terminal region is essential to allow it to modulate its protein-binding sites and adapt its conformation to accommodate both ligands. This appears to be driven by the variability of the conformation of the C-lobe-binding site, which has ramifications for the target specificity and diversity of NCS-1. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  17. Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information.

    Science.gov (United States)

    Panwar, Bharat; Gupta, Sudheer; Raghava, Gajendra P S

    2013-02-07

    The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL). It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i) vitamin interacting residues (VIRs), (ii) vitamin-A interacting residues (VAIRs), (iii) vitamin-B interacting residues (VBIRs) and (iv) pyridoxal-5-phosphate (vitamin B6) interacting residues (PLPIRs) have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM) features of protein sequences. Finally, we selected best performing SVM modules and obtained highest MCC of 0.53, 0.48, 0.61, 0

  18. Prediction of binding free energy for adsorption of antimicrobial peptide lactoferricin B on a POPC membrane

    Science.gov (United States)

    Vivcharuk, Victor; Tomberli, Bruno; Tolokh, Igor S.; Gray, C. G.

    2008-03-01

    Molecular dynamics (MD) simulations are used to study the interaction of a zwitterionic palmitoyl-oleoyl-phosphatidylcholine (POPC) bilayer with the cationic antimicrobial peptide bovine lactoferricin (LFCinB) in a 100 mM NaCl solution at 310 K. The interaction of LFCinB with POPC is used as a model system for studying the details of membrane-peptide interactions, with the peptide selected because of its antimicrobial nature. Seventy-two 3 ns MD simulations, with six orientations of LFCinB at 12 different distances from a POPC membrane, are carried out to determine the potential of mean force (PMF) or free energy profile for the peptide as a function of the distance between LFCinB and the membrane surface. To calculate the PMF for this relatively large system a new variant of constrained MD and thermodynamic integration is developed. A simplified method for relating the PMF to the LFCinB-membrane binding free energy is described and used to predict a free energy of adsorption (or binding) of -1.05±0.39kcal/mol , and corresponding maximum binding force of about 20 pN, for LFCinB-POPC. The contributions of the ions-LFCinB and the water-LFCinB interactions to the PMF are discussed. The method developed will be a useful starting point for future work simulating peptides interacting with charged membranes and interactions involved in the penetration of membranes, features necessary to understand in order to rationally design peptides as potential alternatives to traditional antibiotics.

  19. Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

    Science.gov (United States)

    Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

    2014-11-01

    As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of

  20. Color vision predicts processing modes of goal activation during action cascading.

    Science.gov (United States)

    Jongkees, Bryant J; Steenbergen, Laura; Colzato, Lorenza S

    2017-09-01

    One of the most important functions of cognitive control is action cascading: the ability to cope with multiple response options when confronted with various task goals. A recent study implicates a key role for dopamine (DA) in this process, suggesting higher D1 efficiency shifts the action cascading strategy toward a more serial processing mode, whereas higher D2 efficiency promotes a shift in the opposite direction by inducing a more parallel processing mode (Stock, Arning, Epplen, & Beste, 2014). Given that DA is found in high concentration in the retina and modulation of retinal DA release displays characteristics of D2-receptors (Peters, Schweibold, Przuntek, & Müller, 2000), color vision discrimination might serve as an index of D2 efficiency. We used color discrimination, assessed with the Lanthony Desaturated Panel D-15 test, to predict individual differences (N = 85) in a stop-change paradigm that provides a well-established measure of action cascading. In this task it is possible to calculate an individual slope value for each participant that estimates the degree of overlap in task goal activation. When the stopping process of a previous task goal has not finished at the time the change process toward a new task goal is initiated (parallel processing), the slope value becomes steeper. In case of less overlap (more serial processing), the slope value becomes flatter. As expected, participants showing better color vision were more prone to activate goals in a parallel manner as indicated by a steeper slope. Our findings suggest that color vision might represent a predictor of D2 efficiency and the predisposed processing mode of goal activation during action cascading. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Predicted MHC peptide binding promiscuity explains MHC class I 'hotspots' of antigen presentation defined by mass spectrometry eluted ligand data.

    Science.gov (United States)

    Jappe, Emma Christine; Kringelum, Jens; Trolle, Thomas; Nielsen, Morten

    2018-02-15

    Peptides that bind to and are presented by MHC class I and class II molecules collectively make up the immunopeptidome. In the context of vaccine development, an understanding of the immunopeptidome is essential, and much effort has been dedicated to its accurate and cost-effective identification. Current state-of-the-art methods mainly comprise in silico tools for predicting MHC binding, which is strongly correlated with peptide immunogenicity. However, only a small proportion of the peptides that bind to MHC molecules are, in fact, immunogenic, and substantial work has been dedicated to uncovering additional determinants of peptide immunogenicity. In this context, and in light of recent advancements in mass spectrometry (MS), the existence of immunological hotspots has been given new life, inciting the hypothesis that hotspots are associated with MHC class I peptide immunogenicity. We here introduce a precise terminology for defining these hotspots and carry out a systematic analysis of MS and in silico predicted hotspots. We find that hotspots defined from MS data are largely captured by peptide binding predictions, enabling their replication in silico. This leads us to conclude that hotspots, to a great degree, are simply a result of promiscuous HLA binding, which disproves the hypothesis that the identification of hotspots provides novel information in the context of immunogenic peptide prediction. Furthermore, our analyses demonstrate that the signal of ligand processing, although present in the MS data, has very low predictive power to discriminate between MS and in silico defined hotspots. © 2018 John Wiley & Sons Ltd.

  2. ProBiS-ligands: a web server for prediction of ligands by examination of protein binding sites.

    Science.gov (United States)

    Konc, Janez; Janežič, Dušanka

    2014-07-01

    The ProBiS-ligands web server predicts binding of ligands to a protein structure. Starting with a protein structure or binding site, ProBiS-ligands first identifies template proteins in the Protein Data Bank that share similar binding sites. Based on the superimpositions of the query protein and the similar binding sites found, the server then transposes the ligand structures from those sites to the query protein. Such ligand prediction supports many activities, e.g. drug repurposing. The ProBiS-ligands web server, an extension of the ProBiS web server, is open and free to all users at http://probis.cmm.ki.si/ligands. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  3. Improving density functional tight binding predictions of free energy surfaces for peptide condensation reactions in solution

    Science.gov (United States)

    Kroonblawd, Matthew; Goldman, Nir

    First principles molecular dynamics using highly accurate density functional theory (DFT) is a common tool for predicting chemistry, but the accessible time and space scales are often orders of magnitude beyond the resolution of experiments. Semi-empirical methods such as density functional tight binding (DFTB) offer up to a thousand-fold reduction in required CPU hours and can approach experimental scales. However, standard DFTB parameter sets lack good transferability and calibration for a particular system is usually necessary. Force matching the pairwise repulsive energy term in DFTB to short DFT trajectories can improve the former's accuracy for chemistry that is fast relative to DFT simulation times (Contract DE-AC52-07NA27344.

  4. Improving Density Functional Tight Binding Predictions of Free Energy Surfaces for Slow Chemical Reactions in Solution

    Science.gov (United States)

    Kroonblawd, Matthew; Goldman, Nir

    2017-06-01

    First principles molecular dynamics using highly accurate density functional theory (DFT) is a common tool for predicting chemistry, but the accessible time and space scales are often orders of magnitude beyond the resolution of experiments. Semi-empirical methods such as density functional tight binding (DFTB) offer up to a thousand-fold reduction in required CPU hours and can approach experimental scales. However, standard DFTB parameter sets lack good transferability and calibration for a particular system is usually necessary. Force matching the pairwise repulsive energy term in DFTB to short DFT trajectories can improve the former's accuracy for reactions that are fast relative to DFT simulation times (Contract DE-AC52-07NA27344.

  5. Prediction of pressure induced structural phase transitions and internal mode frequency changes in solid N2+

    International Nuclear Information System (INIS)

    Etters, R.D.; Kobashi, K.; Chandrasekharan, V.

    1983-01-01

    A rhombohedral distortion of the Pm3n structure is introduced which shows that a low temperature phase transition occurs from P4 2 /mnm into the R3c calcite structure at P approx. = 19.2 kbar with a volume change of 0.125 cm 3 /mole. This transition agrees with recent Raman scattering measurements. Another transition from R3c into R3m is predicted at P approx. = 67.5 kbar, with a volume change of 0.1 cm 3 /mole. The pressure dependence of the intramolecular mode frequencies for the R3c structure is in reasonably good agreement with the two main branches observed experimentally

  6. Predicting the creep life and failure mode of low-alloy steel weldments

    Energy Technology Data Exchange (ETDEWEB)

    Brear, J.M.; Middleton, C.J.; Aplin, P.F. [ERA Technology Ltd., Leatherhead (United Kingdom)

    1998-12-31

    This presentation reviews and consolidates experience gained through a number of research projects and practical plant assessments in predicting both the life and the likely failure mode and location in low alloy steel weldments. The approach adopted begins with the recognition that the relative strength difference between the microstructural regions is a key factor controlling both life and failure location. Practical methods based on hardness measurement and adaptable to differing weld geometries are presented and evidence for correlations between hardness ratio, damage accumulation and strain development is discussed. Predictor diagrams relating weld life and failure location to the service conditions and the hardness of the individual microstructural constituents are suggested and comments are given on the implications for identifying the circumstances in which Type IV cracking is to be expected. (orig.) 6 refs.

  7. Predicting the creep life and failure mode of low-alloy steel weldments

    Energy Technology Data Exchange (ETDEWEB)

    Brear, J M; Middleton, C J; Aplin, P F [ERA Technology Ltd., Leatherhead (United Kingdom)

    1999-12-31

    This presentation reviews and consolidates experience gained through a number of research projects and practical plant assessments in predicting both the life and the likely failure mode and location in low alloy steel weldments. The approach adopted begins with the recognition that the relative strength difference between the microstructural regions is a key factor controlling both life and failure location. Practical methods based on hardness measurement and adaptable to differing weld geometries are presented and evidence for correlations between hardness ratio, damage accumulation and strain development is discussed. Predictor diagrams relating weld life and failure location to the service conditions and the hardness of the individual microstructural constituents are suggested and comments are given on the implications for identifying the circumstances in which Type IV cracking is to be expected. (orig.) 6 refs.

  8. Intramolecular binding mode of the C-terminus of Escherichia coli single-stranded DNA binding protein determined by nuclear magnetic resonance spectroscopy

    OpenAIRE

    Shishmarev, Dmitry; Wang, Yao; Mason, Claire E.; Su, Xun-Cheng; Oakley, Aaron J.; Graham, Bim; Huber, Thomas; Dixon, Nicholas E.; Otting, Gottfried

    2013-01-01

    Single-stranded DNA (ssDNA) binding protein (SSB) is an essential protein to protect ssDNA and recruit specific ssDNA-processing proteins. Escherichia coli SSB forms a tetramer at neutral pH, comprising a structurally well-defined ssDNA binding domain (OB-domain) and a disordered C-terminal domain (C-domain) of ∼64 amino acid residues. The C-terminal eight-residue segment of SSB (C-peptide) has been shown to interact with the OB-domain, but crystal structures failed to reveal any electron den...

  9. Delivery Mode and the Transition of Pioneering Gut-Microbiota Structure, Composition and Predicted Metabolic Function

    Directory of Open Access Journals (Sweden)

    Noel T. Mueller

    2017-12-01

    Full Text Available Cesarean (C-section delivery, recently shown to cause excess weight gain in mice, perturbs human neonatal gut microbiota development due to the lack of natural mother-to-newborn transfer of microbes. Neonates excrete first the in-utero intestinal content (referred to as meconium hours after birth, followed by intestinal contents reflective of extra-uterine exposure (referred to as transition stool 2 to 3 days after birth. It is not clear when the effect of C-section on the neonatal gut microbiota emerges. We examined bacterial DNA in carefully-collected meconium, and the subsequent transitional stool, from 59 neonates [13 born by scheduled C-section and 46 born by vaginal delivery] in a private hospital in Brazil. Bacterial DNA was extracted, and the V4 region of the 16S rRNA gene was sequenced using the Illumina MiSeq (San Diego, CA, USA platform. We found evidence of bacterial DNA in the majority of meconium samples in our study. The bacterial DNA structure (i.e., beta diversity of meconium differed significantly from that of the transitional stool microbiota. There was a significant reduction in bacterial alpha diversity (e.g., number of observed bacterial species and change in bacterial composition (e.g., reduced Proteobacteria in the transition from meconium to stool. However, changes in predicted microbiota metabolic function from meconium to transitional stool were only observed in vaginally-delivered neonates. Within sample comparisons showed that delivery mode was significantly associated with bacterial structure, composition and predicted microbiota metabolic function in transitional-stool samples, but not in meconium samples. Specifically, compared to vaginally delivered neonates, the transitional stool of C-section delivered neonates had lower proportions of the genera Bacteroides, Parabacteroides and Clostridium. These differences led to C-section neonates having lower predicted abundance of microbial genes related to metabolism of

  10. Structure of calmodulin complexed with an olfactory CNG channel fragment and role of the central linker: Residual dipolar couplings to evaluate calmodulin binding modes outside the kinase family

    International Nuclear Information System (INIS)

    Contessa, Gian Marco; Orsale, Maria; Melino, Sonia; Torre, Vincent; Paci, Maurizio; Desideri, Alessandro; Cicero, Daniel O.

    2005-01-01

    The NMR high-resolution structure of calmodulin complexed with a fragment of the olfactory cyclic-nucleotide gated channel is described. This structure shows features that are unique for this complex, including an active role of the linker connecting the N- and C-lobes of calmodulin upon binding of the peptide. Such linker is not only involved in the formation of an hydrophobic pocket to accommodate a bulky peptide residue, but it also provides a positively charged region complementary to a negative charge of the target. This complex of calmodulin with a target not belonging to the kinase family was used to test the residual dipolar coupling (RDC) approach for the determination of calmodulin binding modes to peptides. Although the complex here characterized belongs to the (1--14) family, high Q values were obtained with all the 1:1 complexes for which crystalline structures are available. Reduction of the RDC data set used for the correlation analysis to structured regions of the complex allowed a clear identification of the binding mode. Excluded regions comprise calcium binding loops and loops connecting the EF-hand motifs

  11. Large-scale binding ligand prediction by improved patch-based method Patch-Surfer2.0.

    Science.gov (United States)

    Zhu, Xiaolei; Xiong, Yi; Kihara, Daisuke

    2015-03-01

    Ligand binding is a key aspect of the function of many proteins. Thus, binding ligand prediction provides important insight in understanding the biological function of proteins. Binding ligand prediction is also useful for drug design and examining potential drug side effects. We present a computational method named Patch-Surfer2.0, which predicts binding ligands for a protein pocket. By representing and comparing pockets at the level of small local surface patches that characterize physicochemical properties of the local regions, the method can identify binding pockets of the same ligand even if they do not share globally similar shapes. Properties of local patches are represented by an efficient mathematical representation, 3D Zernike Descriptor. Patch-Surfer2.0 has significant technical improvements over our previous prototype, which includes a new feature that captures approximate patch position with a geodesic distance histogram. Moreover, we constructed a large comprehensive database of ligand binding pockets that will be searched against by a query. The benchmark shows better performance of Patch-Surfer2.0 over existing methods. http://kiharalab.org/patchsurfer2.0/ CONTACT: dkihara@purdue.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  12. Ensemble Architecture for Prediction of Enzyme-ligand Binding Residues Using Evolutionary Information.

    Science.gov (United States)

    Pai, Priyadarshini P; Dattatreya, Rohit Kadam; Mondal, Sukanta

    2017-11-01

    Enzyme interactions with ligands are crucial for various biochemical reactions governing life. Over many years attempts to identify these residues for biotechnological manipulations have been made using experimental and computational techniques. The computational approaches have gathered impetus with the accruing availability of sequence and structure information, broadly classified into template-based and de novo methods. One of the predominant de novo methods using sequence information involves application of biological properties for supervised machine learning. Here, we propose a support vector machines-based ensemble for prediction of protein-ligand interacting residues using one of the most important discriminative contributing properties in the interacting residue neighbourhood, i. e., evolutionary information in the form of position-specific- scoring matrix (PSSM). The study has been performed on a non-redundant dataset comprising of 9269 interacting and 91773 non-interacting residues for prediction model generation and further evaluation. Of the various PSSM-based models explored, the proposed method named ROBBY (pRediction Of Biologically relevant small molecule Binding residues on enzYmes) shows an accuracy of 84.0 %, Matthews Correlation Coefficient of 0.343 and F-measure of 39.0 % on 78 test enzymes. Further, scope of adding domain knowledge such as pocket information has also been investigated; results showed significant enhancement in method precision. Findings are hoped to boost the reliability of small-molecule ligand interaction prediction for enzyme applications and drug design. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. In Silico Prediction of Chemicals Binding to Aromatase with Machine Learning Methods.

    Science.gov (United States)

    Du, Hanwen; Cai, Yingchun; Yang, Hongbin; Zhang, Hongxiao; Xue, Yuhan; Liu, Guixia; Tang, Yun; Li, Weihua

    2017-05-15

    Environmental chemicals may affect endocrine systems through multiple mechanisms, one of which is via effects on aromatase (also known as CYP19A1), an enzyme critical for maintaining the normal balance of estrogens and androgens in the body. Therefore, rapid and efficient identification of aromatase-related endocrine disrupting chemicals (EDCs) is important for toxicology and environment risk assessment. In this study, on the basis of the Tox21 10K compound library, in silico classification models for predicting aromatase binders/nonbinders were constructed by machine learning methods. To improve the prediction ability of the models, a combined classifier (CC) strategy that combines different independent machine learning methods was adopted. Performances of the models were measured by test and external validation sets containing 1336 and 216 chemicals, respectively. The best model was obtained with the MACCS (Molecular Access System) fingerprint and CC method, which exhibited an accuracy of 0.84 for the test set and 0.91 for the external validation set. Additionally, several representative substructures for characterizing aromatase binders, such as ketone, lactone, and nitrogen-containing derivatives, were identified using information gain and substructure frequency analysis. Our study provided a systematic assessment of chemicals binding to aromatase. The built models can be helpful to rapidly identify potential EDCs targeting aromatase.

  14. Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology.

    Science.gov (United States)

    Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil

    2014-09-07

    Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. An analysis of the binding of repressor protein ModE to modABCD (molybdate transport) operator/promoter DNA of Escherichia coli.

    Science.gov (United States)

    Grunden, A M; Self, W T; Villain, M; Blalock, J E; Shanmugam, K T

    1999-08-20

    Expression of the modABCD operon in Escherichia coli, which codes for a molybdate-specific transporter, is repressed by ModE in vivo in a molybdate-dependent fashion. In vitro DNase I-footprinting experiments identified three distinct regions of protection by ModE-molybdate on the modA operator/promoter DNA, GTTATATT (-15 to -8; region 1), GCCTACAT (-4 to +4; region 2), and GTTACAT (+8 to +14; region 3). Within the three regions of the protected DNA, a pentamer sequence, TAYAT (Y = C or T), can be identified. DNA-electrophoretic mobility experiments showed that the protected regions 1 and 2 are essential for binding of ModE-molybdate to DNA, whereas the protected region 3 increases the affinity of the DNA to the repressor. The stoichiometry of this interaction was found to be two ModE-molybdate per modA operator DNA. ModE-molybdate at 5 nM completely protected the modABCD operator/promoter DNA from DNase I-catalyzed hydrolysis, whereas ModE alone failed to protect the DNA even at 100 nM. The apparent K(d) for the interaction between the modA operator DNA and ModE-molybdate was 0.3 nM, and the K(d) increased to 8 nM in the absence of molybdate. Among the various oxyanions tested, only tungstate replaced molybdate in the repression of modA by ModE, but the affinity of ModE-tungstate for modABCD operator DNA was 6 times lower than with ModE-molybdate. A mutant ModE(T125I) protein, which repressed modA-lac even in the absence of molybdate, protected the same region of modA operator DNA in the absence of molybdate. The apparent K(d) for the interaction between modA operator DNA and ModE(T125I) was 3 nM in the presence of molybdate and 4 nM without molybdate. The binding of molybdate to ModE resulted in a decrease in fluorescence emission, indicating a conformational change of the protein upon molybdate binding. The fluorescence emission spectra of mutant ModE proteins, ModE(T125I) and ModE(Q216*), were unaffected by molybdate. The molybdate-independent mutant ModE

  16. Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

    Science.gov (United States)

    Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

    2017-09-01

    This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

  17. Usefulness of intestinal fatty acid-binding protein in predicting strangulated small bowel obstruction.

    Directory of Open Access Journals (Sweden)

    Hirotada Kittaka

    Full Text Available BACKGROUND: The level of intestinal fatty acid-binding protein (I-FABP is considered to be useful diagnostic markers of small bowel ischemia. The purpose of this retrospective study was to investigate whether the serum I-FABP level is a predictive marker of strangulation in patients with small bowel obstruction (SBO. METHODS: A total of 37 patients diagnosed with SBO were included in this study. The serum I-FABP levels were retrospectively compared between the patients with strangulation and those with simple obstruction, and cut-off values for the diagnosis of strangulation were calculated using a receiver operating characteristic curve. In addition, the sensitivity, specificity, positive predictive value (PPV and negative predictive value (NPV were calculated. RESULTS: Twenty-one patients were diagnosed with strangulated SBO. The serum I-FABP levels were significantly higher in the patients with strangulation compared with those observed in the patients with simple obstruction (18.5 vs. 1.6 ng/ml p<0.001. Using a cut-off value of 6.5 ng/ml, the sensitivity, specificity, PPV and NPV were 71.4%, 93.8%, 93.8% and 71.4%, respectively. An I-FABP level greater than 6.5 ng/ml was found to be the only independent significant factor for a higher likelihood of strangulated SBO (P =  0.02; odds ratio: 19.826; 95% confidence interval: 2.1560 - 488.300. CONCLUSIONS: The I-FABP level is a useful marker for discriminating between strangulated SBO and simple SBO in patients with SBO.

  18. Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection

    Directory of Open Access Journals (Sweden)

    Xin Ma

    2015-01-01

    Full Text Available The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR method, followed by incremental feature selection (IFS. We incorporated features of conjoint triad features and three novel features: binding propensity (BP, nonbinding propensity (NBP, and evolutionary information combined with physicochemical properties (EIPP. The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient. High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

  19. A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals.

    Science.gov (United States)

    Hong, Huixiao; Shen, Jie; Ng, Hui Wen; Sakkiah, Sugunadevi; Ye, Hao; Ge, Weigong; Gong, Ping; Xiao, Wenming; Tong, Weida

    2016-03-25

    Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest) and the molecular descriptors calculated from two-dimensional structures by Mold² software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69%) and external validations using 22 chemicals (balanced accuracy of 71%). Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence) in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed.

  20. Search for β2 adrenergic receptor ligands by virtual screening via grid computing and investigation of binding modes by docking and molecular dynamics simulations.

    Directory of Open Access Journals (Sweden)

    Qifeng Bai

    Full Text Available We designed a program called MolGridCal that can be used to screen small molecule database in grid computing on basis of JPPF grid environment. Based on MolGridCal program, we proposed an integrated strategy for virtual screening and binding mode investigation by combining molecular docking, molecular dynamics (MD simulations and free energy calculations. To test the effectiveness of MolGridCal, we screened potential ligands for β2 adrenergic receptor (β2AR from a database containing 50,000 small molecules. MolGridCal can not only send tasks to the grid server automatically, but also can distribute tasks using the screensaver function. As for the results of virtual screening, the known agonist BI-167107 of β2AR is ranked among the top 2% of the screened candidates, indicating MolGridCal program can give reasonable results. To further study the binding mode and refine the results of MolGridCal, more accurate docking and scoring methods are used to estimate the binding affinity for the top three molecules (agonist BI-167107, neutral antagonist alprenolol and inverse agonist ICI 118,551. The results indicate agonist BI-167107 has the best binding affinity. MD simulation and free energy calculation are employed to investigate the dynamic interaction mechanism between the ligands and β2AR. The results show that the agonist BI-167107 also has the lowest binding free energy. This study can provide a new way to perform virtual screening effectively through integrating molecular docking based on grid computing, MD simulations and free energy calculations. The source codes of MolGridCal are freely available at http://molgridcal.codeplex.com.

  1. Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information

    Directory of Open Access Journals (Sweden)

    Panwar Bharat

    2013-02-01

    Full Text Available Abstract Background The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. Results In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL. It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i vitamin interacting residues (VIRs, (ii vitamin-A interacting residues (VAIRs, (iii vitamin-B interacting residues (VBIRs and (iv pyridoxal-5-phosphate (vitamin B6 interacting residues (PLPIRs have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM features of protein sequences. Finally, we selected best performing SVM modules and

  2. Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

    Science.gov (United States)

    de Ávila, Maurício Boff; Xavier, Mariana Morrone; Pintro, Val Oliveira; de Azevedo, Walter Filgueira

    2017-12-09

    Here we report the development of a machine-learning model to predict binding affinity based on the crystallographic structures of protein-ligand complexes. We used an ensemble of crystallographic structures (resolution better than 1.5 Å resolution) for which half-maximal inhibitory concentration (IC 50 ) data is available. Polynomial scoring functions were built using as explanatory variables the energy terms present in the MolDock and PLANTS scoring functions. Prediction performance was tested and the supervised machine learning models showed improvement in the prediction power, when compared with PLANTS and MolDock scoring functions. In addition, the machine-learning model was applied to predict binding affinity of CDK2, which showed a better performance when compared with AutoDock4, AutoDock Vina, MolDock, and PLANTS scores. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Prediction of protein binding sites using physical and chemical descriptors and the support vector machine regression method

    International Nuclear Information System (INIS)

    Sun Zhong-Hua; Jiang Fan

    2010-01-01

    In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression (SVR) method than by the support vector classification method. (rapid communication)

  4. Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations

    DEFF Research Database (Denmark)

    Poongavanam, Vasanthanathan; Olsen, Lars; Jørgensen, Flemming Steen

    2010-01-01

    , and methods based on statistical mechanics. In the present investigation, we started from an LIE model to predict the binding free energy of structurally diverse compounds of cytochrome P450 1A2 ligands, one of the important human metabolizing isoforms of the cytochrome P450 family. The data set includes both...... substrates and inhibitors. It appears that the electrostatic contribution to the binding free energy becomes negligible in this particular protein and a simple empirical model was derived, based on a training set of eight compounds. The root mean square error for the training set was 3.7 kJ/mol. Subsequent......Predicting binding affinities for receptor-ligand complexes is still one of the challenging processes in computational structure-based ligand design. Many computational methods have been developed to achieve this goal, such as docking and scoring methods, the linear interaction energy (LIE) method...

  5. Molecular modeling reveals the novel inhibition mechanism and binding mode of three natural compounds to staphylococcal α-hemolysin.

    Directory of Open Access Journals (Sweden)

    Jiazhang Qiu

    Full Text Available α-Hemolysin (α-HL is a self-assembling, channel-forming toxin that is produced as a soluble monomer by Staphylococcus aureus strains. Until now, α-HL has been a significant virulence target for the treatment of S. aureus infection. In our previous report, we demonstrated that some natural compounds could bind to α-HL. Due to the binding of those compounds, the conformational transition of α-HL from the monomer to the oligomer was blocked, which resulted in inhibition of the hemolytic activity of α-HL. However, these results have not indicated how the binding of the α-HL inhibitors influence the conformational transition of the whole protein during the oligomerization process. In this study, we found that three natural compounds, Oroxylin A 7-O-glucuronide (OLG, Oroxin A (ORA, and Oroxin B (ORB, when inhibiting the hemolytic activity of α-HL, could bind to the "stem" region of α-HL. This was completed using conventional Molecular Dynamics (MD simulations. By interacting with the novel binding sites of α-HL, the ligands could form strong interactions with both sides of the binding cavity. The results of the principal component analysis (PCA indicated that because of the inhibitors that bind to the "stem" region of α-HL, the conformational transition of α-HL from the monomer to the oligomer was restricted. This caused the inhibition of the hemolytic activity of α-HL. This novel inhibition mechanism has been confirmed by both the steered MD simulations and the experimental data obtained from a deoxycholate-induced oligomerization assay. This study can facilitate the design of new antibacterial drugs against S. aureus.

  6. Predicting protein-ATP binding sites from primary sequence through fusing bi-profile sampling of multi-view features

    Directory of Open Access Journals (Sweden)

    Zhang Ya-Nan

    2012-05-01

    Full Text Available Abstract Background Adenosine-5′-triphosphate (ATP is one of multifunctional nucleotides and plays an important role in cell biology as a coenzyme interacting with proteins. Revealing the binding sites between protein and ATP is significantly important to understand the functionality of the proteins and the mechanisms of protein-ATP complex. Results In this paper, we propose a novel framework for predicting the proteins’ functional residues, through which they can bind with ATP molecules. The new prediction protocol is achieved by combination of sequence evolutional information and bi-profile sampling of multi-view sequential features and the sequence derived structural features. The hypothesis for this strategy is single-view feature can only represent partial target’s knowledge and multiple sources of descriptors can be complementary. Conclusions Prediction performances evaluated by both 5-fold and leave-one-out jackknife cross-validation tests on two benchmark datasets consisting of 168 and 227 non-homologous ATP binding proteins respectively demonstrate the efficacy of the proposed protocol. Our experimental results also reveal that the residue structural characteristics of real protein-ATP binding sites are significant different from those normal ones, for example the binding residues do not show high solvent accessibility propensities, and the bindings prefer to occur at the conjoint points between different secondary structure segments. Furthermore, results also show that performance is affected by the imbalanced training datasets by testing multiple ratios between positive and negative samples in the experiments. Increasing the dataset scale is also demonstrated useful for improving the prediction performances.

  7. Macro-architectured cellular materials: Properties, characteristic modes, and prediction methods

    Science.gov (United States)

    Ma, Zheng-Dong

    2017-12-01

    Macro-architectured cellular (MAC) material is defined as a class of engineered materials having configurable cells of relatively large (i.e., visible) size that can be architecturally designed to achieve various desired material properties. Two types of novel MAC materials, negative Poisson's ratio material and biomimetic tendon reinforced material, were introduced in this study. To estimate the effective material properties for structural analyses and to optimally design such materials, a set of suitable homogenization methods was developed that provided an effective means for the multiscale modeling of MAC materials. First, a strain-based homogenization method was developed using an approach that separated the strain field into a homogenized strain field and a strain variation field in the local cellular domain superposed on the homogenized strain field. The principle of virtual displacements for the relationship between the strain variation field and the homogenized strain field was then used to condense the strain variation field onto the homogenized strain field. The new method was then extended to a stress-based homogenization process based on the principle of virtual forces and further applied to address the discrete systems represented by the beam or frame structures of the aforementioned MAC materials. The characteristic modes and the stress recovery process used to predict the stress distribution inside the cellular domain and thus determine the material strengths and failures at the local level are also discussed.

  8. Mode-coupling theory predictions for a limited valency attractive square well model

    International Nuclear Information System (INIS)

    Zaccarelli, E; Saika-Voivod, I; Moreno, A J; Nave, E La; Buldyrev, S V; Sciortino, F; Tartaglia, P

    2006-01-01

    Recently we have studied, using numerical simulations, a limited valency model, i.e. an attractive square well model with a constraint on the maximum number of bonded neighbours. Studying a large region of temperatures T and packing fractions φ, we have estimated the location of the liquid-gas phase separation spinodal and the loci of dynamic arrest, where the system is trapped in a disordered non-ergodic state. Two distinct arrest lines for the system are present in the system: a (repulsive) glass line at high packing fraction, and a gel line at low φ and T. The former is essentially vertical φ controlled), while the latter is rather horizontal (T controlled) in the φ-T) plane. We here complement the molecular dynamics results with mode coupling theory calculations, using the numerical structure factors as input. We find that the theory predicts a repulsive glass line-in satisfactory agreement with the simulation results-and an attractive glass line, which appears to be unrelated to the gel line

  9. Structure of Calmodulin Bound to a Calcineurin Peptide: A New Way of Making an Old Binding Mode

    International Nuclear Information System (INIS)

    Ye, Q.; Li, X.; Wong, A.; Wei, Q.; Jia, Z.

    2006-01-01

    Calcineurin is a calmodulin-binding protein in brain and the only serine/threonine protein phosphatase under the control of Ca 2+ /calmodulin (CaM), which plays a critical role in coupling Ca 2+ signals to cellular responses. CaM up-regulates the phosphatase activity of calcineurin by binding to the CaM-binding domain (CBD) of calcineurin subunit A. Here, we report crystal structural studies of CaM bound to a CBD peptide. The chimeric protein containing CaM and the CBD peptide forms an intimate homodimer, in which CaM displays a native-like extended conformation and the CBD peptide shows -helical structure. Unexpectedly, the N-terminal lobe from one CaM and the C-terminal lobe from the second molecule form a combined binding site to trap the peptide. Thus, the dimer provides two binding sites, each of which is reminiscent of the fully collapsed conformation of CaM commonly observed in complex with, for example, the myosin light chain kinase (MLCK) peptide. The interaction between the peptide and CaM is highly specific and similar to MLCK

  10. Surface plasmon resonance imaging reveals multiple binding modes of Agrobacterium transformation mediator VirE2 to ssDNA.

    Science.gov (United States)

    Kim, Sanghyun; Zbaida, David; Elbaum, Michael; Leh, Hervé; Nogues, Claude; Buckle, Malcolm

    2015-07-27

    VirE2 is the major secreted protein of Agrobacterium tumefaciens in its genetic transformation of plant hosts. It is co-expressed with a small acidic chaperone VirE1, which prevents VirE2 oligomerization. After secretion into the host cell, VirE2 serves functions similar to a viral capsid in protecting the single-stranded transferred DNA en route to the nucleus. Binding of VirE2 to ssDNA is strongly cooperative and depends moreover on protein-protein interactions. In order to isolate the protein-DNA interactions, imaging surface plasmon resonance (SPRi) studies were conducted using surface-immobilized DNA substrates of length comparable to the protein-binding footprint. Binding curves revealed an important influence of substrate rigidity with a notable preference for poly-T sequences and absence of binding to both poly-A and double-stranded DNA fragments. Dissociation at high salt concentration confirmed the electrostatic nature of the interaction. VirE1-VirE2 heterodimers also bound to ssDNA, though by a different mechanism that was insensitive to high salt. Neither VirE2 nor VirE1-VirE2 followed the Langmuir isotherm expected for reversible monomeric binding. The differences reflect the cooperative self-interactions of VirE2 that are suppressed by VirE1. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Computational analysis and prediction of the binding motif and protein interacting partners of the Abl SH3 domain.

    Directory of Open Access Journals (Sweden)

    Tingjun Hou

    2006-01-01

    Full Text Available Protein-protein interactions, particularly weak and transient ones, are often mediated by peptide recognition domains, such as Src Homology 2 and 3 (SH2 and SH3 domains, which bind to specific sequence and structural motifs. It is important but challenging to determine the binding specificity of these domains accurately and to predict their physiological interacting partners. In this study, the interactions between 35 peptide ligands (15 binders and 20 non-binders and the Abl SH3 domain were analyzed using molecular dynamics simulation and the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. The calculated binding free energies correlated well with the rank order of the binding peptides and clearly distinguished binders from non-binders. Free energy component analysis revealed that the van der Waals interactions dictate the binding strength of peptides, whereas the binding specificity is determined by the electrostatic interaction and the polar contribution of desolvation. The binding motif of the Abl SH3 domain was then determined by a virtual mutagenesis method, which mutates the residue at each position of the template peptide relative to all other 19 amino acids and calculates the binding free energy difference between the template and the mutated peptides using the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. A single position mutation free energy profile was thus established and used as a scoring matrix to search peptides recognized by the Abl SH3 domain in the human genome. Our approach successfully picked ten out of 13 experimentally determined binding partners of the Abl SH3 domain among the top 600 candidates from the 218,540 decapeptides with the PXXP motif in the SWISS-PROT database. We expect that this physical-principle based method can be applied to other protein domains as well.

  12. Predicting transcription factor binding sites using local over-representation and comparative genomics

    Directory of Open Access Journals (Sweden)

    Touzet Hélène

    2006-08-01

    Full Text Available Abstract Background Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms. Results We have developed a method, named TFM-Explorer, that searches for locally overrepresented TFBSs in a set of coregulated genes, which are modeled by profiles provided by a database of position weight matrices. The novelty of the method is that it takes advantage of spatial conservation in the sequence and supports multiple species. The efficiency of the underlying algorithm and its robustness to noise allow weak regulatory signals to be detected in large heterogeneous data sets. Conclusion TFM-Explorer provides an efficient way to predict TFBS overrepresentation in related sequences. Promising results were obtained in a variety of examples in human, mouse, and rat genomes. The software is publicly available at http://bioinfo.lifl.fr/TFM-Explorer.

  13. Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

    Science.gov (United States)

    Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

    2018-01-01

    Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development. Therefore, PPB prediction models are receiving an increased attention. In the current study, we present a systematic approach using Support vector machine, Artificial neural network, k- nearest neighbor, Probabilistic neural network, Partial least square and Linear discriminant analysis to relate various in vitro and in silico molecular descriptors to a diverse dataset of 736 drugs/drug-like compounds. The overall accuracy of Support vector machine with Radial basis function kernel came out to be comparatively better than the rest of the applied algorithms. The training set accuracy, validation set accuracy, precision, sensitivity, specificity and F1 score for the Suprort vector machine was found to be 89.73%, 89.97%, 92.56%, 87.26%, 91.97% and 0.898, respectively. This model can potentially be useful in screening of relevant drug candidates at the preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  14. COMPARATIVE MODELLING AND LIGAND BINDING SITE PREDICTION OF A FAMILY 43 GLYCOSIDE HYDROLASE FROM Clostridium thermocellum

    Directory of Open Access Journals (Sweden)

    Shadab Ahmed

    2012-06-01

    Full Text Available The phylogenetic analysis of Clostridium thermocellum family 43 glycoside hydrolase (CtGH43 showed close evolutionary relation with carbohydrate binding family 6 proteins from C. cellulolyticum, C. papyrosolvens, C. cellulyticum, and A. cellulyticum. Comparative modeling of CtGH43 was performed based on crystal structures with PDB IDs 3C7F, 1YIF, 1YRZ, 2EXH and 1WL7. The structure having lowest MODELLER objective function was selected. The three-dimensional structure revealed typical 5-fold beta–propeller architecture. Energy minimization and validation of predicted model with VERIFY 3D indicated acceptability of the proposed atomic structure. The Ramachandran plot analysis by RAMPAGE confirmed that family 43 glycoside hydrolase (CtGH43 contains little or negligible segments of helices. It also showed that out of 301 residues, 267 (89.3% were in most favoured region, 23 (7.7% were in allowed region and 9 (3.0% were in outlier region. IUPred analysis of CtGH43 showed no disordered region. Active site analysis showed presence of two Asp and one Glu, assumed to form a catalytic triad. This study gives us information about three-dimensional structure and reaffirms the fact that it has the similar core 5-fold beta–propeller architecture and so probably has the same inverting mechanism of action with the formation of above mentioned catalytic triad for catalysis of polysaccharides.

  15. Structures of the APC–ARM domain in complexes with discrete Amer1/WTX fragments reveal that it uses a consensus mode to recognize its binding partners

    Science.gov (United States)

    Zhang, Zhenyi; Akyildiz, Senem; Xiao, Yafei; Gai, Zhongchao; An, Ying; Behrens, Jürgen; Wu, Geng

    2015-01-01

    The tumor suppressor APC employs its conserved armadillo repeat (ARM) domain to recognize many of its binding partners, including Amer1/WTX, which is mutated in Wilms' tumor and bone overgrowth syndrome. The APC–Amer1 complex has important roles in regulating Wnt signaling and cell adhesion. Three sites A1, A2, and A3 of Amer1 have been reported to mediate its interaction with APC-ARM. In this study, crystal structures of APC–ARM in complexes with Amer1-A1, -A2, and -A4, which is newly identified in this work, were determined. Combined with our GST pull-down, yeast two-hybrid, and isothermal titration calorimetry (ITC) assay results using mutants of APC and Amer1 interface residues, our structures demonstrate that Amer1-A1, -A2, and -A4, as well as other APC-binding proteins such as Asef and Sam68, all employ a common recognition pattern to associate with APC–ARM. In contrast, Amer1-A3 binds to the C-terminal side of APC–ARM through a bipartite interaction mode. Composite mutations on either APC or Amer1 disrupting all four interfaces abrogated their association in cultured cells and impaired the membrane recruitment of APC by Amer1. Our study thus comprehensively elucidated the recognition mechanism between APC and Amer1, and revealed a consensus recognition sequence employed by various APC–ARM binding partners. PMID:27462415

  16. Structures of the APC-ARM domain in complexes with discrete Amer1/WTX fragments reveal that it uses a consensus mode to recognize its binding partners.

    Science.gov (United States)

    Zhang, Zhenyi; Akyildiz, Senem; Xiao, Yafei; Gai, Zhongchao; An, Ying; Behrens, Jürgen; Wu, Geng

    2015-01-01

    The tumor suppressor APC employs its conserved armadillo repeat (ARM) domain to recognize many of its binding partners, including Amer1/WTX, which is mutated in Wilms' tumor and bone overgrowth syndrome. The APC-Amer1 complex has important roles in regulating Wnt signaling and cell adhesion. Three sites A1, A2, and A3 of Amer1 have been reported to mediate its interaction with APC-ARM. In this study, crystal structures of APC-ARM in complexes with Amer1-A1, -A2, and -A4, which is newly identified in this work, were determined. Combined with our GST pull-down, yeast two-hybrid, and isothermal titration calorimetry (ITC) assay results using mutants of APC and Amer1 interface residues, our structures demonstrate that Amer1-A1, -A2, and -A4, as well as other APC-binding proteins such as Asef and Sam68, all employ a common recognition pattern to associate with APC-ARM. In contrast, Amer1-A3 binds to the C-terminal side of APC-ARM through a bipartite interaction mode. Composite mutations on either APC or Amer1 disrupting all four interfaces abrogated their association in cultured cells and impaired the membrane recruitment of APC by Amer1. Our study thus comprehensively elucidated the recognition mechanism between APC and Amer1, and revealed a consensus recognition sequence employed by various APC-ARM binding partners.

  17. Substituent and noncovalent interaction effects in the reactivity of purine derivatives with tetracarboxylato-dirhodium(II) units. Rationalization of a rare binding mode via N3.

    Science.gov (United States)

    Amo-Ochoa, Pilar; Castillo, Oscar; Harrington, Ross W; Zamora, Félix; Houlton, Andrew

    2013-02-18

    Reactions between [Rh(2)(CH(3)COO)(4)] with 2,6-diaminopurine (HDap) or 6-chloro-2-aminopurine (HClap) and [Rh(2)((CH(3))(3)CCOO)(4)] with HClap produce, three new dirhodium(II) carboxylate complexes of the general form, [Rh(2)(RCOO)(4)(Purine)(2)] (R = CH(3), (CH(3))(3)C). Single crystal X-ray diffraction studies confirm that in all cases the purine coordinates to the axial position of the dirhodium(II)tetracarboxylate unit. However, while the complex obtained with HDap features the typical purine binding mode via N(7), complexes containing HClap show unusual N3 coordination. This is an extremely rare instance of an unrestricted purine binding via N3. Some rationalization of these data is offered based on a series of DFT calculations.

  18. Characterization of the differences in the cyclopiazonic acid binding mode to mammalian and P. Falciparum Ca2+ pumps: a computational study.

    KAUST Repository

    Di Marino, Daniele; D'Annessa, Ilda; Coletta, Andrea; Via, Allegra; Tramontano, Anna

    2015-01-01

    Despite the investments in malaria research, an effective vaccine has not yet been developed and the causative parasites are becoming increasingly resistant to most of the available drugs. PfATP6, the sarco/endoplasmic reticulum Ca2+ pump (SERCA) of P. falciparum, has been recently genetically validated as a potential antimalarial target and cyclopiazonic acid (CPA) has been found to be a potent inhibitor of SERCAs in several organisms, including P. falciparum. In position 263, PfATP6 displays a leucine residue, whilst the corresponding position in the mammalian SERCA is occupied by a glutamic acid. The PfATP6 L263E mutation has been studied in relation to the artemisinin inhibitory effect on P. falciparum and recent studies have provided evidence that the parasite with this mutation is more susceptible to CPA. Here, we characterized, for the first time, the interaction of CPA with PfATP6 and its mammalian counterpart to understand similarities and differences in the mode of binding of the inhibitor to the two Ca2+ pumps. We found that, even though CPA does not directly interact with the residue in position 263, the presence of a hydrophobic residue in this position in PfATP6 rather than a negatively charged one, as in the mammalian SERCA, entails a conformational arrangement of the binding pocket which, in turn, determines a relaxation of CPA leading to a different binding mode of the compound. Our findings highlight differences between the plasmodial and human SERCA CPA-binding pockets that may be exploited to design CPA derivatives more selective toward PfATP6.

  19. Characterization of the differences in the cyclopiazonic acid binding mode to mammalian and P. Falciparum Ca2+ pumps: a computational study.

    KAUST Repository

    Di Marino, Daniele

    2015-03-01

    Despite the investments in malaria research, an effective vaccine has not yet been developed and the causative parasites are becoming increasingly resistant to most of the available drugs. PfATP6, the sarco/endoplasmic reticulum Ca2+ pump (SERCA) of P. falciparum, has been recently genetically validated as a potential antimalarial target and cyclopiazonic acid (CPA) has been found to be a potent inhibitor of SERCAs in several organisms, including P. falciparum. In position 263, PfATP6 displays a leucine residue, whilst the corresponding position in the mammalian SERCA is occupied by a glutamic acid. The PfATP6 L263E mutation has been studied in relation to the artemisinin inhibitory effect on P. falciparum and recent studies have provided evidence that the parasite with this mutation is more susceptible to CPA. Here, we characterized, for the first time, the interaction of CPA with PfATP6 and its mammalian counterpart to understand similarities and differences in the mode of binding of the inhibitor to the two Ca2+ pumps. We found that, even though CPA does not directly interact with the residue in position 263, the presence of a hydrophobic residue in this position in PfATP6 rather than a negatively charged one, as in the mammalian SERCA, entails a conformational arrangement of the binding pocket which, in turn, determines a relaxation of CPA leading to a different binding mode of the compound. Our findings highlight differences between the plasmodial and human SERCA CPA-binding pockets that may be exploited to design CPA derivatives more selective toward PfATP6.

  20. Seasonal difference in brain serotonin transporter binding predicts symptom severity in patients with seasonal affective disorder

    DEFF Research Database (Denmark)

    Mc Mahon, Brenda; Andersen, Sofie B.; Madsen, Martin K.

    2016-01-01

    controls with low seasonality scores and 17 patients diagnosed with seasonal affective disorder were scanned in both summer and winter to investigate differences in cerebral serotonin transporter binding across groups and across seasons. The two groups had similar cerebral serotonin transporter binding...... between summer and winter (Psex-(P = 0.02) and genotype-(P = 0.04) dependent. In the patients with seasonal affective disorder, the seasonal change in serotonin transporter binding was positively associated with change in depressive symptom...

  1. Conservation of transcription factor binding events predicts gene expression across species

    OpenAIRE

    Hemberg, Martin; Kreiman, Gabriel

    2011-01-01

    Recent technological advances have made it possible to determine the genome-wide binding sites of transcription factors (TFs). Comparisons across species have suggested a relatively low degree of evolutionary conservation of experimentally defined TF binding events (TFBEs). Using binding data for six different TFs in hepatocytes and embryonic stem cells from human and mouse, we demonstrate that evolutionary conservation of TFBEs within orthologous proximal promoters is closely linked to funct...

  2. Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method.

    Directory of Open Access Journals (Sweden)

    Marharyta Petukh

    2015-07-01

    Full Text Available A new methodology termed Single Amino Acid Mutation based change in Binding free Energy (SAAMBE was developed to predict the changes of the binding free energy caused by mutations. The method utilizes 3D structures of the corresponding protein-protein complexes and takes advantage of both approaches: sequence- and structure-based methods. The method has two components: a MM/PBSA-based component, and an additional set of statistical terms delivered from statistical investigation of physico-chemical properties of protein complexes. While the approach is rigid body approach and does not explicitly consider plausible conformational changes caused by the binding, the effect of conformational changes, including changes away from binding interface, on electrostatics are mimicked with amino acid specific dielectric constants. This provides significant improvement of SAAMBE predictions as indicated by better match against experimentally determined binding free energy changes over 1300 mutations in 43 proteins. The final benchmarking resulted in a very good agreement with experimental data (correlation coefficient 0.624 while the algorithm being fast enough to allow for large-scale calculations (the average time is less than a minute per mutation.

  3. Structure-guided approach identifies a novel class of HIV-1 ribonuclease H inhibitors: binding mode insights through magnesium complexation and site-directed mutagenesis studies

    DEFF Research Database (Denmark)

    Poongavanam, Vasanthanathan; Corona, Angela; Steinmann, Casper

    2018-01-01

    is a long and expensive process that can be speeded up by in silico methods. In the present study, a structure-guided screening is coupled with a similarity-based search on the Specs database to identify a new class of HIV-1 RNase H inhibitors. Out of the 45 compounds selected for experimental testing, 15...... inhibited the RNase H function below 100 μM with three hits exhibiting IC50 values active compound, AA, inhibits HIV-1 RNase H with an IC50 of 5.1 μM and exhibits a Mg-independent mode of inhibition. Site-directed mutagenesis studies provide valuable insight into the binding mode of newly...

  4. In silico engineering and optimization of Transcription Activator-Like Effectors and their derivatives for improved DNA binding predictions.

    KAUST Repository

    Piatek, Marek J.

    2015-12-01

    Transcription Activator-Like Effectors (TALEs) can be used as adaptable DNAbinding modules to create site-specific chimeric nucleases or synthetic transcriptional regulators. The central repeat domain mediates specific DNA binding via hypervariable repeat di-residues (RVDs). This DNA-Binding Domain can be engineered to bind preferentially to any user-selected DNA sequence if engineered appropriately. Therefore, TALEs and their derivatives have become indispensable molecular tools in site-specific manipulation of genes and genomes. This thesis revolves around two problems: in silico design and improved binding site prediction of TALEs. In the first part, a study is shown where TALEs are successfully designed in silico and validated in laboratory to yield the anticipated effects on selected genes. Software is developed to accompany the process of designing and prediction of binding sites. I expanded the functionality of the software to be used as a more generic set of tools for the design, target and offtarget searching. Part two contributes a method and associated toolkit developed to allow users to design in silico optimized synthetic TALEs with user-defined specificities for various experimental purposes. This method is based on a mutual relationship of three consecutive tandem repeats in the DNA-binding domain. This approach revealed positional and compositional bias behind the binding of TALEs to DNA. In conclusion, I developed methods, approaches, and software to enhance the functionality of synthetic TALEs, which should improve understanding of TALEs biology and will further advance genome-engineering applications in various organisms and cell types.

  5. New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity.

    Science.gov (United States)

    Hattotuwagama, Channa K; Guan, Pingping; Doytchinova, Irini A; Flower, Darren R

    2004-11-21

    Quantitative structure-activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide-protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2-D(b), H2-K(b) and H2-K(k). As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online ( http://www.jenner.ac.uk/MHCPred).

  6. Alternative binding modes identified for growth and differentiation factor-associated serum protein (GASP) family antagonism of myostatin.

    Science.gov (United States)

    Walker, Ryan G; Angerman, Elizabeth B; Kattamuri, Chandramohan; Lee, Yun-Sil; Lee, Se-Jin; Thompson, Thomas B

    2015-03-20

    Myostatin, a member of the TGF-β family of ligands, is a strong negative regulator of muscle growth. As such, it is a prime therapeutic target for muscle wasting disorders. Similar to other TGF-β family ligands, myostatin is neutralized by binding one of a number of structurally diverse antagonists. Included are the antagonists GASP-1 and GASP-2, which are unique in that they specifically antagonize myostatin. However, little is known from a structural standpoint describing the interactions of GASP antagonists with myostatin. Here, we present the First low resolution solution structure of myostatin-free and myostatin-bound states of GASP-1 and GASP-2. Our studies have revealed GASP-1, which is 100 times more potent than GASP-2, preferentially binds myostatin in an asymmetrical 1:1 complex, whereas GASP-2 binds in a symmetrical 2:1 complex. Additionally, C-terminal truncations of GASP-1 result in less potent myostatin inhibitors that form a 2:1 complex, suggesting that the C-terminal domains of GASP-1 are the primary mediators for asymmetric complex formation. Overall, this study provides a new perspective on TGF-β antagonism, where closely related antagonists can utilize different ligand-binding strategies. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  7. Alternative Binding Modes Identified for Growth and Differentiation Factor-associated Serum Protein (GASP) Family Antagonism of Myostatin*

    Science.gov (United States)

    Walker, Ryan G.; Angerman, Elizabeth B.; Kattamuri, Chandramohan; Lee, Yun-Sil; Lee, Se-Jin; Thompson, Thomas B.

    2015-01-01

    Myostatin, a member of the TGF-β family of ligands, is a strong negative regulator of muscle growth. As such, it is a prime therapeutic target for muscle wasting disorders. Similar to other TGF-β family ligands, myostatin is neutralized by binding one of a number of structurally diverse antagonists. Included are the antagonists GASP-1 and GASP-2, which are unique in that they specifically antagonize myostatin. However, little is known from a structural standpoint describing the interactions of GASP antagonists with myostatin. Here, we present the First low resolution solution structure of myostatin-free and myostatin-bound states of GASP-1 and GASP-2. Our studies have revealed GASP-1, which is 100 times more potent than GASP-2, preferentially binds myostatin in an asymmetrical 1:1 complex, whereas GASP-2 binds in a symmetrical 2:1 complex. Additionally, C-terminal truncations of GASP-1 result in less potent myostatin inhibitors that form a 2:1 complex, suggesting that the C-terminal domains of GASP-1 are the primary mediators for asymmetric complex formation. Overall, this study provides a new perspective on TGF-β antagonism, where closely related antagonists can utilize different ligand-binding strategies. PMID:25657005

  8. Inhibition and Larvicidal Activity of Phenylpropanoids from Piper sarmentosum on Acetylcholinesterase against Mosquito Vectors and Their Binding Mode of Interaction.

    Directory of Open Access Journals (Sweden)

    Arshia Hematpoor

    Full Text Available Aedes aegypti, Aedes albopictus and Culex quinquefasciatus are vectors of dengue fever and West Nile virus diseases. This study was conducted to determine the toxicity, mechanism of action and the binding interaction of three active phenylpropanoids from Piper sarmentosum (Piperaceae toward late 3rd or early 4th larvae of above vectors. A bioassay guided-fractionation on the hexane extract from the roots of Piper sarmentosum led to the isolation and identification of three active phenylpropanoids; asaricin 1, isoasarone 2 and trans-asarone 3. The current study involved evaluation of the toxicity and acetylcholinesterase (AChE inhibition of these compounds against Aedes aegypti, Aedes albopictus and Culex quinquefasciatus larvae. Asaricin 1 and isoasarone 2 were highly potent against Aedes aegypti, Aedes albopictus and Culex quinquefasciatus larvae causing up to 100% mortality at ≤ 15 μg/mL concentration. The ovicidal activity of asaricin 1, isoasarone 2 and trans-asarone 3 were evaluated through egg hatching. Asaricin 1 and isoasarone 2 showed potent ovicidal activity. Ovicidal activity for both compounds was up to 95% at 25μg/mL. Asaricin 1 and isoasarone 2 showed strong inhibition on acetylcholinesterase with relative IC50 values of 0.73 to 1.87 μg/mL respectively. These findings coupled with the high AChE inhibition may suggest that asaricin 1 and isoasarone 2 are neuron toxic compounds toward Aedes aegypti, Aedes albopictus and Culex quinquefasciatus. Further computational docking with Autodock Vina elaborates the possible interaction of asaricin 1 and isoasarone 2 with three possible binding sites of AChE which includes catalytic triads (CAS: S238, E367, H480, the peripheral sites (PAS: E72, W271 and anionic binding site (W83. The binding affinity of asaricin 1 and isoasarone 2 were relatively strong with asaricin 1 showed a higher binding affinity in the anionic pocket.

  9. Inhibition and Larvicidal Activity of Phenylpropanoids from Piper sarmentosum on Acetylcholinesterase against Mosquito Vectors and Their Binding Mode of Interaction.

    Science.gov (United States)

    Hematpoor, Arshia; Liew, Sook Yee; Chong, Wei Lim; Azirun, Mohd Sofian; Lee, Vannajan Sanghiran; Awang, Khalijah

    2016-01-01

    Aedes aegypti, Aedes albopictus and Culex quinquefasciatus are vectors of dengue fever and West Nile virus diseases. This study was conducted to determine the toxicity, mechanism of action and the binding interaction of three active phenylpropanoids from Piper sarmentosum (Piperaceae) toward late 3rd or early 4th larvae of above vectors. A bioassay guided-fractionation on the hexane extract from the roots of Piper sarmentosum led to the isolation and identification of three active phenylpropanoids; asaricin 1, isoasarone 2 and trans-asarone 3. The current study involved evaluation of the toxicity and acetylcholinesterase (AChE) inhibition of these compounds against Aedes aegypti, Aedes albopictus and Culex quinquefasciatus larvae. Asaricin 1 and isoasarone 2 were highly potent against Aedes aegypti, Aedes albopictus and Culex quinquefasciatus larvae causing up to 100% mortality at ≤ 15 μg/mL concentration. The ovicidal activity of asaricin 1, isoasarone 2 and trans-asarone 3 were evaluated through egg hatching. Asaricin 1 and isoasarone 2 showed potent ovicidal activity. Ovicidal activity for both compounds was up to 95% at 25μg/mL. Asaricin 1 and isoasarone 2 showed strong inhibition on acetylcholinesterase with relative IC50 values of 0.73 to 1.87 μg/mL respectively. These findings coupled with the high AChE inhibition may suggest that asaricin 1 and isoasarone 2 are neuron toxic compounds toward Aedes aegypti, Aedes albopictus and Culex quinquefasciatus. Further computational docking with Autodock Vina elaborates the possible interaction of asaricin 1 and isoasarone 2 with three possible binding sites of AChE which includes catalytic triads (CAS: S238, E367, H480), the peripheral sites (PAS: E72, W271) and anionic binding site (W83). The binding affinity of asaricin 1 and isoasarone 2 were relatively strong with asaricin 1 showed a higher binding affinity in the anionic pocket.

  10. Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case study.

    Science.gov (United States)

    Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J

    2014-08-27

    State-of-the-art protein-ligand docking methods are generally limited by the traditionally low accuracy of their scoring functions, which are used to predict binding affinity and thus vital for discriminating between active and inactive compounds. Despite intensive research over the years, classical scoring functions have reached a plateau in their predictive performance. These assume a predetermined additive functional form for some sophisticated numerical features, and use standard multivariate linear regression (MLR) on experimental data to derive the coefficients. In this study we show that such a simple functional form is detrimental for the prediction performance of a scoring function, and replacing linear regression by machine learning techniques like random forest (RF) can improve prediction performance. We investigate the conditions of applying RF under various contexts and find that given sufficient training samples RF manages to comprehensively capture the non-linearity between structural features and measured binding affinities. Incorporating more structural features and training with more samples can both boost RF performance. In addition, we analyze the importance of structural features to binding affinity prediction using the RF variable importance tool. Lastly, we use Cyscore, a top performing empirical scoring function, as a baseline for comparison study. Machine-learning scoring functions are fundamentally different from classical scoring functions because the former circumvents the fixed functional form relating structural features with binding affinities. RF, but not MLR, can effectively exploit more structural features and more training samples, leading to higher prediction performance. The future availability of more X-ray crystal structures will further widen the performance gap between RF-based and MLR-based scoring functions. This further stresses the importance of substituting RF for MLR in scoring function development.

  11. Linear Interaction Energy Based Prediction of Cytochrome P450 1A2 Binding Affinities with Reliability Estimation.

    Directory of Open Access Journals (Sweden)

    Luigi Capoferri

    Full Text Available Prediction of human Cytochrome P450 (CYP binding affinities of small ligands, i.e., substrates and inhibitors, represents an important task for predicting drug-drug interactions. A quantitative assessment of the ligand binding affinity towards different CYPs can provide an estimate of inhibitory activity or an indication of isoforms prone to interact with the substrate of inhibitors. However, the accuracy of global quantitative models for CYP substrate binding or inhibition based on traditional molecular descriptors can be limited, because of the lack of information on the structure and flexibility of the catalytic site of CYPs. Here we describe the application of a method that combines protein-ligand docking, Molecular Dynamics (MD simulations and Linear Interaction Energy (LIE theory, to allow for quantitative CYP affinity prediction. Using this combined approach, a LIE model for human CYP 1A2 was developed and evaluated, based on a structurally diverse dataset for which the estimated experimental uncertainty was 3.3 kJ mol-1. For the computed CYP 1A2 binding affinities, the model showed a root mean square error (RMSE of 4.1 kJ mol-1 and a standard error in prediction (SDEP in cross-validation of 4.3 kJ mol-1. A novel approach that includes information on both structural ligand description and protein-ligand interaction was developed for estimating the reliability of predictions, and was able to identify compounds from an external test set with a SDEP for the predicted affinities of 4.6 kJ mol-1 (corresponding to 0.8 pKi units.

  12. Predictions and Experimental Microstructural Characterization of High Strain Rate Failure Modes in Layered Aluminum Composites

    Science.gov (United States)

    Khanikar, Prasenjit

    Different aluminum alloys can be combined, as composites, for tailored dynamic applications. Most investigations pertaining to metallic alloy layered composites, however, have been based on quasi-static approaches. The dynamic failure of layered metallic composites, therefore, needs to be characterized in terms of strength, toughness, and fracture response. A dislocation-density based crystalline plasticity formulation, finite-element techniques, rational crystallographic orientation relations and a new fracture methodology were used to predict the failure modes associated with the high strain rate behavior of aluminum layered composites. Two alloy layers, a high strength alloy, aluminum 2195, and an aluminum alloy 2139, with high toughness, were modeled with representative microstructures that included precipitates, dispersed particles, and different grain boundary (GB) distributions. The new fracture methodology, based on an overlap method and phantom nodes, is used with a fracture criteria specialized for fracture on different cleavage planes. One of the objectives of this investigation, therefore, was to determine the optimal arrangements of the 2139 and 2195 aluminum alloys for a metallic layered composite that would combine strength, toughness and fracture resistance for high strain-rate applications. Different layer arrangements were investigated for high strain-rate applications, and the optimal arrangement was with the high toughness 2139 layer on the bottom, which provided extensive shear strain localization, and the high strength 2195 layer on the top for high strength resistance. The layer thickness of the bottom high toughness layer also affected the bending behavior of the roll-boned interface and the potential delamination of the layers. Shear strain localization, dynamic cracking and delamination were the mutually competing failure mechanisms for the layered metallic composite, and control of these failure modes can be optimized for high strain

  13. Integrated predictive modeling of high-mode tokamak plasmas using a combination of core and pedestal models

    International Nuclear Information System (INIS)

    Bateman, Glenn; Bandres, Miguel A.; Onjun, Thawatchai; Kritz, Arnold H.; Pankin, Alexei

    2003-01-01

    A new integrated modeling protocol is developed using a model for the temperature and density pedestal at the edge of high-mode (H-mode) plasmas [Onjun et al., Phys. Plasmas 9, 5018 (2002)] together with the Multi-Mode core transport model (MMM95) [Bateman et al., Phys. Plasmas 5, 1793 (1998)] in the BALDUR integrated modeling code to predict the temperature and density profiles of 33 H-mode discharges. The pedestal model is used to provide the boundary conditions in the simulations, once the heating power rises above the H-mode power threshold. Simulations are carried out for 20 discharges in the Joint European Torus and 13 discharges in the DIII-D tokamak. These discharges include systematic scans in normalized gyroradius, plasma pressure, collisionality, isotope mass, elongation, heating power, and plasma density. The average rms deviation between experimental data and the predicted profiles of temperature and density, normalized by central values, is found to be about 10%. It is found that the simulations tend to overpredict the temperature profiles in discharges with low heating power per plasma particle and to underpredict the temperature profiles in discharges with high heating power per particle. Variations of the pedestal model are used to test the sensitivity of the simulation results

  14. MHC class I epitope binding prediction trained on small data sets

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Nielsen, Morten; Lamberth, K.

    2004-01-01

    The identification of potential T-cell epitopes is important for development of new human or vetenary vaccines, both considering single protein/subunit vaccines, and for epitope/peptide vaccines as such. The highly diverse MHC class I alleles bind very different peptides, and accurate binding pre...... in situations where only very limited data are available for training....

  15. Evolved pesticide tolerance in amphibians: Predicting mechanisms based on pesticide novelty and mode of action

    International Nuclear Information System (INIS)

    Hua, Jessica; Jones, Devin K.; Mattes, Brian M.; Cothran, Rickey D.; Relyea, Rick A.; Hoverman, Jason T.

    2015-01-01

    We examined 10 wood frog populations distributed along an agricultural gradient for their tolerance to six pesticides (carbaryl, malathion, cypermethrin, permethrin, imidacloprid, and thiamethoxam) that differed in date of first registration (pesticide novelty) and mode-of-action (MOA). Our goals were to assess whether: 1) tolerance was correlated with distance to agriculture for each pesticide, 2) pesticide novelty predicted the likelihood of evolved tolerance, and 3) populations display cross-tolerance between pesticides that share and differ in MOA. Wood frog populations located close to agriculture were more tolerant to carbaryl and malathion than populations far from agriculture. Moreover, the strength of the relationship between distance to agriculture and tolerance was stronger for older pesticides compared to newer pesticides. Finally, we found evidence for cross-tolerance between carbaryl and malathion (two pesticides that share MOA). This study provides one of the most comprehensive approaches for understanding patterns of evolved tolerance in non-pest species. - Highlights: • We explored patterns of tolerance to six insecticides across 10 wood frog populations. • We found evidence that wood frogs have evolved tolerance to carbaryl and malathion. • The likelihood of evolved tolerance was stronger for older compared to newer pesticides. • We found evidence for cross-tolerance between carbaryl and malathion. • This is one of the most comprehensive approaches studying evolved tolerance in a non-pest species. - Using 10 wood frog populations, we detected evidence for evolved tolerance, found that the evolved tolerance depends on insecticide novelty, and found evidence for cross-tolerance.

  16. Discriminant analysis to predict the occurrence of ELMs in H-mode discharges

    International Nuclear Information System (INIS)

    Kardaun, O.J.W.F.; Itoh, S.; Itoh, K.; Kardaun, J.W.P.F.

    1993-08-01

    After an exposition of its theoretical background, discriminant analysis is applied to the H-mode confinement database to find the region in plasma parameter space in which H-mode with small ELMs (Edge Localized Modes) is likely to occur. The boundary of this region is determined by the condition that the probability of appearance of such a type of H-mode, as a function of the plasma parameters, should be (1) larger than some threshold value and (2) larger than the corresponding probability for other types of H-mode (i.e., H-mode without ELMs or with giant ELMs). In practice, the discrimination has been performed for the ASDEX, JET and JFT-2M tokamaks (a) using four instantaneous plasma parameters (injected power P inj , magnetic field B t , plasma current I p and line averaged electron density (n-bar e ) and (b) taking also memory effects of the plasma and the distance between the plasma and the wall into account, while using variables that are normalised with respect to machine size. Generally speaking, it is found that there is a substantial overlap between the region of H-mode with small ELMs and the region of the two other types of H-mode. However, the ELM-free and the giant ELM H-modes relatively rarely appear in the region, that, according to the analysis, is allocated to small ELMs. A reliable production of H-mode with only small ELMs seems well possible by choosing this regime in parameter space. In the present study, it was not attempted to arrive at a unified discrimination across the machines. So, projection from one machine to another remains difficult, and a reliable determination of the region where small ELMs occur still requires a training sample from the device under consideration. (author) 53 refs

  17. PROCARB: A Database of Known and Modelled Carbohydrate-Binding Protein Structures with Sequence-Based Prediction Tools

    Directory of Open Access Journals (Sweden)

    Adeel Malik

    2010-01-01

    Full Text Available Understanding of the three-dimensional structures of proteins that interact with carbohydrates covalently (glycoproteins as well as noncovalently (protein-carbohydrate complexes is essential to many biological processes and plays a significant role in normal and disease-associated functions. It is important to have a central repository of knowledge available about these protein-carbohydrate complexes as well as preprocessed data of predicted structures. This can be significantly enhanced by tools de novo which can predict carbohydrate-binding sites for proteins in the absence of structure of experimentally known binding site. PROCARB is an open-access database comprising three independently working components, namely, (i Core PROCARB module, consisting of three-dimensional structures of protein-carbohydrate complexes taken from Protein Data Bank (PDB, (ii Homology Models module, consisting of manually developed three-dimensional models of N-linked and O-linked glycoproteins of unknown three-dimensional structure, and (iii CBS-Pred prediction module, consisting of web servers to predict carbohydrate-binding sites using single sequence or server-generated PSSM. Several precomputed structural and functional properties of complexes are also included in the database for quick analysis. In particular, information about function, secondary structure, solvent accessibility, hydrogen bonds and literature reference, and so forth, is included. In addition, each protein in the database is mapped to Uniprot, Pfam, PDB, and so forth.

  18. Nuclear factor 90 uses an ADAR2-like binding mode to recognize specific bases in dsRNA.

    Science.gov (United States)

    Jayachandran, Uma; Grey, Heather; Cook, Atlanta G

    2016-02-29

    Nuclear factors 90 and 45 (NF90 and NF45) form a protein complex involved in the post-transcriptional control of many genes in vertebrates. NF90 is a member of the dsRNA binding domain (dsRBD) family of proteins. RNA binding partners identified so far include elements in 3' untranslated regions of specific mRNAs and several non-coding RNAs. In NF90, a tandem pair of dsRBDs separated by a natively unstructured segment confers dsRNA binding activity. We determined a crystal structure of the tandem dsRBDs of NF90 in complex with a synthetic dsRNA. This complex shows surprising similarity to the tandem dsRBDs from an adenosine-to-inosine editing enzyme, ADAR2 in complex with a substrate RNA. Residues involved in unusual base-specific recognition in the minor groove of dsRNA are conserved between NF90 and ADAR2. These data suggest that, like ADAR2, underlying sequences in dsRNA may influence how NF90 recognizes its target RNAs. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  19. Fear on the move: predator hunting mode predicts variation in prey mortality and plasticity in prey spatial response.

    Science.gov (United States)

    Miller, Jennifer R B; Ament, Judith M; Schmitz, Oswald J

    2014-01-01

    Ecologists have long searched for a framework of a priori species traits to help predict predator-prey interactions in food webs. Empirical evidence has shown that predator hunting mode and predator and prey habitat domain are useful traits for explaining predator-prey interactions. Yet, individual experiments have yet to replicate predator hunting mode, calling into question whether predator impacts can be attributed to hunting mode or merely species identity. We tested the effects of spider predators with sit-and-wait, sit-and-pursue and active hunting modes on grasshopper habitat domain, activity and mortality in a grassland system. We replicated hunting mode by testing two spider predator species of each hunting mode on the same grasshopper prey species. We observed grasshoppers with and without each spider species in behavioural cages and measured their mortality rates, movements and habitat domains. We likewise measured the movements and habitat domains of spiders to characterize hunting modes. We found that predator hunting mode explained grasshopper mortality and spider and grasshopper movement activity and habitat domain size. Sit-and-wait spider predators covered small distances over a narrow domain space and killed fewer grasshoppers than sit-and-pursue and active predators, which ranged farther distances across broader domains and killed more grasshoppers, respectively. Prey adjusted their activity levels and horizontal habitat domains in response to predator presence and hunting mode: sedentary sit-and-wait predators with narrow domains caused grasshoppers to reduce activity in the same-sized domain space; more mobile sit-and-pursue predators with broader domains caused prey to reduce their activity within a contracted horizontal (but not vertical) domain space; and highly mobile active spiders led grasshoppers to increase their activity across the same domain area. All predators impacted prey activity, and sit-and-pursue predators generated strong

  20. Mapping the heparin-binding site of the BMP antagonist gremlin by site-directed mutagenesis based on predictive modelling.

    Science.gov (United States)

    Tatsinkam, Arnold Junior; Mulloy, Barbara; Rider, Christopher C

    2015-08-15

    Gremlin is a member of the CAN (cerberus and DAN) family of secreted BMP (bone morphogenetic protein) antagonists and also an agonist of VEGF (vascular endothelial growth factor) receptor-2. It is critical in limb skeleton and kidney development and is re-expressed during tissue fibrosis. Gremlin binds strongly to heparin and heparan sulfate and, in the present study, we sought to investigate its heparin-binding site. In order to explore a putative non-contiguous binding site predicted by computational molecular modelling, we substituted a total of 11 key arginines and lysines located in three basic residue sequence clusters with homologous sequences from cerberus and DAN (differential screening selected gene abberative in neuroblastoma), CAN proteins which lack basic residues in these positions. A panel of six Myc-tagged gremlin mutants, MGR-1-MGR-6 (MGR, mutant gremlin), each containing different combinations of targeted substitutions, all showed markedly reduced affinity for heparin as demonstrated by their NaCl elution on heparin affinity chromatography, thus verifying our predictions. Both MGR-5 and MGR-6 retained BMP-4-binding activity comparable to that of wild-type gremlin. Low-molecular-mass heparin neither promoted nor inhibited BMP-4 binding. Finally, glutaraldehyde cross-linking demonstrated that gremlin forms non-covalent dimers, similar behaviour to that of DAN and also PRDC (protein related to cerberus and DAN), another CAN protein. The resulting dimer would possess two heparin-binding sites, each running along an exposed surface on the second β-strand finger loop of one of the monomers. © 2015 Authors; published by Portland Press Limited.

  1. Agrobacterium uses a unique ligand-binding mode for trapping opines and acquiring a competitive advantage in the niche construction on plant host.

    Directory of Open Access Journals (Sweden)

    Julien Lang

    2014-10-01

    Full Text Available By modifying the nuclear genome of its host, the plant pathogen Agrobacterium tumefaciens induces the development of plant tumours in which it proliferates. The transformed plant tissues accumulate uncommon low molecular weight compounds called opines that are growth substrates for A. tumefaciens. In the pathogen-induced niche (the plant tumour, a selective advantage conferred by opine assimilation has been hypothesized, but not experimentally demonstrated. Here, using genetics and structural biology, we deciphered how the pathogen is able to bind opines and use them to efficiently compete in the plant tumour. We report high resolution X-ray structures of the periplasmic binding protein (PBP NocT unliganded and liganded with the opine nopaline (a condensation product of arginine and α-ketoglurate and its lactam derivative pyronopaline. NocT exhibited an affinity for pyronopaline (K(D of 0.6 µM greater than that for nopaline (KD of 3.7 µM. Although the binding-mode of the arginine part of nopaline/pyronopaline in NocT resembled that of arginine in other PBPs, affinity measurement by two different techniques showed that NocT did not bind arginine. In contrast, NocT presented specific residues such as M117 to stabilize the bound opines. NocT relatives that exhibit the nopaline/pyronopaline-binding mode were only found in genomes of the genus Agrobacterium. Transcriptomics and reverse genetics revealed that A. tumefaciens uses the same pathway for assimilating nopaline and pyronopaline. Fitness measurements showed that NocT is required for a competitive colonization of the plant tumour by A. tumefaciens. Moreover, even though the Ti-plasmid conjugal transfer was not regulated by nopaline, the competitive advantage gained by the nopaline-assimilating Ti-plasmid donors led to a preferential horizontal propagation of this Ti-plasmid amongst the agrobacteria colonizing the plant-tumour niche. This work provided structural and genetic evidences to

  2. Agrobacterium uses a unique ligand-binding mode for trapping opines and acquiring a competitive advantage in the niche construction on plant host.

    Science.gov (United States)

    Lang, Julien; Vigouroux, Armelle; Planamente, Sara; El Sahili, Abbas; Blin, Pauline; Aumont-Nicaise, Magali; Dessaux, Yves; Moréra, Solange; Faure, Denis

    2014-10-01

    By modifying the nuclear genome of its host, the plant pathogen Agrobacterium tumefaciens induces the development of plant tumours in which it proliferates. The transformed plant tissues accumulate uncommon low molecular weight compounds called opines that are growth substrates for A. tumefaciens. In the pathogen-induced niche (the plant tumour), a selective advantage conferred by opine assimilation has been hypothesized, but not experimentally demonstrated. Here, using genetics and structural biology, we deciphered how the pathogen is able to bind opines and use them to efficiently compete in the plant tumour. We report high resolution X-ray structures of the periplasmic binding protein (PBP) NocT unliganded and liganded with the opine nopaline (a condensation product of arginine and α-ketoglurate) and its lactam derivative pyronopaline. NocT exhibited an affinity for pyronopaline (K(D) of 0.6 µM) greater than that for nopaline (KD of 3.7 µM). Although the binding-mode of the arginine part of nopaline/pyronopaline in NocT resembled that of arginine in other PBPs, affinity measurement by two different techniques showed that NocT did not bind arginine. In contrast, NocT presented specific residues such as M117 to stabilize the bound opines. NocT relatives that exhibit the nopaline/pyronopaline-binding mode were only found in genomes of the genus Agrobacterium. Transcriptomics and reverse genetics revealed that A. tumefaciens uses the same pathway for assimilating nopaline and pyronopaline. Fitness measurements showed that NocT is required for a competitive colonization of the plant tumour by A. tumefaciens. Moreover, even though the Ti-plasmid conjugal transfer was not regulated by nopaline, the competitive advantage gained by the nopaline-assimilating Ti-plasmid donors led to a preferential horizontal propagation of this Ti-plasmid amongst the agrobacteria colonizing the plant-tumour niche. This work provided structural and genetic evidences to support the niche

  3. A highly tilted binding mode by a self-reactive T cell receptor results in altered engagement of peptide and MHC

    Energy Technology Data Exchange (ETDEWEB)

    Sethi, D.K.; Heroux, A.; Schubert, D. A.; Anders, A.-K.; Bonsor, D. A.; Thomas, C. P.; Sundberg, E. J.; Pyrdol, J.; Wucherpfennig, K. W.

    2011-01-17

    Self-reactive T cells that escape elimination in the thymus can cause autoimmune pathology, and it is therefore important to understand the structural mechanisms of self-antigen recognition. We report the crystal structure of a T cell receptor (TCR) from a patient with relapsing-remitting multiple sclerosis that engages its self-peptide-major histocompatibility complex (pMHC) ligand in an unusual manner. The TCR is bound in a highly tilted orientation that prevents interaction of the TCR-{alpha} chain with the MHC class II {beta} chain helix. In this structure, only a single germline-encoded TCR loop engages the MHC protein, whereas in most other TCR-pMHC structures all four germline-encoded TCR loops bind to the MHC helices. The tilted binding mode also prevents peptide contacts by the short complementarity-determining region (CDR) 3{beta} loop, and interactions that contribute to peptide side chain specificity are focused on the CDR3{alpha} loop. This structure is the first example in which only a single germline-encoded TCR loop contacts the MHC helices. Furthermore, the reduced interaction surface with the peptide may facilitate TCR cross-reactivity. The structural alterations in the trimolecular complex are distinct from previously characterized self-reactive TCRs, indicating that there are multiple unusual ways for self-reactive TCRs to bind their pMHC ligand.

  4. A Highly Tilted Binding Mode by a Self-Reactive T Cell Receptor Results in Altered Engagement of Peptide and MHC

    Energy Technology Data Exchange (ETDEWEB)

    D Sethi; D Schubert; A Anders; A Heroux; D Bonsor; C Thomas; E Sundberg; J Pyrdol; K Wucherpfennig

    2011-12-31

    Self-reactive T cells that escape elimination in the thymus can cause autoimmune pathology, and it is therefore important to understand the structural mechanisms of self-antigen recognition. We report the crystal structure of a T cell receptor (TCR) from a patient with relapsing-remitting multiple sclerosis that engages its self-peptide-major histocompatibility complex (pMHC) ligand in an unusual manner. The TCR is bound in a highly tilted orientation that prevents interaction of the TCR-{alpha} chain with the MHC class II {beta} chain helix. In this structure, only a single germline-encoded TCR loop engages the MHC protein, whereas in most other TCR-pMHC structures all four germline-encoded TCR loops bind to the MHC helices. The tilted binding mode also prevents peptide contacts by the short complementarity-determining region (CDR) 3{beta} loop, and interactions that contribute to peptide side chain specificity are focused on the CDR3{alpha} loop. This structure is the first example in which only a single germline-encoded TCR loop contacts the MHC helices. Furthermore, the reduced interaction surface with the peptide may facilitate TCR cross-reactivity. The structural alterations in the trimolecular complex are distinct from previously characterized self-reactive TCRs, indicating that there are multiple unusual ways for self-reactive TCRs to bind their pMHC ligand.

  5. A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain.

    Science.gov (United States)

    Panel, Nicolas; Sun, Young Joo; Fuentes, Ernesto J; Simonson, Thomas

    2017-01-01

    PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB) continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or "PB/LIE" free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α 2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo . The overall performance of the model should allow its use in the design of new PDZ ligands in the future.

  6. Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints.

    Science.gov (United States)

    Schwessinger, Ron; Suciu, Maria C; McGowan, Simon J; Telenius, Jelena; Taylor, Stephen; Higgs, Doug R; Hughes, Jim R

    2017-10-01

    In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k -mer-based analysis of DNase footprints to determine any k -mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome. © 2017 Schwessinger et al.; Published by Cold Spring Harbor Laboratory Press.

  7. A strategy for interaction site prediction between phospho-binding modules and their partners identified from proteomic data.

    Science.gov (United States)

    Aucher, Willy; Becker, Emmanuelle; Ma, Emilie; Miron, Simona; Martel, Arnaud; Ochsenbein, Françoise; Marsolier-Kergoat, Marie-Claude; Guerois, Raphaël

    2010-12-01

    Small and large scale proteomic technologies are providing a wealth of potential interactions between proteins bearing phospho-recognition modules and their substrates. Resulting interaction maps reveal such a dense network of interactions that the functional dissection and understanding of these networks often require to break specific interactions while keeping the rest intact. Here, we developed a computational strategy, called STRIP, to predict the precise interaction site involved in an interaction with a phospho-recognition module. The method was validated by a two-hybrid screen carried out using the ForkHead Associated (FHA)1 domain of Rad53, a key protein of Saccharomyces cerevisiae DNA checkpoint, as a bait. In this screen we detected 11 partners, including Cdc7 and Cdc45, essential components of the DNA replication machinery. FHA domains are phospho-threonine binding modules and the threonines involved in both interactions could be predicted using the STRIP strategy. The threonines T484 and T189 in Cdc7 and Cdc45, respectively, were mutated and loss of binding could be monitored experimentally with the full-length proteins. The method was further tested for the analysis of 63 known Rad53 binding partners and provided several key insights regarding the threonines likely involved in these interactions. The STRIP method relies on a combination of conservation, phosphorylation likelihood, and binding specificity criteria and can be accessed via a web interface at http://biodev.extra.cea.fr/strip/.

  8. A Strategy for Interaction Site Prediction between Phospho-binding Modules and their Partners Identified from Proteomic Data*

    Science.gov (United States)

    Aucher, Willy; Becker, Emmanuelle; Ma, Emilie; Miron, Simona; Martel, Arnaud; Ochsenbein, Françoise; Marsolier-Kergoat, Marie-Claude; Guerois, Raphaël

    2010-01-01

    Small and large scale proteomic technologies are providing a wealth of potential interactions between proteins bearing phospho-recognition modules and their substrates. Resulting interaction maps reveal such a dense network of interactions that the functional dissection and understanding of these networks often require to break specific interactions while keeping the rest intact. Here, we developed a computational strategy, called STRIP, to predict the precise interaction site involved in an interaction with a phospho-recognition module. The method was validated by a two-hybrid screen carried out using the ForkHead Associated (FHA)1 domain of Rad53, a key protein of Saccharomyces cerevisiae DNA checkpoint, as a bait. In this screen we detected 11 partners, including Cdc7 and Cdc45, essential components of the DNA replication machinery. FHA domains are phospho-threonine binding modules and the threonines involved in both interactions could be predicted using the STRIP strategy. The threonines T484 and T189 in Cdc7 and Cdc45, respectively, were mutated and loss of binding could be monitored experimentally with the full-length proteins. The method was further tested for the analysis of 63 known Rad53 binding partners and provided several key insights regarding the threonines likely involved in these interactions. The STRIP method relies on a combination of conservation, phosphorylation likelihood, and binding specificity criteria and can be accessed via a web interface at http://biodev.extra.cea.fr/strip/. PMID:20733106

  9. A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain

    Directory of Open Access Journals (Sweden)

    Nicolas Panel

    2017-09-01

    Full Text Available PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or “PB/LIE” free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo. The overall performance of the model should allow its use in the design of new PDZ ligands in the future.

  10. SVM prediction of ligand-binding sites in bacterial lipoproteins employing shape and physio-chemical descriptors.

    Science.gov (United States)

    Kadam, Kiran; Prabhakar, Prashant; Jayaraman, V K

    2012-11-01

    Bacterial lipoproteins play critical roles in various physiological processes including the maintenance of pathogenicity and numbers of them are being considered as potential candidates for generating novel vaccines. In this work, we put forth an algorithm to identify and predict ligand-binding sites in bacterial lipoproteins. The method uses three types of pocket descriptors, namely fpocket descriptors, 3D Zernike descriptors and shell descriptors, and combines them with Support Vector Machine (SVM) method for the classification. The three types of descriptors represent shape-based properties of the pocket as well as its local physio-chemical features. All three types of descriptors, along with their hybrid combinations are evaluated with SVM and to improve classification performance, WEKA-InfoGain feature selection is applied. Results obtained in the study show that the classifier successfully differentiates between ligand-binding and non-binding pockets. For the combination of three types of descriptors, 10 fold cross-validation accuracy of 86.83% is obtained for training while the selected model achieved test Matthews Correlation Coefficient (MCC) of 0.534. Individually or in combination with new and existing methods, our model can be a very useful tool for the prediction of potential ligand-binding sites in bacterial lipoproteins.

  11. Novel N-allyl/propargyl tetrahydroquinolines: Synthesis via Three-component Cationic Imino Diels-Alder Reaction, Binding Prediction, and Evaluation as Cholinesterase Inhibitors.

    Science.gov (United States)

    Rodríguez, Yeray A; Gutiérrez, Margarita; Ramírez, David; Alzate-Morales, Jans; Bernal, Cristian C; Güiza, Fausto M; Romero Bohórquez, Arnold R

    2016-10-01

    New N-allyl/propargyl 4-substituted 1,2,3,4-tetrahydroquinolines derivatives were efficiently synthesized using acid-catalyzed three components cationic imino Diels-Alder reaction (70-95%). All compounds were tested in vitro as dual acetylcholinesterase and butyryl-cholinesterase inhibitors and their potential binding modes, and affinity, were predicted by molecular docking and binding free energy calculations (∆G) respectively. The compound 4af (IC50 = 72 μm) presented the most effective inhibition against acetylcholinesterase despite its poor selectivity (SI = 2), while the best inhibitory activity on butyryl-cholinesterase was exhibited by compound 4ae (IC50 = 25.58 μm) with considerable selectivity (SI = 0.15). Molecular docking studies indicated that the most active compounds fit in the reported acetylcholinesterase and butyryl-cholinesterase active sites. Moreover, our computational data indicated a high correlation between the calculated ∆G and the experimental activity values in both targets. © 2016 The Authors Chemical Biology & Drug Design Published by John Wiley & Sons Ltd.

  12. An integrative approach to CTL epitope prediction: A combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions

    DEFF Research Database (Denmark)

    Larsen, Mette Voldby; Lundegaard, Claus; Lamberth, K

    2005-01-01

    Reverse immunogenetic approaches attempt to optimize the selection of candidate epitopes, and thus minimize the experimental effort needed to identify new epitopes. When predicting cytotoxic T cell epitopes, the main focus has been on the highly specific MHC class I binding event. Methods have al.......The method is available at http://www.cbs.dtu.dk/services/NetCTL. Supplementary material is available at http://www.cbs.dtu.dk/suppl/immunology/CTL.php....

  13. Predictions of RNA-binding ability and aggregation propensity of proteins

    OpenAIRE

    Agostini, Federico, 1985-

    2014-01-01

    RNA-binding proteins (RBPs) control the fate of a multitude of coding and non-coding transcripts. Formation of ribonucleoprotein (RNP) complexes fine-tunes regulation of post-transcriptional events and influences gene expression. Recently, it has been observed that non-canonical proteins with RNA-binding ability are enriched in structurally disordered and low-complexity regions that are generally involved in functional and dysfunctional associations. Therefore, it is possible that interaction...

  14. Microstructurally Based Prediction of High Strain Failure Modes in Crystalline Solids

    Science.gov (United States)

    2016-07-05

    interfaces in hcp– fcc systems subjected to high strain-rate deformation and fracture modes, Journal of Materials Research, (8 2015): 0. doi: 10.1557/jmr...rupture • Comparison and validation with experimental observations/ measurements • New dislocation-density crystalline plasticity that accounts for...relationships between coherent interfaces in hcp– fcc systems subjected to high strain-rate deformation and fracture modes, Journal of Materials Research, Vol. 30

  15. Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints

    OpenAIRE

    Schwessinger, R; Suciu, MC; McGowan, SJ; Telenius, J; Taylor, S; Higgs, DR; Hughes, JR

    2017-01-01

    In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor bin...

  16. Combining structural modeling with ensemble machine learning to accurately predict protein fold stability and binding affinity effects upon mutation.

    Directory of Open Access Journals (Sweden)

    Niklas Berliner

    Full Text Available Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases.

  17. Improved pan-specific prediction of MHC class I peptide binding using a novel receptor clustering data partitioning strategy

    DEFF Research Database (Denmark)

    Mattsson, Andreas Holm; Kringelum, Jens Vindahl; Garde, C.

    2016-01-01

    Pan-specific prediction of receptor-ligand interaction is conventionally done using machine-learning methods that integrates information about both receptor and ligand primary sequences. To achieve optimal performance using machine learning, dealing with overfitting and data redundancy is critical....... Most often so-called ligand clustering methods have been used to deal with these issues in the context of pan-specific receptor-ligand predictions, and the MHC system the approach has proven highly effective for extrapolating information from a limited set of receptors with well characterized binding...

  18. Kinetic and structural studies reveal a unique binding mode of sulfite to the nickel center in urease.

    Science.gov (United States)

    Mazzei, Luca; Cianci, Michele; Benini, Stefano; Bertini, Leonardo; Musiani, Francesco; Ciurli, Stefano

    2016-01-01

    Urease is the most efficient enzyme known to date, and catalyzes the hydrolysis of urea using two Ni(II) ions in the active site. Urease is a virulence factor in several human pathogens, while causing severe environmental and agronomic problems. Sporosarcina pasteurii urease has been used extensively in the structural characterization of the enzyme. Sodium sulfite has been widely used as a preservative in urease solutions to prevent oxygen-induced oxidation, but its role as an inhibitor has also been suggested. In the present study, isothermal titration microcalorimetry was used to establish sulfite as a competitive inhibitor for S. pasteurii urease, with an inhibition constant of 0.19mM at pH7. The structure of the urease-sulfite complex, determined at 1.65Å resolution, shows the inhibitor bound to the dinuclear Ni(II) center of urease in a tridentate mode involving bonds between the two Ni(II) ions in the active site and all three oxygen atoms of the inhibitor, supporting the observed competitive inhibition kinetics. This coordination mode of sulfite has never been observed, either in proteins or in small molecule complexes, and could inspire synthetic coordination chemists as well as biochemists to develop urease inhibitors based on this chemical moiety. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Positive predictive values by mammographic density and screening mode in the Norwegian Breast Cancer Screening Program.

    Science.gov (United States)

    Moshina, Nataliia; Ursin, Giske; Roman, Marta; Sebuødegård, Sofie; Hofvind, Solveig

    2016-01-01

    To investigate the probability of breast cancer among women recalled due to abnormal findings on the screening mammograms (PPV-1) and among women who underwent an invasive procedure (PPV-2) by mammographic density (MD), screening mode and age. We used information about 28,826 recall examinations from 26,951 subsequently screened women in the Norwegian Breast Cancer Screening Program, 1996-2010. The radiologists who performed the recall examinations subjectively classified MD on the mammograms into three categories: fatty (70%). Screening mode was defined as screen-film mammography (SFM) and full-field digital mammography (FFDM). We examined trends of PPVs by MD, screening mode and age. We used logistic regression to estimate odds ratio (OR) of screen-detected breast cancer associated with MD among women recalled, adjusting for screening mode and age. PPV-1 and PPV-2 decreased by increasing MD, regardless of screening mode (p for trend breasts. Among women recalled, the adjusted OR of breast cancer decreased with increasing MD. Compared with women with fatty breasts, the OR was 0.90 (95% CI: 0.84-0.96) for those with medium dense breasts and 0.85 (95% CI: 0.76-0.95) for those with dense breasts. PPVs decreased by increasing MD. Fewer women needed to be recalled or undergo an invasive procedure to detect one breast cancer among those with fatty versus dense breasts in the screening program in Norway, 1996-2010. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  20. Salience and Default Mode Network Coupling Predicts Cognition in Aging and Parkinson's Disease.

    Science.gov (United States)

    Putcha, Deepti; Ross, Robert S; Cronin-Golomb, Alice; Janes, Amy C; Stern, Chantal E

    2016-02-01

    Cognitive impairment is common in Parkinson's disease (PD). Three neurocognitive networks support efficient cognition: the salience network, the default mode network, and the central executive network. The salience network is thought to switch between activating and deactivating the default mode and central executive networks. Anti-correlated interactions between the salience and default mode networks in particular are necessary for efficient cognition. Our previous work demonstrated altered functional coupling between the neurocognitive networks in non-demented individuals with PD compared to age-matched control participants. Here, we aim to identify associations between cognition and functional coupling between these neurocognitive networks in the same group of participants. We investigated the extent to which intrinsic functional coupling among these neurocognitive networks is related to cognitive performance across three neuropsychological domains: executive functioning, psychomotor speed, and verbal memory. Twenty-four non-demented individuals with mild to moderate PD and 20 control participants were scanned at rest and evaluated on three neuropsychological domains. PD participants were impaired on tests from all three domains compared to control participants. Our imaging results demonstrated that successful cognition across healthy aging and Parkinson's disease participants was related to anti-correlated coupling between the salience and default mode networks. Individuals with poorer performance scores across groups demonstrated more positive salience network/default-mode network coupling. Successful cognition relies on healthy coupling between the salience and default mode networks, which may become dysfunctional in PD. These results can help inform non-pharmacological interventions (repetitive transcranial magnetic stimulation) targeting these specific networks before they become vulnerable in early stages of Parkinson's disease.

  1. A community resource benchmarking predictions of peptide binding to MHC-I molecules

    DEFF Research Database (Denmark)

    Peters, B; Bui, HH; Pletscher-Frankild, Sune

    2006-01-01

    on the internet. While differences in the data used to generate these predictions hamper direct comparisons, we do conclude that tools based on combinatorial peptide libraries perform remarkably well. The transparent prediction evaluation on this dataset provides tool developers with a benchmark for comparison...... of newly developed prediction methods. In addition, to generate and evaluate our own prediction methods, we have established an easily extensible web-based prediction framework that allows automated side-by-side comparisons of prediction methods implemented by experts. This is an advance over the current...

  2. Dynamical Binding Modes Determine Agonistic and Antagonistic Ligand Effects in the Prostate-Specific G-Protein Coupled Receptor (PSGR).

    Science.gov (United States)

    Wolf, Steffen; Jovancevic, Nikolina; Gelis, Lian; Pietsch, Sebastian; Hatt, Hanns; Gerwert, Klaus

    2017-11-22

    We analysed the ligand-based activation mechanism of the prostate-specific G-protein coupled receptor (PSGR), which is an olfactory receptor that mediates cellular growth in prostate cancer cells. Furthermore, it is an olfactory receptor with a known chemically near identic antagonist/agonist pair, α- and β-ionone. Using a combined theoretical and experimental approach, we propose that this receptor is activated by a ligand-induced rearrangement of a protein-internal hydrogen bond network. Surprisingly, this rearrangement is not induced by interaction of the ligand with the network, but by dynamic van der Waals contacts of the ligand with the involved amino acid side chains, altering their conformations and intraprotein connectivity. Ligand recognition in this GPCR is therefore highly stereo selective, but seemingly lacks any ligand recognition via polar contacts. A putative olfactory receptor-based drug design scheme will have to take this unique mode of protein/ligand action into account.

  3. Confirmation of a predicted lack of IgE binding to Cry3Bb1 from genetically modified (GM) crops.

    Science.gov (United States)

    Nakajima, Osamu; Koyano, Satoru; Akiyama, Hiroshi; Sawada, Jun-Ichi; Teshima, Reiko

    2010-04-01

    Some GM crops including MON863 corn and stack varieties contain Cry3Bb1 protein. Cry3Bb1 is very important from the standpoint of assessing the safety of GM crops. In this study Cry3Bb1 was assessed from the standpoint of possible binding to IgE from allergy patients. First, an ELISA that was improved in our laboratory was used to test serum samples from 13 corn allergy patients in the United States with recombinant Cry3Bb1 expressed in Escherichia coli, and serum samples from 55 patients in Japan with various food allergies were also assayed. Two samples from the Japanese allergy patients were suspected of being positive, but Western blotting analysis with purified Cry3Bb1 indicated that the binding between IgE and Cry3Bb1 was nonspecific. Ultimately, no specific binding between IgE and recombinant Cry3Bb1 was detected. Next, all proteins extracted from MON863 corn and non-GM corn were probed with IgE antibodies in serum samples from the corn allergy patients by Western blotting, but the staining patterns of MON863 and non-GM corn were similar, meaning that unintended allergic reactions to MON863 are unlikely to occur. Our study provides additional information that confirms the predicted lack of IgE binding to Cry3Bb1 in people with existing food allergies. Copyright 2009 Elsevier Inc. All rights reserved.

  4. Relative binding affinity prediction of farnesoid X receptor in the D3R Grand Challenge 2 using FEP+

    Science.gov (United States)

    Schindler, Christina; Rippmann, Friedrich; Kuhn, Daniel

    2018-01-01

    Physics-based free energy simulations have increasingly become an important tool for predicting binding affinity and the recent introduction of automated protocols has also paved the way towards a more widespread use in the pharmaceutical industry. The D3R 2016 Grand Challenge 2 provided an opportunity to blindly test the commercial free energy calculation protocol FEP+ and assess its performance relative to other affinity prediction methods. The present D3R free energy prediction challenge was built around two experimental data sets involving inhibitors of farnesoid X receptor (FXR) which is a promising anticancer drug target. The FXR binding site is predominantly hydrophobic with few conserved interaction motifs and strong induced fit effects making it a challenging target for molecular modeling and drug design. For both data sets, we achieved reasonable prediction accuracy (RMSD ≈ 1.4 kcal/mol, rank 3-4 according to RMSD out of 20 submissions) comparable to that of state-of-the-art methods in the field. Our D3R results boosted our confidence in the method and strengthen our desire to expand its applications in future in-house drug design projects.

  5. Relative binding affinity prediction of farnesoid X receptor in the D3R Grand Challenge 2 using FEP.

    Science.gov (United States)

    Schindler, Christina; Rippmann, Friedrich; Kuhn, Daniel

    2018-01-01

    Physics-based free energy simulations have increasingly become an important tool for predicting binding affinity and the recent introduction of automated protocols has also paved the way towards a more widespread use in the pharmaceutical industry. The D3R 2016 Grand Challenge 2 provided an opportunity to blindly test the commercial free energy calculation protocol FEP+ and assess its performance relative to other affinity prediction methods. The present D3R free energy prediction challenge was built around two experimental data sets involving inhibitors of farnesoid X receptor (FXR) which is a promising anticancer drug target. The FXR binding site is predominantly hydrophobic with few conserved interaction motifs and strong induced fit effects making it a challenging target for molecular modeling and drug design. For both data sets, we achieved reasonable prediction accuracy (RMSD ≈ 1.4 kcal/mol, rank 3-4 according to RMSD out of 20 submissions) comparable to that of state-of-the-art methods in the field. Our D3R results boosted our confidence in the method and strengthen our desire to expand its applications in future in-house drug design projects.

  6. Sex hormone-binding globulin levels predict insulin sensitivity, disposition index, and cardiovascular risk during puberty

    DEFF Research Database (Denmark)

    Sørensen, Kaspar; Aksglaede, Lise; Munch-Andersen, Thor

    2009-01-01

    Early puberty is associated with increased risk of subsequent cardiovascular disease. Low sex hormone-binding globulin (SHBG) levels are a feature of early puberty and of conditions associated with increased cardiovascular risk. The aim of the present study was to evaluate SHBG as a predictor...... of glucose metabolism and metabolic risk during puberty....

  7. Conservation of transcription factor binding events predicts gene expression across species

    Science.gov (United States)

    Hemberg, Martin; Kreiman, Gabriel

    2011-01-01

    Recent technological advances have made it possible to determine the genome-wide binding sites of transcription factors (TFs). Comparisons across species have suggested a relatively low degree of evolutionary conservation of experimentally defined TF binding events (TFBEs). Using binding data for six different TFs in hepatocytes and embryonic stem cells from human and mouse, we demonstrate that evolutionary conservation of TFBEs within orthologous proximal promoters is closely linked to function, defined as expression of the target genes. We show that (i) there is a significantly higher degree of conservation of TFBEs when the target gene is expressed in both species; (ii) there is increased conservation of binding events for groups of TFs compared to individual TFs; and (iii) conserved TFBEs have a greater impact on the expression of their target genes than non-conserved ones. These results link conservation of structural elements (TFBEs) to conservation of function (gene expression) and suggest a higher degree of functional conservation than implied by previous studies. PMID:21622661

  8. Interaction Pattern of Arg 62 in the A-Pocket of Differentially Disease-Associated HLA-B27 Subtypes Suggests Distinct TCR Binding Modes

    Science.gov (United States)

    Cauli, Alberto; Mathieu, Alessandro; Tedeschi, Valentina; Caristi, Silvana; Sorrentino, Rosa; Böckmann, Rainer A.; Fiorillo, Maria Teresa

    2012-01-01

    The single amino acid replacement Asp116His distinguishes the two subtypes HLA-B*2705 and HLA-B*2709 which are, respectively, associated and non-associated with Ankylosing Spondylitis, an autoimmune chronic inflammatory disease. The reason for this differential association is so far poorly understood and might be related to subtype-specific HLA:peptide conformations as well as to subtype/peptide-dependent dynamical properties on the nanoscale. Here, we combine functional experiments with extensive molecular dynamics simulations to investigate the molecular dynamics and function of the conserved Arg62 of the α1-helix for both B27 subtypes in complex with the self-peptides pVIPR (RRKWRRWHL) and TIS (RRLPIFSRL), and the viral peptides pLMP2 (RRRWRRLTV) and NPflu (SRYWAIRTR). Simulations of HLA:peptide systems suggest that peptide-stabilizing interactions of the Arg62 residue observed in crystal structures are metastable for both B27 subtypes under physiological conditions, rendering this arginine solvent-exposed and, probably, a key residue for TCR interaction more than peptide-binding. This view is supported by functional experiments with conservative (R62K) and non-conservative (R62A) B*2705 and B*2709 mutants that showed an overall reduction in their capability to present peptides to CD8+ T cells. Moreover, major subtype-dependent differences in the peptide recognition suggest distinct TCR binding modes for the B*2705 versus the B*2709 subtype. PMID:22403718

  9. Studies on 16α-Hydroxylation of Steroid Molecules and Regioselective Binding Mode in Homology-Modeled Cytochrome P450-2C11

    Directory of Open Access Journals (Sweden)

    Hamed I. Ali

    2011-01-01

    Full Text Available We investigated the 16α-hydroxylation of steroid molecules and regioselective binding mode in homology-modeled cytochrome P450-2C11 to correlate the biological study with the computational molecular modeling. It revealed that there was a positive relationship between the observed inhibitory potencies and the binding free energies. Docking of steroid molecules into this homology-modeled CYP2C11 indicated that 16α-hydroxylation is favored with steroidal molecules possessing the following components, (1 a bent A-B ring configuration (5β-reduced, (2 C-3 α-hydroxyl group, (3 C-17β-acetyl group, and (4 methyl group at both the C-18 and C-19. These respective steroid components requirements were defined as the inhibitory contribution factor. Overall studies of the male rat CYP2C11 metabolism revealed that the above-mentioned steroid components requirements were essential to induce an effective inhibition of [3H]progesterone 16α-hydroxylation. As far as docking of homology-modeled CYP2C11 against investigated steroids is concerned, they are docked at the active site superimposed with flurbiprofen. It was also found that the distance between heme iron and C16α-H was between 4 to 6 Å and that the related angle was in the range of 180±45∘.

  10. Vitual screening and binding mode elucidation of curcumin analogues on Cyclooxygenase-2 using AYO_COX2_V1.1 protocol

    Science.gov (United States)

    Mulatsari, E.; Mumpuni, E.; Herfian, A.

    2017-05-01

    Curcumin is yellow colored phenolic compounds contained in Curcuma longa. Curcumin is known to have biological activities as anti-inflammatory, antiviral, antioxidant, and anti-infective agent [1]. Synthesis of curcumin analogue compounds has been done and some of them had biological activity like curcumin. In this research, the virtual screening of curcumin analogue compounds has been conducted. The purpose of this research was to determine the activity of these compounds as selective Cyclooxygenase-2inhibitors in in-silico. Binding mode elucidation was made by active and inactive representative compounds to see the interaction of the amino acids in the binding site of the compounds. This research used AYO_COX2_V.1.1, a structure-based virtual screening protocol (SBVS) that has been validated by Mumpuni E et al, 2014 [2]. AYO_COX2_V.1.1 protocol using a variety of integrated applications such as SPORES, PLANTS, BKchem, OpenBabel and PyMOL. The results of virtual screening conducted on 49 curcumin analogue compounds obtained 8 compounds with 4 active amino acid residues (GLY340, ILE503, PHE343, and PHE367) that were considered active as COX-2 inhibitor.

  11. NetMHCpan 4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data

    OpenAIRE

    Jurtz, Vanessa; Paul, Sinu; Andreatta, Massimo; Marcatili, Paolo; Peters, Bjoern; Nielsen, Morten

    2017-01-01

    Cytotoxic T cells are of central importance in the immune systems response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC (major histocompatibility complex) class I molecules. Peptide binding to MHC molecules is the single most selective step in the antigen presentation pathway. On the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has therefore attracted large attention. In the past, predictors of peptide-...

  12. Improved model predictive control of resistive wall modes by error field estimator in EXTRAP T2R

    Science.gov (United States)

    Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

    2016-12-01

    Many implementations of a model-based approach for toroidal plasma have shown better control performance compared to the conventional type of feedback controller. One prerequisite of model-based control is the availability of a control oriented model. This model can be obtained empirically through a systematic procedure called system identification. Such a model is used in this work to design a model predictive controller to stabilize multiple resistive wall modes in EXTRAP T2R reversed-field pinch. Model predictive control is an advanced control method that can optimize the future behaviour of a system. Furthermore, this paper will discuss an additional use of the empirical model which is to estimate the error field in EXTRAP T2R. Two potential methods are discussed that can estimate the error field. The error field estimator is then combined with the model predictive control and yields better radial magnetic field suppression.

  13. Comparison of high-mode predictive simulations using Mixed Bohm/gyro-Bohm and Multi-Mode (MMM95) transport models

    International Nuclear Information System (INIS)

    Hannum, David; Bateman, Glenn; Kinsey, Jon; Kritz, Arnold H.; Onjun, Thawatchai; Pankin, Alexei

    2001-01-01

    Two different transport models -- the Mixed Bohm/gyro-Bohm [Joint European Torus (JET)] model [Erba , Plasma Phys. Controlled Fusion 39, 261 (1997)] and the Multi-Mode model (MMM95) [Bateman , Phys. Plasmas 5, 1793 (1998)] -- are used in predictive transport simulations of 22 high-mode discharges. Fourteen discharges that include systematic scans in normalized gyroradius (ρ * ), plasma pressure (β), collisionality, and isotope mass in the JET tokamak [Rebut , Nucl. Fusion 25, 1011 (1985)] and eight discharges that include scans in ρ * , elongation (κ), power, and density in the DIII-D tokamak [J. L. Luxon and L. G. Davis, Fusion Technol. 8, 441 (1985)] are considered. When simulation temperature and density profiles are compared with processed experimental data from the International Profile Database, it is found that the results with either the JET or MMM95 transport model match experimental data about equally well. With either model, the average normalized rms deviation is approximately 10%. In the simulations carried out using the JET model, the component of the model with Bohm scaling (which is proportional to gyroradius) dominates over much of the plasma. In contrast, the MMM95 model has purely gyro-Bohm scaling (proportional to gyroradius squared). In spite of the differences in the underlying scaling of these transport models, both models reproduce the global confinement scalings observed in the scans equally well. These results are explained by changes in profile shapes from one end of each scan to the other. These changes in the profile shapes are caused by changes in boundary conditions, heating and particle source profiles, large scale instabilities, and transport

  14. Numerical Predictions of Mode Reflections in an Open Circular Duct: Comparison with Theory

    Science.gov (United States)

    Dahl, Milo D.; Hixon, Ray

    2015-01-01

    The NASA Broadband Aeroacoustic Stator Simulation code was used to compute the acoustic field for higher-order modes in a circular duct geometry. To test the accuracy of the results computed by the code, the duct was terminated by an open end with an infinite flange or no flange. Both open end conditions have a theoretical solution that was used to compare with the computed results. Excellent comparison for reflection matrix values was achieved after suitable refinement of the grid at the open end. The study also revealed issues with the level of the mode amplitude introduced into the acoustic held from the source boundary and the amount of reflection that occurred at the source boundary when a general nonreflecting boundary condition was applied.

  15. A Novel Procedure for Prediction of Mixed Mode I/II in Fracture Toughness of Laminate Composites

    Directory of Open Access Journals (Sweden)

    M. Mahmood Shokrieh

    2014-06-01

    Full Text Available Delamination is one of the important modes of failure in laminated composite materials. In this respect, the mixed mode I/II fracture is the most major mode of delamination incidence in laminated composite. In the present research, a relation between the fracture toughness of double cantilever beam (DCB and asymmetric double cantilever beam (ADCB specimens is presented. The DCB and ADCB samples are used for measuring the mode I and mixed mode I/II fracture toughness (G of laminated composite materials, respectively. By considering the diversity of the stacking sequence of lay-ups, the test performance on all different types of lay-ups in order to measure the fracture toughness of laminated composites is a tedious, costly and time consuming task. The purpose of deriving this relation is to estimate the value of the strain energy release rate of laminated composite ADCB specimens by testing a unidirectional DCB. To develop this relationship, the geometry of DCB and ADCB specimens are considered to obtain fracture toughness of multi-directional laminate composites of ADCB samples with arbitrary ply sequence which may be used for design purposes. The procedure presented here reduces the calculation costs of the finite element modeling and its corresponding test significantly. The results obtained by this method are compared with those of experimental and numerical methods. It is shown that the fracture toughness of multi-directional lay-ups can be predicted by measuring the unidirectional ply with an error less than 10% demonstrating the accuracy of the procedure developed in the present research.

  16. Predictions on the modes of decay of even Z superheavy isotopes within the range 104 ≤ Z ≤ 136

    Science.gov (United States)

    Santhosh, K. P.; Nithya, C.

    2018-01-01

    The decay modes and half lives of all the even Z isotopes of superheavy elements within the range 104 ≤ Z ≤ 136 have been predicted by comparing the alpha decay half-lives with the spontaneous fission half-lives. The Coulomb and proximity potential model for deformed nuclei (CPPMDN) and the shell-effect-dependent formula of Santhosh et al. are used to calculate the alpha half-lives and spontaneous fission half-lives respectively. For theoretical comparison the alpha decay half-lives are also calculated using Coulomb and proximity potential model (CPPM), the Viola-Seaborg-Sobiczewski semi-empirical (VSS) relation, the universal (UNIV) curve of Poenaru et al., the analytical formula of Royer and the universal decay law (UDL) of Qi et al. Another tool used for the evaluation of spontaneous fission half-lives is the semi-empirical formula of Xu et al. The nuclei with alpha decay half-lives less than spontaneous fission half-lives will survive fission and hence decay through alpha emission. The predicted half lives and decay modes are compared with the available experimental results. The one-proton and two-proton separation energies of all the isotopes are calculated to find nuclei which lie beyond the proton drip line. Among 1119 even Z nuclei within the range 104 ≤ Z ≤ 136, 164 nuclei show sequential alpha emission followed by subsequent spontaneous fission. Since the isotopes decay through alpha decay chain and the half-lives are in measurable range, these isotopes are predicted to be synthesized and detected in laboratory via alpha decay. 2 nuclei will decay by alpha decay followed by proton emission, 54 nuclei show full alpha chains, 642 nuclei will decay through spontaneous fission, 166 nuclei exhibit proton decay and 91 isotopes are found to be stable against alpha decay. All the isotopes are tabulated according to their decay modes. The study is intended to enhance further experimental investigations in superheavy region.

  17. Predicting the occurrence of mixed mode failure associated with hydraulic fracturing, part 2 water saturated tests

    Energy Technology Data Exchange (ETDEWEB)

    Bauer, Stephen J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Broome, Scott Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Choens, Charles [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Barrow, Perry Carl [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-09-14

    Seven water-saturated triaxial extension experiments were conducted on four sedimentary rocks. This experimental condition was hypothesized more representative of that existing for downhole hydrofracture and thus it may improve our understanding of the phenomena. In all tests the pore pressure was 10 MPa and confirming pressure was adjusted to achieve tensile and transitional failure mode conditions. Using previous work in this LDRD for comparison, the law of effective stress is demonstrated in extension using this sample geometry. In three of the four lithologies, no apparent chemo-mechanical effect of water is apparent, and in the fourth lithology test results indicate some chemo-mechanical effect of water.

  18. Prediction of DtxR regulon: Identification of binding sites and operons controlled by Diphtheria toxin repressor in Corynebacterium diphtheriae

    Directory of Open Access Journals (Sweden)

    Hasnain Seyed

    2004-09-01

    Full Text Available Abstract Background The diphtheria toxin repressor, DtxR, of Corynebacterium diphtheriae has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of Corynebacterium diphtheriae. Result Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within C. diphtheriae genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG, an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin. Conclusions We have used an in silico approach to identify the putative binding sites and genes controlled by DtxR in Corynebacterium diphtheriae. Our analysis shows that DtxR could provide a molecular link between Fe+2-induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe+2 and H2O2 and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase

  19. Evaluation of B3LYP, X3LYP, and M06-class density functionals for predicting the binding energies of neutral, protonated, and deprotonated water clusters

    OpenAIRE

    Bryantsev, Vyacheslav S.; Diallo, Mamadou S.; van Duin, Adri C. T.; Goddard, William A., III

    2009-01-01

    In this paper we assess the accuracy of the B3LYP, X3LYP, and newly developed M06-L, M06-2X, and M06 functionals to predict the binding energies of neutral and charged water clusters including (H_2O)_n, n = 2−8, 20), H_3O+(H_2O_)n, n = 1−6, and OH−(H_2O)_n, n = 1−6. We also compare the predicted energies of two ion hydration and neutralization reactions on the basis of the calculated binding energies. In all cases, we use as benchmarks calculated binding energies of water clusters extrapolate...

  20. DBAC: A simple prediction method for protein binding hot spots based on burial levels and deeply buried atomic contacts

    Science.gov (United States)

    2011-01-01

    Background A protein binding hot spot is a cluster of residues in the interface that are energetically important for the binding of the protein with its interaction partner. Identifying protein binding hot spots can give useful information to protein engineering and drug design, and can also deepen our understanding of protein-protein interaction. These residues are usually buried inside the interface with very low solvent accessible surface area (SASA). Thus SASA is widely used as an outstanding feature in hot spot prediction by many computational methods. However, SASA is not capable of distinguishing slightly buried residues, of which most are non hot spots, and deeply buried ones that are usually inside a hot spot. Results We propose a new descriptor called “burial level” for characterizing residues, atoms and atomic contacts. Specifically, burial level captures the depth the residues are buried. We identify different kinds of deeply buried atomic contacts (DBAC) at different burial levels that are directly broken in alanine substitution. We use their numbers as input for SVM to classify between hot spot or non hot spot residues. We achieve F measure of 0.6237 under the leave-one-out cross-validation on a data set containing 258 mutations. This performance is better than other computational methods. Conclusions Our results show that hot spot residues tend to be deeply buried in the interface, not just having a low SASA value. This indicates that a high burial level is not only a necessary but also a more sufficient condition than a low SASA for a residue to be a hot spot residue. We find that those deeply buried atoms become increasingly more important when their burial levels rise up. This work also confirms the contribution of deeply buried interfacial atomic contacts to the energy of protein binding hot spot. PMID:21689480

  1. Predictive transport modelling of type I ELMy H-mode dynamics using a theory-motivated combined ballooning-peeling model

    International Nuclear Information System (INIS)

    Loennroth, J-S; Parail, V; Dnestrovskij, A; Figarella, C; Garbet, X; Wilson, H

    2004-01-01

    This paper discusses predictive transport simulations of the type I ELMy high confinement mode (H-mode) with a theory-motivated edge localized mode (ELM) model based on linear ballooning and peeling mode stability theory. In the model, a total mode amplitude is calculated as a sum of the individual mode amplitudes given by two separate linear differential equations for the ballooning and peeling mode amplitudes. The ballooning and peeling mode growth rates are represented by mutually analogous terms, which differ from zero upon the violation of a critical pressure gradient and an analytical peeling mode stability criterion, respectively. The damping of the modes due to non-ideal magnetohydrodynamic effects is controlled by a term driving the mode amplitude towards the level of background fluctuations. Coupled to simulations with the JETTO transport code, the model qualitatively reproduces the experimental dynamics of type I ELMy H-mode, including an ELM frequency that increases with the external heating power. The dynamics of individual ELM cycles is studied. Each ELM is usually triggered by a ballooning mode instability. The ballooning phase of the ELM reduces the pressure gradient enough to make the plasma peeling unstable, whereby the ELM continues driven by the peeling mode instability, until the edge current density has been depleted to a stable level. Simulations with current ramp-up and ramp-down are studied as examples of situations in which pure peeling and pure ballooning mode ELMs, respectively, can be obtained. The sensitivity with respect to the ballooning and peeling mode growth rates is investigated. Some consideration is also given to an alternative formulation of the model as well as to a pure peeling model

  2. Prediction of the FOM FEM experimental results using multi-mode time-dependent simulations

    NARCIS (Netherlands)

    Caplan, M.; Bongers, W. A.; Verhoeven, A. G. A.; van der Geer, C. A. J.; Valentini, M.; Urbanus, W. H.

    1998-01-01

    The Free Electron Maser (FEM) constructed at the FOM Institute, Netherlands is now ready to undergo the first set of short pulse (< 20 mu s) experiments to demonstrate the capability of generating 1 MW of microwave power in the range 130-250 GHz. Predictions of the FEM performance requires a

  3. Predicting Success in an Online Course Using Expectancies, Values, and Typical Mode of Instruction

    Science.gov (United States)

    Zimmerman, Whitney Alicia

    2017-01-01

    Expectancies of success and values were used to predict success in an online undergraduate-level introductory statistics course. Students who identified as primarily face-to-face learners were compared to students who identified as primarily online learners. Expectancy value theory served as a model. Expectancies of success were operationalized as…

  4. Computational study on the inhibitor binding mode and allosteric regulation mechanism in hepatitis C virus NS3/4A protein.

    Directory of Open Access Journals (Sweden)

    Weiwei Xue

    Full Text Available HCV NS3/4A protein is an attractive therapeutic target responsible for harboring serine protease and RNA helicase activities during the viral replication. Small molecules binding at the interface between the protease and helicase domains can stabilize the closed conformation of the protein and thus block the catalytic function of HCV NS3/4A protein via an allosteric regulation mechanism. But the detailed mechanism remains elusive. Here, we aimed to provide some insight into the inhibitor binding mode and allosteric regulation mechanism of HCV NS3/4A protein by using computational methods. Four simulation systems were investigated. They include: apo state of HCV NS3/4A protein, HCV NS3/4A protein in complex with an allosteric inhibitor and the truncated form of the above two systems. The molecular dynamics simulation results indicate HCV NS3/4A protein in complex with the allosteric inhibitor 4VA adopts a closed conformation (inactive state, while the truncated apo protein adopts an open conformation (active state. Further residue interaction network analysis suggests the communication of the domain-domain interface play an important role in the transition from closed to open conformation of HCV NS3/4A protein. However, the inhibitor stabilizes the closed conformation through interaction with several key residues from both the protease and helicase domains, including His57, Asp79, Asp81, Asp168, Met485, Cys525 and Asp527, which blocks the information communication between the functional domains interface. Finally, a dynamic model about the allosteric regulation and conformational changes of HCV NS3/4A protein was proposed and could provide fundamental insights into the allosteric mechanism of HCV NS3/4A protein function regulation and design of new potent inhibitors.

  5. New insights into the structure and mode of action of Mo-CBP3, an antifungal chitin-binding protein of Moringa oleifera seeds.

    Directory of Open Access Journals (Sweden)

    Adelina B Batista

    Full Text Available Mo-CBP3 is a chitin-binding protein purified from Moringa oleifera Lam. seeds that displays inhibitory activity against phytopathogenic fungi. This study investigated the structural properties and the antifungal mode of action of this protein. To this end, circular dichroism spectroscopy, antifungal assays, measurements of the production of reactive oxygen species and microscopic analyses were utilized. Mo-CBP3 is composed of 30.3% α-helices, 16.3% β-sheets, 22.3% turns and 30.4% unordered forms. The Mo-CBP3 structure is highly stable and retains its antifungal activity regardless of temperature and pH. Fusarium solani was used as a model organism for studying the mechanisms by which this protein acts as an antifungal agent. Mo-CBP3 significantly inhibited spore germination and mycelial growth at 0.05 mg.mL-1. Mo-CBP3 has both fungistatic and fungicidal effects, depending on the concentration used. Binding of Mo-CBP3 to the fungal cell surface is achieved, at least in part, via electrostatic interactions, as salt was able to reduce its inhibitory effect. Mo-CBP3 induced the production of ROS and caused disorganization of both the cytoplasm and the plasma membrane in F. solani cells. Based on its high stability and specific toxicity, with broad-spectrum efficacy against important phytopathogenic fungi at low inhibitory concentrations but not to human cells, Mo-CBP3 has great potential for the development of new antifungal drugs or transgenic crops with enhanced resistance to phytopathogens.

  6. Functional SNPs of INCENP Affect Semen Quality by Alternative Splicing Mode and Binding Affinity with the Target Bta-miR-378 in Chinese Holstein Bulls.

    Directory of Open Access Journals (Sweden)

    Juan Liu

    Full Text Available Inner centromere protein (INCENP plays an important role in mitosis and meiosis as the main member of chromosomal passenger protein complex (CPC. To investigate the functional markers of the INCENP gene associated with semen quality, the single nucleotide polymorphisms (SNPs g.19970 A>G and g.34078 T>G were identified and analyzed. The new splice variant INCENP-TV is characterized by the deletion of exon 12. The g.19970 A>G in the exonic splicing enhancer (ESE motif region results in an aberrant splice variant by constructing two minigene expression vectors using the pSPL3 exon capturing vector and transfecting vectors into MLTC-1 cells. INCENP-TV was more highly expressed than INCENP-reference in adult bull testes. The g.34078 T>G located in the binding region of bta-miR-378 could affect the expression of INCENP, which was verified by luciferase assay. To analyze comprehensively the correlation of SNPs with sperm quality, haplotype combinations constructed by g.19970 A>G and g.34078 T>G, as well as g.-692 C>T and g.-556 G>T reported in our previous studies, were analyzed. The bulls with H1H12 and H2H2 exhibited a higher ejaculate volume than those with H2H10 and H9H12, respectively (P G and g.34078 T>G in INCENP both of which appear to change the molecular and biological characteristics of the mRNA transcribed from the locus may serve as a biomarkers of male bovine fertility by affecting alternative splicing mode and binding affinity with the target bta-miR-378.

  7. MPC-based energy management with adaptive Markov-chain prediction for a dual-mode hybrid electric vehicle

    Institute of Scientific and Technical Information of China (English)

    XIANG; ChangLe; DING; Feng; WANG; WeiDa; HE; Wei; QI; YunLong

    2017-01-01

    The and energy to management strategy battery is state an important part of a hybrid electrical vehicle design.It is used to improve various fuel economy sustain a proper of charge an by controlling control the power components is while satisfying to constraints and driving demands.However,achieving optimal and performance challenging due the nonlinearities of the hybrid powertrain,conflicting vehicle the time varying constraints,the dilemma capable in which controller control complexity and real-time capability are generally objectives.In this paper,a of real-time cascaded complies strategy is proposed for a dual-mode hybrid electric that considers controller based nonlinearities based the system model and with all time-varying with constraints.sampling The strategy consists of a supervisory controller on a non-linear predictive control short(MPC)sampling a long time with future strategy interval and a coordinating on linear model predictive based control with a time interval to deal different load dynamics of the system.The Additionally,a novel data methodology using adaptive Markov chains to predict demand is introduced.predictive future information is used to improve controller cycles performance.conducted.The The proposed is implemented validity on a real test-bed approach and experimental trials using economy unknown is driving are results other demonstrate the of the proposed and show that fuel significantly improved compared with methods.

  8. MPC-based energy management with adaptive Markov-chain prediction for a dual-mode hybrid electric vehicle

    Institute of Scientific and Technical Information of China (English)

    XIANG ChangLe; DING Feng; WANG WeiDa; HE Wei; QI YunLong

    2017-01-01

    The energy management strategy is an important part of a hybrid electrical vehicle design.It is used to improve fuel economy and to sustain a proper battery state of charge by controlling the power components while satisfying various constraints and driving demands.However,achieving an optimal control performance is challenging due to the nonlinearities of the hybrid powertrain,the time varying constraints,and the dilemma in which controller complexity and real-time capability are generally conflicting objectives.In this paper,a real-time capable cascaded control strategy is proposed for a dual-mode hybrid electric vehicle that considers nonlinearities of the system and complies with all time-varying constraints.The strategy consists of a supervisory controller based on a non-linear model predictive control (MPC) with a long sampling time interval and a coordinating controller based on linear model predictive control with a short sampling time interval to deal with different dynamics of the system.Additionally,a novel data based methodology using adaptive Markov chains to predict future load demand is introduced.The predictive future information is used to improve controller performance.The proposed strategy is implemented on a real test-bed and experimental trials using unknown driving cycles are conducted.The results demonstrate the validity of the proposed approach and show that fuel economy is significantly improved compared with other methods.

  9. Computational immunology meets bioinformatics: the use of prediction tools for molecular binding in the simulation of the immune system.

    Directory of Open Access Journals (Sweden)

    Nicolas Rapin

    Full Text Available We present a new approach to the study of the immune system that combines techniques of systems biology with information provided by data-driven prediction methods. To this end, we have extended an agent-based simulator of the immune response, C-ImmSim, such that it represents pathogens, as well as lymphocytes receptors, by means of their amino acid sequences and makes use of bioinformatics methods for T and B cell epitope prediction. This is a key step for the simulation of the immune response, because it determines immunogenicity. The binding of the epitope, which is the immunogenic part of an invading pathogen, together with activation and cooperation from T helper cells, is required to trigger an immune response in the affected host. To determine a pathogen's epitopes, we use existing prediction methods. In addition, we propose a novel method, which uses Miyazawa and Jernigan protein-protein potential measurements, for assessing molecular binding in the context of immune complexes. We benchmark the resulting model by simulating a classical immunization experiment that reproduces the development of immune memory. We also investigate the role of major histocompatibility complex (MHC haplotype heterozygosity and homozygosity with respect to the influenza virus and show that there is an advantage to heterozygosity. Finally, we investigate the emergence of one or more dominating clones of lymphocytes in the situation of chronic exposure to the same immunogenic molecule and show that high affinity clones proliferate more than any other. These results show that the simulator produces dynamics that are stable and consistent with basic immunological knowledge. We believe that the combination of genomic information and simulation of the dynamics of the immune system, in one single tool, can offer new perspectives for a better understanding of the immune system.

  10. Intrinsic default mode network connectivity predicts spontaneous verbal descriptions of autobiographical memories during social processing

    Directory of Open Access Journals (Sweden)

    Xiao-Fei eYang

    2013-01-01

    Full Text Available Neural systems activated in a coordinated way during rest, known as the default mode network (DMN, also support autobiographical memory (AM retrieval and social processing/mentalizing. However, little is known about how individual variability in reliance on personal memories during social processing relates to individual differences in DMN functioning during rest (intrinsic functional connectivity. Here we examined 18 participants’ spontaneous descriptions of autobiographical memories during a two-hour, private, open-ended interview in which they reacted to a series of true stories about real people’s social situations and responded to the prompt, how does this person’s story make you feel? We classified these descriptions as either containing factual information (semantic AMs or more elaborate descriptions of emotionally meaningful events (episodic AMs. We also collected resting state fMRI scans from the participants and related individual differences in frequency of described AMs to participants’ intrinsic functional connectivity within regions of the DMN. We found that producing more descriptions of either memory type correlated with stronger intrinsic connectivity in the parahippocampal and middle temporal gyri. Additionally, episodic AM descriptions correlated with connectivity in the bilateral hippocampi and medial prefrontal cortex, and semantic memory descriptions correlated with connectivity in right inferior lateral parietal cortex. These findings suggest that in individuals who naturally invoke more memories during social processing, brain regions involved in memory retrieval and self/social processing are more strongly coupled to the DMN during rest.

  11. Failure mode prediction for composite structural insulated panels with MgO board facings

    Science.gov (United States)

    Smakosz, Łukasz; Kreja, Ireneusz

    2018-01-01

    Sandwich panels are readily used in civil engineering due to their high strength to weight ratio and the ease and speed of assembly. The idea of a sandwich section is to combine thin and durable facings with a light-weight core and the choice of materials used allows obtaining the desired behaviour. Panels in consideration consist of MgO (magnesium oxide) board facings and expanded polystyrene core and are characterized by immunity to biological corrosion, a high thermal insulation and a relatively low impact on environment. Customizing the range of panels to meet market needs requires frequent size changes, leading to different failure modes, which are identified in a series of costly full-scale laboratory tests. A nonlinear numerical model was created with a use of a commercial ABAQUS code and a user-defined procedure, which is able to reproduce observed failure mechanisms; its parameters were established on the basis of small-scale tests and numerical experiments. The model was validated by a comparison with the results of the full-scale bending and compression tests. The results obtained were in satisfactory agreement with the test data.

  12. Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling.

    Science.gov (United States)

    Vlot, Anna H C; de Witte, Wilhelmus E A; Danhof, Meindert; van der Graaf, Piet H; van Westen, Gerard J P; de Lange, Elizabeth C M

    2017-12-04

    Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (K D ) and the target dissociation rate constant on target and tissue selectivity. The K D values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ 8 -tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the K D and k off for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal K D value is often not the lowest K D value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.

  13. Serum Mac-2 binding protein glycosylation isomer predicts grade F4 liver fibrosis in patients with biliary atresia.

    Science.gov (United States)

    Yamada, Naoya; Sanada, Yukihiro; Tashiro, Masahisa; Hirata, Yuta; Okada, Noriki; Ihara, Yoshiyuki; Urahashi, Taizen; Mizuta, Koichi

    2017-02-01

    Mac-2 Binding Protein Glycosylation Isomer (M2BPGi) is a novel fibrosis marker. We examined the ability of M2BPGi to predict liver fibrosis in patients with biliary atresia. Sixty-four patients who underwent living donor liver transplantation (LDLT) were included [median age, 1.1 years (range 0.4-16.0), male 16 patients (25.0 %)]. We examined M2BPGi levels in serum obtained the day before LDLT, and we compared the value of the preoperative M2BPGi levels with the histological evaluation of fibrosis using the METAVIR fibrosis score. Subsequently, we assessed the ability of M2BPGi levels to predict fibrosis. The median M2BPGi level in patients with BA was 6.02 (range, 0.36-20.0), and 0, 1, 1, 11, and 51 patients had METAVIR fibrosis scores of F0, F1, F2, F3, and F4, respectively. In patients with F4 fibrosis, the median M2BPGi level was 6.88 (quartile; 5.235, 12.10), significantly higher than that in patients with F3 fibrosis who had a median level of 2.42 (quartile; 1.93, 2.895, p F4 fibrosis. M2BPGi is a novel fibrosis marker for evaluating the status of the liver in patients with BA, especially when predicting grade F4 fibrosis.

  14. An Exploration of the Calcium-Binding Mode of Egg White Peptide, Asp-His-Thr-Lys-Glu, and In Vitro Calcium Absorption Studies of Peptide-Calcium Complex.

    Science.gov (United States)

    Sun, Na; Jin, Ziqi; Li, Dongmei; Yin, Hongjie; Lin, Songyi

    2017-11-08

    The binding mode between the pentapeptide (DHTKE) from egg white hydrolysates and calcium ions was elucidated upon its structural and thermodynamics characteristics. The present study demonstrated that the DHTKE peptide could spontaneously bind calcium with a 1:1 stoichiometry, and that the calcium-binding site corresponded to the carboxyl oxygen, amino nitrogen, and imidazole nitrogen atoms of the DHTKE peptide. Moreover, the effect of the DHTKE-calcium complex on improving the calcium absorption was investigated in vitro using Caco-2 cells. Results showed that the DHTKE-calcium complex could facilitate the calcium influx into the cytosol and further improve calcium absorption across Caco-2 cell monolayers by more than 7 times when compared to calcium-free control. This study facilitates the understanding about the binding mechanism between peptides and calcium ions as well as suggests a potential application of egg white peptides as nutraceuticals to improve calcium absorption.

  15. An Entropy-Based Upper Bound Methodology for Robust Predictive Multi-Mode RCPSP Schedules

    Directory of Open Access Journals (Sweden)

    Angela Hsiang-Ling Chen

    2014-09-01

    Full Text Available Projects are an important part of our activities and regardless of their magnitude, scheduling is at the very core of every project. In an ideal world makespan minimization, which is the most commonly sought objective, would give us an advantage. However, every time we execute a project we have to deal with uncertainty; part of it coming from known sources and part remaining unknown until it affects us. For this reason, it is much more practical to focus on making our schedules robust, capable of handling uncertainty, and even to determine a range in which the project could be completed. In this paper we focus on an approach to determine such a range for the Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP, a widely researched, NP-complete problem, but without adding any subjective considerations to its estimation. We do this by using a concept well known in the domain of thermodynamics, entropy and a three-stage approach. First we use Artificial Bee Colony (ABC—an effective and powerful meta-heuristic—to determine a schedule with minimized makespan which serves as a lower bound. The second stage defines buffer times and creates an upper bound makespan using an entropy function, with the advantage over other methods that it only considers elements which are inherent to the schedule itself and does not introduce any subjectivity to the buffer time generation. In the last stage, we use the ABC algorithm with an objective function that seeks to maximize robustness while staying within the makespan boundaries defined previously and in some cases even below the lower boundary. We evaluate our approach with two different benchmarks sets: when using the PSPLIB for the MRCPSP benchmark set, the computational results indicate that it is possible to generate robust schedules which generally result in an increase of less than 10% of the best known solutions while increasing the robustness in at least 20% for practically every

  16. Mannose binding lectin (MBL levels predict lung function decline in severe asthma

    Directory of Open Access Journals (Sweden)

    Ilonka. H. van Veen

    2006-12-01

    Full Text Available There is increasing evidence that activation of the complement system in asthma contributes to ongoing inflammation, tissue damage and airway remodeling. Mannose binding lectin (MBL is a pattern recognition molecule that serves as the key mediator of the lectin pathway of complement activation. MBL levels are genetically determined and vary widely amongst individuals. In the present study we hypothesized that high MBL levels in asthma are associated with increased loss of lung function over time, as a consequence of inflammatory tissue damage. We measured serum MBL levels by ELISA in 68 patients with severe asthma and prospectively determined the change in post-bronchodilator (pb FEV1 over a mean period of 5.7 years. The relationship between MBL and change in pbFEV1 (FEV1 was analysed using (multiple regression analysis and corrected for possible confounders (age, sex, age of onset, asthma duration, and pbFEV1. The median (range MBL level was 332 (10.8-3587 ng·ml–1. MBL was significantly associated with FEV1 (p<0.04. Patients with a high MBL level (332 ng·ml–1 had an increased risk of lung function decline compared to those with low MBL levels (OR (CI: 3.16 (1.14-8.79, p = 0.027; the excess decline being 42 ml·yr–1 (p = 0.01. We conclude that a high MBL level is associated with an increased decline in lung function in patients with severe asthma. MBL might provide a clue towards better understanding of the pathophysiology of ongoing inflammation and subsequent decline in lung function of patients with severe asthma.

  17. RBscore&NBench: a high-level web server for nucleic acid binding residues prediction with a large-scale benchmarking database.

    Science.gov (United States)

    Miao, Zhichao; Westhof, Eric

    2016-07-08

    RBscore&NBench combines a web server, RBscore and a database, NBench. RBscore predicts RNA-/DNA-binding residues in proteins and visualizes the prediction scores and features on protein structures. The scoring scheme of RBscore directly links feature values to nucleic acid binding probabilities and illustrates the nucleic acid binding energy funnel on the protein surface. To avoid dataset, binding site definition and assessment metric biases, we compared RBscore with 18 web servers and 3 stand-alone programs on 41 datasets, which demonstrated the high and stable accuracy of RBscore. A comprehensive comparison led us to develop a benchmark database named NBench. The web server is available on: http://ahsoka.u-strasbg.fr/rbscorenbench/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. Computational Immunology Meets Bioinformatics: The Use of Prediction Tools for Molecular Binding in the Simulation of the Immune System

    DEFF Research Database (Denmark)

    Rapin, N.; Lund, Ole; Bernaschi, M.

    2010-01-01

    potential measurements, for assessing molecular binding in the context of immune complexes. We benchmark the resulting model by simulating a classical immunization experiment that reproduces the development of immune memory. We also investigate the role of major histocompatibility complex (MHC) haplotype...... proliferate more than any other. These results show that the simulator produces dynamics that are stable and consistent with basic immunological knowledge. We believe that the combination of genomic information and simulation of the dynamics of the immune system, in one single tool, can offer new perspectives......We present a new approach to the study of the immune system that combines techniques of systems biology with information provided by data-driven prediction methods. To this end, we have extended an agent-based simulator of the immune response, C-IMMSIM, such that it represents pathogens, as well...

  19. NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data

    DEFF Research Database (Denmark)

    Jurtz, Vanessa Isabell; Paul, Sinu; Andreatta, Massimo

    2017-01-01

    by mass spectrometry have been reported containing information about peptide-processing steps in the presentation pathway and the length distribution of naturally presented peptides. In this article, we present NetMHCpan-4.0, a method trained on binding affinity and eluted ligand data leveraging......Cytotoxic T cells are of central importance in the immune system's response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC class I molecules. Peptide binding to MHC molecules is the single most selective step in the Ag-presentation pathway....... Therefore, in the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has attracted widespread attention. In the past, predictors of peptide-MHC interactions have primarily been trained on binding affinity data. Recently, an increasing number of MHC-presented peptides identified...

  20. Modeling and sliding mode predictive control of the ultra-supercritical boiler-turbine system with uncertainties and input constraints.

    Science.gov (United States)

    Tian, Zhen; Yuan, Jingqi; Zhang, Xiang; Kong, Lei; Wang, Jingcheng

    2018-05-01

    The coordinated control system (CCS) serves as an important role in load regulation, efficiency optimization and pollutant reduction for coal-fired power plants. The CCS faces with tough challenges, such as the wide-range load variation, various uncertainties and constraints. This paper aims to improve the load tacking ability and robustness for boiler-turbine units under wide-range operation. To capture the key dynamics of the ultra-supercritical boiler-turbine system, a nonlinear control-oriented model is developed based on mechanism analysis and model reduction techniques, which is validated with the history operation data of a real 1000 MW unit. To simultaneously address the issues of uncertainties and input constraints, a discrete-time sliding mode predictive controller (SMPC) is designed with the dual-mode control law. Moreover, the input-to-state stability and robustness of the closed-loop system are proved. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves good tracking performance, disturbance rejection ability and compatibility to input constraints. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Accelerating early anti-tuberculosis drug discovery by creating mycobacterial indicator strains that predict mode of action

    KAUST Repository

    Boot, Maikel

    2018-04-13

    Due to the rise of drug resistant forms of tuberculosis there is an urgent need for novel antibiotics to effectively combat these cases and shorten treatment regimens. Recently, drug screens using whole cell analyses have been shown to be successful. However, current high-throughput screens focus mostly on stricto sensu life-death screening that give little qualitative information. In doing so, promising compound scaffolds or non-optimized compounds that fail to reach inhibitory concentrations are missed. To accelerate early TB drug discovery, we performed RNA sequencing on Mycobacterium tuberculosis and Mycobacterium marinum to map the stress responses that follow upon exposure to sub-inhibitory concentrations of antibiotics with known targets: ciprofloxacin, ethambutol, isoniazid, streptomycin and rifampicin. The resulting dataset comprises the first overview of transcriptional stress responses of mycobacteria to different antibiotics. We show that antibiotics can be distinguished based on their specific transcriptional stress fingerprint. Notably, this fingerprint was more distinctive in M. marinum. We decided to use this to our advantage and continue with this model organism. A selection of diverse antibiotic stress genes was used to construct stress reporters. In total, three functional reporters were constructed to respond to DNA damage, cell wall damage and ribosomal inhibition. Subsequently, these reporter strains were used to screen a small anti-TB compound library to predict the mode of action. In doing so, we could identify the putative mode of action for three novel compounds, which confirms our approach.

  2. A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Bangzhu Zhu

    2012-02-01

    Full Text Available Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble forecasting model integrating empirical mode decomposition (EMD, genetic algorithm (GA and artificial neural network (ANN is proposed to forecast carbon price. Firstly, the proposed model uses EMD to decompose carbon price data into several intrinsic mode functions (IMFs and one residue. Then, the IMFs and residue are composed into a high frequency component, a low frequency component and a trend component which have similar frequency characteristics, simple components and strong regularity using the fine-to-coarse reconstruction algorithm. Finally, those three components are predicted using an ANN trained by GA, i.e., a GAANN model, and the final forecasting results can be obtained by the sum of these three forecasting results. For verification and testing, two main carbon future prices with different maturity in the European Climate Exchange (ECX are used to test the effectiveness of the proposed multiscale ensemble forecasting model. Empirical results obtained demonstrate that the proposed multiscale ensemble forecasting model can outperform the single random walk (RW, ARIMA, ANN and GAANN models without EMD preprocessing and the ensemble ARIMA model with EMD preprocessing.

  3. Microstructure-based constitutive modeling of TRIP steel: Prediction of ductility and failure modes under different loading conditions

    International Nuclear Information System (INIS)

    Choi, K.S.; Liu, W.N.; Sun, X.; Khaleel, M.A.

    2009-01-01

    We study the ultimate ductility and failure modes of a commercial transformation-induced plasticity (TRIP) 800 steel under different loading conditions with an advanced microstructure-based finite-element analysis. The representative volume element (RVE) for the TRIP 800 under examination is developed based on an actual microstructure obtained from scanning electron microscopy. The ductile failure of the TRIP 800 under different loading conditions is predicted in the form of plastic strain localization without any prescribed failure criteria for the individual phases. This indicates that the microstructure-level inhomogeneity of the various constituent phases can be the key factor influencing the final ductility of the TRIP 800 steel under different loading conditions. Comparisons of the computational results with experimental measurements suggest that the microstructure-based modeling approach accurately captures the overall macroscopic behavior of the TRIP 800 steel under different loading and boundary conditions.

  4. NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets

    DEFF Research Database (Denmark)

    Nielsen, Morten; Andreatta, Massimo

    2016-01-01

    Background: Binding of peptides to MHC class I molecules (MHC-I) is essential for antigen presentation to cytotoxic T-cells.Results: Here, we demonstrate how a simple alignment step allowing insertions and deletions in a pan-specific MHC-I binding machine-learning model enables combining informat...... specificities and ligand length scales, and demonstrated how this approach significantly improves the accuracy for prediction of peptide binding and identification of MHC ligands. The method is available at www.cbs.dtu.dk/services/NetMHCpan-3.0....

  5. Penicillin-Binding Protein Transpeptidase Signatures for Tracking and Predicting β-Lactam Resistance Levels in Streptococcus pneumoniae

    Directory of Open Access Journals (Sweden)

    Yuan Li

    2016-06-01

    Full Text Available β-Lactam antibiotics are the drugs of choice to treat pneumococcal infections. The spread of β-lactam-resistant pneumococci is a major concern in choosing an effective therapy for patients. Systematically tracking β-lactam resistance could benefit disease surveillance. Here we developed a classification system in which a pneumococcal isolate is assigned to a “PBP type” based on sequence signatures in the transpeptidase domains (TPDs of the three critical penicillin-binding proteins (PBPs, PBP1a, PBP2b, and PBP2x. We identified 307 unique PBP types from 2,528 invasive pneumococcal isolates, which had known MICs to six β-lactams based on broth microdilution. We found that increased β-lactam MICs strongly correlated with PBP types containing divergent TPD sequences. The PBP type explained 94 to 99% of variation in MICs both before and after accounting for genomic backgrounds defined by multilocus sequence typing, indicating that genomic backgrounds made little independent contribution to β-lactam MICs at the population level. We further developed and evaluated predictive models of MICs based on PBP type. Compared to microdilution MICs, MICs predicted by PBP type showed essential agreement (MICs agree within 1 dilution of >98%, category agreement (interpretive results agree of >94%, a major discrepancy (sensitive isolate predicted as resistant rate of <3%, and a very major discrepancy (resistant isolate predicted as sensitive rate of <2% for all six β-lactams. Thus, the PBP transpeptidase signatures are robust indicators of MICs to different β-lactam antibiotics in clinical pneumococcal isolates and serve as an accurate alternative to phenotypic susceptibility testing.

  6. Crystal structure of the thioesterification conformation of Bacillus subtilis o-succinylbenzoyl-CoA synthetase reveals a distinct substrate-binding mode.

    Science.gov (United States)

    Chen, Yaozong; Li, Tin Lok; Lin, Xingbang; Li, Xin; Li, Xiang David; Guo, Zhihong

    2017-07-21

    o -Succinylbenzoyl-CoA (OSB-CoA) synthetase (MenE) is an essential enzyme in bacterial vitamin K biosynthesis and an important target in the development of new antibiotics. It is a member of the adenylating enzymes (ANL) family, which reconfigure their active site in two different active conformations, one for the adenylation half-reaction and the other for a thioesterification half-reaction, in a domain-alternation catalytic mechanism. Although several aspects of the adenylating mechanism in MenE have recently been uncovered, its thioesterification conformation remains elusive. Here, using a catalytically competent Bacillus subtilis mutant protein complexed with an OSB-CoA analogue, we determined MenE high-resolution structures to 1.76 and 1.90 Å resolution in a thioester-forming conformation. By comparison with the adenylation conformation, we found that MenE's C-domain rotates around the Ser-384 hinge by 139.5° during domain-alternation catalysis. The structures also revealed a thioesterification active site specifically conserved among MenE orthologues and a substrate-binding mode distinct from those of many other acyl/aryl-CoA synthetases. Of note, using site-directed mutagenesis, we identified several residues that specifically contribute to the thioesterification half-reaction without affecting the adenylation half-reaction. Moreover, we observed a substantial movement of the activated succinyl group in the thioesterification half-reaction. These findings provide new insights into the domain-alternation catalysis of a bacterial enzyme essential for vitamin K biosynthesis and of its adenylating homologues in the ANL enzyme family. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  7. Protein-DNA binding dynamics predict transcriptional response to nutrients in archaea.

    Science.gov (United States)

    Todor, Horia; Sharma, Kriti; Pittman, Adrianne M C; Schmid, Amy K

    2013-10-01

    Organisms across all three domains of life use gene regulatory networks (GRNs) to integrate varied stimuli into coherent transcriptional responses to environmental pressures. However, inferring GRN topology and regulatory causality remains a central challenge in systems biology. Previous work characterized TrmB as a global metabolic transcription factor in archaeal extremophiles. However, it remains unclear how TrmB dynamically regulates its ∼100 metabolic enzyme-coding gene targets. Using a dynamic perturbation approach, we elucidate the topology of the TrmB metabolic GRN in the model archaeon Halobacterium salinarum. Clustering of dynamic gene expression patterns reveals that TrmB functions alone to regulate central metabolic enzyme-coding genes but cooperates with various regulators to control peripheral metabolic pathways. Using a dynamical model, we predict gene expression patterns for some TrmB-dependent promoters and infer secondary regulators for others. Our data suggest feed-forward gene regulatory topology for cobalamin biosynthesis. In contrast, purine biosynthesis appears to require TrmB-independent regulators. We conclude that TrmB is an important component for mediating metabolic modularity, integrating nutrient status and regulating gene expression dynamics alone and in concert with secondary regulators.

  8. Direct model-based predictive control scheme without cost function for voltage source inverters with reduced common-mode voltage

    Science.gov (United States)

    Kim, Jae-Chang; Moon, Sung-Ki; Kwak, Sangshin

    2018-04-01

    This paper presents a direct model-based predictive control scheme for voltage source inverters (VSIs) with reduced common-mode voltages (CMVs). The developed method directly finds optimal vectors without using repetitive calculation of a cost function. To adjust output currents with the CMVs in the range of -Vdc/6 to +Vdc/6, the developed method uses voltage vectors, as finite control resources, excluding zero voltage vectors which produce the CMVs in the VSI within ±Vdc/2. In a model-based predictive control (MPC), not using zero voltage vectors increases the output current ripples and the current errors. To alleviate these problems, the developed method uses two non-zero voltage vectors in one sampling step. In addition, the voltage vectors scheduled to be used are directly selected at every sampling step once the developed method calculates the future reference voltage vector, saving the efforts of repeatedly calculating the cost function. And the two non-zero voltage vectors are optimally allocated to make the output current approach the reference current as close as possible. Thus, low CMV, rapid current-following capability and sufficient output current ripple performance are attained by the developed method. The results of a simulation and an experiment verify the effectiveness of the developed method.

  9. A novel transcriptomics based in vitro method to compare and predict hepatotoxicity based on mode of action

    International Nuclear Information System (INIS)

    De Abrew, K. Nadira; Overmann, Gary J.; Adams, Rachel L.; Tiesman, Jay P.; Dunavent, John; Shan, Yuqing K.; Carr, Gregory J.; Daston, George P.; Naciff, Jorge M.

    2015-01-01

    High-content data have the potential to inform mechanism of action for toxicants. However, most data to support this notion have been generated in vivo. Because many cell lines and primary cells maintain a differentiated cell phenotype, it is possible that cells grown in culture may also be useful in predictive toxicology via high-content approaches such as whole-genome microarray. We evaluated global changes in gene expression in primary rat hepatocytes exposed to two concentrations of ten hepatotoxicants: acetaminophen (APAP), β-naphthoflavone (BNF), chlorpromazine (CPZ), clofibrate (CLO), bis(2-ethylhexyl)phthalate (DEHP), diisononyl phthalate (DINP), methapyrilene (MP), valproic acid (VPA), phenobarbital (PB) and WY14643 at two separate time points. These compounds were selected to cover a range of mechanisms of toxicity, with some overlap in expected mechanism to address the question of how predictive gene expression analysis is, for a given mode of action. Gene expression microarray analysis was performed on cells after 24 h and 48 h of exposure to each chemical using Affymetrix microarrays. Cluster analysis suggests that the primary hepatocyte model was capable of responding to these hepatotoxicants, with changes in gene expression that appear to be mode of action-specific. Among the different methods used for analysis of the data, a combination method that used pathways (MOAs) to filter total probesets provided the most robust analysis. The analysis resulted in the phthalates clustering closely together, with the two other peroxisome proliferators, CLO and WY14643, eliciting similar responses at the whole-genome and pathway levels. The Cyp inducers PB, MP, CPZ and BNF also clustered together. VPA and APAP had profiles that were unique. A similar analysis was performed on externally available (TG-GATES) in vivo data for 6 of the chemicals (APAP, CLO, CPZ, MP, MP and WY14643) and compared to the in vitro result. These results indicate that transcription

  10. Mutational analysis of the extracellular disulphide bridges of the atypical chemokine receptor ACKR3/CXCR7 uncovers multiple binding and activation modes for its chemokine and endogenous non-chemokine agonists.

    Science.gov (United States)

    Szpakowska, Martyna; Meyrath, Max; Reynders, Nathan; Counson, Manuel; Hanson, Julien; Steyaert, Jan; Chevigné, Andy

    2018-07-01

    The atypical chemokine receptor ACKR3/CXCR7 plays crucial roles in numerous physiological processes but also in viral infection and cancer. ACKR3 shows strong propensity for activation and, unlike classical chemokine receptors, can respond to chemokines from both the CXC and CC families as well as to the endogenous peptides BAM22 and adrenomedullin. Moreover, despite belonging to the G protein coupled receptor family, its function appears to be mainly dependent on β-arrestin. ACKR3 has also been shown to continuously cycle between the plasma membrane and the endosomal compartments, suggesting a possible role as a scavenging receptor. So far, the molecular basis accounting for these atypical binding and signalling properties remains elusive. Noteworthy, ACKR3 extracellular domains bear three disulphide bridges. Two of them lie on top of the two main binding subpockets and are conserved among chemokine receptors, and one, specific to ACKR3, forms an intra-N terminus four-residue-loop of so far unknown function. Here, by mutational and functional studies, we examined the impact of the different disulphide bridges for ACKR3 folding, ligand binding and activation. We showed that, in contrast to most classical chemokine receptors, none of the extracellular disulphide bridges was essential for ACKR3 function. However, the disruption of the unique ACKR3 N-terminal loop drastically reduced the binding of CC chemokines whereas it only had a mild impact on CXC chemokine binding. Mutagenesis also uncovered that chemokine and endogenous non-chemokine ligands interact and activate ACKR3 according to distinct binding modes characterized by different transmembrane domain subpocket occupancy and N-terminal loop contribution, with BAM22 mimicking the binding mode of CC chemokine N terminus. Copyright © 2018 Elsevier Inc. All rights reserved.

  11. Improved pan-specific MHC class I peptide-binding predictions using a novel representation of the MHC-binding cleft environment

    DEFF Research Database (Denmark)

    Carrasco Pro, S.; Zimic, M.; Nielsen, Morten

    2014-01-01

    of the current state-of-the-art methods for MHC class I is NetMHCpan, which has a core ingredient for the representation of the MHC class I molecule using a pseudo-sequence representation of the binding cleft amino acid environment. New and large MHC-peptide-binding data sets are constantly being made available...... of different MHC data sets including human leukocyte antigen (HLA), non-human primates (chimpanzee, macaque and gorilla) and other animal alleles (cattle, mouse and swine). From these constructs, we showed that by focusing on MHC sequence positions found to be polymorphic across the MHC molecules used to train...

  12. Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties

    Science.gov (United States)

    2011-01-01

    Background Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. Results This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m=22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m=28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der

  13. A Study of Subseasonal Predictability of the Atmospheric Circulation Low-frequency Modes based on SL-AV forecasts

    Science.gov (United States)

    Kruglova, Ekaterina; Kulikova, Irina; Khan, Valentina; Tischenko, Vladimir

    2017-04-01

    The subseasonal predictability of low-frequency modes and the atmospheric circulation regimes is investigated based on the using of outputs from global Semi-Lagrangian (SL-AV) model of the Hydrometcentre of Russia and Institute of Numerical Mathematics of Russian Academy of Science. Teleconnection indices (AO, WA, EA, NAO, EU, WP, PNA) are used as the quantitative characteristics of low-frequency variability to identify zonal and meridional flow regimes with focus on control distribution of high impact weather patterns in the Northern Eurasia. The predictability of weekly and monthly averaged indices is estimated by the methods of diagnostic verification of forecast and reanalysis data covering the hindcast period, and also with the use of the recommended WMO quantitative criteria. Characteristics of the low frequency variability have been discussed. Particularly, it is revealed that the meridional flow regimes are reproduced by SL-AV for summer season better comparing to winter period. It is shown that the model's deterministic forecast (ensemble mean) skill at week 1 (days 1-7) is noticeably better than that of climatic forecasts. The decrease of skill scores at week 2 (days 8-14) and week 3( days 15-21) is explained by deficiencies in the modeling system and inaccurate initial conditions. It was noticed the slightly improvement of the skill of model at week 4 (days 22-28), when the condition of atmosphere is more determined by the flow of energy from the outside. The reliability of forecasts of monthly (days 1-30) averaged indices is comparable to that at week 1 (days 1-7). Numerical experiments demonstrated that the forecast accuracy can be improved (thus the limit of practical predictability can be extended) through the using of probabilistic approach based on ensemble forecasts. It is shown that the quality of forecasts of the regimes of circulation like blocking is higher, than that of zonal flow.

  14. Default mode network deactivation to smoking cue relative to food cue predicts treatment outcome in nicotine use disorder.

    Science.gov (United States)

    Wilcox, Claire E; Claus, Eric D; Calhoun, Vince D; Rachakonda, Srinivas; Littlewood, Rae A; Mickey, Jessica; Arenella, Pamela B; Goodreau, Natalie; Hutchison, Kent E

    2018-01-01

    Identifying predictors of treatment outcome for nicotine use disorders (NUDs) may help improve efficacy of established treatments, like varenicline. Brain reactivity to drug stimuli predicts relapse risk in nicotine and other substance use disorders in some studies. Activity in the default mode network (DMN) is affected by drug cues and other palatable cues, but its clinical significance is unclear. In this study, 143 individuals with NUD (male n = 91, ages 18-55 years) received a functional magnetic resonance imaging scan during a visual cue task during which they were presented with a series of smoking-related or food-related video clips prior to randomization to treatment with varenicline (n = 80) or placebo. Group independent components analysis was utilized to isolate the DMN, and temporal sorting was used to calculate the difference between the DMN blood-oxygen-level dependent signal during smoke cues and that during food cues for each individual. Food cues were associated with greater deactivation compared with smoke cues in the DMN. In correcting for baseline smoking and other clinical variables, which have been shown to be related to treatment outcome in previous work, a less positive Smoke - Food difference score predicted greater smoking at 6 and 12 weeks when both treatment groups were combined (P = 0.005, β = -0.766). An exploratory analysis of executive control and salience networks demonstrated that a more positive Smoke - Food difference score for executive control network predicted a more robust response to varenicline relative to placebo. These findings provide further support to theories that brain reactivity to palatable cues, and in particular in DMN, may have a direct clinical relevance in NUD. © 2017 Society for the Study of Addiction.

  15. Sex hormone binding globulin - an important biomarker for predicting PCOS risk: A systematic review and meta-analysis.

    Science.gov (United States)

    Deswal, Ritu; Yadav, Arun; Dang, Amita Suneja

    2018-02-01

    Sex hormone-binding globulin (SHBG) is a glycoprotein which regulates bioavailability of sex steroid hormones. Interest in SHBG has escalated in recent years because of its inverse association with polycystic ovary syndrome (PCOS), obesity, insulin resistance, metabolic syndrome, and diabetes type II. This meta-analysis was performed to examine the associations of SHBG with PCOS and to correlate serum SHBG levels with various PCOS associated endocrine and metabolic dysregulation as well as to determine the effects of various therapeutic agents on serum SHBG levels in PCOS patients in order to assess the true accuracy of SHBG in the prediction of PCOS. A literature search was performed using Pub-Med, Science direct, google scholar, EMBASE, and Cochrane library. A total of 675 relevant records were identified, of which 62 articles were included. Meta-analysis using a random-effects model was performed using STATA version 13 to calculate standardized mean difference (SMD) with 95% confidence intervals (95 % CIs). SHBG levels in controls were significantly higher than that of PCOS patients (SMD= -0.83, 95%CI = -1.01, -0.64), with significant heterogeneity across studies (I 2 = 93.9% and p=0.000). Our results suggest that the lower serum SHBG levels are associated with the risk of PCOS. SHBG may also play an important role in various metabolic disturbances in PCOS patients. Therapeutic interventions improved SHBG levels in PCOS women which further reduced PCOS associated complications. Therefore, SHBG levels may prove to be a useful biomarker for the diagnosis and treatment of PCOS. Systematic review registration: PROSPERO CRD42017057972 Abbreviations: PCOS: polycystic ovary syndrome; SHBG: sex hormone-binding globulin.

  16. How to deal with multiple binding poses in alchemical relative protein-ligand binding free energy calculations.

    Science.gov (United States)

    Kaus, Joseph W; Harder, Edward; Lin, Teng; Abel, Robert; McCammon, J Andrew; Wang, Lingle

    2015-06-09

    Recent advances in improved force fields and sampling methods have made it possible for the accurate calculation of protein–ligand binding free energies. Alchemical free energy perturbation (FEP) using an explicit solvent model is one of the most rigorous methods to calculate relative binding free energies. However, for cases where there are high energy barriers separating the relevant conformations that are important for ligand binding, the calculated free energy may depend on the initial conformation used in the simulation due to the lack of complete sampling of all the important regions in phase space. This is particularly true for ligands with multiple possible binding modes separated by high energy barriers, making it difficult to sample all relevant binding modes even with modern enhanced sampling methods. In this paper, we apply a previously developed method that provides a corrected binding free energy for ligands with multiple binding modes by combining the free energy results from multiple alchemical FEP calculations starting from all enumerated poses, and the results are compared with Glide docking and MM-GBSA calculations. From these calculations, the dominant ligand binding mode can also be predicted. We apply this method to a series of ligands that bind to c-Jun N-terminal kinase-1 (JNK1) and obtain improved free energy results. The dominant ligand binding modes predicted by this method agree with the available crystallography, while both Glide docking and MM-GBSA calculations incorrectly predict the binding modes for some ligands. The method also helps separate the force field error from the ligand sampling error, such that deviations in the predicted binding free energy from the experimental values likely indicate possible inaccuracies in the force field. An error in the force field for a subset of the ligands studied was identified using this method, and improved free energy results were obtained by correcting the partial charges assigned to the

  17. How To Deal with Multiple Binding Poses in Alchemical Relative Protein–Ligand Binding Free Energy Calculations

    Science.gov (United States)

    2016-01-01

    Recent advances in improved force fields and sampling methods have made it possible for the accurate calculation of protein–ligand binding free energies. Alchemical free energy perturbation (FEP) using an explicit solvent model is one of the most rigorous methods to calculate relative binding free energies. However, for cases where there are high energy barriers separating the relevant conformations that are important for ligand binding, the calculated free energy may depend on the initial conformation used in the simulation due to the lack of complete sampling of all the important regions in phase space. This is particularly true for ligands with multiple possible binding modes separated by high energy barriers, making it difficult to sample all relevant binding modes even with modern enhanced sampling methods. In this paper, we apply a previously developed method that provides a corrected binding free energy for ligands with multiple binding modes by combining the free energy results from multiple alchemical FEP calculations starting from all enumerated poses, and the results are compared with Glide docking and MM-GBSA calculations. From these calculations, the dominant ligand binding mode can also be predicted. We apply this method to a series of ligands that bind to c-Jun N-terminal kinase-1 (JNK1) and obtain improved free energy results. The dominant ligand binding modes predicted by this method agree with the available crystallography, while both Glide docking and MM-GBSA calculations incorrectly predict the binding modes for some ligands. The method also helps separate the force field error from the ligand sampling error, such that deviations in the predicted binding free energy from the experimental values likely indicate possible inaccuracies in the force field. An error in the force field for a subset of the ligands studied was identified using this method, and improved free energy results were obtained by correcting the partial charges assigned to the

  18. Predictions on the modes of decay of odd Z superheavy isotopes within the range 105 ≤ Z ≤ 135

    Science.gov (United States)

    Santhosh, K. P.; Nithya, C.

    2018-05-01

    The decay modes of 1051 odd Z superheavy nuclei within the range 105 ≤ Z ≤ 135, and their daughter nuclei are studied by comparing the alpha decay half-lives with the spontaneous fission half-lives. The alpha decay half-lives are calculated using the Coulomb and proximity potential model for deformed nuclei (CPPMDN) proposed by Santhosh et al. (2011) and the spontaneous fission half-lives are obtained with the shell-effect dependent formula of Santhosh et al. (Santhosh and Nithya, 2016). For a theoretical comparison, the alpha decay half-lives are also computed with the Coulomb and proximity potential model (CPPM), Viola-Seaborg-Sobiczewski semi-empirical relation (VSS), Universal curve of Poenaru et al. (UNIV), the analytical formula of Royer, and the Universal decay law of Qi et al. (UDL). The predicted decay modes and half-lives were compared with the available experimental results. The proton and neutron separation energies are calculated to identify those nuclei, which decay through proton and neutron emission. From the entire study of odd Z superheavy elements, it is seen that among 1051 nuclei, 233 nuclei exhibit proton emission and 18 nuclei exhibit neutron emission. 56 nuclei are stable against alpha decay with negative Q value for the decay. 92 nuclei show alpha decay followed by spontaneous fission and 9 nuclei show alpha decay followed by proton emission. 39 nuclei decay through full alpha chain and 595 nuclei decay through spontaneous fission. We hope that the study will be very useful for the future experimental investigations in this field.

  19. NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lund, Ole

    2009-01-01

    this binding event. RESULTS: Here, we present a novel artificial neural network-based method, NN-align that allows for simultaneous identification of the MHC class II binding core and binding affinity. NN-align is trained using a novel training algorithm that allows for correction of bias in the training data...

  20. AutoSite: an automated approach for pseudo-ligands prediction—from ligand-binding sites identification to predicting key ligand atoms

    Science.gov (United States)

    Ravindranath, Pradeep Anand; Sanner, Michel F.

    2016-01-01

    Motivation: The identification of ligand-binding sites from a protein structure facilitates computational drug design and optimization, and protein function assignment. We introduce AutoSite: an efficient software tool for identifying ligand-binding sites and predicting pseudo ligand corresponding to each binding site identified. Binding sites are reported as clusters of 3D points called fills in which every point is labelled as hydrophobic or as hydrogen bond donor or acceptor. From these fills AutoSite derives feature points: a set of putative positions of hydrophobic-, and hydrogen-bond forming ligand atoms. Results: We show that AutoSite identifies ligand-binding sites with higher accuracy than other leading methods, and produces fills that better matches the ligand shape and properties, than the fills obtained with a software program with similar capabilities, AutoLigand. In addition, we demonstrate that for the Astex Diverse Set, the feature points identify 79% of hydrophobic ligand atoms, and 81% and 62% of the hydrogen acceptor and donor hydrogen ligand atoms interacting with the receptor, and predict 81.2% of water molecules mediating interactions between ligand and receptor. Finally, we illustrate potential uses of the predicted feature points in the context of lead optimization in drug discovery projects. Availability and Implementation: http://adfr.scripps.edu/AutoDockFR/autosite.html Contact: sanner@scripps.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27354702

  1. A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors

    Energy Technology Data Exchange (ETDEWEB)

    Carriger, John F. [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States); Martin, Todd M. [U.S. Environmental Protection Agency, Office of Research and Development, Sustainable Technology Division, Cincinnati, OH, 45220 (United States); Barron, Mace G., E-mail: barron.mace@epa.gov [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States)

    2016-11-15

    Highlights: • A Bayesian network was developed to classify chemical mode of action (MoA). • The network was based on the aquatic toxicity MoA for over 1000 chemicals. • A Markov blanket algorithm selected a subset of theoretical molecular descriptors. • Sensitivity analyses found influential descriptors for classifying the MoAs. • Overall precision of the Bayesian MoA classification model was 80%. - Abstract: The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool. The model was developed through augmented Markov blanket discovery from the dataset of 1098 chemicals with the MoA broad classifications as a target node. From cross validation, the overall precision for the model was 80.2%. The best precision was for the AChEI MoA (93.5%) where 257 chemicals out of 275 were correctly classified. Model precision was poorest for the reactivity MoA (48.5%) where 48 out of 99 reactive chemicals were correctly classified. Narcosis represented the largest class within the MoA dataset and had a precision and reliability of 80.0%, reflecting the global precision across all of the MoAs. False negatives for narcosis most often fell into electron transport inhibition, neurotoxicity or reactivity MoAs. False negatives for all other MoAs were most often narcosis. A probabilistic sensitivity analysis was undertaken for each MoA to examine the sensitivity to individual and multiple descriptor findings. The results show that the Markov blanket of a structurally complex dataset can simplify analysis and interpretation by

  2. Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

    Science.gov (United States)

    Grudinin, Sergei; Kadukova, Maria; Eisenbarth, Andreas; Marillet, Simon; Cazals, Frédéric

    2016-09-01

    The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.

  3. Oligosaccharide binding to barley alpha-amylase 1

    DEFF Research Database (Denmark)

    Robert, X.; Haser, R.; Mori, H.

    2005-01-01

    Enzymatic subsite mapping earlier predicted 10 binding subsites in the active site substrate binding cleft of barley alpha-amylase isozymes. The three-dimensional structures of the oligosaccharide complexes with barley alpha-amylase isozyme 1 (AMY1) described here give for the first time a thorough...... in barley alpha-amylase isozyme 2 (AMY2), and the sugar binding modes are compared between the two isozymes. The "sugar tongs" surface binding site discovered in the AMY1-thio-DP4 complex is confirmed in the present work. A site that putatively serves as an entrance for the substrate to the active site...

  4. The timing of associative memory formation: frontal lobe and anterior medial temporal lobe activity at associative binding predicts memory

    Science.gov (United States)

    Hales, J. B.

    2011-01-01

    The process of associating items encountered over time and across variable time delays is fundamental for creating memories in daily life, such as for stories and episodes. Forming associative memory for temporally discontiguous items involves medial temporal lobe structures and additional neocortical processing regions, including prefrontal cortex, parietal lobe, and lateral occipital regions. However, most prior memory studies, using concurrently presented stimuli, have failed to examine the temporal aspect of successful associative memory formation to identify when activity in these brain regions is predictive of associative memory formation. In the current study, functional MRI data were acquired while subjects were shown pairs of sequentially presented visual images with a fixed interitem delay within pairs. This design allowed the entire time course of the trial to be analyzed, starting from onset of the first item, across the 5.5-s delay period, and through offset of the second item. Subjects then completed a postscan recognition test for the items and associations they encoded during the scan and their confidence for each. After controlling for item-memory strength, we isolated brain regions selectively involved in associative encoding. Consistent with prior findings, increased regional activity predicting subsequent associative memory success was found in anterior medial temporal lobe regions of left perirhinal and entorhinal cortices and in left prefrontal cortex and lateral occipital regions. The temporal separation within each pair, however, allowed extension of these findings by isolating the timing of regional involvement, showing that increased response in these regions occurs during binding but not during maintenance. PMID:21248058

  5. Validation of the Predicted Circumferential and Radial Mode Sound Power Levels in the Inlet and Exhaust Ducts of a Fan Ingesting Distorted Inflow

    Science.gov (United States)

    Koch, L. Danielle

    2012-01-01

    Fan inflow distortion tone noise has been studied computationally and experimentally. Data from two experiments in the NASA Glenn Advanced Noise Control Fan rig have been used to validate acoustic predictions. The inflow to the fan was distorted by cylindrical rods inserted radially into the inlet duct one rotor chord length upstream of the fan. The rods were arranged in both symmetric and asymmetric circumferential patterns. In-duct and farfield sound pressure level measurements were recorded. It was discovered that for positive circumferential modes, measured circumferential mode sound power levels in the exhaust duct were greater than those in the inlet duct and for negative circumferential modes, measured total circumferential mode sound power levels in the exhaust were less than those in the inlet. Predicted trends in overall sound power level were proven to be useful in identifying circumferentially asymmetric distortion patterns that reduce overall inlet distortion tone noise, as compared to symmetric arrangements of rods. Detailed comparisons between the measured and predicted radial mode sound power in the inlet and exhaust duct indicate limitations of the theory.

  6. Shielding Characteristics Using an Ultrasonic Configurable Fan Artificial Noise Source to Generate Modes - Experimental Measurements and Analytical Predictions

    Science.gov (United States)

    Sutliff, Daniel L.; Walker, Bruce E.

    2014-01-01

    An Ultrasonic Configurable Fan Artificial Noise Source (UCFANS) was designed, built, and tested in support of the NASA Langley Research Center's 14x22 wind tunnel test of the Hybrid Wing Body (HWB) full 3-D 5.8% scale model. The UCFANS is a 5.8% rapid prototype scale model of a high-bypass turbofan engine that can generate the tonal signature of proposed engines using artificial sources (no flow). The purpose of the program was to provide an estimate of the acoustic shielding benefits possible from mounting an engine on the upper surface of a wing; a flat plate model was used as the shielding surface. Simple analytical simulations were used to preview the radiation patterns - Fresnel knife-edge diffraction was coupled with a dense phased array of point sources to compute shielded and unshielded sound pressure distributions for potential test geometries and excitation modes. Contour plots of sound pressure levels, and integrated power levels, from nacelle alone and shielded configurations for both the experimental measurements and the analytical predictions are presented in this paper.

  7. An integrative computational framework based on a two-step random forest algorithm improves prediction of zinc-binding sites in proteins.

    Directory of Open Access Journals (Sweden)

    Cheng Zheng

    Full Text Available Zinc-binding proteins are the most abundant metalloproteins in the Protein Data Bank where the zinc ions usually have catalytic, regulatory or structural roles critical for the function of the protein. Accurate prediction of zinc-binding sites is not only useful for the inference of protein function but also important for the prediction of 3D structure. Here, we present a new integrative framework that combines multiple sequence and structural properties and graph-theoretic network features, followed by an efficient feature selection to improve prediction of zinc-binding sites. We investigate what information can be retrieved from the sequence, structure and network levels that is relevant to zinc-binding site prediction. We perform a two-step feature selection using random forest to remove redundant features and quantify the relative importance of the retrieved features. Benchmarking on a high-quality structural dataset containing 1,103 protein chains and 484 zinc-binding residues, our method achieved >80% recall at a precision of 75% for the zinc-binding residues Cys, His, Glu and Asp on 5-fold cross-validation tests, which is a 10%-28% higher recall at the 75% equal precision compared to SitePredict and zincfinder at residue level using the same dataset. The independent test also indicates that our method has achieved recall of 0.790 and 0.759 at residue and protein levels, respectively, which is a performance better than the other two methods. Moreover, AUC (the Area Under the Curve and AURPC (the Area Under the Recall-Precision Curve by our method are also respectively better than those of the other two methods. Our method can not only be applied to large-scale identification of zinc-binding sites when structural information of the target is available, but also give valuable insights into important features arising from different levels that collectively characterize the zinc-binding sites. The scripts and datasets are available at http://protein.cau.edu.cn/zincidentifier/.

  8. NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data.

    Science.gov (United States)

    Jurtz, Vanessa; Paul, Sinu; Andreatta, Massimo; Marcatili, Paolo; Peters, Bjoern; Nielsen, Morten

    2017-11-01

    Cytotoxic T cells are of central importance in the immune system's response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC class I molecules. Peptide binding to MHC molecules is the single most selective step in the Ag-presentation pathway. Therefore, in the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has attracted widespread attention. In the past, predictors of peptide-MHC interactions have primarily been trained on binding affinity data. Recently, an increasing number of MHC-presented peptides identified by mass spectrometry have been reported containing information about peptide-processing steps in the presentation pathway and the length distribution of naturally presented peptides. In this article, we present NetMHCpan-4.0, a method trained on binding affinity and eluted ligand data leveraging the information from both data types. Large-scale benchmarking of the method demonstrates an increase in predictive performance compared with state-of-the-art methods when it comes to identification of naturally processed ligands, cancer neoantigens, and T cell epitopes. Copyright © 2017 by The American Association of Immunologists, Inc.

  9. Fatty acid-binding protein 4 predicts gestational hypertension and preeclampsia in women with gestational diabetes mellitus.

    Directory of Open Access Journals (Sweden)

    Boya Li

    Full Text Available Fatty acid-binding protein 4 (FABP4 has been proposed to be a potential predictive factor of gestational hypertension or preeclampsia (GH/PE because of its integrating metabolic and inflammatory responses. Women with gestational diabetes mellitus (GDM are more likely to develop both GH/PE, than the normal population. The aim of our study was to examine the relationship between plasma FABP4 in the second trimester of pregnancy and the risk of GH/PE in women with GDM.This was a nested case-control study conducted within a large on-going prospective cohort study conducted at Peking University First Hospital. A total of 1344 women, who were diagnosed with GDM, according to a 75 g oral glucose tolerance test, participated in the GDM One-Day Clinic at Peking University First Hospital from February 24, 2016 to February 9, 2017. Of the 748 GDM women who agreed to the blood sample collection, 637 were followed until their delivery. The cases included GDM patients who developed gestational hypertension or preeclampsia (GDM-GH/PE group, n = 41. Another 41 matched GDM women without major complications were selected as the control group (GDM group.The incidence of GH/PE was 6.44% and 3.30% for preeclampsia. The level of the second trimester plasma FABP4 in the GDM-GH/PE group was significantly higher than the GDM group (17.53±11.35 vs. 12.79±6.04 ng/ml, P = 0.020. The AUC ROC for the second trimester plasma FABP4 predicted GH/PE in the GDM patients alone was 0.647 (95%CI 0.529-0.766. Multivariate analysis showed that the elevated second trimester FABP4 level was independently associated with GH/PE in the GDM patients (OR 1.136 [95% CI 1.003-1.286], P = 0.045.Increased second trimester plasma FABP4 independently predicted GH/PE in GDM patients.

  10. A Physiologically Based Pharmacokinetic Model to Predict the Pharmacokinetics of Highly Protein-Bound Drugs and Impact of Errors in Plasma Protein Binding

    Science.gov (United States)

    Ye, Min; Nagar, Swati; Korzekwa, Ken

    2015-01-01

    Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057

  11. A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

    Science.gov (United States)

    Ye, Min; Nagar, Swati; Korzekwa, Ken

    2016-04-01

    Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  12. Botulinum neurotoxin G binds synaptotagmin-II in a mode similar to that of serotype B: tyrosine 1186 and lysine 1191 cause its lower affinity.

    Science.gov (United States)

    Willjes, Gesche; Mahrhold, Stefan; Strotmeier, Jasmin; Eichner, Timo; Rummel, Andreas; Binz, Thomas

    2013-06-04

    Botulinum neurotoxins (BoNTs) block neurotransmitter release by proteolyzing SNARE proteins in peripheral nerve terminals. Entry into neurons occurs subsequent to interaction with gangliosides and a synaptic vesicle protein. Isoforms I and II of synaptotagmin were shown to act as protein receptors for two of the seven BoNT serotypes, BoNT/B and BoNT/G, and for mosaic-type BoNT/DC. BoNT/B and BoNT/G exhibit a homologous binding site for synaptotagmin whose interacting part adopts helical structure upon binding to BoNT/B. Whereas the BoNT/B-synaptotagmin-II interaction has been elucidated in molecular detail, corresponding information about BoNT/G is lacking. Here we systematically mutated the synaptotagmin binding site in BoNT/G and performed a comparative binding analysis with mutants of the cell binding subunit of BoNT/B. The results suggest that synaptotagmin takes the same overall orientation in BoNT/B and BoNT/G governed by the strictly conserved central parts of the toxins' binding site. The surrounding nonconserved areas differently contribute to receptor binding. Reciprocal mutations Y1186W and L1191Y increased the level of binding of BoNT/G approximately to the level of BoNT/B affinity, suggesting a similar synaptotagmin-bound state. The effects of the mutations were confirmed by studying the activity of correspondingly mutated full-length BoNTs. On the basis of these data, molecular modeling experiments were employed to reveal an atomistic model of BoNT/G-synaptotagmin recognition. These data suggest a reduced length and/or a bend in the C-terminal part of the synaptotagmin helix that forms upon contact with BoNT/G as compared with BoNT/B and are in agreement with the data of the mutational analyses.

  13. Cloning of cDNA sequences encoding cowpea (Vigna unguiculata) vicilins: Computational simulations suggest a binding mode of cowpea vicilins to chitin oligomers.

    Science.gov (United States)

    Rocha, Antônio J; Sousa, Bruno L; Girão, Matheus S; Barroso-Neto, Ito L; Monteiro-Júnior, José E; Oliveira, José T A; Nagano, Celso S; Carneiro, Rômulo F; Monteiro-Moreira, Ana C O; Rocha, Bruno A M; Freire, Valder N; Grangeiro, Thalles B

    2018-05-27

    Vicilins are 7S globulins which constitute the major seed storage proteins in leguminous species. Variant vicilins showing differential binding affinities for chitin have been implicated in the resistance and susceptibility of cowpea to the bruchid Callosobruchus maculatus. These proteins are members of the cupin superfamily, which includes a wide variety of enzymes and non-catalytic seed storage proteins. The cupin fold does not share similarity with any known chitin-biding domain. Therefore, it is poorly understood how these storage proteins bind to chitin. In this work, partial cDNA sequences encoding β-vignin, the major component of cowpea vicilins, were obtained from developing seeds. Three-dimensional molecular models of β-vignin showed the characteristic cupin fold and computational simulations revealed that each vicilin trimer contained 3 chitin-binding sites. Interaction models showed that chito-oligosaccharides bound to β-vignin were stabilized mainly by hydrogen bonds, a common structural feature of typical carbohydrate-binding proteins. Furthermore, many of the residues involved in the chitin-binding sites of β-vignin are conserved in other 7S globulins. These results support previous experimental evidences on the ability of vicilin-like proteins from cowpea and other leguminous species to bind in vitro to chitin as well as in vivo to chitinous structures of larval C. maculatus midgut. Copyright © 2018. Published by Elsevier B.V.

  14. Spectroscopic investigations on the complexation of Cm(III) and Eu(III) with organic model ligands and their binding mode in human urine (in vitro)

    International Nuclear Information System (INIS)

    Heller, Anne

    2011-01-01

    In case of incorporation, trivalent actinides (An(III)) and lanthanides (Ln(III)) pose a serious health risk to humans. An(III) are artificial, highly radioactive elements which are mainly produced during the nuclear fuel cycle in nuclear power plants. Via hazardous accidents or nonprofessional storage of radioactive waste, they can be released in the environment and enter the human food chain. In contrast, Ln(III) are nonradioactive, naturally occurring elements with multiple applications in technique and medicine. Consequently it is possible that humans get in contact and incorporate both, An(III) and Ln(III). Therefore, it is of particular importance to elucidate the behaviour of these elements in the human body. While macroscopic processes such as distribution, accumulation and excretion are studied quite well, knowledge about the chemical binding form (speciation) of An(III) and Ln(III) in various body fluids is still sparse. In the present work, for the first time, the speciation of Cm(III) and Eu(III) in natural human urine (in vitro) has been investigated spectroscopically and the formed complex identified. For this purpose, also basic investigations on the complex formation of Cm(III) and Eu(III) in synthetic model urine as well as with the urinary relevant, organic model ligands urea, alanine, phenylalanine, threonine and citrate have been performed and the previously unknown complex stability constants determined. Finally, all experimental results were compared to literature data and predictions calculated by thermodynamic modelling. Since both, Cm(III) and Eu(III), exhibit unique luminescence properties, particularly the suitability of time-resolved laser-induced fluorescence spectroscopy (TRLFS) could be demonstrated as a method to investigate these metal ions in untreated, complex biofluids. The results of this work provide new scientific findings on the biochemical reactions of An(III) and Ln(III) in human body fluids on a molecular scale and

  15. Predictions of the near edge transport shortfall in DIII-D L-mode plasmas using the trapped gyro-Landau-fluid model

    Energy Technology Data Exchange (ETDEWEB)

    Kinsey, J. E. [CompX, P.O. Box 2672, Del Mar, California 92014 (United States); Staebler, G. M.; Candy, J.; Petty, C. C.; Waltz, R. E. [General Atomics, P.O. Box 85608, San Diego, California 92186-5608 (United States); Rhodes, T. L. [Physics Department and PSTI, University of California, Los Angeles, California 90095 (United States)

    2015-01-15

    Previous studies of DIII-D L-mode plasmas have shown that a transport shortfall exists in that our current models of turbulent transport can significantly underestimate the energy transport in the near edge region. In this paper, the Trapped Gyro-Landau-Fluid (TGLF) drift wave transport model is used to simulate the near edge transport in a DIII-D L-mode experiment designed to explore the impact of varying the safety factor on the shortfall. We find that the shortfall systematically increases with increasing safety factor and is more pronounced for the electrons than for the ions. Within the shortfall dataset, a single high current case has been found where no transport shortfall is predicted. Reduced neutral beam injection power has been identified as the key parameter separating this discharge from other discharges exhibiting a shortfall. Further analysis shows that the energy transport in the L-mode near edge region is not stiff according to TGLF. Unlike the H-mode core region, the predicted temperature profiles are relatively more responsive to changes in auxiliary heating power. In testing the fidelity of TGLF for the near edge region, we find that a recalibration of the collision model is warranted. A recalibration improves agreement between TGLF and nonlinear gyrokinetic simulations performed using the GYRO code with electron-ion collisions. The recalibration only slightly impacts the predicted shortfall.

  16. Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naïve Bayes.

    Directory of Open Access Journals (Sweden)

    Wangchao Lou

    Full Text Available Developing an efficient method for determination of the DNA-binding proteins, due to their vital roles in gene regulation, is becoming highly desired since it would be invaluable to advance our understanding of protein functions. In this study, we proposed a new method for the prediction of the DNA-binding proteins, by performing the feature rank using random forest and the wrapper-based feature selection using forward best-first search strategy. The features comprise information from primary sequence, predicted secondary structure, predicted relative solvent accessibility, and position specific scoring matrix. The proposed method, called DBPPred, used Gaussian naïve Bayes as the underlying classifier since it outperformed five other classifiers, including decision tree, logistic regression, k-nearest neighbor, support vector machine with polynomial kernel, and support vector machine with radial basis function. As a result, the proposed DBPPred yields the highest average accuracy of 0.791 and average MCC of 0.583 according to the five-fold cross validation with ten runs on the training benchmark dataset PDB594. Subsequently, blind tests on the independent dataset PDB186 by the proposed model trained on the entire PDB594 dataset and by other five existing methods (including iDNA-Prot, DNA-Prot, DNAbinder, DNABIND and DBD-Threader were performed, resulting in that the proposed DBPPred yielded the highest accuracy of 0.769, MCC of 0.538, and AUC of 0.790. The independent tests performed by the proposed DBPPred on completely a large non-DNA binding protein dataset and two RNA binding protein datasets also showed improved or comparable quality when compared with the relevant prediction methods. Moreover, we observed that majority of the selected features by the proposed method are statistically significantly different between the mean feature values of the DNA-binding and the non DNA-binding proteins. All of the experimental results indicate that

  17. Predicting core losses and efficiency of SRM in continuous current mode of operation using improved analytical technique

    International Nuclear Information System (INIS)

    Parsapour, Amir; Dehkordi, Behzad Mirzaeian; Moallem, Mehdi

    2015-01-01

    In applications in which the high torque per ampere at low speed and rated power at high speed are required, the continuous current method is the best solution. However, there is no report on calculating the core loss of SRM in continuous current mode of operation. Efficiency and iron loss calculation which are complex tasks in case of conventional mode of operation is even more involved in continuous current mode of operation. In this paper, the Switched Reluctance Motor (SRM) is modeled using finite element method and core loss and copper loss of SRM in discontinuous and continuous current modes of operation are calculated using improved analytical techniques to include the minor loop losses in continuous current mode of operation. Motor efficiency versus speed in both operation modes is obtained and compared. - Highlights: • Continuous current method for Switched Reluctance Motor (SRM) is explained. • An improved analytical technique is presented for SRM core loss calculation. • SRM losses in discontinuous and continuous current operation modes are presented. • Effect of mutual inductances on SRM performance is investigated

  18. Predicting core losses and efficiency of SRM in continuous current mode of operation using improved analytical technique

    Energy Technology Data Exchange (ETDEWEB)

    Parsapour, Amir, E-mail: amirparsapour@gmail.com [Department of Electrical Engineering, University of Isfahan, Isfahan (Iran, Islamic Republic of); Dehkordi, Behzad Mirzaeian, E-mail: mirzaeian@eng.ui.ac.ir [Department of Electrical Engineering, University of Isfahan, Isfahan (Iran, Islamic Republic of); Moallem, Mehdi, E-mail: moallem@cc.iut.ac.ir [Department of Electrical Engineering, Isfahan University of Technology, Isfahan (Iran, Islamic Republic of)

    2015-03-15

    In applications in which the high torque per ampere at low speed and rated power at high speed are required, the continuous current method is the best solution. However, there is no report on calculating the core loss of SRM in continuous current mode of operation. Efficiency and iron loss calculation which are complex tasks in case of conventional mode of operation is even more involved in continuous current mode of operation. In this paper, the Switched Reluctance Motor (SRM) is modeled using finite element method and core loss and copper loss of SRM in discontinuous and continuous current modes of operation are calculated using improved analytical techniques to include the minor loop losses in continuous current mode of operation. Motor efficiency versus speed in both operation modes is obtained and compared. - Highlights: • Continuous current method for Switched Reluctance Motor (SRM) is explained. • An improved analytical technique is presented for SRM core loss calculation. • SRM losses in discontinuous and continuous current operation modes are presented. • Effect of mutual inductances on SRM performance is investigated.

  19. Evaluation of B3LYP, X3LYP, and M06-Class Density Functionals for Predicting the Binding Energies of Neutral, Protonated, and Deprotonated Water Clusters.

    Science.gov (United States)

    Bryantsev, Vyacheslav S; Diallo, Mamadou S; van Duin, Adri C T; Goddard, William A

    2009-04-14

    In this paper we assess the accuracy of the B3LYP, X3LYP, and newly developed M06-L, M06-2X, and M06 functionals to predict the binding energies of neutral and charged water clusters including (H2O)n, n = 2-8, 20), H3O(+)(H2O)n, n = 1-6, and OH(-)(H2O)n, n = 1-6. We also compare the predicted energies of two ion hydration and neutralization reactions on the basis of the calculated binding energies. In all cases, we use as benchmarks calculated binding energies of water clusters extrapolated to the complete basis set limit of the second-order Møller-Plesset perturbation theory with the effects of higher order correlation estimated at the coupled-cluster theory with single, double, and perturbative triple excitations in the aug-cc-pVDZ basis set. We rank the accuracy of the functionals on the basis of the mean unsigned error (MUE) between calculated benchmark and density functional theory energies. The corresponding MUE (kcal/mol) for each functional is listed in parentheses. We find that M06-L (0.73) and M06 (0.84) give the most accurate binding energies using very extended basis sets such as aug-cc-pV5Z. For more affordable basis sets, the best methods for predicting the binding energies of water clusters are M06-L/aug-cc-pVTZ (1.24), B3LYP/6-311++G(2d,2p) (1.29), and M06/aug-cc-PVTZ (1.33). M06-L/aug-cc-pVTZ also gives more accurate energies for the neutralization reactions (1.38), whereas B3LYP/6-311++G(2d,2p) gives more accurate energies for the ion hydration reactions (1.69).

  20. Geological predictions for the long-term isolation of radioactive waste based on extrapolating uniform mode and rate of crustal movements

    International Nuclear Information System (INIS)

    Umeda, Koji; Tanikawa, Shin-ichi; Yasue, Ken-ichi

    2013-01-01

    Long-term predictions of geological and tectonic disturbances are key issues for the safety assessment of radioactive waste disposal, especially on the Japanese Islands. Geological predictions of disturbances should be performed by extrapolating uniform mode and rate of crustal movements under the current framework. Multiple lines of geological evidence in Japan strongly suggest that the present mode of tectonics began during the late Pliocene to early Quaternary, and was fully developed by the middle Pleistocene. The uplift rates of mountains in Japan are determined to have been approximately constant until the middle Pleistocene based on simulations of temporal changes in mean altitude developed under concurrent tectonics and denudation processes. The onset of the neotectonic mode of deformation was probably triggered by the initiation of the eastward movement of the Amur Plate and the collision of the Izu block with central Honshu. The uncertainty of predictions beyond steady-state crustal deformation would, in general, increase for long-term predictions using the extrapolation procedure. Consequently, future geological and tectonic disturbances in Japan can be estimated with relatively high reliability for the next 100,000 years. (author)

  1. Three-dimensional (3D) structure prediction and function analysis of the chitin-binding domain 3 protein HD73_3189 from Bacillus thuringiensis HD73.

    Science.gov (United States)

    Zhan, Yiling; Guo, Shuyuan

    2015-01-01

    Bacillus thuringiensis (Bt) is capable of producing a chitin-binding protein believed to be functionally important to bacteria during the stationary phase of its growth cycle. In this paper, the chitin-binding domain 3 protein HD73_3189 from B. thuringiensis has been analyzed by computer technology. Primary and secondary structural analyses demonstrated that HD73_3189 is negatively charged and contains several α-helices, aperiodical coils and β-strands. Domain and motif analyses revealed that HD73_3189 contains a signal peptide, an N-terminal chitin binding 3 domains, two copies of a fibronectin-like domain 3 and a C-terminal carbohydrate binding domain classified as CBM_5_12. Moreover, analysis predicted the protein's associated localization site to be the cell wall. Ligand site prediction determined that amino acid residues GLU-312, TRP-334, ILE-341 and VAL-382 exposed on the surface of the target protein exhibit polar interactions with the substrate.

  2. A method for predicting individual residue contributions to enzyme specificity and binding-site energies, and its application to MTH1.

    Science.gov (United States)

    Stewart, James J P

    2016-11-01

    A new method for predicting the energy contributions to substrate binding and to specificity has been developed. Conventional global optimization methods do not permit the subtle effects responsible for these properties to be modeled with sufficient precision to allow confidence to be placed in the results, but by making simple alterations to the model, the precisions of the various energies involved can be improved from about ±2 kcal mol -1 to ±0.1 kcal mol -1 . This technique was applied to the oxidized nucleotide pyrophosphohydrolase enzyme MTH1. MTH1 is unusual in that the binding and reaction sites are well separated-an advantage from a computational chemistry perspective, as it allows the energetics involved in docking to be modeled without the need to consider any issues relating to reaction mechanisms. In this study, two types of energy terms were investigated: the noncovalent interactions between the binding site and the substrate, and those responsible for discriminating between the oxidized nucleotide 8-oxo-dGTP and the normal dGTP. Both of these were investigated using the semiempirical method PM7 in the program MOPAC. The contributions of the individual residues to both the binding energy and the specificity of MTH1 were calculated by simulating the effect of mutations. Where comparisons were possible, all calculated results were in agreement with experimental observations. This technique provides fresh insight into the binding mechanism that enzymes use for discriminating between possible substrates.

  3. Prediction of exotic octupole excitation modes in superdeformed A ∼ 150 and A ∼ 190 nuclei: Bending, Banana and other modes

    International Nuclear Information System (INIS)

    Dudek, J.

    1990-01-01

    Results of the first calculations aiming at determination of the exotic shape effects at large elongations are presented. After discussing some formal aspects of our generalised approach based on the deformed Woods-Saxon potential, the overall trends in the quantal (shell) effects leading to the deformation driving forces in terms of Y λ=3,μ multipole components are presented. Finally, the nuclei are identified in which (at least at a low spin limit) the predicted exotic shape effects should manifest themselves in the most pronounced way. 10 figs

  4. Predictive modelling of the impact of argon injection on H-mode plasmas in JET with the RITM code

    International Nuclear Information System (INIS)

    Unterberg, B; Kalupin, D; Tokar', M Z; Corrigan, G; Dumortier, P; Huber, A; Jachmich, S; Kempenaars, M; Kreter, A; Messiaen, A M; Monier-Garbet, P; Ongena, J; Puiatti, M E; Valisa, M; Hellermann, M von

    2004-01-01

    Self-consistent modelling of energy and particle transport of the plasma background and impurities has been performed with the code RITM for argon seeded high density H-mode plasmas in JET. The code can reproduce both the profiles in the plasma core and the structure of the edge pedestal. The impact of argon on core transport is found to be small; in particular, no significant change in confinement is observed in both experimental and modelling results. The same transport model, which has been used to reproduce density peaking in the radiative improved mode in TEXTOR, reveals a flat density profile in Ar seeded JET H-mode plasmas in agreement with the experimental observations. This behaviour is attributed to the rather flat profile of the safety factor in the bulk of H-mode discharges

  5. Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme.

    Science.gov (United States)

    Leong, Max K; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

    2017-01-06

    The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r 2  = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pK i values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r 2  = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q 2  = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

  6. Epistatic mutations in PUMA BH3 drive an alternate binding mode to potently and selectively inhibit anti-apoptotic Bfl-1

    Energy Technology Data Exchange (ETDEWEB)

    Jenson, Justin M.; Ryan, Jeremy A.; Grant, Robert A.; Letai, Anthony; Keating, Amy E. (DFCI); (MIT)

    2017-06-08

    Overexpression of anti-apoptotic Bcl-2 family proteins contributes to cancer progression and confers resistance to chemotherapy. Small molecules that target Bcl-2 are used in the clinic to treat leukemia, but tight and selective inhibitors are not available for Bcl-2 paralog Bfl-1. Guided by computational analysis, we designed variants of the native BH3 motif PUMA that are > 150-fold selective for Bfl-1 binding. The designed peptides potently trigger disruption of the mitochondrial outer membrane in cells dependent on Bfl-1, but not in cells dependent on other anti-apoptotic homologs. High-resolution crystal structures show that designed peptide FS2 binds Bfl-1 in a shifted geometry, relative to PUMA and other binding partners, due to a set of epistatic mutations. FS2 modified with an electrophile reacts with a cysteine near the peptide-binding groove to augment specificity. Designed Bfl-1 binders provide reagents for cellular profiling and leads for developing enhanced and cell-permeable peptide or small-molecule inhibitors.

  7. Two distinct binding modes define the interaction of Brox with the C-terminal tails of CHMP5 and CHMP4B.

    Science.gov (United States)

    Mu, Ruiling; Dussupt, Vincent; Jiang, Jiansheng; Sette, Paola; Rudd, Victoria; Chuenchor, Watchalee; Bello, Nana F; Bouamr, Fadila; Xiao, Tsan Sam

    2012-05-09

    Interactions of the CHMP protein carboxyl terminal tails with effector proteins play important roles in retroviral budding, cytokinesis, and multivesicular body biogenesis. Here we demonstrate that hydrophobic residues at the CHMP4B C-terminal amphipathic α helix bind a concave surface of Brox, a mammalian paralog of Alix. Unexpectedly, CHMP5 was also found to bind Brox and specifically recruit endogenous Brox to detergent-resistant membrane fractions through its C-terminal 20 residues. Instead of an α helix, the CHMP5 C-terminal tail adopts a tandem β-hairpin structure that binds Brox at the same site as CHMP4B. Additional Brox:CHMP5 interface is furnished by a unique CHMP5 hydrophobic pocket engaging the Brox residue Y348 that is not conserved among the Bro1 domains. Our studies thus unveil a β-hairpin conformation of the CHMP5 protein C-terminal tail, and provide insights into the overlapping but distinct binding profiles of ESCRT-III and the Bro1 domain proteins. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

    Science.gov (United States)

    Fukunishi, Yoshifumi

    2010-01-01

    For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

  9. The Relative Importance of Family History, Gender, Mode of Onset, and Age at Onsetin Predicting Clinical Features of First-Episode Psychotic Disorders.

    Science.gov (United States)

    Compton, Michael T; Berez, Chantal; Walker, Elaine F

    Family history of psychosis, gender, mode of onset, and age at onset are considered prognostic factors important to clinicians evaluating first-episode psychosis; yet, clinicians have little guidance as to how these four factors differentially predict early-course substance abuse, symptomatology, and functioning. We conducted a "head-to-head comparison" of these four factors regarding their associations with key clinical features at initial hospitalization. We also assessed potential interactions between gender and family history with regard to age at onset of psychosis and symptom severity. Consecutively admitted first-episode patients (n=334) were evaluated in two studies that rigorously assessed a number of early-course variables. Associations among variables of interest were examined using Pearson correlations, χ 2 tests, Student's t-tests, and 2×2 factorial analyses of variance. Substance (nicotine, alcohol, and cannabis) abuse and positive symptom severity were predicted only by male gender. Negative symptom severity and global functioning impairments were predicted by earlier age at onset of psychosis. General psychopathology symptom severity was predicted by both mode of onset and age at onset. Interaction effects were not observed with regard to gender and family history in predicting age at onset or symptom severity. The four prognostic features have differential associations with substance abuse, domains of symptom severity, and global functioning. Gender and age at onset of psychosis appear to be more predictive of clinical features at the time of initial evaluation (and thus presumably longer term outcomes) than the presence of a family history of psychosis and a more gradual mode of onset.

  10. Field-Evolved Mode 1 Resistance of the Fall Armyworm to Transgenic Cry1Fa-Expressing Corn Associated with Reduced Cry1Fa Toxin Binding and Midgut Alkaline Phosphatase Expression

    Science.gov (United States)

    Jakka, Siva R. K.; Gong, Liang; Hasler, James; Banerjee, Rahul; Sheets, Joel J.; Narva, Kenneth; Blanco, Carlos A.

    2015-01-01

    Insecticidal protein genes from the bacterium Bacillus thuringiensis (Bt) are expressed by transgenic Bt crops (Bt crops) for effective and environmentally safe pest control. The development of resistance to these insecticidal proteins is considered the most serious threat to the sustainability of Bt crops. Resistance in fall armyworm (Spodoptera frugiperda) populations from Puerto Rico to transgenic corn producing the Cry1Fa insecticidal protein resulted, for the first time in the United States, in practical resistance, and Bt corn was withdrawn from the local market. In this study, we used a field-collected Cry1Fa corn-resistant strain (456) of S. frugiperda to identify the mechanism responsible for field-evolved resistance. Binding assays detected reduced Cry1Fa, Cry1Ab, and Cry1Ac but not Cry1Ca toxin binding to midgut brush border membrane vesicles (BBMV) from the larvae of strain 456 compared to that from the larvae of a susceptible (Ben) strain. This binding phenotype is descriptive of the mode 1 type of resistance to Bt toxins. A comparison of the transcript levels for putative Cry1 toxin receptor genes identified a significant downregulation (>90%) of a membrane-bound alkaline phosphatase (ALP), which translated to reduced ALP protein levels and a 75% reduction in ALP activity in BBMV from 456 compared to that of Ben larvae. We cloned and heterologously expressed this ALP from susceptible S. frugiperda larvae and demonstrated that it specifically binds with Cry1Fa toxin. This study provides a thorough mechanistic description of field-evolved resistance to a transgenic Bt crop and supports an association between resistance and reduced Cry1Fa toxin binding and levels of a putative Cry1Fa toxin receptor, ALP, in the midguts of S. frugiperda larvae. PMID:26637593

  11. Tyrosine 105 and threonine 212 at outermost substrate binding subsites -6 and +4 control substrate specificity, oligosaccharide cleavage patterns, and multiple binding modes of barley alpha-amylase 1

    DEFF Research Database (Denmark)

    Bak-Jensen, K.S.; André, G.; Gottschalk, T.E.

    2004-01-01

    and oligosaccharides, respectively. Bond cleavage analysis of oligosaccharide degradation by wild-type and mutant AMY1 supports that Tyr105 is critical for binding at subsite -6. Substrate binding is improved by T212(Y/W) introduced at subsite +4 and the [Y105A/ T212(Y/W)] AMY1 double mutants synergistically enhanced......The role in activity of outer regions in the substrate binding cleft in alpha-amylases is illustrated by mutational analysis of Tyr(105) and Thr(212) localized at subsites - 6 and +4 ( substrate cleavage occurs between subsites -1 and +1) in barley alpha-amylase 1 (AMY1). Tyr(105) is conserved...... in plant alpha-amylases whereas Thr(212) varies in these and related enzymes. Compared with wild-type AMY1, the subsite -6 mutant Y105A has 140, 15, and 1% activity (k(cat)/K-m) on starch, amylose DP17, and 2-chloro-4-nitrophenyl β-D-maltoheptaoside, whereas T212Y at subsite +4 has 32, 370, and 90...

  12. Development of neural network models for the prediction of solidification mode, weld bead geometry and sensitisation in austenitic stainless steels

    International Nuclear Information System (INIS)

    Vasudevan, M.; Raj, B.; Prasad Rao, K.

    2005-01-01

    Quantitative models describing the effect of weld composition on the solidification mode, ferrite content and process parameters on the weld bead geometry are necessary in order to design composition of the welding consumable to ensure primary ferritic solidification mode, proper ferrite content and to ensure right choice of process parameters to achieve good bead geometry. A quantitative model on sensitisation behaviour of austenitic stainless steels is also necessary to optimise the composition of the austenitic stainless steel and to limit the strain on the material in order to enhance the resistance to sensitisation. The present paper discuss the development of quantitative models using artificial neural networks to correlate weld metal composition with solidification mode, process parameter with weld bead geometry and time for sensitisation with composition, strain in the material before welding and the temperature of exposure in austenitic stainless steels. (author)

  13. Use of 13NMR to delineate the mode of association or binding of 13C-labeled pollutants with humic materials

    International Nuclear Information System (INIS)

    Bortiatynski, J.M.; Minard, R.D.; Hatcher, P.G.

    1993-01-01

    13 C NMR has recently been shown to be a powerful technique for the examination of the covalent binding of pollutants to humic materials when the latter are enriched with 13 C. Enhanced signals are observed for the carbons that are highly enriched with 13 C while the remaining signals due to naturally abundant 13 C form unlabeled pollutant carbons or humic substances are at the baseline noise level. If covalent bonding and/or non covalent associations take place at or near the site of the 13 C label(s), the nature of the bonding or association can be discerned and the adsorption coefficients can be calculated. In this paper, the authors present the results of such binding studies which demonstrate the great potential of this technique

  14. The structure of tubulin-binding cofactor A from Leishmania major infers a mode of association during the early stages of microtubule assembly

    Energy Technology Data Exchange (ETDEWEB)

    Barrack, Keri L.; Fyfe, Paul K.; Hunter, William N., E-mail: w.n.hunter@dundee.ac.uk [University of Dundee, Dow Street, Dundee DD1 5EH, Scotland (United Kingdom)

    2015-04-21

    The structure of a tubulin-binding cofactor from L. major is reported and compared with yeast, plant and human orthologues. Tubulin-binding cofactor A (TBCA) participates in microtubule formation, a key process in eukaryotic biology to create the cytoskeleton. There is little information on how TBCA might interact with β-tubulin en route to microtubule biogenesis. To address this, the protozoan Leishmania major was targeted as a model system. The crystal structure of TBCA and comparisons with three orthologous proteins are presented. The presence of conserved features infers that electrostatic interactions that are likely to involve the C-terminal tail of β-tubulin are key to association. This study provides a reagent and template to support further work in this area.

  15. Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs.

    Science.gov (United States)

    Le, Nguyen-Quoc-Khanh; Ou, Yu-Yen

    2016-07-30

    Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9-45 % and its Matthew's correlation coefficient was 0.14-0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron

  16. Design and synthesis of BODIPY-clickate based Hg(2+) sensors: the effect of triazole binding mode with Hg(2+) on signal transduction.

    Science.gov (United States)

    Vedamalai, Mani; Kedaria, Dhaval; Vasita, Rajesh; Mori, Shigeki; Gupta, Iti

    2016-02-14

    BODIPY-clickates, F1 and F2, for the detection of Hg(2+) have been designed, synthesized and characterized. Both F1 and F2 showed hyperchromic shifts in the UV-visible spectra in response to increasing Hg(2+) concentrations. Hg(2+) ion binding caused perturbation of the emission quenching process and chelation induced enhanced bathochromic emission of F1 and F2 to 620 nm and 660 nm, respectively. Job's plot clearly indicated that the binding ratio of F1 and F2 with Hg(2+) was 1 : 1. The NMR titration of BODIPY-clickates with Hg(2+) confirmed that aromatic amines and triazoles were involved in the binding event. Furthermore, HRMS data of F1-Hg(2+) and F2-Hg(2+) supported the formation of mercury complexes of BODIPY-clickates. The dissociation constant for the interaction between fluorescent probes F1 and F2 with Hg(2+) was found to be 24.4 ± 5.1 μM and 22.0 ± 3.9 μM, respectively. The Hg(2+) ion induced fluorescence enhancement was almost stable in a pH range of 5 to 8. Having less toxicity to live cells, both the probes were successfully used to map the Hg(2+) ions in live A549 cells.

  17. Coarse-grained/molecular mechanics of the TAS2R38 bitter taste receptor: experimentally-validated detailed structural prediction of agonist binding.

    Directory of Open Access Journals (Sweden)

    Alessandro Marchiori

    Full Text Available Bitter molecules in humans are detected by ∼25 G protein-coupled receptors (GPCRs. The lack of atomic resolution structure for any of them is complicating an in depth understanding of the molecular mechanisms underlying bitter taste perception. Here, we investigate the molecular determinants of the interaction of the TAS2R38 bitter taste receptor with its agonists phenylthiocarbamide (PTC and propylthiouracil (PROP. We use the recently developed hybrid Molecular Mechanics/Coarse Grained (MM/CG method tailored specifically for GPCRs. The method, through an extensive exploration of the conformational space in the binding pocket, allows the identification of several residues important for agonist binding that would have been very difficult to capture from the standard bioinformatics/docking approach. Our calculations suggest that both agonists bind to Asn103, Phe197, Phe264 and Trp201, whilst they do not interact with the so-called extra cellular loop 2, involved in cis-retinal binding in the GPCR rhodopsin. These predictions are consistent with data sets based on more than 20 site-directed mutagenesis and functional calcium imaging experiments of TAS2R38. The method could be readily used for other GPCRs for which experimental information is currently lacking.

  18. Elucidation of the sequence selective binding mode of the DNA minor groove binder adozelesin, by high-field 1H NMR and restrained molecular dynamics

    International Nuclear Information System (INIS)

    Cameron, L.

    1999-01-01

    Adozelesin (formerly U73-975, The Upjohn Co.) is a covalent, minor-groove binding analogue of the antitumour antibiotic (+)CC-1065. Adozelesin consists of a cyclopropapyrroloindole alkylating sub-unit identical to (+)CC-1065, plus indole and benzofuran sub-units which replace the more complex pyrroloindole B and C sub-units, respectively, of (+)CC-1065. Adozelesin is a clinically important drug candidate, since it does not contain the ethylene bridge moieties on the B and C sub-units which are thought to be responsible for the unusual delayed hepatotoxicity exhibited by (+)CC-1065. Sequencing techniques identified two consensus sequences for adozelesin binding as p(dA) and 5'(T/A)(T/A)T-A*(C/G)G. This suggests that adozelesin spans a total of five base-pairs and shows a preference for A=T base-pair rich sequences, thus avoiding steric crowding around the exocyclic NH 2 of guanine and a wide minor groove. In this project, the covalent modification of two DNA sequences, i.e. 5'd(CGTAAGCGCTTA*CG) 2 and 5'-d(CGAAAAA*CGG)· 5'-d(CCGTTTTTCG), by adozelesin was examined by high-field NMR and restrained molecular mechanics and dynamics. Previous studies of minor groove binding drugs, using techniques as diverse as NMR, X-ray crystallography and molecular modelling, indicate that the incorporation of a guanine into the consensus sequence sterically hinders binding and, more importantly, produces a wider minor groove which is a 'slack' fit for the ligand. The aim of this investigation was to provide an insight into the sequence selective binding of adozelesin to 5'-AAAAA*CG and 5'-GCTTA*CG. The 1 H NMR data revealed that, in both cases, β-helical structure and Watson-Crick base-pairing was maintained on adduct formation. The 5'-GCTTA*CG adduct displayed significant distortion of the guanine base on the non-covalently modified strand. This distortion resulted from an amalgamation of two factors. Firstly, the presence of a strong hydrogen-bond between the amide linker of the

  19. Predicted RNA Binding Proteins Pes4 and Mip6 Regulate mRNA Levels, Translation, and Localization during Sporulation in Budding Yeast.

    Science.gov (United States)

    Jin, Liang; Zhang, Kai; Sternglanz, Rolf; Neiman, Aaron M

    2017-05-01

    In response to starvation, diploid cells of Saccharomyces cerevisiae undergo meiosis and form haploid spores, a process collectively referred to as sporulation. The differentiation into spores requires extensive changes in gene expression. The transcriptional activator Ndt80 is a central regulator of this process, which controls many genes essential for sporulation. Ndt80 induces ∼300 genes coordinately during meiotic prophase, but different mRNAs within the NDT80 regulon are translated at different times during sporulation. The protein kinase Ime2 and RNA binding protein Rim4 are general regulators of meiotic translational delay, but how differential timing of individual transcripts is achieved was not known. This report describes the characterization of two related NDT80 -induced genes, PES4 and MIP6 , encoding predicted RNA binding proteins. These genes are necessary to regulate the steady-state expression, translational timing, and localization of a set of mRNAs that are transcribed by NDT80 but not translated until the end of meiosis II. Mutations in the predicted RNA binding domains within PES4 alter the stability of target mRNAs. PES4 and MIP6 affect only a small portion of the NDT80 regulon, indicating that they act as modulators of the general Ime2/Rim4 pathway for specific transcripts. Copyright © 2017 American Society for Microbiology.

  20. Use of thermodynamic coupling between antibody-antigen binding and phospholipid acyl chain phase transition energetics to predict immunoliposome targeting affinity.

    Science.gov (United States)

    Klegerman, Melvin E; Zou, Yuejiao; Golunski, Eva; Peng, Tao; Huang, Shao-Ling; McPherson, David D

    2014-09-01

    Thermodynamic analysis of ligand-target binding has been a useful tool for dissecting the nature of the binding mechanism and, therefore, potentially can provide valuable information regarding the utility of targeted formulations. Based on a consistent coupling of antibody-antigen binding and gel-liquid crystal transition energetics observed for antibody-phosphatidylethanolamine (Ab-PE) conjugates, we hypothesized that the thermodynamic parameters and the affinity for antigen of the Ab-PE conjugates could be effectively predicted once the corresponding information for the unconjugated antibody is determined. This hypothesis has now been tested in nine different antibody-targeted echogenic liposome (ELIP) preparations, where antibody is conjugated to dipalmitoylphosphatidylethanolamine (DPPE) head groups through a thioether linkage. Predictions were satisfactory (affinity not significantly different from the population of values found) in five cases (55.6%), but the affinity of the unconjugated antibody was not significantly different from the population of values found in six cases (66.7%), indicating that the affinities of the conjugated antibody tended not to deviate appreciably from those of the free antibody. While knowledge of the affinities of free antibodies may be sufficient to judge their suitability as targeting agents, thermodynamic analysis may still provide valuable information regarding their usefulness for specific applications.

  1. Bedside Heart Type Fatty Acid Binding Protein (H-FABP): Is an Early Predictive Marker of Cardiac Syncope

    International Nuclear Information System (INIS)

    Sonmez, B. M.; Yilmaz, F.; Durdu, T.; Hakbilir, O.; Ongar, M.; Ozturk, D.; Altinbilek, E.; Kavalci, C.; Turhan, T.

    2015-01-01

    Objective: To determine the value of bedside heart-type fatty acid binding protein in diagnosis of cardiac syncope in patients presenting with syncope or presyncope. Methods: The prospective study was conducted at Ankara Numune Training and Research Hospital, Ankara, Turkey, between September 1, 2010, and January 1, 2011, and comprised patients aged over 18 years who presented with syncope or presyncope. Patients presenting to emergency department within 4 hours of syncope or presyncope underwent a bedside heart-type fatty acid binding protein test measurement. SPSS 16 was used for statistical analysis, Results: Of the 100 patients evaluated, 22(22 percent) were diagnosed with cardiac syncope. Of them, 13(59.1 percent) patients had a positive and 9(40.9 percent) had a negative heart-type fatty acid binding protein result. Consequently, the test result was 12.64 times more positive in patients with cardiac syncope compared to those without. Conclusions: Bedside heart-type fatty acid binding protein, particularly at early phase of myocardial injury, reduces diagnostic and therapeutic uncertainity of cardiac origin in syncope patients. (author)

  2. Urinary liver-type fatty acid-binding protein predicts progression to nephropathy in type 1 diabetic patients

    DEFF Research Database (Denmark)

    Nielsen, Stine Elkjaer; Sugaya, Takeshi; Hovind, Peter

    2010-01-01

    Urinary liver-type fatty acid-binding protein (u-LFABP) is a marker of tubulointerstitial inflammation and has been shown to be increased in patients with type 1 diabetes and is further increased in patients who progress to micro- and macroalbuminuria. Our aim was to evaluate u-LFABP as a predictor...... of progression to micro- and macroalbuminuria in type 1 diabetes....

  3. Interplay between magnetism and energetics in Fe-Cr alloys from a predictive noncollinear magnetic tight-binding model

    DEFF Research Database (Denmark)

    Soulairol, R.; Barreteau, Cyrille; Fu, Chu-Chun

    2016-01-01

    Magnetism is a key driving force controlling several thermodynamic and kinetic properties of Fe-Cr systems. We present a tight-binding model for Fe-Cr, where magnetism is treated beyond the usual collinear approximation. A major advantage of this model consists in a rather simple fitting procedur...

  4. Urinary liver-type fatty acid-binding protein predicts progression to nephropathy in type 1 diabetic patients

    DEFF Research Database (Denmark)

    Nielsen, Stine Elkjaer; Sugaya, Takeshi; Hovind, Peter

    2010-01-01

    Urinary liver-type fatty acid-binding protein (u-LFABP) is a marker of tubulointerstitial inflammation and has been shown to be increased in patients with type 1 diabetes and is further increased in patients who progress to micro- and macroalbuminuria. Our aim was to evaluate u-LFABP as a predictor...

  5. Predicting the mixed-mode I/II spatial damage propagation along 3D-printed soft interfacial layer via a hyperelastic softening model

    Science.gov (United States)

    Liu, Lei; Li, Yaning

    2018-07-01

    A methodology was developed to use a hyperelastic softening model to predict the constitutive behavior and the spatial damage propagation of nonlinear materials with damage-induced softening under mixed-mode loading. A user subroutine (ABAQUS/VUMAT) was developed for numerical implementation of the model. 3D-printed wavy soft rubbery interfacial layer was used as a material system to verify and validate the methodology. The Arruda - Boyce hyperelastic model is incorporated with the softening model to capture the nonlinear pre-and post- damage behavior of the interfacial layer under mixed Mode I/II loads. To characterize model parameters of the 3D-printed rubbery interfacial layer, a series of scarf-joint specimens were designed, which enabled systematic variation of stress triaxiality via a single geometric parameter, the slant angle. It was found that the important model parameter m is exponentially related to the stress triaxiality. Compact tension specimens of the sinusoidal wavy interfacial layer with different waviness were designed and fabricated via multi-material 3D printing. Finite element (FE) simulations were conducted to predict the spatial damage propagation of the material within the wavy interfacial layer. Compact tension experiments were performed to verify the model prediction. The results show that the model developed is able to accurately predict the damage propagation of the 3D-printed rubbery interfacial layer under complicated stress-state without pre-defined failure criteria.

  6. Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods

    International Nuclear Information System (INIS)

    Zhang, Yachao; Liu, Kaipei; Qin, Liang; An, Xueli

    2016-01-01

    Highlights: • Variational mode decomposition is adopted to process original wind power series. • A novel combined model based on machine learning methods is established. • An improved differential evolution algorithm is proposed for weight adjustment. • Probabilistic interval prediction is performed by quantile regression averaging. - Abstract: Due to the increasingly significant energy crisis nowadays, the exploitation and utilization of new clean energy gains more and more attention. As an important category of renewable energy, wind power generation has become the most rapidly growing renewable energy in China. However, the intermittency and volatility of wind power has restricted the large-scale integration of wind turbines into power systems. High-precision wind power forecasting is an effective measure to alleviate the negative influence of wind power generation on the power systems. In this paper, a novel combined model is proposed to improve the prediction performance for the short-term wind power forecasting. Variational mode decomposition is firstly adopted to handle the instability of the raw wind power series, and the subseries can be reconstructed by measuring sample entropy of the decomposed modes. Then the base models can be established for each subseries respectively. On this basis, the combined model is developed based on the optimal virtual prediction scheme, the weight matrix of which is dynamically adjusted by a self-adaptive multi-strategy differential evolution algorithm. Besides, a probabilistic interval prediction model based on quantile regression averaging and variational mode decomposition-based hybrid models is presented to quantify the potential risks of the wind power series. The simulation results indicate that: (1) the normalized mean absolute errors of the proposed combined model from one-step to three-step forecasting are 4.34%, 6.49% and 7.76%, respectively, which are much lower than those of the base models and the hybrid

  7. Genetic Analysis of the Mode of Interplay between an ATPase Subunit and Membrane Subunits of the Lipoprotein-Releasing ATP-Binding Cassette Transporter LolCDE†

    OpenAIRE

    Ito, Yasuko; Matsuzawa, Hitomi; Matsuyama, Shin-ichi; Narita, Shin-ichiro; Tokuda, Hajime

    2006-01-01

    The LolCDE complex, an ATP-binding cassette (ABC) transporter, releases lipoproteins from the inner membrane, thereby initiating lipoprotein sorting to the outer membrane of Escherichia coli. The LolCDE complex is composed of two copies of an ATPase subunit, LolD, and one copy each of integral membrane subunits LolC and LolE. LolD hydrolyzes ATP on the cytoplasmic side of the inner membrane, while LolC and/or LolE recognize and release lipoproteins anchored to the periplasmic leaflet of the i...

  8. In silico peptide-binding predictions of passerine MHC class I reveal similarities across distantly related species, suggesting convergence on the level of protein function.

    Science.gov (United States)

    Follin, Elna; Karlsson, Maria; Lundegaard, Claus; Nielsen, Morten; Wallin, Stefan; Paulsson, Kajsa; Westerdahl, Helena

    2013-04-01

    The major histocompatibility complex (MHC) genes are the most polymorphic genes found in the vertebrate genome, and they encode proteins that play an essential role in the adaptive immune response. Many songbirds (passerines) have been shown to have a large number of transcribed MHC class I genes compared to most mammals. To elucidate the reason for this large number of genes, we compared 14 MHC class I alleles (α1-α3 domains), from great reed warbler, house sparrow and tree sparrow, via phylogenetic analysis, homology modelling and in silico peptide-binding predictions to investigate their functional and genetic relationships. We found more pronounced clustering of the MHC class I allomorphs (allele specific proteins) in regards to their function (peptide-binding specificities) compared to their genetic relationships (amino acid sequences), indicating that the high number of alleles is of functional significance. The MHC class I allomorphs from house sparrow and tree sparrow, species that diverged 10 million years ago (MYA), had overlapping peptide-binding specificities, and these similarities across species were also confirmed in phylogenetic analyses based on amino acid sequences. Notably, there were also overlapping peptide-binding specificities in the allomorphs from house sparrow and great reed warbler, although these species diverged 30 MYA. This overlap was not found in a tree based on amino acid sequences. Our interpretation is that convergent evolution on the level of the protein function, possibly driven by selection from shared pathogens, has resulted in allomorphs with similar peptide-binding repertoires, although trans-species evolution in combination with gene conversion cannot be ruled out.

  9. Interactions of L-3,5,3'-Triiodothyronine [corrected], Allopregnanolone, and Ivermectin with the GABAA Receptor: Evidence for Overlapping Intersubunit Binding Modes.

    Science.gov (United States)

    Westergard, Thomas; Salari, Reza; Martin, Joseph V; Brannigan, Grace

    2015-01-01

    Structural mechanisms of modulation of γ-aminobutyric acid (GABA) type A receptors by neurosteroids and hormones remain unclear. The thyroid hormone L-3,5,3'-triiodothyronine (T3) inhibits GABAA receptors at micromolar concentrations and has common features with neurosteroids such as allopregnanolone (ALLOP). Here we use functional experiments on α2β1γ2 GABAA receptors expressed in Xenopus oocytes to detect competitive interactions between T3 and an agonist (ivermectin, IVM) with a crystallographically determined binding site at subunit interfaces in the transmembrane domain of a homologous receptor (glutamate-gated chloride channel, GluCl). T3 and ALLOP also show competitive effects, supporting the presence of both a T3 and ALLOP binding site at one or more subunit interfaces. Molecular dynamics (MD) simulations over 200 ns are used to investigate the dynamics and energetics of T3 in the identified intersubunit sites. In these simulations, T3 molecules occupying all intersubunit sites (with the exception of the α-β interface) display numerous energetically favorable conformations with multiple hydrogen bonding partners, including previously implicated polar/acidic sidechains and a structurally conserved deformation in the M1 backbone.

  10. Interactions of L-3,5,3'-Triiodothyronine, Allopregnanolone, and Ivermectin with the GABAA Receptor: Evidence for Overlapping Intersubunit Binding Modes

    Science.gov (United States)

    Westergard, Thomas; Salari, Reza; Martin, Joseph V.; Brannigan, Grace

    2015-01-01

    Structural mechanisms of modulation of γ-aminobutyric acid (GABA) type A receptors by neurosteroids and hormones remain unclear. The thyroid hormone L-3,5,3’-triiodothyronine (T3) inhibits GABAA receptors at micromolar concentrations and has common features with neurosteroids such as allopregnanolone (ALLOP). Here we use functional experiments on α2β1γ2 GABAA receptors expressed in Xenopus oocytes to detect competitive interactions between T3 and an agonist (ivermectin, IVM) with a crystallographically determined binding site at subunit interfaces in the transmembrane domain of a homologous receptor (glutamate-gated chloride channel, GluCl). T3 and ALLOP also show competitive effects, supporting the presence of both a T3 and ALLOP binding site at one or more subunit interfaces. Molecular dynamics (MD) simulations over 200 ns are used to investigate the dynamics and energetics of T3 in the identified intersubunit sites. In these simulations, T3 molecules occupying all intersubunit sites (with the exception of the α-β interface) display numerous energetically favorable conformations with multiple hydrogen bonding partners, including previously implicated polar/acidic sidechains and a structurally conserved deformation in the M1 backbone. PMID:26421724

  11. Dihydroquinazolines as a novel class of Trypanosoma brucei trypanothione reductase inhibitors: discovery, synthesis, and characterization of their binding mode by protein crystallography.

    Science.gov (United States)

    Patterson, Stephen; Alphey, Magnus S; Jones, Deuan C; Shanks, Emma J; Street, Ian P; Frearson, Julie A; Wyatt, Paul G; Gilbert, Ian H; Fairlamb, Alan H

    2011-10-13

    Trypanothione reductase (TryR) is a genetically validated drug target in the parasite Trypanosoma brucei , the causative agent of human African trypanosomiasis. Here we report the discovery, synthesis, and development of a novel series of TryR inhibitors based on a 3,4-dihydroquinazoline scaffold. In addition, a high resolution crystal structure of TryR, alone and in complex with substrates and inhibitors from this series, is presented. This represents the first report of a high resolution complex between a noncovalent ligand and this enzyme. Structural studies revealed that upon ligand binding the enzyme undergoes a conformational change to create a new subpocket which is occupied by an aryl group on the ligand. Therefore, the inhibitor, in effect, creates its own small binding pocket within the otherwise large, solvent exposed active site. The TryR-ligand structure was subsequently used to guide the synthesis of inhibitors, including analogues that challenged the induced subpocket. This resulted in the development of inhibitors with improved potency against both TryR and T. brucei parasites in a whole cell assay.

  12. Toward Fast and Accurate Binding Affinity Prediction with pmemdGTI: An Efficient Implementation of GPU-Accelerated Thermodynamic Integration.

    Science.gov (United States)

    Lee, Tai-Sung; Hu, Yuan; Sherborne, Brad; Guo, Zhuyan; York, Darrin M

    2017-07-11

    We report the implementation of the thermodynamic integration method on the pmemd module of the AMBER 16 package on GPUs (pmemdGTI). The pmemdGTI code typically delivers over 2 orders of magnitude of speed-up relative to a single CPU core for the calculation of ligand-protein binding affinities with no statistically significant numerical differences and thus provides a powerful new tool for drug discovery applications.

  13. MULTIPRED2: A computational system for large-scale identification of peptides predicted to bind to HLA supertypes and alleles

    DEFF Research Database (Denmark)

    Zhang, Guang Lan; DeLuca, David S.; Keskin, Derin B.

    2011-01-01

    binding peptides and immunological hotspots in an intuitive manner and also to provide a global view of results as heat maps. Another function of MULTIPRED2, which has direct relevance to vaccine design, is the calculation of population coverage. Currently it calculates population coverage in five major...... groups in North America. MULTIPRED2 is an important tool to complement wet-lab experimental methods for identification of T-cell epitopes. It is available at http://cvc.dfci.harvard.edu/multipred2/....

  14. The PRC2-binding long non-coding RNAs in human and mouse genomes are associated with predictive sequence features

    Science.gov (United States)

    Tu, Shiqi; Yuan, Guo-Cheng; Shao, Zhen

    2017-01-01

    Recently, long non-coding RNAs (lncRNAs) have emerged as an important class of molecules involved in many cellular processes. One of their primary functions is to shape epigenetic landscape through interactions with chromatin modifying proteins. However, mechanisms contributing to the specificity of such interactions remain poorly understood. Here we took the human and mouse lncRNAs that were experimentally determined to have physical interactions with Polycomb repressive complex 2 (PRC2), and systematically investigated the sequence features of these lncRNAs by developing a new computational pipeline for sequences composition analysis, in which each sequence is considered as a series of transitions between adjacent nucleotides. Through that, PRC2-binding lncRNAs were found to be associated with a set of distinctive and evolutionarily conserved sequence features, which can be utilized to distinguish them from the others with considerable accuracy. We further identified fragments of PRC2-binding lncRNAs that are enriched with these sequence features, and found they show strong PRC2-binding signals and are more highly conserved across species than the other parts, implying their functional importance.

  15. Experimental validation of plant peroxisomal targeting prediction algorithms by systematic comparison of in vivo import efficiency and in vitro PTS1 binding affinity.

    Science.gov (United States)

    Skoulding, Nicola S; Chowdhary, Gopal; Deus, Mara J; Baker, Alison; Reumann, Sigrun; Warriner, Stuart L

    2015-03-13

    Most peroxisomal matrix proteins possess a C-terminal targeting signal type 1 (PTS1). Accurate prediction of functional PTS1 sequences and their relative strength by computational methods is essential for determination of peroxisomal proteomes in silico but has proved challenging due to high levels of sequence variability of non-canonical targeting signals, particularly in higher plants, and low levels of availability of experimentally validated non-canonical examples. In this study, in silico predictions were compared with in vivo targeting analyses and in vitro thermodynamic binding of mutated variants within the context of one model targeting sequence. There was broad agreement between the methods for entire PTS1 domains and position-specific single amino acid residues, including residues upstream of the PTS1 tripeptide. The hierarchy Leu>Met>Ile>Val at the C-terminal position was determined for all methods but both experimental approaches suggest that Tyr is underweighted in the prediction algorithm due to the absence of this residue in the positive training dataset. A combination of methods better defines the score range that discriminates a functional PTS1. In vitro binding to the PEX5 receptor could discriminate among strong targeting signals while in vivo targeting assays were more sensitive, allowing detection of weak functional import signals that were below the limit of detection in the binding assay. Together, the data provide a comprehensive assessment of the factors driving PTS1 efficacy and provide a framework for the more quantitative assessment of the protein import pathway in higher plants. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. In silico simulations of STAT1 and STAT3 inhibitors predict SH2 domain cross-binding specificity.

    Science.gov (United States)

    Szelag, Malgorzata; Sikorski, Krzysztof; Czerwoniec, Anna; Szatkowska, Katarzyna; Wesoly, Joanna; Bluyssen, Hans A R

    2013-11-15

    Signal transducers and activators of transcription (STATs) comprise a family of transcription factors that are structurally related and which participate in signaling pathways activated by cytokines, growth factors and pathogens. Activation of STAT proteins is mediated by the highly conserved Src homology 2 (SH2) domain, which interacts with phosphotyrosine motifs for specific contacts between STATs and receptors and for STAT dimerization. By generating new models for human (h)STAT1, hSTAT2 and hSTAT3 we applied comparative in silico docking to determine SH2-binding specificity of the STAT3 inhibitor stattic, and of fludarabine (STAT1 inhibitor). Thus, we provide evidence that by primarily targeting the highly conserved phosphotyrosine (pY+0) SH2 binding pocket stattic is not a specific hSTAT3 inhibitor, but is equally effective towards hSTAT1 and hSTAT2. This was confirmed in Human Micro-vascular Endothelial Cells (HMECs) in vitro, in which stattic inhibited interferon-α-induced phosphorylation of all three STATs. Likewise, fludarabine inhibits both hSTAT1 and hSTAT3 phosphorylation, but not hSTAT2, by competing with the highly conserved pY+0 and pY-X binding sites, which are less well-preserved in hSTAT2. Moreover we observed that in HMECs in vitro fludarabine inhibits cytokine and lipopolysaccharide-induced phosphorylation of hSTAT1 and hSTAT3 but does not affect hSTAT2. Finally, multiple sequence alignment of STAT-SH2 domain sequences confirmed high conservation between hSTAT1 and hSTAT3, but not hSTAT2, with respect to stattic and fludarabine binding sites. Together our data offer a molecular basis that explains STAT cross-binding specificity of stattic and fludarabine, thereby questioning the present selection strategies of SH2 domain-based competitive small inhibitors. © 2013 Elsevier B.V. All rights reserved.

  17. Positive and negative ion mode comparison for the determination of DNA/peptide noncovalent binding sites through the formation of "three-body" noncovalent fragment ions.

    Science.gov (United States)

    Brahim, Bessem; Tabet, Jean-Claude; Alves, Sandra

    2018-02-01

    Gas-phase fragmentation of single strand DNA-peptide noncovalent complexes is investigated in positive and negative electrospray ionization modes.Collision-induced dissociation experiments, performed on the positively charged noncovalent complex precursor ions, have confirmed the trend previously observed in negative ion mode, i.e. a high stability of noncovalent complexes containing very basic peptidic residues (i.e. R > K) and acidic nucleotide units (i.e. Thy units), certainly incoming from the existence of salt bridge interactions. Independent of the ion polarity, stable noncovalent complex precursor ions were found to dissociate preferentially through covalent bond cleavages of the partners without disrupting noncovalent interactions. The resulting DNA fragment ions were found to be still noncovalently linked to the peptides. Additionally, the losses of an internal nucleic fragment producing "three-body" noncovalent fragment ions were also observed in both ion polarities, demonstrating the spectacular salt bridge interaction stability. The identical fragmentation patterns (regardless of the relative fragment ion abundances) observed in both polarities have shown a common location of salt bridge interaction certainly preserved from solution. Nonetheless, most abundant noncovalent fragment ions (and particularly three-body ones) are observed from positively charged noncovalent complexes. Therefore, we assume that, independent of the preexisting salt bridge interaction and zwitterion structures, multiple covalent bond cleavages from single-stranded DNA/peptide complexes rely on an excess of positive charges in both electrospray ionization ion polarities.

  18. Fuzzy Sliding Mode Observer with Grey Prediction for the Estimation of the State-of-Charge of a Lithium-Ion Battery

    Directory of Open Access Journals (Sweden)

    Daehyun Kim

    2015-11-01

    Full Text Available We propose a state-of-charge (SOC estimation method for Li-ion batteries that combines a fuzzy sliding mode observer (FSMO with grey prediction. Unlike the existing methods based on a conventional first-order sliding mode observer (SMO and an adaptive gain SMO, the proposed method eliminates chattering in SOC estimation. In this method, which uses a fuzzy inference system, the gains of the SMO are adjusted according to the predicted future error and present estimation error of the terminal voltage. To forecast the future error value, a one-step-ahead terminal voltage prediction is obtained using a grey predictor. The proposed estimation method is validated through two types of discharge tests (a pulse discharge test and a random discharge test. The SOC estimation results are compared to the results of the conventional first-order SMO-based and the adaptive gain SMO-based methods. The experimental results show that the proposed method not only reduces chattering, but also improves estimation accuracy.

  19. A model for prediction of fume formation rate in gas metal arc welding (GMAW), globular and spray modes, DC electrode positive.

    Science.gov (United States)

    Dennis, J H; Hewitt, P J; Redding, C A; Workman, A D

    2001-03-01

    Prediction of fume formation rate during metal arc welding and the composition of the fume are of interest to occupational hygienists concerned with risk assessment and to manufacturers of welding consumables. A model for GMAW (DC electrode positive) is described based on the welder determined process parameters (current, wire feed rate and wire composition), on the surface area of molten metal in the arc and on the partial vapour pressures of the component metals of the alloy wire. The model is applicable to globular and spray welding transfer modes but not to dip mode. Metal evaporation from a droplet is evaluated for short time increments and total evaporation obtained by summation over the life of the droplet. The contribution of fume derived from the weld pool and spatter (particles of metal ejected from the arc) is discussed, as are limitations of the model. Calculated droplet temperatures are similar to values determined by other workers. A degree of relationship between predicted and measured fume formation rates is demonstrated but the model does not at this stage provide a reliable predictive tool.

  20. A mode of error: Immunoglobulin binding protein (a subset of anti-citrullinated proteins can cause false positive tuberculosis test results in rheumatoid arthritis

    Directory of Open Access Journals (Sweden)

    Maria Greenwald

    2017-12-01

    Full Text Available Citrullinated Immunoglobulin Binding Protein (BiP is a newly described autoimmune target in rheumatoid arthritis (RA, one of many cyclic citrullinated peptides(CCP or ACPA. BiP is over-expressed in RA patients causing T cell expansion and increased interferon levels during incubation for the QuantiFERON-Gold tuberculosis test (QFT-G TB. The QFT-G TB has never been validated where interferon is increased by underlying disease, as for example RA.Of ACPA-positive RA patients (n = 126, we found a 13% false-positive TB test rate by QFT-G TB. Despite subsequent biologic therapy for 3 years of all 126 RA patients, none showed evidence of TB without INH. Most of the false-positive RA patients after treatment with biologic therapy reverted to a negative QFT-G test. False TB tests correlated with ACPA level (p < 0.02.Three healthy women without arthritis or TB exposure had negative QFT-G TB. In vitro, all three tested positive every time for TB correlating to the dose of BiP or anti-BiP added, at 2 ug/ml, 5 ug/ml, 10 ug/ml, and 20 ug/ml.BiP naturally found in the majority of ACPA-positive RA patients can result in a false positive QFT-G TB. Subsequent undertreatment of RA, if biologic therapy is withheld, and overtreatment of presumed latent TB may harm patients. Keywords: Tuberculosis, IGRA, Rheumatoid arthritis, Interferon, Anti-citrullinated peptide antibody (ACPA, Immunoglobulin binding protein (BiP

  1. Scale-up of counter-current chromatography: demonstration of predictable isocratic and quasi-continuous operating modes from the test tube to pilot/process scale.

    Science.gov (United States)

    Sutherland, Ian; Hewitson, Peter; Ignatova, Svetlana

    2009-12-11

    Predictable scale-up from test tube derived distribution ratios and analytical-scale sample loading optimisation is demonstrated using a model sample system of benzyl alcohol and p-cresol in a heptane:ethyl acetate:methanol:water phase system with the new 18 L Maxi counter-current chromatography centrifuge. The versatility of having a liquid stationary phase with its high loading capacity and flexible operating modes is demonstrated at two different scales by separating and concentrating target compounds using a mixture of caffeine, vanillin, naringenin and carvone using a quasi-continuous technique called intermittent counter-current extraction.

  2. Immune hierarchy among HIV-1 CD8+ T cell epitopes delivered by dendritic cells depends on MHC-I binding irrespective of mode of loading and immunization in HLA-A*0201 mice

    DEFF Research Database (Denmark)

    Kloverpris, Henrik N; Karlsson, Ingrid; Thorn, Mette

    2009-01-01

    Recent human immunodeficiency virus type 1 (HIV-1) vaccination strategies aim at targeting a broad range of cytotoxic T lymphocyte (CTL) epitopes from different HIV-1 proteins by immunization with multiple CTL epitopes simultaneously. However, this may establish an immune hierarchical response......, where the immune system responds to only a small number of the epitopes administered. To evaluate the feasibility of such vaccine strategies, we used the human leukocyte antigen (HLA)-A*0201 transgenic (tg) HHD murine in vivo model and immunized with dendritic cells pulsed with seven HIV-1-derived HLA......-gamma)-producing CD8(+) T cells, mainly focused on two of seven administered epitopes. The magnitude of individual T-cell responses induced by immunization with multiple peptides correlated with their individual immunogenicity that depended on major histocompatibility class I binding and was not influenced by mode...

  3. Resolving dual binding conformations of cellulosome cohesin-dockerin complexes using single-molecule force spectroscopy.

    Science.gov (United States)

    Jobst, Markus A; Milles, Lukas F; Schoeler, Constantin; Ott, Wolfgang; Fried, Daniel B; Bayer, Edward A; Gaub, Hermann E; Nash, Michael A

    2015-10-31

    Receptor-ligand pairs are ordinarily thought to interact through a lock and key mechanism, where a unique molecular conformation is formed upon binding. Contrary to this paradigm, cellulosomal cohesin-dockerin (Coh-Doc) pairs are believed to interact through redundant dual binding modes consisting of two distinct conformations. Here, we combined site-directed mutagenesis and single-molecule force spectroscopy (SMFS) to study the unbinding of Coh:Doc complexes under force. We designed Doc mutations to knock out each binding mode, and compared their single-molecule unfolding patterns as they were dissociated from Coh using an atomic force microscope (AFM) cantilever. Although average bulk measurements were unable to resolve the differences in Doc binding modes due to the similarity of the interactions, with a single-molecule method we were able to discriminate the two modes based on distinct differences in their mechanical properties. We conclude that under native conditions wild-type Doc from Clostridium thermocellum exocellulase Cel48S populates both binding modes with similar probabilities. Given the vast number of Doc domains with predicted dual binding modes across multiple bacterial species, our approach opens up new possibilities for understanding assembly and catalytic properties of a broad range of multi-enzyme complexes.

  4. Crystal complexes of a predicted S-adenosylmethionine-dependent methyltransferase reveal a typical AdoMet binding domain and a substrate recognition domain

    Energy Technology Data Exchange (ETDEWEB)

    Miller, D.J.; Ouellette, N.; Evodokimova, E.; Savchenko, A.; Edwards, A.; Anderson, W.F. (Toronto); (NWU)

    2010-03-08

    S-adenosyl-L-methionine-dependent methyltransferases (MTs) are abundant, and highly conserved across phylogeny. These enzymes use the cofactor AdoMet to methylate a wide variety of molecular targets, thereby modulating important cellular and metabolic activities. Thermotoga maritima protein 0872 (TM0872) belongs to a large sequence family of predicted MTs, ranging phylogenetically from relatively simple bacteria to humans. The genes for many of the bacterial homologs are located within operons involved in cell wall synthesis and cell division. Despite preliminary biochemical studies in E. coli and B. subtilis, the substrate specificity of this group of more than 150 proteins is unknown. As part of the Midwest Center for Structural Genomics initiative (www.mcsg.anl.gov), we have determined the structure of TM0872 in complexes with AdoMet and with S-adenosyl-L-homocysteine (AdoHcy). As predicted, TM0872 has a typical MT domain, and binds endogenous AdoMet, or co-crystallized AdoHcy, in a manner consistent with other known MT structures. In addition, TM0872 has a second domain that is novel among MTs in both its location in the sequence and its structure. The second domain likely acts in substrate recognition and binding, and there is a potential substrate-binding cleft spanning the two domains. This long and narrow cleft is lined with positively charged residues which are located opposite the S{sup +}-CH{sub 3} bond, suggesting that a negatively charged molecule might be targeted for catalysis. However, AdoMet and AdoHcy are both buried, and access to the methyl group would presumably require structural rearrangement. These TM0872 crystal structures offer the first structural glimpses at this phylogenetically conserved sequence family.

  5. Elucidation of the CCR1- and CCR5-binding modes of MIP-1α by application of an NMR spectra reconstruction method to the transferred cross-saturation experiments

    Energy Technology Data Exchange (ETDEWEB)

    Yoshiura, Chie; Ueda, Takumi; Kofuku, Yutaka; Matsumoto, Masahiko; Okude, Junya; Kondo, Keita; Shiraishi, Yutaro; Shimada, Ichio, E-mail: shimada@iw-nmr.f.u-tokyo.ac.jp [The University of Tokyo, Graduate School of Pharmaceutical Sciences (Japan)

    2015-12-15

    C–C chemokine receptor 1 (CCR1) and CCR5 are involved in various inflammation and immune responses, and regulate the progression of the autoimmune diseases differently. However, the number of residues identified at the binding interface was not sufficient to clarify the differences in the CCR1- and CCR5-binding modes to MIP-1α, because the NMR measurement time for CCR1 and CCR5 samples was limited to 24 h, due to their low stability. Here we applied a recently developed NMR spectra reconstruction method, Conservation of experimental data in ANAlysis of FOuRier, to the amide-directed transferred cross-saturation experiments of chemokine receptors, CCR1 and CCR5, embedded in lipid bilayers of the reconstituted high density lipoprotein, and MIP-1α. Our experiments revealed that the residues on the N-loop and β-sheets of MIP-1α are close to both CCR1 and CCR5, and those in the C-terminal helix region are close to CCR5. These results suggest that the genetic influence of the single nucleotide polymorphisms of MIP-1α that accompany substitution of residues in the C-terminal helix region, E57 and V63, would provide clues toward elucidating how the CCR5–MIP-1α interaction affects the progress of autoimmune diseases.

  6. Soaking suggests "alternative facts": Only co-crystallization discloses major ligand-induced interface rearrangements of a homodimeric tRNA-binding protein indicating a novel mode-of-inhibition.

    Directory of Open Access Journals (Sweden)

    Frederik Rainer Ehrmann

    Full Text Available For the efficient pathogenesis of Shigella, the causative agent of bacillary dysentery, full functionality of tRNA-guanine transglycosylase (TGT is mandatory. TGT performs post-transcriptional modifications of tRNAs in the anticodon loop taking impact on virulence development. This suggests TGT as a putative target for selective anti-shigellosis drug therapy. Since bacterial TGT is only functional as homodimer, its activity can be inhibited either by blocking its active site or by preventing dimerization. Recently, we discovered that in some crystal structures obtained by soaking the full conformational adaptation most likely induced in solution upon ligand binding is not displayed. Thus, soaked structures may be misleading and suggest irrelevant binding modes. Accordingly, we re-investigated these complexes by co-crystallization. The obtained structures revealed large conformational rearrangements not visible in the soaked complexes. They result from spatial perturbations in the ribose-34/phosphate-35 recognition pocket and, consequently, an extended loop-helix motif required to prevent access of water molecules into the dimer interface loses its geometric integrity. Thermodynamic profiles of ligand binding in solution indicate favorable entropic contributions to complex formation when large conformational adaptations in the dimer interface are involved. Native MS titration experiments reveal the extent to which the homodimer is destabilized in the presence of each inhibitor. Unexpectedly, one ligand causes a complete rearrangement of subunit packing within the homodimer, never observed in any other TGT crystal structure before. Likely, this novel twisted dimer is catalytically inactive and, therefore, suggests that stabilizing this non-productive subunit arrangement may be used as a further strategy for TGT inhibition.

  7. Methods for Real-Time Prediction of the Mode of Travel Using Smartphone-Based GPS and Accelerometer Data.

    Science.gov (United States)

    Martin, Bryan D; Addona, Vittorio; Wolfson, Julian; Adomavicius, Gediminas; Fan, Yingling

    2017-09-08

    We propose and compare combinations of several methods for classifying transportation activity data from smartphone GPS and accelerometer sensors. We have two main objectives. First, we aim to classify our data as accurately as possible. Second, we aim to reduce the dimensionality of the data as much as possible in order to reduce the computational burden of the classification. We combine dimension reduction and classification algorithms and compare them with a metric that balances accuracy and dimensionality. In doing so, we develop a classification algorithm that accurately classifies five different modes of transportation (i.e., walking, biking, car, bus and rail) while being computationally simple enough to run on a typical smartphone. Further, we use data that required no behavioral changes from the smartphone users to collect. Our best classification model uses the random forest algorithm to achieve 96.8% accuracy.

  8. Retention prediction of highly polar ionizable solutes under gradient conditions on a mixed-mode reversed-phase and weak anion-exchange stationary phase.

    Science.gov (United States)

    Balkatzopoulou, P; Fasoula, S; Gika, H; Nikitas, P; Pappa-Louisi, A

    2015-05-29

    In the present work the retention of three highly polar and ionizable solutes - uric acid, nicotinic acid and ascorbic acid - was investigated on a mixed-mode reversed-phase and weak anion-exchange (RP/WAX) stationary phase in buffered aqueous acetonitrile (ACN) mobile phases. A U-shaped retention behavior was observed for all solutes with respect to the eluent organic modifier content studied in a range of 5-95% (v/v). This retention behavior clearly demonstrates the presence of a HILIC-type retention mechanism at ACN-rich hydro-organic eluents and an RP-like retention at aqueous-rich hydro-organic eluents. Hence, this column should be promising for application under both RP and HILIC gradient elution modes. For this reason, a series of programmed elution runs were carried out with increasing (RP) and decreasing (HILIC) organic solvent concentration in the mobile phase. This dual gradient process was successfully modeled by two retention models exhibiting a quadratic or a cubic dependence of the logarithm of the solute retention factor (lnk) upon the organic modifier volume fraction (φ). It was found that both models produced by gradient retention data allow the prediction of solute retention times for both types of programmed elution on the mixed-mode column. Four, in the case of the quadratic model, or five, in the case of the cubic model, initial HILIC- and RP-type gradient runs gave satisfactory retention predictions of any similar kind elution program, even with different flow rate, with an overall error of only 2.5 or 1.7%, respectively. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Predicting treatment response in Schizophrenia: the role of stratal and frontal dopamine D2/D3 receptor binding potential

    DEFF Research Database (Denmark)

    Wulff, Sanne; Nørbak-Emig, Henrik; Nielsen, Mette Ødegaard

    2014-01-01

    Background One of the best validated findings in schizophrenia is an association between increased presynaptic striatal dopaminergic activity and psychotic symptoms. We have previously reported an association between positive symptoms and dopamine D2 receptor binding potentials (BPs) in frontal...... cortex in antipsychotic-naïve first-episode male schizophrenia patients(1). Preclinical studies suggest an inverse relationship between frontal and striatal dopamine activity. This activity can indirectly be expressed by the BP of dopamine receptors using Single Photon Emission Computed Tomography (SPECT......) where low striatal BP is believed to reflect high dopamine availability. We aim to assess the association between D2 receptor BPs in antipsychotic-naïve first-episode schizophrenia patients and their response to the first treatment with an antipsychotic compound. We hypothesise that patients with low...

  10. Thermodynamic analysis of water molecules at the surface of proteins and applications to binding site prediction and characterization.

    Science.gov (United States)

    Beuming, Thijs; Che, Ye; Abel, Robert; Kim, Byungchan; Shanmugasundaram, Veerabahu; Sherman, Woody

    2012-03-01

    Water plays an essential role in determining the structure and function of all biological systems. Recent methodological advances allow for an accurate and efficient estimation of the thermodynamic properties of water molecules at the surface of proteins. In this work, we characterize these thermodynamic properties and relate them to various structural and functional characteristics of the protein. We find that high-energy hydration sites often exist near protein motifs typically characterized as hydrophilic, such as backbone amide groups. We also find that waters around alpha helices and beta sheets tend to be less stable than waters around loops. Furthermore, we find no significant correlation between the hydration site-free energy and the solvent accessible surface area of the site. In addition, we find that the distribution of high-energy hydration sites on the protein surface can be used to identify the location of binding sites and that binding sites of druggable targets tend to have a greater density of thermodynamically unstable hydration sites. Using this information, we characterize the FKBP12 protein and show good agreement between fragment screening hit rates from NMR spectroscopy and hydration site energetics. Finally, we show that water molecules observed in crystal structures are less stable on average than bulk water as a consequence of the high degree of spatial localization, thereby resulting in a significant loss in entropy. These findings should help to better understand the characteristics of waters at the surface of proteins and are expected to lead to insights that can guide structure-based drug design efforts. Copyright © 2011 Wiley Periodicals, Inc.

  11. Identification and Validation of Novel Hedgehog-Responsive Enhancers Predicted by Computational Analysis of Ci/Gli Binding Site Density

    Science.gov (United States)

    Richards, Neil; Parker, David S.; Johnson, Lisa A.; Allen, Benjamin L.; Barolo, Scott; Gumucio, Deborah L.

    2015-01-01

    The Hedgehog (Hh) signaling pathway directs a multitude of cellular responses during embryogenesis and adult tissue homeostasis. Stimulation of the pathway results in activation of Hh target genes by the transcription factor Ci/Gli, which binds to specific motifs in genomic enhancers. In Drosophila, only a few enhancers (patched, decapentaplegic, wingless, stripe, knot, hairy, orthodenticle) have been shown by in vivo functional assays to depend on direct Ci/Gli regulation. All but one (orthodenticle) contain more than one Ci/Gli site, prompting us to directly test whether homotypic clustering of Ci/Gli binding sites is sufficient to define a Hh-regulated enhancer. We therefore developed a computational algorithm to identify Ci/Gli clusters that are enriched over random expectation, within a given region of the genome. Candidate genomic regions containing Ci/Gli clusters were functionally tested in chicken neural tube electroporation assays and in transgenic flies. Of the 22 Ci/Gli clusters tested, seven novel enhancers (and the previously known patched enhancer) were identified as Hh-responsive and Ci/Gli-dependent in one or both of these assays, including: Cuticular protein 100A (Cpr100A); invected (inv), which encodes an engrailed-related transcription factor expressed at the anterior/posterior wing disc boundary; roadkill (rdx), the fly homolog of vertebrate Spop; the segment polarity gene gooseberry (gsb); and two previously untested regions of the Hh receptor-encoding patched (ptc) gene. We conclude that homotypic Ci/Gli clustering is not sufficient information to ensure Hh-responsiveness; however, it can provide a clue for enhancer recognition within putative Hedgehog target gene loci. PMID:26710299

  12. Impulsive Stimulated Light Scattering Studies of the Liquid-Glass Transition: on the Experimental Verification of Mode-Coupling Theory Predictions.

    Science.gov (United States)

    Halalay, Ion C.

    A study of the structural glass transition trough impulsive stimulated light scattering experiments has been carried out in concentrated aqueous lithium chloride solutions, at temperatures ranging from ambient to cryogenic. A specially designed sample cell made it possible to cover the whole temperature interval from simple liquid, to viscoelastic supercooled liquid, to glass. It is shown that a phenomenological description of the results of these experiments in terms of a spectrum of relaxation times through the use of a Kohlrausch-Williams-Watts relaxation function is inadequate. Based on predictions of mode-coupling theory of the liquid-glass transition, an alternative approach to data interpretation is proposed. It is shown that for an aqueous lithium chloride solution, the prediction of simple scaling and identical scaling for mechanical and electrical susceptibilities seems to be valid. However, another prediction of theory is called into question: instead of a power-law behavior on temperature difference, it is found experimentally that the behavior of the susceptibility spectrum minimum is exponential. Similar disagreements are found for other two materials, triphenyl phosphite and polypropylene oxide. The causes for these discrepancies are discussed and it is concluded that additional experimentation is necessary to verify theoretical claims. Experiments are proposed which can test these predictions and serve as guide for the construction of theoretical models for the glass transition in real systems. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617 -253-5668; Fax 617-253-1690.).

  13. Near State Vector Selection-Based Model Predictive Control with Common Mode Voltage Mitigation for a Three-Phase Four-Leg Inverter

    Directory of Open Access Journals (Sweden)

    Abdul Mannan Dadu

    2017-12-01

    Full Text Available A high computational burden is required in conventional model predictive control, as all of the voltage vectors of a power inverter are used to predict the future behavior of the system. Apart from that, the common mode voltage (CMV of a three-phase four-leg inverter utilizes up to half of the DC-link voltage due to the use of all of the available voltage vectors. Thus, this paper proposes a near state vector selection-based model predictive control (NSV-MPC scheme to mitigate the CMV and reduce computational burden. In the proposed technique, only six active voltage vectors are used in the predictive model, and the vectors are selected based on the position of the future reference vector. In every sampling period, the position of the reference current is used to detect the voltage vectors surrounding the reference voltage vector. Besides the six active vectors, one of the zero vectors is also used. The proposed technique is compared with the conventional control scheme in terms of execution time, CMV variation, and load current ripple in both simulation and an experimental setup. The LabVIEW Field programmable gate array rapid prototyping controller is used to validate the proposed control scheme experimentally, and demonstrate that the CMV can be bounded within one-fourth of the DC-link voltage.

  14. Expression of Cry1Ac toxin-binding region in Plutella xyllostella cadherin-like receptor and studying their interaction mode by molecular docking and site-directed mutagenesis.

    Science.gov (United States)

    Hu, Xiaodan; Zhang, Xiao; Zhong, Jianfeng; Liu, Yuan; Zhang, Cunzheng; Xie, Yajing; Lin, Manman; Xu, Chongxin; Lu, Lina; Zhu, Qing; Liu, Xianjin

    2018-05-01

    Cadherin-like protein has been identified as the primary Bacillus thuringiensis (Bt) Cry toxin receptor in Lepidoptera pests and plays a key role in Cry toxin insecticidal. In this study, we successfully expressed the putative Cry1Ac toxin-binding region (CR7-CR11) of Plutella xylostella cadherin-like in Escherichia coli BL21 (DE3). The expressed CR7-CR11 fragment showed binding ability to Cry1Ac toxin under denaturing (Ligand blot) and non-denaturing (ELISA) conditions. The three-dimensional structure of CR7-CR11 was constructed by homology modeling. Molecular docking results of CR7-CR11 and Cry1Ac showed that domain II and domain III of Cry1Ac were taking part in binding to CR7-CR11, while CR7-CR8 was the region of CR7-CR11 in interacting with Cry1Ac. The interaction of toxin-receptor complex was found to arise from hydrogen bond and hydrophobic interaction. Through the computer-aided alanine mutation scanning, amino acid residues of Cry1Ac (Met341, Asn442 and Ser486) and CR7-CR11 (Asp32, Arg101 and Arg127) were predicted as the hot spot residues involved in the interaction of the toxin-receptor complex. At last, we verified the importance role of these key amino acid residues by binding assay. These results will lay a foundation for further elucidating the insecticidal mechanism of Cry toxin and enhancing Cry toxin insecticidal activity by molecular modification. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Accurate and sensitive quantification of protein-DNA binding affinity.

    Science.gov (United States)

    Rastogi, Chaitanya; Rube, H Tomas; Kribelbauer, Judith F; Crocker, Justin; Loker, Ryan E; Martini, Gabriella D; Laptenko, Oleg; Freed-Pastor, William A; Prives, Carol; Stern, David L; Mann, Richard S; Bussemaker, Harmen J

    2018-04-17

    Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes. Copyright © 2018 the Author(s). Published by PNAS.

  16. The ties that bind: genetic relatedness predicts the fission and fusion of social groups in wild African elephants.

    Science.gov (United States)

    Archie, Elizabeth A; Moss, Cynthia J; Alberts, Susan C

    2006-03-07

    Many social animals live in stable groups. In contrast, African savannah elephants (Loxodonta africana) live in unusually fluid, fission-fusion societies. That is, 'core' social groups are composed of predictable sets of individuals; however, over the course of hours or days, these groups may temporarily divide and reunite, or they may fuse with other social groups to form much larger social units. Here, we test the hypothesis that genetic relatedness predicts patterns of group fission and fusion among wild, female African elephants. Our study of a single Kenyan population spans 236 individuals in 45 core social groups, genotyped at 11 microsatellite and one mitochondrial DNA (mtDNA) locus. We found that genetic relatedness predicted group fission; adult females remained with their first order maternal relatives when core groups fissioned temporarily. Relatedness also predicted temporary fusion between social groups; core groups were more likely to fuse with each other when the oldest females in each group were genetic relatives. Groups that shared mtDNA haplotypes were also significantly more likely to fuse than groups that did not share mtDNA. Our results suggest that associations between core social groups persist for decades after the original maternal kin have died. We discuss these results in the context of kin selection and its possible role in the evolution of elephant sociality.

  17. Production in Pichia pastoris, antifungal activity and crystal structure of a class I chitinase from cowpea (Vigna unguiculata): Insights into sugar binding mode and hydrolytic action.

    Science.gov (United States)

    Landim, Patrícia G Castro; Correia, Tuana O; Silva, Fredy D A; Nepomuceno, Denise R; Costa, Helen P S; Pereira, Humberto M; Lobo, Marina D P; Moreno, Frederico B M B; Brandão-Neto, José; Medeiros, Suelen C; Vasconcelos, Ilka M; Oliveira, José T A; Sousa, Bruno L; Barroso-Neto, Ito L; Freire, Valder N; Carvalho, Cristina P S; Monteiro-Moreira, Ana C O; Grangeiro, Thalles B

    2017-04-01

    A cowpea class I chitinase (VuChiI) was expressed in the methylotrophic yeast P. pastoris. The recombinant protein was secreted into the culture medium and purified by affinity chromatography on a chitin matrix. The purified chitinase migrated on SDS-polyacrylamide gel electrophoresis as two closely-related bands with apparent molecular masses of 34 and 37 kDa. The identity of these bands as VuChiI was demonstrated by mass spectrometry analysis of tryptic peptides and N-terminal amino acid sequencing. The recombinant chitinase was able to hydrolyze colloidal chitin but did not exhibit enzymatic activity toward synthetic substrates. The highest hydrolytic activity of the cowpea chitinase toward colloidal chitin was observed at pH 5.0. Furthermore, most VuChiI activity (approximately 92%) was retained after heating to 50 °C for 30 min, whereas treatment with 5 mM Cu 2+ caused a reduction of 67% in the enzyme's chitinolytic activity. The recombinant protein had antifungal activity as revealed by its ability to inhibit the spore germination and mycelial growth of Penicillium herquei. The three-dimensional structure of VuChiI was resolved at a resolution of 1.55 Å by molecular replacement. The refined model had 245 amino acid residues and 381 water molecules, and the final R-factor and R free values were 14.78 and 17.22%, respectively. The catalytic domain of VuChiI adopts an α-helix-rich fold, stabilized by 3 disulfide bridges and possessing a wide catalytic cleft. Analysis of the crystallographic model and molecular docking calculations using chito-oligosaccharides provided evidences about the VuChiI residues involved in sugar binding and catalysis, and a possible mechanism of antifungal action is suggested. Copyright © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

  18. D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies

    Scienc