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

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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.

The interrelationship between ligand binding and thermal unfolding of the folate binding protein. The role of self-association and pH

DEFF Research Database (Denmark)

Holm, Jan; Babol, Linnea N.; Markova, Natalia

2014-01-01

The present study utilized a combination of DLS (dynamic light scattering) and DSC (differential scanning calorimetry) to address thermostability of high-affinity folate binding protein (FBP), a transport protein and cellular receptor for the vitamin folate. At pH7.4 (pI=7-8) ligand binding......, intermolecular forces involved in concentration-dependent multimerization thus contribute to the thermostability of holo-FBP. Hence, thermal unfolding and dissociation of holo-FBP multimers occur simultaneously consistent with a gradual decrease from octameric to monomeric holo-FBP (10μM) in DLS after a step-wise...

Structural and binding studies of a C-type galactose-binding lectin from Bothrops jararacussu snake venom.

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Sartim, Marco A; Pinheiro, Matheus P; de Pádua, Ricardo A P; Sampaio, Suely V; Nonato, M Cristina

2017-02-01

BJcuL is a snake venom galactoside-binding lectin (SVgalL) isolated from Bothrops jararacussu and is involved in a wide variety of biological activities including triggering of pro-inflammatory response, disruption of microbial biofilm structure and induction of apoptosis. In the present work, we determined the crystallographic structure of BJcuL, the first holo structure of a SVgalL, and introduced the fluorescence-based thermal stability assay (Thermofluor) as a tool for screening and characterization of the binding mechanism of SVgalL ligands. BJcuL structure revealed the existence of a porous and flexible decameric arrangement composed of disulfide-linked dimers related by a five-fold symmetry. Each monomer contains the canonical carbohydrate recognition domain, a calcium ion required for BJcuL lectinic activity and a sodium ion required for protein stabilization. BJcuL thermostability was found to be induced by calcium ion and galactoside sugars which exhibit hyperbolic saturation profiles dependent on ligand concentration. Serendipitously, the gentamicin group of aminoglycoside antibiotics (gAGAs) was also identified as BJcuL ligands. On contrast, gAGAs exhibited a sigmoidal saturation profile compatible with a cooperative mechanism of binding. Thermofluor, hemagglutination inhibition assay and molecular docking strategies were used to identify a distinct binding site in BJcuL localized at the dimeric interface near the fully conserved intermolecular Cys86-Cys86 disulfide bond. The hybrid approach used in the present work provided novel insights into structural behavior and functional diversification of SVgaLs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Augmented Reality Technology Using Microsoft HoloLens in Anatomic Pathology.

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Hanna, Matthew G; Ahmed, Ishtiaque; Nine, Jeffrey; Prajapati, Shyam; Pantanowitz, Liron

2018-05-01

Context Augmented reality (AR) devices such as the Microsoft HoloLens have not been well used in the medical field. Objective To test the HoloLens for clinical and nonclinical applications in pathology. Design A Microsoft HoloLens was tested for virtual annotation during autopsy, viewing 3D gross and microscopic pathology specimens, navigating whole slide images, telepathology, as well as real-time pathology-radiology correlation. Results Pathology residents performing an autopsy wearing the HoloLens were remotely instructed with real-time diagrams, annotations, and voice instruction. 3D-scanned gross pathology specimens could be viewed as holograms and easily manipulated. Telepathology was supported during gross examination and at the time of intraoperative consultation, allowing users to remotely access a pathologist for guidance and to virtually annotate areas of interest on specimens in real-time. The HoloLens permitted radiographs to be coregistered on gross specimens and thereby enhanced locating important pathologic findings. The HoloLens also allowed easy viewing and navigation of whole slide images, using an AR workstation, including multiple coregistered tissue sections facilitating volumetric pathology evaluation. Conclusions The HoloLens is a novel AR tool with multiple clinical and nonclinical applications in pathology. The device was comfortable to wear, easy to use, provided sufficient computing power, and supported high-resolution imaging. It was useful for autopsy, gross and microscopic examination, and ideally suited for digital pathology. Unique applications include remote supervision and annotation, 3D image viewing and manipulation, telepathology in a mixed-reality environment, and real-time pathology-radiology correlation.

Binding and Endocytosis of Bovine Hololactoferrin by the Parasite Entamoeba histolytica

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Guillermo Ortíz-Estrada

2015-01-01

Full Text Available Entamoeba histolytica is a human parasite that requires iron (Fe for its metabolic function and virulence. Bovine lactoferrin (B-Lf and its peptides can be found in the digestive tract after dairy products are ingested. The aim of this study was to compare virulent trophozoites recently isolated from hamster liver abscesses with nonvirulent trophozoites maintained for more than 30 years in cultures in vitro regarding their interaction with iron-charged B-Lf (B-holo-Lf. We performed growth kinetics analyses of trophozoites in B-holo-Lf and throughout several consecutive transfers. The virulent parasites showed higher growth and tolerance to iron than nonvirulent parasites. Both amoeba variants specifically bound B-holo-Lf with a similar Kd. However, averages of 9.45 × 105 and 6.65 × 106 binding sites/cell were found for B-holo-Lf in nonvirulent and virulent amoebae, respectively. Virulent amoebae bound more efficiently to human and bovine holo-Lf, human holo-transferrin, and human and bovine hemoglobin than nonvirulent amoebae. Virulent amoebae showed two types of B-holo-Lf binding proteins. Although both amoebae endocytosed this glycoprotein through clathrin-coated vesicles, the virulent amoebae also endocytosed B-holo-Lf through a cholesterol-dependent mechanism. Both amoeba variants secreted cysteine proteases cleaving B-holo-Lf. These data demonstrate that the B-Lf endocytosis is more efficient in virulent amoebae.

Binding and Endocytosis of Bovine Hololactoferrin by the Parasite Entamoeba histolytica.

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Ortíz-Estrada, Guillermo; Calderón-Salinas, Víctor; Shibayama-Salas, Mineko; León-Sicairos, Nidia; de la Garza, Mireya

2015-01-01

Entamoeba histolytica is a human parasite that requires iron (Fe) for its metabolic function and virulence. Bovine lactoferrin (B-Lf) and its peptides can be found in the digestive tract after dairy products are ingested. The aim of this study was to compare virulent trophozoites recently isolated from hamster liver abscesses with nonvirulent trophozoites maintained for more than 30 years in cultures in vitro regarding their interaction with iron-charged B-Lf (B-holo-Lf). We performed growth kinetics analyses of trophozoites in B-holo-Lf and throughout several consecutive transfers. The virulent parasites showed higher growth and tolerance to iron than nonvirulent parasites. Both amoeba variants specifically bound B-holo-Lf with a similar K d . However, averages of 9.45 × 10(5) and 6.65 × 10(6) binding sites/cell were found for B-holo-Lf in nonvirulent and virulent amoebae, respectively. Virulent amoebae bound more efficiently to human and bovine holo-Lf, human holo-transferrin, and human and bovine hemoglobin than nonvirulent amoebae. Virulent amoebae showed two types of B-holo-Lf binding proteins. Although both amoebae endocytosed this glycoprotein through clathrin-coated vesicles, the virulent amoebae also endocytosed B-holo-Lf through a cholesterol-dependent mechanism. Both amoeba variants secreted cysteine proteases cleaving B-holo-Lf. These data demonstrate that the B-Lf endocytosis is more efficient in virulent amoebae.

Ligand Binding Induces Conformational Changes in Human Cellular Retinol-binding Protein 1 (CRBP1) Revealed by Atomic Resolution Crystal Structures.

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Silvaroli, Josie A; Arne, Jason M; Chelstowska, Sylwia; Kiser, Philip D; Banerjee, Surajit; Golczak, Marcin

2016-04-15

Important in regulating the uptake, storage, and metabolism of retinoids, cellular retinol-binding protein 1 (CRBP1) is essential for trafficking vitamin A through the cytoplasm. However, the molecular details of ligand uptake and targeted release by CRBP1 remain unclear. Here we report the first structure of CRBP1 in a ligand-free form as well as ultra-high resolution structures of this protein bound to either all-trans-retinol or retinylamine, the latter a therapeutic retinoid that prevents light-induced retinal degeneration. Superpositioning of human apo- and holo-CRBP1 revealed major differences within segments surrounding the entrance to the retinoid-binding site. These included α-helix II and hairpin turns between β-strands βC-βD and βE-βF as well as several side chains, such as Phe-57, Tyr-60, and Ile-77, that change their orientations to accommodate the ligand. Additionally, we mapped hydrogen bond networks inside the retinoid-binding cavity and demonstrated their significance for the ligand affinity. Analyses of the crystallographic B-factors indicated several regions with higher backbone mobility in the apoprotein that became more rigid upon retinoid binding. This conformational flexibility of human apo-CRBP1 facilitates interaction with the ligands, whereas the more rigid holoprotein structure protects the labile retinoid moiety during vitamin A transport. These findings suggest a mechanism of induced fit upon ligand binding by mammalian cellular retinol-binding proteins. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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

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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.

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

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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.

Canadian Whole-Farm Model Holos - Development, Stakeholder Involvement, and Model Application

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Kroebel, R.; Janzen, H.; Beauchemin, K. A.

2017-12-01

modelling approach based on the ICBM model. Also under development are sub-models to predict ammonia volatilization and water budgets. Development of Holos is expected to continue, forging an interactive link between ongoing research and the interests of stakeholders in an ever-changing agricultural environment.

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

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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.

Structure of the plasminogen kringle 4 binding calcium-free form of the C-type lectin-like domain of tetranectin

DEFF Research Database (Denmark)

Nielbo, Steen Günther; Thomsen, J.K.; Graversen, J. H.

2004-01-01

. A conserved proline, which was found to be in the cis conformation in holoTN3, is in apoTN3 predominantly in the trans conformation. Backbone dynamics indicate that, in apoTN3 especially, two of the three calcium-binding loops and two of the three K4-binding residues exhibit increased flexibility, whereas...

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

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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.

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

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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.

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

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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.

Holographic Rovers: Augmented Reality and the Microsoft HoloLens

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Toler, Laura

2017-01-01

Augmented Reality is an emerging field in technology, and encompasses Head Mounted Displays, smartphone apps, and even projected images. HMDs include the Meta 2, Magic Leap, Avegant Light Field, and the Microsoft HoloLens, which is evaluated specifically. The Microsoft HoloLens is designed to be used as an AR personal computer, and is being optimized with that goal in mind. Microsoft allied with the Unity3D game engine to create an SDK for interested application developers that can be used in the Unity environment.

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

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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.

An Overview of the Prediction of Protein DNA-Binding Sites

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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.

Interactive Molecular Graphics for Augmented Reality Using HoloLens.

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Müller, Christoph; Krone, Michael; Huber, Markus; Biener, Verena; Herr, Dominik; Koch, Steffen; Reina, Guido; Weiskopf, Daniel; Ertl, Thomas

2018-06-13

Immersive technologies like stereo rendering, virtual reality, or augmented reality (AR) are often used in the field of molecular visualisation. Modern, comparably lightweight and affordable AR headsets like Microsoft's HoloLens open up new possibilities for immersive analytics in molecular visualisation. A crucial factor for a comprehensive analysis of molecular data in AR is the rendering speed. HoloLens, however, has limited hardware capabilities due to requirements like battery life, fanless cooling and weight. Consequently, insights from best practises for powerful desktop hardware may not be transferable. Therefore, we evaluate the capabilities of the HoloLens hardware for modern, GPU-enabled, high-quality rendering methods for the space-filling model commonly used in molecular visualisation. We also assess the scalability for large molecular data sets. Based on the results, we discuss ideas and possibilities for immersive molecular analytics. Besides more obvious benefits like the stereoscopic rendering offered by the device, this specifically includes natural user interfaces that use physical navigation instead of the traditional virtual one. Furthermore, we consider different scenarios for such an immersive system, ranging from educational use to collaborative scenarios.

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

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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.

Modulation of microtubule assembly by the HIV-1 Tat protein is strongly dependent on zinc binding to Tat

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Muller Sylviane

2008-07-01

Full Text Available Abstract Background During HIV-1 infection, the Tat protein plays a key role by transactivating the transcription of the HIV-1 proviral DNA. In addition, Tat induces apoptosis of non-infected T lymphocytes, leading to a massive loss of immune competence. This apoptosis is notably mediated by the interaction of Tat with microtubules, which are dynamic components essential for cell structure and division. Tat binds two Zn2+ ions through its conserved cysteine-rich region in vitro, but the role of zinc in the structure and properties of Tat is still controversial. Results To investigate the role of zinc, we first characterized Tat apo- and holo-forms by fluorescence correlation spectroscopy and time-resolved fluorescence spectroscopy. Both of the Tat forms are monomeric and poorly folded but differ by local conformational changes in the vicinity of the cysteine-rich region. The interaction of the two Tat forms with tubulin dimers and microtubules was monitored by analytical ultracentrifugation, turbidity measurements and electron microscopy. At 20°C, both of the Tat forms bind tubulin dimers, but only the holo-Tat was found to form discrete complexes. At 37°C, both forms promoted the nucleation and increased the elongation rates of tubulin assembly. However, only the holo-Tat increased the amount of microtubules, decreased the tubulin critical concentration, and stabilized the microtubules. In contrast, apo-Tat induced a large amount of tubulin aggregates. Conclusion Our data suggest that holo-Tat corresponds to the active form, responsible for the Tat-mediated apoptosis.

FEI Titan G2 60-300 HOLO

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Chris Boothroyd

2016-02-01

Full Text Available The FEI Titan G2 60-300 HOLO is a unique fourth generation transmission electron microscope, which has been specifically designed for the investigation of electromagnetic fields of materials using off-axis electron holography. It has a Lorentz lens to allow magnetic field free imaging plus two electron biprisms, which in combination enable more uniform holographic fringes to be used. The instrument also has an ultra-wide objective lens pole piece gap which is ideal for in situ experiments. For these purposes, the FEI Titan G2 60-300 HOLO is equipped with a Schottky type high-brightness electron gun (FEI X-FEG, an image Cs corrector (CEOS, a post-column energy filter system (Gatan Tridiem 865 ER as well as a 4 megapixel CCD system (Gatan UltraScan 1000 XP. Typical examples of use and technical specifications for the instrument are given below.

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

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

2015-06-01

most performance measures. To the best of our knowledge, this is the first sequence-based prediction of protein-binding nucleotides in RNA which considers the binding partner of RNA. The new model will provide valuable information for designing biochemical experiments to find putative protein-binding sites in RNA with unknown structure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Prediction of GPCR-Ligand Binding Using Machine Learning Algorithms

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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.

Knowledge-based Fragment Binding Prediction

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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

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

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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.

Holo-transcobalamin is an indicator of vitamin B-12 absorption in healthy adults with adequate vitamin B-12 status

DEFF Research Database (Denmark)

von Castel-Roberts, Kristina M; Mørkbak, Anne Louise; Nexo, Ebba

2007-01-01

BACKGROUND: It has been hypothesized that the response of holo-transcobalamin (holo-TC) to oral vitamin B-12 may be used to assess absorption. To develop a reliable clinical absorption test that uses holo-TC, it is necessary to determine the optimal timeline for vitamin B-12 administration...... and postdose assessment. OBJECTIVE: The objective of this study was to assess the magnitude and patterns of change in the postabsorption response of holo-TC to oral vitamin B-12. DESIGN: Adult (18-49 y) male and female participants (n = 21) with normal vitamin B-12 status were given three 9-mug doses...... of vitamin B-12 at 6-h intervals beginning early morning (baseline) on day 1. Blood was drawn at 17 timed intervals over the course of 3 d for the analysis of holo-TC and other indicators of vitamin B-12 status. RESULTS: Mean holo-TC increased significantly (P

Probing the 3-D Structure, Dynamics, and Stability of Bacterial Collagenase Collagen Binding Domain (apo- versus holo-) by Limited Proteolysis MALDI-TOF MS

Science.gov (United States)

Sides, Cynthia R.; Liyanage, Rohana; Lay, Jackson O.; Philominathan, Sagaya Theresa Leena; Matsushita, Osamu; Sakon, Joshua

2012-03-01

Pairing limited proteolysis and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) to probe clostridial collagenase collagen binding domain (CBD) reveals the solution dynamics and stability of the protein, as these factors are crucial to CBD effectiveness as a drug-delivery vehicle. MS analysis of proteolytic digests indicates initial cleavage sites, thereby specifying the less stable and highly accessible regions of CBD. Modulation of protein structure and stability upon metal binding is shown through MS analysis of calcium-bound and cobalt-bound CBD proteolytic digests. Previously determined X-ray crystal structures illustrate that calcium binding induces secondary structure transformation in the highly mobile N-terminal arm and increases protein stability. MS-based detection of exposed residues confirms protein flexibility, accentuates N-terminal dynamics, and demonstrates increased global protein stability exported by calcium binding. Additionally, apo- and calcium-bound CBD proteolysis sites correlate well with crystallographic B-factors, accessibility, and enzyme specificity. MS-observed cleavage sites with no clear correlations are explained either by crystal contacts of the X-ray crystal structures or by observed differences between Molecules A and B in the X-ray crystal structures. The study newly reveals the absence of the βA strand and thus the very dynamic N-terminal linker, as corroborated by the solution X-ray scattering results. Cobalt binding has a regional effect on the solution phase stability of CBD, as limited proteolysis data implies the capture of an intermediate-CBD solution structure when cobalt is bound.

The crystal structures of apo and cAMP-bound GlxR from Corynebacterium glutamicum reveal structural and dynamic changes upon cAMP binding in CRP/FNR family transcription factors.

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Philip D Townsend

Full Text Available The cyclic AMP-dependent transcriptional regulator GlxR from Corynebacterium glutamicum is a member of the super-family of CRP/FNR (cyclic AMP receptor protein/fumarate and nitrate reduction regulator transcriptional regulators that play central roles in bacterial metabolic regulatory networks. In C. glutamicum, which is widely used for the industrial production of amino acids and serves as a non-pathogenic model organism for members of the Corynebacteriales including Mycobacterium tuberculosis, the GlxR homodimer controls the transcription of a large number of genes involved in carbon metabolism. GlxR therefore represents a key target for understanding the regulation and coordination of C. glutamicum metabolism. Here we investigate cylic AMP and DNA binding of GlxR from C. glutamicum and describe the crystal structures of apo GlxR determined at a resolution of 2.5 Å, and two crystal forms of holo GlxR at resolutions of 2.38 and 1.82 Å, respectively. The detailed structural analysis and comparison of GlxR with CRP reveals that the protein undergoes a distinctive conformational change upon cyclic AMP binding leading to a dimer structure more compatible to DNA-binding. As the two binding sites in the GlxR homodimer are structurally identical dynamic changes upon binding of the first ligand are responsible for the allosteric behavior. The results presented here show how dynamic and structural changes in GlxR lead to optimization of orientation and distance of its two DNA-binding helices for optimal DNA recognition.

HoloR: Interactive Mixed-Reality Rooms

OpenAIRE

Schwede, Carsten; Hermann, Thomas

2015-01-01

Existing virtual reality technologies only cover certain areas of the mixed-reality spectrum: Augmented reality goggles are unable to provide immersion while head-mounted displays make it difficult to interact with the real world. In this paper we introduce HoloR - short for Holographic Room: A stereoscopic, multi-person, multi-viewer, spatial projected augmented reality system, which enables applications to fade between different parts of the mixed-reality spectrum. By using web-technologies...

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

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

Statistical Profiling of One Promiscuous Protein Binding Site: Illustrated by Urokinase Catalytic Domain.

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Cerisier, Natacha; Regad, Leslie; Triki, Dhoha; Petitjean, Michel; Flatters, Delphine; Camproux, Anne-Claude

2017-10-01

While recent literature focuses on drug promiscuity, the characterization of promiscuous binding sites (ability to bind several ligands) remains to be explored. Here, we present a proteochemometric modeling approach to analyze diverse ligands and corresponding multiple binding sub-pockets associated with one promiscuous binding site to characterize protein-ligand recognition. We analyze both geometrical and physicochemical profile correspondences. This approach was applied to examine the well-studied druggable urokinase catalytic domain inhibitor binding site, which results in a large number of complex structures bound to various ligands. This approach emphasizes the importance of jointly characterizing pocket and ligand spaces to explore the impact of ligand diversity on sub-pocket properties and to establish their main profile correspondences. This work supports an interest in mining available 3D holo structures associated with a promiscuous binding site to explore its main protein-ligand recognition tendency. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nucleos: a web server for the identification of nucleotide-binding sites in protein structures.

Science.gov (United States)

Parca, Luca; Ferré, Fabrizio; Ausiello, Gabriele; Helmer-Citterich, Manuela

2013-07-01

Nucleos is a web server for the identification of nucleotide-binding sites in protein structures. Nucleos compares the structure of a query protein against a set of known template 3D binding sites representing nucleotide modules, namely the nucleobase, carbohydrate and phosphate. Structural features, clustering and conservation are used to filter and score the predictions. The predicted nucleotide modules are then joined to build whole nucleotide-binding sites, which are ranked by their score. The server takes as input either the PDB code of the query protein structure or a user-submitted structure in PDB format. The output of Nucleos is composed of ranked lists of predicted nucleotide-binding sites divided by nucleotide type (e.g. ATP-like). For each ranked prediction, Nucleos provides detailed information about the score, the template structure and the structural match for each nucleotide module composing the nucleotide-binding site. The predictions on the query structure and the template-binding sites can be viewed directly on the web through a graphical applet. In 98% of the cases, the modules composing correct predictions belong to proteins with no homology relationship between each other, meaning that the identification of brand-new nucleotide-binding sites is possible using information from non-homologous proteins. Nucleos is available at http://nucleos.bio.uniroma2.it/nucleos/.

MicroRNA-target binding structures mimic microRNA duplex structures in humans.

Directory of Open Access Journals (Sweden)

Xi Chen

Full Text Available Traditionally, researchers match a microRNA guide strand to mRNA sequences using sequence comparisons to predict its potential target genes. However, many of the predictions can be false positives due to limitations in sequence comparison alone. In this work, we consider the association of two related RNA structures that share a common guide strand: the microRNA duplex and the microRNA-target binding structure. We have analyzed thousands of such structure pairs and found many of them share high structural similarity. Therefore, we conclude that when predicting microRNA target genes, considering just the microRNA guide strand matches to gene sequences may not be sufficient--the microRNA duplex structure formed by the guide strand and its companion passenger strand must also be considered. We have developed software to translate RNA binding structure into encoded representations, and we have also created novel automatic comparison methods utilizing such encoded representations to determine RNA structure similarity. Our software and methods can be utilized in the other RNA secondary structure comparisons as well.

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

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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.

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.

A high pressure study of calmodulin-ligand interactions using small-angle X-ray and elastic incoherent neutron scattering.

Science.gov (United States)

Cinar, Süleyman; Al-Ayoubi, Samy; Sternemann, Christian; Peters, Judith; Winter, Roland; Czeslik, Claus

2018-01-31

Calmodulin (CaM) is a Ca 2+ sensor and mediates Ca 2+ signaling through binding of numerous target ligands. The binding of ligands by Ca 2+ -saturated CaM (holo-CaM) is governed by attractive hydrophobic and electrostatic interactions that are weakened under high pressure in aqueous solutions. Moreover, the potential formation of void volumes upon ligand binding creates a further source of pressure sensitivity. Hence, high pressure is a suitable thermodynamic variable to probe protein-ligand interactions. In this study, we compare the binding of two different ligands to holo-CaM as a function of pressure by using X-ray and neutron scattering techniques. The two ligands are the farnesylated hypervariable region (HVR) of the K-Ras4B protein, which is a natural binding partner of holo-CaM, and the antagonist trifluoperazine (TFP), which is known to inhibit holo-CaM activity. From small-angle X-ray scattering experiments performed up to 3000 bar, we observe a pressure-induced partial unfolding of the free holo-CaM in the absence of ligands, where the two lobes of the dumbbell-shaped protein are slightly swelled. In contrast, upon binding TFP, holo-CaM forms a closed globular conformation, which is pressure stable at least up to 3000 bar. The HVR of K-Ras4B shows a different binding behavior, and the data suggest the dissociation of the holo-CaM/HVR complex under high pressure, probably due to a less dense protein contact of the HVR as compared to TFP. The elastic incoherent neutron scattering experiments corroborate these findings. Below 2000 bar, pressure induces enhanced atomic fluctuations in both holo-CaM/ligand complexes, but those of the holo-CaM/HVR complex seem to be larger. Thus, the inhibition of holo-CaM by TFP is supported by a low-volume ligand binding, albeit this is not associated with a rigidification of the complex structure on the sub-ns Å-scale.

Characterization of a monoclonal antibody with specificity for holo-transcobalamin

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Fedosov Sergey N

2006-01-01

Full Text Available Abstract Background Holotranscobalamin, cobalamin-saturated transcobalamin, is the minor fraction of circulating cobalamin (vitamin B12, which is available for cellular uptake and hence is physiologically relevant. Currently, no method allows simple, direct quantification of holotranscobalamin. We now report on the identification and characterization of a monoclonal antibody with a unique specificity for holotranscobalamin. Methods The specificity and affinity of the monoclonal antibodies were determined using surface plasmon resonance and recombinant transcobalamin as well as by immobilizing the antibodies on magnetic microspheres and using native transcobalamin in serum. The epitope of the holotranscobalamin specific antibody was identified using phage display and comparison to a de novo generated three-dimensional model of transcobalamin using the program Rosetta. A direct assay for holotrnscobalamin in the ELISA format was developed using the specific antibody and compared to the commercial assay HoloTC RIA. Results An antibody exhibiting >100-fold specificity for holotranscobalamin over apotranscobalamin was identified. The affinity but not the specificity varied inversely with ionic strength and pH, indicating importance of electrostatic interactions. The epitope was discontinuous and epitope mapping of the antibody by phage display identified two similar motifs with no direct sequence similarity to transcobalamin. A comparison of the motifs with a de novo generated three-dimensional model of transcobalamin identified two structures in the N-terminal part of transcobalamin that resembled the motif. Using this antibody an ELISA based prototype assay was developed and compared to the only available commercial assay for measuring holotranscobalamin, HoloTC RIA. Conclusion The identified antibody possesses a unique specificity for holotranscobalamin and can be used to develop a direct assay for the quantification of holotranscobalamin.

RNAcontext: a new method for learning the sequence and structure binding preferences of RNA-binding proteins.

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Hilal Kazan

2010-07-01

Full Text Available Metazoan genomes encode hundreds of RNA-binding proteins (RBPs. These proteins regulate post-transcriptional gene expression and have critical roles in numerous cellular processes including mRNA splicing, export, stability and translation. Despite their ubiquity and importance, the binding preferences for most RBPs are not well characterized. In vitro and in vivo studies, using affinity selection-based approaches, have successfully identified RNA sequence associated with specific RBPs; however, it is difficult to infer RBP sequence and structural preferences without specifically designed motif finding methods. In this study, we introduce a new motif-finding method, RNAcontext, designed to elucidate RBP-specific sequence and structural preferences with greater accuracy than existing approaches. We evaluated RNAcontext on recently published in vitro and in vivo RNA affinity selected data and demonstrate that RNAcontext identifies known binding preferences for several control proteins including HuR, PTB, and Vts1p and predicts new RNA structure preferences for SF2/ASF, RBM4, FUSIP1 and SLM2. The predicted preferences for SF2/ASF are consistent with its recently reported in vivo binding sites. RNAcontext is an accurate and efficient motif finding method ideally suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RBPs for a wide range of RNA sequences and structures.

Implicit ligand theory for relative binding free energies

Science.gov (United States)

Nguyen, Trung Hai; Minh, David D. L.

2018-03-01

Implicit ligand theory enables noncovalent binding free energies to be calculated based on an exponential average of the binding potential of mean force (BPMF)—the binding free energy between a flexible ligand and rigid receptor—over a precomputed ensemble of receptor configurations. In the original formalism, receptor configurations were drawn from or reweighted to the apo ensemble. Here we show that BPMFs averaged over a holo ensemble yield binding free energies relative to the reference ligand that specifies the ensemble. When using receptor snapshots from an alchemical simulation with a single ligand, the new statistical estimator outperforms the original.

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

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.

Application of quantitative structure-activity relationship to the determination of binding constant based on fluorescence quenching

Energy Technology Data Exchange (ETDEWEB)

Wen Yingying [Department of Applied Chemistry, Yantai University, Yantai 264005 (China); Liu Huitao, E-mail: liuht-ytu@163.co [Department of Applied Chemistry, Yantai University, Yantai 264005 (China); Luan Feng; Gao Yuan [Department of Applied Chemistry, Yantai University, Yantai 264005 (China)

2011-01-15

Quantitative structure-activity relationship (QSAR) model was used to predict and explain binding constant (log K) determined by fluorescence quenching. This method allowed us to predict binding constants of a variety of compounds with human serum albumin (HSA) based on their structures alone. Stepwise multiple linear regression (MLR) and nonlinear radial basis function neural network (RBFNN) were performed to build the models. The statistical parameters provided by the MLR model (R{sup 2}=0.8521, RMS=0.2678) indicated satisfactory stability and predictive ability while the RBFNN predictive ability is somewhat superior (R{sup 2}=0.9245, RMS=0.1736). The proposed models were used to predict the binding constants of two bioactive components in traditional Chinese medicines (isoimperatorin and chrysophanol) whose experimental results were obtained in our laboratory and the predicted results were in good agreement with the experimental results. This QSAR approach can contribute to a better understanding of structural factors of the compounds responsible for drug-protein interactions, and can be useful in predicting the binding constants of other compounds. - Research Highlights: QSAR models for binding constants of some compounds to HSA were developed. The models provide a simple and straightforward way to predict binding constant. QSAR can give some insight into structural features related to binding behavior.

Calcium-induced conformational changes of Thrombospondin-1 signature domain: implications for vascular disease.

Science.gov (United States)

Gupta, Akanksha; Agarwal, Rahul; Singh, Ashutosh; Bhatnagar, Sonika

2017-06-01

Thrombospondin1 (TSP1) participates in numerous signaling pathways critical for vascular physiology and disease. The conserved signature domain of thrombospondin 1 (TSP1-Sig1) comprises three epidermal growth factor (EGF), 13 calcium-binding type 3 thrombospondin (T3) repeats, and one lectin-like module arranged in a stalk-wire-globe topology. TSP1 is known to be present in both calcium-replete (Holo-) and calcium-depleted (Apo-) state, each with distinct downstream signaling effects. To prepare a homology model of TSP1-Sig1 and investigate the effect of calcium on its dynamic structure and interactions. A homology model of Holo-TSP1-Sig1 was prepared with TSP2 as template in Swissmodel workspace. The Apo-form of the model was obtained by omitting the bound calcium ions from the homology model. Molecular dynamics (MD) simulation studies (100 ns) were performed on the Holo- and Apo- forms of TSP1 using Gromacs4.6.5. After simulation, Holo-TSP1-Sig1 showed significant reorientation at the interface of the EGF1-2 and EGF2-3 modules. The T3 wire is predicted to show the maximum mobility and deviation from the initial model. In Apo-TSP1-Sig1 model, the T3 repeats unfolded and formed coils with predicted increase in flexibility. Apo-TSP1-Sig1model also predicted the exposure of the binding sites for neutrophil elastase, integrin and fibroblast growth factor 2. We present a structural model and hypothesis for the role of TSP1-Sig1 interactions in the development of vascular disorders. The simulated model of the fully calcium-loaded and calcium-depleted TSP1-Sig1 may enable the development of its interactions as a novel therapeutic target for the treatment of vascular diseases.

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....

Structural and functional investigation of flavin binding center of the NqrC subunit of sodium-translocating NADH:quinone oxidoreductase from Vibrio harveyi.

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Valentin Borshchevskiy

Full Text Available Na+-translocating NADH:quinone oxidoreductase (NQR is a redox-driven sodium pump operating in the respiratory chain of various bacteria, including pathogenic species. The enzyme has a unique set of redox active prosthetic groups, which includes two covalently bound flavin mononucleotide (FMN residues attached to threonine residues in subunits NqrB and NqrC. The reason of FMN covalent bonding in the subunits has not been established yet. In the current work, binding of free FMN to the apo-form of NqrC from Vibrio harveyi was studied showing very low affinity of NqrC to FMN in the absence of its covalent bonding. To study structural aspects of flavin binding in NqrC, its holo-form was crystallized and its 3D structure was solved at 1.56 Å resolution. It was found that the isoalloxazine moiety of the FMN residue is buried in a hydrophobic cavity and that its pyrimidine ring is squeezed between hydrophobic amino acid residues while its benzene ring is extended from the protein surroundings. This structure of the flavin-binding pocket appears to provide flexibility of the benzene ring, which can help the FMN residue to take the bended conformation and thus to stabilize the one-electron reduced form of the prosthetic group. These properties may also lead to relatively weak noncovalent binding of the flavin. This fact along with periplasmic location of the FMN-binding domains in the vast majority of NqrC-like proteins may explain the necessity of the covalent bonding of this prosthetic group to prevent its loss to the external medium.

Use of Microsoft HoloLens to survey and visualize buried networks

CERN Multimedia

CERN. Geneva

2017-01-01

Survey and positioning of buried infrastructure networks are crucial issues for their maintenance and a starting point for every new Civil Engineering project. 3DCity is a research & development project which consists in a development of software providing a method for quick underground pipe networks surveying and holographic visualization, by using Microsoft HoloLens devices.

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

Conformational Dynamics and Binding Free Energies of Inhibitors of BACE-1: From the Perspective of Protonation Equilibria.

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M Olivia Kim

2015-10-01

Full Text Available BACE-1 is the β-secretase responsible for the initial amyloidogenesis in Alzheimer's disease, catalyzing hydrolytic cleavage of substrate in a pH-sensitive manner. The catalytic mechanism of BACE-1 requires water-mediated proton transfer from aspartyl dyad to the substrate, as well as structural flexibility in the flap region. Thus, the coupling of protonation and conformational equilibria is essential to a full in silico characterization of BACE-1. In this work, we perform constant pH replica exchange molecular dynamics simulations on both apo BACE-1 and five BACE-1-inhibitor complexes to examine the effect of pH on dynamics and inhibitor binding properties of BACE-1. In our simulations, we find that solution pH controls the conformational flexibility of apo BACE-1, whereas bound inhibitors largely limit the motions of the holo enzyme at all levels of pH. The microscopic pKa values of titratable residues in BACE-1 including its aspartyl dyad are computed and compared between apo and inhibitor-bound states. Changes in protonation between the apo and holo forms suggest a thermodynamic linkage between binding of inhibitors and protons localized at the dyad. Utilizing our recently developed computational protocol applying the binding polynomial formalism to the constant pH molecular dynamics (CpHMD framework, we are able to obtain the pH-dependent binding free energy profiles for various BACE-1-inhibitor complexes. Our results highlight the importance of correctly addressing the binding-induced protonation changes in protein-ligand systems where binding accompanies a net proton transfer. This work comprises the first application of our CpHMD-based free energy computational method to protein-ligand complexes and illustrates the value of CpHMD as an all-purpose tool for obtaining pH-dependent dynamics and binding free energies of biological systems.

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.

The Holo-Transcriptome of the Zoantharian Protopalythoa variabilis (Cnidaria: Anthozoa: A Plentiful Source of Enzymes for Potential Application in Green Chemistry, Industrial and Pharmaceutical Biotechnology

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Jean-Étienne R. L. Morlighem

2018-06-01

Full Text Available Marine invertebrates, such as sponges, tunicates and cnidarians (zoantharians and scleractinian corals, form functional assemblages, known as holobionts, with numerous microbes. This type of species-specific symbiotic association can be a repository of myriad valuable low molecular weight organic compounds, bioactive peptides and enzymes. The zoantharian Protopalythoa variabilis (Cnidaria: Anthozoa is one such example of a marine holobiont that inhabits the coastal reefs of the tropical Atlantic coast and is an interesting source of secondary metabolites and biologically active polypeptides. In the present study, we analyzed the entire holo-transcriptome of P. variabilis, looking for enzyme precursors expressed in the zoantharian-microbiota assemblage that are potentially useful as industrial biocatalysts and biopharmaceuticals. In addition to hundreds of predicted enzymes that fit into the classes of hydrolases, oxidoreductases and transferases that were found, novel enzyme precursors with multiple activities in single structures and enzymes with incomplete Enzyme Commission numbers were revealed. Our results indicated the predictive expression of thirteen multifunctional enzymes and 694 enzyme sequences with partially characterized activities, distributed in 23 sub-subclasses. These predicted enzyme structures and activities can prospectively be harnessed for applications in diverse areas of industrial and pharmaceutical biotechnology.

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.

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.

Effect of free cysteine on the denaturation and aggregation of holo α-lactalbumin

DEFF Research Database (Denmark)

Nielsen, Line R.; Lund, Marianne N.; Davies, Michael J.

2018-01-01

α-Lactalbumin (α-LA) is a key commercial whey protein for nutritional purposes. The holo protein (calcium saturated) is considered the most heat stable whey protein, capable of refolding from unfolded states under many conditions. This is due to the absence of free thiols (cysteine residues......) that are typically involved in thermal aggregation and thiol–disulphide exchange reactions of other whey proteins. Heating (0–120 min at 90 °C, pH 7.0) holo α-LA generates free thiols through thermal cleavage of disulphide bonds, resulting in aggregates comprising unfolded α-LA species. The addition of free cysteine...... promotes the formation of soluble aggregates, effectively decreasing the holding time required to reach a particular aggregate size in a dose-dependent manner (0.35–1.4 mM cysteine). Excess cysteine (≥14 mM) causes a destabilisation of α-LA, shown by decreased denaturation temperature and gel formation...

Characterization of the mycobacterial acyl-CoA carboxylase holo complexes reveals their functional expansion into amino acid catabolism.

Directory of Open Access Journals (Sweden)

Matthias T Ehebauer

2015-02-01

Full Text Available Biotin-mediated carboxylation of short-chain fatty acid coenzyme A esters is a key step in lipid biosynthesis that is carried out by multienzyme complexes to extend fatty acids by one methylene group. Pathogenic mycobacteria have an unusually high redundancy of carboxyltransferase genes and biotin carboxylase genes, creating multiple combinations of protein/protein complexes of unknown overall composition and functional readout. By combining pull-down assays with mass spectrometry, we identified nine binary protein/protein interactions and four validated holo acyl-coenzyme A carboxylase complexes. We investigated one of these--the AccD1-AccA1 complex from Mycobacterium tuberculosis with hitherto unknown physiological function. Using genetics, metabolomics and biochemistry we found that this complex is involved in branched amino-acid catabolism with methylcrotonyl coenzyme A as the substrate. We then determined its overall architecture by electron microscopy and found it to be a four-layered dodecameric arrangement that matches the overall dimensions of a distantly related methylcrotonyl coenzyme A holo complex. Our data argue in favor of distinct structural requirements for biotin-mediated γ-carboxylation of α-β unsaturated acid esters and will advance the categorization of acyl-coenzyme A carboxylase complexes. Knowledge about the underlying structural/functional relationships will be crucial to make the target category amenable for future biomedical applications.

First trimester serum levels of the soluble transcobalamin receptor, holo-transcobalamin, and total transcobalamin in relation to preeclampsia risk

DEFF Research Database (Denmark)

Abuyaman, Omar; Torring, Niels; Obeid, Rima

2016-01-01

transcobalamin (TC) with the risk of subsequent preeclampsia using serum samples from asymptomatic first trimester pregnant women. Moreover, we aimed to establish reference intervals of the aforementioned biomarkers for first trimester pregnant women who remained healthy throughout pregnancy. STUDY DESIGN...... preeclampsia while the controls remained normotensive throughout pregnancy. We measured the serum concentration of sCD320, holoTC, and total TC by using in-house ELISA methods. RESULTS: First trimester median concentrations of sCD320, holoTC and total TC were not significantly different between cases...... and controls. The odd ratio for developing preeclampsia based on exposure to low or high levels of sCD320, holoTC or total TC at first trimester was not significant. The reference intervals (2.5-97.5% percentiles (median)) derived from the controls were 50-170 (90) pmol\\L for sCD320, 20-140 (70) pmol...

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...

Structural Fingerprints of Transcription Factor Binding Site Regions

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Peter Willett

2009-03-01

Full Text Available Fourier transforms are a powerful tool in the prediction of DNA sequence properties, such as the presence/absence of codons. We have previously compiled a database of the structural properties of all 32,896 unique DNA octamers. In this work we apply Fourier techniques to the analysis of the structural properties of human chromosomes 21 and 22 and also to three sets of transcription factor binding sites within these chromosomes. We find that, for a given structural property, the structural property power spectra of chromosomes 21 and 22 are strikingly similar. We find common peaks in their power spectra for both Sp1 and p53 transcription factor binding sites. We use the power spectra as a structural fingerprint and perform similarity searching in order to find transcription factor binding site regions. This approach provides a new strategy for searching the genome data for information. Although it is difficult to understand the relationship between specific functional properties and the set of structural parameters in our database, our structural fingerprints nevertheless provide a useful tool for searching for function information in sequence data. The power spectrum fingerprints provide a simple, fast method for comparing a set of functional sequences, in this case transcription factor binding site regions, with the sequences of whole chromosomes. On its own, the power spectrum fingerprint does not find all transcription factor binding sites in a chromosome, but the results presented here show that in combination with other approaches, this technique will improve the chances of identifying functional sequences hidden in genomic data.

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

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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.

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

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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.

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

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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.

The structure of apo and holo forms of xylose reductase, a dimeric aldo-keto reductase from Candida tenuis.

Science.gov (United States)

Kavanagh, Kathryn L; Klimacek, Mario; Nidetzky, Bernd; Wilson, David K

2002-07-16

Xylose reductase is a homodimeric oxidoreductase dependent on NADPH or NADH and belongs to the largely monomeric aldo-keto reductase superfamily of proteins. It catalyzes the first step in the assimilation of xylose, an aldose found to be a major constituent monosaccharide of renewable plant hemicellulosic material, into yeast metabolic pathways. It does this by reducing open chain xylose to xylitol, which is reoxidized to xylulose by xylitol dehydrogenase and metabolically integrated via the pentose phosphate pathway. No structure has yet been determined for a xylose reductase, a dimeric aldo-keto reductase or a family 2 aldo-keto reductase. The structures of the Candida tenuis xylose reductase apo- and holoenzyme, which crystallize in spacegroup C2 with different unit cells, have been determined to 2.2 A resolution and an R-factor of 17.9 and 20.8%, respectively. Residues responsible for mediating the novel dimeric interface include Asp-178, Arg-181, Lys-202, Phe-206, Trp-313, and Pro-319. Alignments with other superfamily members indicate that these interactions are conserved in other dimeric xylose reductases but not throughout the remainder of the oligomeric aldo-keto reductases, predicting alternate modes of oligomerization for other families. An arrangement of side chains in a catalytic triad shows that Tyr-52 has a conserved function as a general acid. The loop that folds over the NAD(P)H cosubstrate is disordered in the apo form but becomes ordered upon cosubstrate binding. A slow conformational isomerization of this loop probably accounts for the observed rate-limiting step involving release of cosubstrate. Xylose binding (K(m) = 87 mM) is mediated by interactions with a binding pocket that is more polar than a typical aldo-keto reductase. Modeling of xylose into the active site of the holoenzyme using ordered waters as a guide for sugar hydroxyls suggests a convincing mode of substrate binding.

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

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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/.

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.

Structure-aided prediction of mammalian transcription factor complexes in conserved non-coding elements

KAUST Repository

Guturu, H.

2013-11-11

Mapping the DNA-binding preferences of transcription factor (TF) complexes is critical for deciphering the functions of cis-regulatory elements. Here, we developed a computational method that compares co-occurring motif spacings in conserved versus unconserved regions of the human genome to detect evolutionarily constrained binding sites of rigid TF complexes. Structural data were used to estimate TF complex physical plausibility, explore overlapping motif arrangements seldom tackled by non-structure-aware methods, and generate and analyse three-dimensional models of the predicted complexes bound to DNA. Using this approach, we predicted 422 physically realistic TF complex motifs at 18% false discovery rate, the majority of which (326, 77%) contain some sequence overlap between binding sites. The set of mostly novel complexes is enriched in known composite motifs, predictive of binding site configurations in TF-TF-DNA crystal structures, and supported by ChIP-seq datasets. Structural modelling revealed three cooperativity mechanisms: direct protein-protein interactions, potentially indirect interactions and \\'through-DNA\\' interactions. Indeed, 38% of the predicted complexes were found to contain four or more bases in which TF pairs appear to synergize through overlapping binding to the same DNA base pairs in opposite grooves or strands. Our TF complex and associated binding site predictions are available as a web resource at http://bejerano.stanford.edu/complex.

Structure-aided prediction of mammalian transcription factor complexes in conserved non-coding elements

KAUST Repository

Guturu, H.; Doxey, A. C.; Wenger, A. M.; Bejerano, G.

2013-01-01

Mapping the DNA-binding preferences of transcription factor (TF) complexes is critical for deciphering the functions of cis-regulatory elements. Here, we developed a computational method that compares co-occurring motif spacings in conserved versus unconserved regions of the human genome to detect evolutionarily constrained binding sites of rigid TF complexes. Structural data were used to estimate TF complex physical plausibility, explore overlapping motif arrangements seldom tackled by non-structure-aware methods, and generate and analyse three-dimensional models of the predicted complexes bound to DNA. Using this approach, we predicted 422 physically realistic TF complex motifs at 18% false discovery rate, the majority of which (326, 77%) contain some sequence overlap between binding sites. The set of mostly novel complexes is enriched in known composite motifs, predictive of binding site configurations in TF-TF-DNA crystal structures, and supported by ChIP-seq datasets. Structural modelling revealed three cooperativity mechanisms: direct protein-protein interactions, potentially indirect interactions and 'through-DNA' interactions. Indeed, 38% of the predicted complexes were found to contain four or more bases in which TF pairs appear to synergize through overlapping binding to the same DNA base pairs in opposite grooves or strands. Our TF complex and associated binding site predictions are available as a web resource at http://bejerano.stanford.edu/complex.

Interaction between holo transferrin and HSA-PPIX complex in the presence of lomefloxacin: An evaluation of PPIX aggregation in protein-protein interactions

Science.gov (United States)

Sattar, Zohreh; Iranfar, Hediye; Asoodeh, Ahmad; Saberi, Mohammad Reza; Mazhari, Mahboobeh; Chamani, Jamshidkhan

2012-11-01

Human serum albumin (HSA) and holo transferrin (TF) are two serum carrier proteins that are able to interact with each other, thereby altering their binding behavior toward their ligands. During the course of this study, the interaction between HSA-PPIX and TF, in the presence and absence of lomefloxacin (LMF), was for the first time investigated using different spectroscopic and molecular modeling techniques. Fluorescence spectroscopy experiments were performed in order to study conformational changes of proteins. The RLS technique was utilized to investigate the effect of LMF on J-aggregation of PPIX, which is the first report of its kind. Our findings present clear-cut evidence for the alteration of interactions between HSA and TF in the presence of PPIX and changes in drug-binding to HSA and HSA-PPIX complex upon interaction with TF. Moreover, molecular modeling studies suggested that the binding site for LMF became switched in the presence of PPIX, and that LMF bound to the site IIA of HSA. The obtained results should give new insight into research in this field and may cast some light on the dynamics of drugs in biological systems.

Ligand Binding Site Detection by Local Structure Alignment and Its Performance Complementarity

Science.gov (United States)

Lee, Hui Sun; Im, Wonpil

2013-01-01

Accurate determination of potential ligand binding sites (BS) is a key step for protein function characterization and structure-based drug design. Despite promising results of template-based BS prediction methods using global structure alignment (GSA), there is a room to improve the performance by properly incorporating local structure alignment (LSA) because BS are local structures and often similar for proteins with dissimilar global folds. We present a template-based ligand BS prediction method using G-LoSA, our LSA tool. A large benchmark set validation shows that G-LoSA predicts drug-like ligands’ positions in single-chain protein targets more precisely than TM-align, a GSA-based method, while the overall success rate of TM-align is better. G-LoSA is particularly efficient for accurate detection of local structures conserved across proteins with diverse global topologies. Recognizing the performance complementarity of G-LoSA to TM-align and a non-template geometry-based method, fpocket, a robust consensus scoring method, CMCS-BSP (Complementary Methods and Consensus Scoring for ligand Binding Site Prediction), is developed and shows improvement on prediction accuracy. The G-LoSA source code is freely available at http://im.bioinformatics.ku.edu/GLoSA. PMID:23957286

Mixed Reality with HoloLens: Where Virtual Reality Meets Augmented Reality in the Operating Room.

Science.gov (United States)

Tepper, Oren M; Rudy, Hayeem L; Lefkowitz, Aaron; Weimer, Katie A; Marks, Shelby M; Stern, Carrie S; Garfein, Evan S

2017-11-01

Virtual reality and augmented reality devices have recently been described in the surgical literature. The authors have previously explored various iterations of these devices, and although they show promise, it has become clear that virtual reality and/or augmented reality devices alone do not adequately meet the demands of surgeons. The solution may lie in a hybrid technology known as mixed reality, which merges many virtual reality and augmented realty features. Microsoft's HoloLens, the first commercially available mixed reality device, provides surgeons intraoperative hands-free access to complex data, the real environment, and bidirectional communication. This report describes the use of HoloLens in the operating room to improve decision-making and surgical workflow. The pace of mixed reality-related technological development will undoubtedly be rapid in the coming years, and plastic surgeons are ideally suited to both lead and benefit from this advance.

Facilitating RNA structure prediction with microarrays.

Science.gov (United States)

Kierzek, Elzbieta; Kierzek, Ryszard; Turner, Douglas H; Catrina, Irina E

2006-01-17

Determining RNA secondary structure is important for understanding structure-function relationships and identifying potential drug targets. This paper reports the use of microarrays with heptamer 2'-O-methyl oligoribonucleotides to probe the secondary structure of an RNA and thereby improve the prediction of that secondary structure. When experimental constraints from hybridization results are added to a free-energy minimization algorithm, the prediction of the secondary structure of Escherichia coli 5S rRNA improves from 27 to 92% of the known canonical base pairs. Optimization of buffer conditions for hybridization and application of 2'-O-methyl-2-thiouridine to enhance binding and improve discrimination between AU and GU pairs are also described. The results suggest that probing RNA with oligonucleotide microarrays can facilitate determination of secondary structure.

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.

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.

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.

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

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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.

Structural motif screening reveals a novel, conserved carbohydrate-binding surface in the pathogenesis-related protein PR-5d

Directory of Open Access Journals (Sweden)

Moffatt Barbara A

2010-08-01

Full Text Available Abstract Background Aromatic amino acids play a critical role in protein-glycan interactions. Clusters of surface aromatic residues and their features may therefore be useful in distinguishing glycan-binding sites as well as predicting novel glycan-binding proteins. In this work, a structural bioinformatics approach was used to screen the Protein Data Bank (PDB for coplanar aromatic motifs similar to those found in known glycan-binding proteins. Results The proteins identified in the screen were significantly associated with carbohydrate-related functions according to gene ontology (GO enrichment analysis, and predicted motifs were found frequently within novel folds and glycan-binding sites not included in the training set. In addition to numerous binding sites predicted in structural genomics proteins of unknown function, one novel prediction was a surface motif (W34/W36/W192 in the tobacco pathogenesis-related protein, PR-5d. Phylogenetic analysis revealed that the surface motif is exclusive to a subfamily of PR-5 proteins from the Solanaceae family of plants, and is absent completely in more distant homologs. To confirm PR-5d's insoluble-polysaccharide binding activity, a cellulose-pulldown assay of tobacco proteins was performed and PR-5d was identified in the cellulose-binding fraction by mass spectrometry. Conclusions Based on the combined results, we propose that the putative binding site in PR-5d may be an evolutionary adaptation of Solanaceae plants including potato, tomato, and tobacco, towards defense against cellulose-containing pathogens such as species of the deadly oomycete genus, Phytophthora. More generally, the results demonstrate that coplanar aromatic clusters on protein surfaces are a structural signature of glycan-binding proteins, and can be used to computationally predict novel glycan-binding proteins from 3 D structure.

Structural motif screening reveals a novel, conserved carbohydrate-binding surface in the pathogenesis-related protein PR-5d.

Science.gov (United States)

Doxey, Andrew C; Cheng, Zhenyu; Moffatt, Barbara A; McConkey, Brendan J

2010-08-03

Aromatic amino acids play a critical role in protein-glycan interactions. Clusters of surface aromatic residues and their features may therefore be useful in distinguishing glycan-binding sites as well as predicting novel glycan-binding proteins. In this work, a structural bioinformatics approach was used to screen the Protein Data Bank (PDB) for coplanar aromatic motifs similar to those found in known glycan-binding proteins. The proteins identified in the screen were significantly associated with carbohydrate-related functions according to gene ontology (GO) enrichment analysis, and predicted motifs were found frequently within novel folds and glycan-binding sites not included in the training set. In addition to numerous binding sites predicted in structural genomics proteins of unknown function, one novel prediction was a surface motif (W34/W36/W192) in the tobacco pathogenesis-related protein, PR-5d. Phylogenetic analysis revealed that the surface motif is exclusive to a subfamily of PR-5 proteins from the Solanaceae family of plants, and is absent completely in more distant homologs. To confirm PR-5d's insoluble-polysaccharide binding activity, a cellulose-pulldown assay of tobacco proteins was performed and PR-5d was identified in the cellulose-binding fraction by mass spectrometry. Based on the combined results, we propose that the putative binding site in PR-5d may be an evolutionary adaptation of Solanaceae plants including potato, tomato, and tobacco, towards defense against cellulose-containing pathogens such as species of the deadly oomycete genus, Phytophthora. More generally, the results demonstrate that coplanar aromatic clusters on protein surfaces are a structural signature of glycan-binding proteins, and can be used to computationally predict novel glycan-binding proteins from 3 D structure.

Combining structural modeling with ensemble machine learning to accurately predict protein fold stability and binding affinity effects upon mutation.

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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.

An integrative computational framework based on a two-step random forest algorithm improves prediction of zinc-binding sites in proteins.

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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/.

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

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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/.

Transcription factor binding sites prediction based on modified nucleosomes.

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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

A tool for calculating binding-site residues on proteins from PDB structures

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Hu Jing

2009-08-01

Full Text Available Abstract Background In the research on protein functional sites, researchers often need to identify binding-site residues on a protein. A commonly used strategy is to find a complex structure from the Protein Data Bank (PDB that consists of the protein of interest and its interacting partner(s and calculate binding-site residues based on the complex structure. However, since a protein may participate in multiple interactions, the binding-site residues calculated based on one complex structure usually do not reveal all binding sites on a protein. Thus, this requires researchers to find all PDB complexes that contain the protein of interest and combine the binding-site information gleaned from them. This process is very time-consuming. Especially, combing binding-site information obtained from different PDB structures requires tedious work to align protein sequences. The process becomes overwhelmingly difficult when researchers have a large set of proteins to analyze, which is usually the case in practice. Results In this study, we have developed a tool for calculating binding-site residues on proteins, TCBRP http://yanbioinformatics.cs.usu.edu:8080/ppbindingsubmit. For an input protein, TCBRP can quickly find all binding-site residues on the protein by automatically combining the information obtained from all PDB structures that consist of the protein of interest. Additionally, TCBRP presents the binding-site residues in different categories according to the interaction type. TCBRP also allows researchers to set the definition of binding-site residues. Conclusion The developed tool is very useful for the research on protein binding site analysis and prediction.

Computational predictions of zinc oxide hollow structures

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Tuoc, Vu Ngoc; Huan, Tran Doan; Thao, Nguyen Thi

2018-03-01

Nanoporous materials are emerging as potential candidates for a wide range of technological applications in environment, electronic, and optoelectronics, to name just a few. Within this active research area, experimental works are predominant while theoretical/computational prediction and study of these materials face some intrinsic challenges, one of them is how to predict porous structures. We propose a computationally and technically feasible approach for predicting zinc oxide structures with hollows at the nano scale. The designed zinc oxide hollow structures are studied with computations using the density functional tight binding and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications.

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

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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.

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

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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.

Structural and Histone Binding Ability Characterizations of Human PWWP Domains

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Wu, Hong; Zeng, Hong; Lam, Robert; Tempel, Wolfram; Amaya, Maria F.; Xu, Chao; Dombrovski, Ludmila; Qiu, Wei; Wang, Yanming; Min, Jinrong (Toronto); (Penn)

2013-09-25

The PWWP domain was first identified as a structural motif of 100-130 amino acids in the WHSC1 protein and predicted to be a protein-protein interaction domain. It belongs to the Tudor domain 'Royal Family', which consists of Tudor, chromodomain, MBT and PWWP domains. While Tudor, chromodomain and MBT domains have long been known to bind methylated histones, PWWP was shown to exhibit histone binding ability only until recently. The PWWP domain has been shown to be a DNA binding domain, but sequence analysis and previous structural studies show that the PWWP domain exhibits significant similarity to other 'Royal Family' members, implying that the PWWP domain has the potential to bind histones. In order to further explore the function of the PWWP domain, we used the protein family approach to determine the crystal structures of the PWWP domains from seven different human proteins. Our fluorescence polarization binding studies show that PWWP domains have weak histone binding ability, which is also confirmed by our NMR titration experiments. Furthermore, we determined the crystal structures of the BRPF1 PWWP domain in complex with H3K36me3, and HDGF2 PWWP domain in complex with H3K79me3 and H4K20me3. PWWP proteins constitute a new family of methyl lysine histone binders. The PWWP domain consists of three motifs: a canonical {beta}-barrel core, an insertion motif between the second and third {beta}-strands and a C-terminal {alpha}-helix bundle. Both the canonical {beta}-barrel core and the insertion motif are directly involved in histone binding. The PWWP domain has been previously shown to be a DNA binding domain. Therefore, the PWWP domain exhibits dual functions: binding both DNA and methyllysine histones.

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

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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.

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

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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 .

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

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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.

Structural properties of MHC class II ligands, implications for the prediction of MHC class II epitopes.

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Kasper Winther Jørgensen

2010-12-01

Full Text Available Major Histocompatibility class II (MHC-II molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from this compartment. Prediction of MHC class II ligands is complicated by the open binding cleft of the MHC class II molecule, allowing binding of peptides extending out of the binding groove. Furthermore, only a few HLA-DR alleles have been characterized with a sufficient number of peptides (100-200 peptides per allele to derive accurate description of their binding motif. Little work has been performed characterizing structural properties of MHC class II ligands. Here, we perform one such large-scale analysis. A large set of SYFPEITHI MHC class II ligands covering more than 20 different HLA-DR molecules was analyzed in terms of their secondary structure and surface exposure characteristics in the context of the native structure of the corresponding source protein. We demonstrated that MHC class II ligands are significantly more exposed and have significantly more coil content than other peptides in the same protein with similar predicted binding affinity. We next exploited this observation to derive an improved prediction method for MHC class II ligands by integrating prediction of MHC- peptide binding with prediction of surface exposure and protein secondary structure. This combined prediction method was shown to significantly outperform the state-of-the-art MHC class II peptide binding prediction method when used to identify MHC class II ligands. We also tried to integrate N- and O-glycosylation in our prediction methods but this additional information was found not to improve prediction performance. In summary, these findings strongly suggest that local structural properties influence antigen processing and/or the accessibility of peptides to the MHC class II molecule.

Structural insights into conserved L-arabinose metabolic enzymes reveal the substrate binding site of a thermophilic L-arabinose isomerase.

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Lee, Yong-Jik; Lee, Sang-Jae; Kim, Seong-Bo; Lee, Sang Jun; Lee, Sung Haeng; Lee, Dong-Woo

2014-03-18

Structural genomics demonstrates that despite low levels of structural similarity of proteins comprising a metabolic pathway, their substrate binding regions are likely to be conserved. Herein based on the 3D-structures of the α/β-fold proteins involved in the ara operon, we attempted to predict the substrate binding residues of thermophilic Geobacillus stearothermophilus L-arabinose isomerase (GSAI) with no 3D-structure available. Comparison of the structures of L-arabinose catabolic enzymes revealed a conserved feature to form the substrate-binding modules, which can be extended to predict the substrate binding site of GSAI (i.e., D195, E261 and E333). Moreover, these data implicated that proteins in the l-arabinose metabolic pathway might retain their substrate binding niches as the modular structure through conserved molecular evolution even with totally different structural scaffolds. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Structure of Drosophila Oskar reveals a novel RNA binding protein

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Yang, Na; Yu, Zhenyu; Hu, Menglong; Wang, Mingzhu; Lehmann, Ruth; Xu, Rui-Ming

2015-01-01

Oskar (Osk) protein plays critical roles during Drosophila germ cell development, yet its functions in germ-line formation and body patterning remain poorly understood. This situation contrasts sharply with the vast knowledge about the function and mechanism of osk mRNA localization. Osk is predicted to have an N-terminal LOTUS domain (Osk-N), which has been suggested to bind RNA, and a C-terminal hydrolase-like domain (Osk-C) of unknown function. Here, we report the crystal structures of Osk-N and Osk-C. Osk-N shows a homodimer of winged-helix–fold modules, but without detectable RNA-binding activity. Osk-C has a lipase-fold structure but lacks critical catalytic residues at the putative active site. Surprisingly, we found that Osk-C binds the 3′UTRs of osk and nanos mRNA in vitro. Mutational studies identified a region of Osk-C important for mRNA binding. These results suggest possible functions of Osk in the regulation of stability, regulation of translation, and localization of relevant mRNAs through direct interaction with their 3′UTRs, and provide structural insights into a novel protein–RNA interaction motif involving a hydrolase-related domain. PMID:26324911

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

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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

Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets

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Ashford Paul

2012-03-01

Full Text Available Abstract Background Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins' dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pocket's boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible. Results We have developed a computational method, Provar, that provides a consistent representation of predicted binding pockets across sets of related protein structures. The outputs are probabilities that each atom or residue of the protein borders a predicted pocket. These probabilities can be readily visualised on a protein using existing molecular graphics software. We show how Provar simplifies comparison of the outputs of different pocket prediction algorithms, of pockets across multiple simulated conformations and between homologous structures. We demonstrate the benefits of use of multiple structures for protein-ligand and protein-protein interface analysis on a set of complexes and consider three case studies in detail: i analysis of a kinase superfamily highlights the

Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets.

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Ashford, Paul; Moss, David S; Alex, Alexander; Yeap, Siew K; Povia, Alice; Nobeli, Irene; Williams, Mark A

2012-03-14

Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins' dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pocket's boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible. We have developed a computational method, Provar, that provides a consistent representation of predicted binding pockets across sets of related protein structures. The outputs are probabilities that each atom or residue of the protein borders a predicted pocket. These probabilities can be readily visualised on a protein using existing molecular graphics software. We show how Provar simplifies comparison of the outputs of different pocket prediction algorithms, of pockets across multiple simulated conformations and between homologous structures. We demonstrate the benefits of use of multiple structures for protein-ligand and protein-protein interface analysis on a set of complexes and consider three case studies in detail: i) analysis of a kinase superfamily highlights the conserved occurrence of surface pockets at the active

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

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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

RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data.

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Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

2016-06-15

Protein-RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein-RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset. We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein-RNA structure-based models on an unprecedented scale. Software and models are freely available at http://rck.csail.mit.edu/ bab@mit.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by

The role of subcutaneous adipose tissue in supporting the copper balance in rats with a chronic deficiency in holo-ceruloplasmin.

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Ekaterina Y Ilyechova

Full Text Available We have previously shown that (1 an acute deficiency in blood serum holo-ceruloplasmin (Cp developed in rats that were fed fodder containing silver ions (Ag-fodder for one month and (2 the deficiency in holo-Cp was compensated by non-hepatic holo-Cp synthesis in rats that were chronically fed Ag-fodder for 6 months (Ag-rats. The purpose of the present study is to identify the organ(s that compensate for the hepatic holo-Cp deficiency in the circulation. This study was performed on rats that were fed Ag-fodder (40 mg Ag·kg-1 body mass daily for 6 months. The relative expression levels of the genes responsible for copper status were measured by RT-PCR. The in vitro synthesis and secretion of [14C]Cp were analyzed using a metabolic labeling approach. Oxidase activity was determined using a gel assay with o-dianisidine. Copper status and some hematological indexes were measured. Differential centrifugation, immunoblotting, immunoelectrophoresis, and atomic absorption spectrometry were included in the investigation. In the Ag-rats, silver accumulation was tissue-specific. Skeletal muscles and internal (IAT and subcutaneous (SAT adipose tissues did not accumulate silver significantly. In SAT, the mRNAs for the soluble and glycosylphosphatidylinositol-anchored ceruloplasmin isoforms were expressed, and their relative levels were increased two-fold in the Ag-rats. In parallel, the levels of the genes responsible for Cp metallation (Ctr1 and Atp7a/b increased correspondingly. In the SAT of the Ag-rats, Cp oxidase activity was observed in the Golgi complex and plasma membrane. Moreover, full-length [14C]Cp polypeptides were released into the medium by slices of SAT. The possibilities that SAT is part of a system that controls the copper balance in mammals, and it plays a significant role in supporting copper homeostasis throughout the body are discussed.

Binding free energy analysis of protein-protein docking model structures by evERdock.

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Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

2018-03-14

To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

Bacillus cereus Fnr binds a [4Fe-4S] cluster and forms a ternary complex with ResD and PlcR

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Esbelin Julia

2012-06-01

Full Text Available Abstract Background Bacillus cereus is a facultative anaerobe that causes diarrheal disease in humans. Diarrheal syndrome may result from the secretion of various virulence factors including hemolysin BL and nonhemolytic enterotoxin Nhe. Expression of genes encoding Hbl and Nhe is regulated by the two redox systems, ResDE and Fnr, and the virulence regulator PlcR. B. cereus Fnr is a member of the Crp/Fnr family of iron-sulfur (Fe-S proteins. Only its apo-form has so far been studied. A major goal in deciphering the Fnr-dependent regulation of enterotoxin genes is thus to obtain and characterize holoFnr. Results Fnr has been subjected to in vitro Fe-S cluster reconstitution under anoxic conditions. UV-visible and EPR spectroscopic analyses together with the chemical estimation of the iron content indicated that Fnr binds one [4Fe-4S]2+ cluster per monomer. Atmospheric O2 causes disassembly of the Fe-S cluster, which exhibited a half-life of 15 min in air. Holo- and apoFnr have similar affinities for the nhe and hbl promoter regions, while holoFnr has a higher affinity for fnr promoter region than apoFnr. Both the apo- and holo-form of Fnr interact with ResD and PlcR to form a ternary complex. Conclusions Overall, this work shows that incorporation of the [4Fe-4S]2+ cluster is not required for DNA binding of Fnr to promoter regions of hbl and nhe enterotoxin genes or for the formation of a ternary complex with ResD and PlcR. This points to some new unusual properties of Fnr that may have physiological relevance in the redox regulation of enterotoxin gene regulation.

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.

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.

HoloMonitor M4: holographic imaging cytometer for real-time kinetic label-free live-cell analysis of adherent cells

Science.gov (United States)

Sebesta, Mikael; Egelberg, Peter J.; Langberg, Anders; Lindskov, Jens-Henrik; Alm, Kersti; Janicke, Birgit

2016-03-01

Live-cell imaging enables studying dynamic cellular processes that cannot be visualized in fixed-cell assays. An increasing number of scientists in academia and the pharmaceutical industry are choosing live-cell analysis over or in addition to traditional fixed-cell assays. We have developed a time-lapse label-free imaging cytometer HoloMonitorM4. HoloMonitor M4 assists researchers to overcome inherent disadvantages of fluorescent analysis, specifically effects of chemical labels or genetic modifications which can alter cellular behavior. Additionally, label-free analysis is simple and eliminates the costs associated with staining procedures. The underlying technology principle is based on digital off-axis holography. While multiple alternatives exist for this type of analysis, we prioritized our developments to achieve the following: a) All-inclusive system - hardware and sophisticated cytometric analysis software; b) Ease of use enabling utilization of instrumentation by expert- and entrylevel researchers alike; c) Validated quantitative assay end-points tracked over time such as optical path length shift, optical volume and multiple derived imaging parameters; d) Reliable digital autofocus; e) Robust long-term operation in the incubator environment; f) High throughput and walk-away capability; and finally g) Data management suitable for single- and multi-user networks. We provide examples of HoloMonitor applications of label-free cell viability measurements and monitoring of cell cycle phase distribution.

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

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

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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.

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.

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 .

The helical structure of DNA facilitates binding

International Nuclear Information System (INIS)

Berg, Otto G; Mahmutovic, Anel; Marklund, Emil; Elf, Johan

2016-01-01

The helical structure of DNA imposes constraints on the rate of diffusion-limited protein binding. Here we solve the reaction–diffusion equations for DNA-like geometries and extend with simulations when necessary. We find that the helical structure can make binding to the DNA more than twice as fast compared to a case where DNA would be reactive only along one side. We also find that this rate advantage remains when the contributions from steric constraints and rotational diffusion of the DNA-binding protein are included. Furthermore, we find that the association rate is insensitive to changes in the steric constraints on the DNA in the helix geometry, while it is much more dependent on the steric constraints on the DNA-binding protein. We conclude that the helical structure of DNA facilitates the nonspecific binding of transcription factors and structural DNA-binding proteins in general. (paper)

Structural characterization and comparison of three acyl-carrier-protein synthases from pathogenic bacteria

Energy Technology Data Exchange (ETDEWEB)

Halavaty, Andrei S. [Center for Structural Genomics of Infectious Diseases, (United States); Northwestern University, Chicago, IL 60611 (United States); Kim, Youngchang [Center for Structural Genomics of Infectious Diseases, (United States); Argonne National Laboratory, Argonne, IL 60439 (United States); University of Chicago, Chicago, IL 60637 (United States); Minasov, George; Shuvalova, Ludmilla; Dubrovska, Ievgeniia; Winsor, James [Center for Structural Genomics of Infectious Diseases, (United States); Northwestern University, Chicago, IL 60611 (United States); Zhou, Min [Center for Structural Genomics of Infectious Diseases, (United States); Argonne National Laboratory, Argonne, IL 60439 (United States); University of Chicago, Chicago, IL 60637 (United States); Onopriyenko, Olena; Skarina, Tatiana [Center for Structural Genomics of Infectious Diseases, (United States); University of Toronto, Toronto, Ontario M5G 1L6 (Canada); Papazisi, Leka; Kwon, Keehwan; Peterson, Scott N. [Center for Structural Genomics of Infectious Diseases, (United States); J. Craig Venter Institute, Rockville, MD 20850 (United States); Joachimiak, Andrzej [Center for Structural Genomics of Infectious Diseases, (United States); Argonne National Laboratory, Argonne, IL 60439 (United States); University of Chicago, Chicago, IL 60637 (United States); Savchenko, Alexei [Center for Structural Genomics of Infectious Diseases, (United States); University of Toronto, Toronto, Ontario M5G 1L6 (Canada); Anderson, Wayne F., E-mail: wf-anderson@northwestern.edu [Center for Structural Genomics of Infectious Diseases, (United States); Northwestern University, Chicago, IL 60611 (United States)

2012-10-01

The structural characterization of acyl-carrier-protein synthase (AcpS) from three different pathogenic microorganisms is reported. One interesting finding of the present work is a crystal artifact related to the activity of the enzyme, which fortuitously represents an opportunity for a strategy to design a potential inhibitor of a pathogenic AcpS. Some bacterial type II fatty-acid synthesis (FAS II) enzymes have been shown to be important candidates for drug discovery. The scientific and medical quest for new FAS II protein targets continues to stimulate research in this field. One of the possible additional candidates is the acyl-carrier-protein synthase (AcpS) enzyme. Its holo form post-translationally modifies the apo form of an acyl carrier protein (ACP), which assures the constant delivery of thioester intermediates to the discrete enzymes of FAS II. At the Center for Structural Genomics of Infectious Diseases (CSGID), AcpSs from Staphylococcus aureus (AcpS{sub SA}), Vibrio cholerae (AcpS{sub VC}) and Bacillus anthracis (AcpS{sub BA}) have been structurally characterized in their apo, holo and product-bound forms, respectively. The structure of AcpS{sub BA} is emphasized because of the two 3′, 5′-adenosine diphosphate (3′, 5′-ADP) product molecules that are found in each of the three coenzyme A (CoA) binding sites of the trimeric protein. One 3′, 5′-ADP is bound as the 3′, 5′-ADP part of CoA in the known structures of the CoA–AcpS and 3′, 5′-ADP–AcpS binary complexes. The position of the second 3′, 5′-ADP has never been described before. It is in close proximity to the first 3′, 5′-ADP and the ACP-binding site. The coordination of two ADPs in AcpS{sub BA} may possibly be exploited for the design of AcpS inhibitors that can block binding of both CoA and ACP.

Structural characterization and comparison of three acyl-carrier-protein synthases from pathogenic bacteria

International Nuclear Information System (INIS)

Halavaty, Andrei S.; Kim, Youngchang; Minasov, George; Shuvalova, Ludmilla; Dubrovska, Ievgeniia; Winsor, James; Zhou, Min; Onopriyenko, Olena; Skarina, Tatiana; Papazisi, Leka; Kwon, Keehwan; Peterson, Scott N.; Joachimiak, Andrzej; Savchenko, Alexei; Anderson, Wayne F.

2012-01-01

The structural characterization of acyl-carrier-protein synthase (AcpS) from three different pathogenic microorganisms is reported. One interesting finding of the present work is a crystal artifact related to the activity of the enzyme, which fortuitously represents an opportunity for a strategy to design a potential inhibitor of a pathogenic AcpS. Some bacterial type II fatty-acid synthesis (FAS II) enzymes have been shown to be important candidates for drug discovery. The scientific and medical quest for new FAS II protein targets continues to stimulate research in this field. One of the possible additional candidates is the acyl-carrier-protein synthase (AcpS) enzyme. Its holo form post-translationally modifies the apo form of an acyl carrier protein (ACP), which assures the constant delivery of thioester intermediates to the discrete enzymes of FAS II. At the Center for Structural Genomics of Infectious Diseases (CSGID), AcpSs from Staphylococcus aureus (AcpS SA ), Vibrio cholerae (AcpS VC ) and Bacillus anthracis (AcpS BA ) have been structurally characterized in their apo, holo and product-bound forms, respectively. The structure of AcpS BA is emphasized because of the two 3′, 5′-adenosine diphosphate (3′, 5′-ADP) product molecules that are found in each of the three coenzyme A (CoA) binding sites of the trimeric protein. One 3′, 5′-ADP is bound as the 3′, 5′-ADP part of CoA in the known structures of the CoA–AcpS and 3′, 5′-ADP–AcpS binary complexes. The position of the second 3′, 5′-ADP has never been described before. It is in close proximity to the first 3′, 5′-ADP and the ACP-binding site. The coordination of two ADPs in AcpS BA may possibly be exploited for the design of AcpS inhibitors that can block binding of both CoA and ACP

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...

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

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.

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.

Physics holo.lab learning experience: using smartglasses for augmented reality labwork to foster the concepts of heat conduction

Science.gov (United States)

Strzys, M. P.; Kapp, S.; Thees, M.; Klein, P.; Lukowicz, P.; Knierim, P.; Schmidt, A.; Kuhn, J.

2018-05-01

Fundamental concepts of thermodynamics rely on abstract physical quantities such as energy, heat and entropy, which play an important role in the process of interpreting thermal phenomena and statistical mechanics. However, these quantities are not covered by human visual perception, and since heat sensation is purely qualitative and easy to deceive, an intuitive understanding often is lacking. Today immersive technologies like head-mounted displays of the newest generation, especially HoloLens, allow for high-quality augmented reality learning experiences, which can overcome this gap in human perception by presenting different representations of otherwise invisible quantities directly in the field of view of the user on the experimental apparatus, which simultaneously avoids a split-attention effect. In a mixed reality (MR) scenario as presented in this paper—which we call a holo.lab—human perception can be extended to the thermal regime by presenting false-color representations of the temperature of objects as a virtual augmentation directly on the real object itself in real-time. Direct feedback to experimental actions of the users in the form of different representations allows for immediate comparison to theoretical principles and predictions and therefore is supposed to intensify the theory–experiment interactions and to increase students’ conceptual understanding. We tested this technology for an experiment on thermal conduction of metals in the framework of undergraduate laboratories. A pilot study with treatment and control groups (N = 59) showed a small positive effect of MR on students’ performance measured with a standardized concept test for thermodynamics, pointing to an improvement of the understanding of the underlying physical concepts. These findings indicate that complex experiments could benefit even more from augmentation. This motivates us to enrich further experiments with MR.

Solution Structure of 4′-Phosphopantetheine - GmACP3 from Geobacter metallireducens: A Specialized Acyl Carrier Protein with Atypical Structural Features and a Putative Role in Lipopolysaccharide Biosynthesis†

Science.gov (United States)

Ramelot, Theresa A.; Smola, Matthew J.; Lee, Hsiau-Wei; Ciccosanti, Colleen; Hamilton, Keith; Acton, Thomas B.; Xiao, Rong; Everett, John K.; Prestegard, James H.; Montelione, Gaetano T.; Kennedy, Michael A.

2011-01-01

GmACP3 from Geobacter metallireducens is a specialized acyl carrier protein (ACP) whose gene, gmet_2339, is located near genes encoding many proteins involved in lipopolysaccharide (LPS) biosynthesis, indicating a likely function for GmACP3 in LPS production. By overexpression in Escherichia coli, about 50% holo-GmACP3 and 50% apo-GmACP3 were obtained. Apo-GmACP3 exhibited slow precipitation and non-monomeric behavior by 15N NMR relaxation measurements. Addition of 4′-phosphopantetheine (4′-PP) via enzymatic conversion by E. coli holo-ACP synthase, resulted in stable >95% holo-GmACP3 that was characterized as monomeric by 15N relaxation measurements and had no indication of conformational exchange. We have determined a high-resolution solution structure of holo-GmACP3 by standard NMR methods, including refinement with two sets of NH residual dipolar couplings, allowing for a detailed structural analysis of the interactions between 4′-PP and GmACP3. Whereas the overall four helix bundle topology is similar to previously solved ACP structures, this structure has unique characteristics, including an ordered 4′-PP conformation that places the thiol at the entrance to a central hydrophobic cavity near a conserved hydrogen-bonded Trp-His pair. These residues are part of a conserved WDSLxH/N motif found in GmACP3 and it’s orthologs. The helix locations and the large hydrophobic cavity are more similar to medium- and long-chain acyl-ACPs than to other apo- and holo-ACP structures. Taken together, structural characterization along with bioinformatic analysis of nearby genes suggest that GmACP3 is involved in lipid A acylation, possibly by atypical long-chain hydroxy fatty acids, and potentially involved in synthesis of secondary metabolites. PMID:21235239

Structural and energetic effects of A2A adenosine receptor mutations on agonist and antagonist binding.

Directory of Open Access Journals (Sweden)

Henrik Keränen

Full Text Available To predict structural and energetic effects of point mutations on ligand binding is of considerable interest in biochemistry and pharmacology. This is not only useful in connection with site-directed mutagenesis experiments, but could also allow interpretation and prediction of individual responses to drug treatment. For G-protein coupled receptors systematic mutagenesis has provided the major part of functional data as structural information until recently has been very limited. For the pharmacologically important A(2A adenosine receptor, extensive site-directed mutagenesis data on agonist and antagonist binding is available and crystal structures of both types of complexes have been determined. Here, we employ a computational strategy, based on molecular dynamics free energy simulations, to rationalize and interpret available alanine-scanning experiments for both agonist and antagonist binding to this receptor. These computer simulations show excellent agreement with the experimental data and, most importantly, reveal the molecular details behind the observed effects which are often not immediately evident from the crystal structures. The work further provides a distinct validation of the computational strategy used to assess effects of point-mutations on ligand binding. It also highlights the importance of considering not only protein-ligand interactions but also those mediated by solvent water molecules, in ligand design projects.

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

Hardware device to physical structure binding and authentication

Science.gov (United States)

Hamlet, Jason R.; Stein, David J.; Bauer, Todd M.

2013-08-20

Detection and deterrence of device tampering and subversion may be achieved by including a cryptographic fingerprint unit within a hardware device for authenticating a binding of the hardware device and a physical structure. The cryptographic fingerprint unit includes an internal physically unclonable function ("PUF") circuit disposed in or on the hardware device, which generate an internal PUF value. Binding logic is coupled to receive the internal PUF value, as well as an external PUF value associated with the physical structure, and generates a binding PUF value, which represents the binding of the hardware device and the physical structure. The cryptographic fingerprint unit also includes a cryptographic unit that uses the binding PUF value to allow a challenger to authenticate the binding.

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.

Identification of antibody glycosylation structures that predict monoclonal antibody Fc-effector function.

Science.gov (United States)

Chung, Amy W; Crispin, Max; Pritchard, Laura; Robinson, Hannah; Gorny, Miroslaw K; Yu, Xiaojie; Bailey-Kellogg, Chris; Ackerman, Margaret E; Scanlan, Chris; Zolla-Pazner, Susan; Alter, Galit

2014-11-13

To determine monoclonal antibody (mAb) features that predict fragment crystalizable (Fc)-mediated effector functions against HIV. Monoclonal antibodies, derived from Chinese hamster ovary cells or Epstein-Barr virus-immortalized mouse heteromyelomas, with specificity to key regions of the HIV envelope including gp120-V2, gp120-V3 loop, gp120-CD4(+) binding site, and gp41-specific antibodies, were functionally profiled to determine the relative contribution of the variable and constant domain features of the antibodies in driving robust Fc-effector functions. Each mAb was assayed for antibody-binding affinity to gp140(SR162), antibody-dependent cellular cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP) and for the ability to bind to FcγRIIa, FcγRIIb and FcγRIIIa receptors. Antibody glycan profiles were determined by HPLC. Neither the specificity nor the affinity of the mAbs determined the potency of Fc-effector function. FcγRIIIa binding strongly predicted ADCC and decreased galactose content inversely correlated with ADCP, whereas N-glycolylneuraminic acid-containing structures exhibited enhanced ADCP. Additionally, the bi-antenary glycan arm onto which galactose was added predicted enhanced binding to FcγRIIIa and ADCC activity, independent of the specificity of the mAb. Our studies point to the specific Fc-glycan structures that can selectively promote Fc-effector functions independently of the antibody specificity. Furthermore, we demonstrated antibody glycan structures associated with enhanced ADCP activity, an emerging Fc-effector function that may aid in the control and clearance of HIV infection.

Comparison of S. cerevisiae F-BAR domain structures reveals a conserved inositol phosphate binding site

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Moravcevic, Katarina; Alvarado, Diego; Schmitz, Karl R.; Kenniston, Jon A.; Mendrola, Jeannine M.; Ferguson, Kathryn M.; Lemmon, Mark A.

2015-01-01

SUMMARY F-BAR domains control membrane interactions in endocytosis, cytokinesis, and cell signaling. Although generally thought to bind curved membranes containing negatively charged phospholipids, numerous functional studies argue that differences in lipid-binding selectivities of F-BAR domains are functionally important. Here, we compare membrane-binding properties of the S. cerevisiae F-BAR domains in vitro and in vivo. Whereas some F-BAR domains (such as Bzz1p and Hof1p F-BARs) bind equally well to all phospholipids, the F-BAR domain from the RhoGAP Rgd1p preferentially binds phosphoinositides. We determined X-ray crystal structures of F-BAR domains from Hof1p and Rgd1p, the latter bound to an inositol phosphate. The structures explain phospholipid-binding selectivity differences, and reveal an F-BAR phosphoinositide binding site that is fully conserved in a mammalian RhoGAP called Gmip, and is partly retained in certain other F-BAR domains. Our findings reveal previously unappreciated determinants of F-BAR domain lipid-binding specificity, and provide a basis for its prediction from sequence. PMID:25620000

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

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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.

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.

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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/.

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

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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

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

OpenAIRE

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through c...

Diverse binding site structures revealed in homology models of polyreactive immunoglobulins

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Ramsland, Paul A.; Guddat, Luke W.; Edmundson, Allen B.; Raison, Robert L.

1997-09-01

We describe here computer-assisted homology models of the combiningsite structure of three polyreactive immunoglobulins. Template-based modelsof Fv (VL-VH) fragments were derived forthe surface IgM expressed by the malignant CD5 positive B cells from threepatients with chronic lymphocytic leukaemia (CLL). The conserved frameworkregions were constructed using crystal coordinates taken from highlyhomologous human variable domain structures (Pot and Hil). Complementaritydetermining regions (CDRs) were predicted by grafting loops, taken fromknown immunoglobulin structures, onto the Fv framework models. The CDRtemplates were chosen, where possible, to be of the same length and of highresidue identity or similarity. LCDR1, 2 and 3 as well as HCDR1 and 2 forthe Fv were constructed using this strategy. For HCDR3 prediction, adatabase containing the Cartesian coordinates of 30 of these loops wascompiled from unliganded antibody X-ray crystallographic structures and anHCDR3 of the same length as that of the B CLL Fv was selected as a template.In one case (Yar), the resulting HCDR3 model gave unfavourable interactionswhen incorporated into the Fv model. This HCDR3 was therefore modelled usingan alternative strategy of construction of the loop stems, using apreviously described HCDR3 conformation (Pot), followed by chain closurewith a β-turn. The template models were subjected to positionalrefinement using energy minimisation and molecular dynamics simulations(X-PLOR). An electrostatic surface description (GRASP) did not reveal acommon structural feature within the binding sites of the three polyreactiveFv. Thus, polyreactive immunoglobulins may recognise similar and multipleantigens through a diverse array of binding site structures.

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.

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.

Structural studies of Pseudomonas and Chromobacterium ω-aminotransferases provide insights into their differing substrate specificity

International Nuclear Information System (INIS)

Sayer, Christopher; Isupov, Michail N.; Westlake, Aaron; Littlechild, Jennifer A.

2013-01-01

The X-ray structures of two ω-aminotransferases from P. aeruginosa and C. violaceum in complex with an inhibitor offer the first detailed insight into the structural basis of the substrate specificity of these industrially important enzymes. The crystal structures and inhibitor complexes of two industrially important ω-aminotransferase enzymes from Pseudomonas aeruginosa and Chromobacterium violaceum have been determined in order to understand the differences in their substrate specificity. The two enzymes share 30% sequence identity and use the same amino acceptor, pyruvate; however, the Pseudomonas enzyme shows activity towards the amino donor β-alanine, whilst the Chromobacterium enzyme does not. Both enzymes show activity towards S-α-methylbenzylamine (MBA), with the Chromobacterium enzyme having a broader substrate range. The crystal structure of the P. aeruginosa enzyme has been solved in the holo form and with the inhibitor gabaculine bound. The C. violaceum enzyme has been solved in the apo and holo forms and with gabaculine bound. The structures of the holo forms of both enzymes are quite similar. There is little conformational difference observed between the inhibitor complex and the holoenzyme for the P. aeruginosa aminotransferase. In comparison, the crystal structure of the C. violaceum gabaculine complex shows significant structural rearrangements from the structures of both the apo and holo forms of the enzyme. It appears that the different rigidity of the protein scaffold contributes to the substrate specificity observed for the two ω-aminotransferases

Prediction of RNA-Binding Proteins by Voting Systems

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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.

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.

Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

Science.gov (United States)

Moghram, Basem Ameen; Nabil, Emad; Badr, Amr

2018-01-01

T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. In this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. The prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95

Modeling the binding affinity of structurally diverse industrial chemicals to carbon using the artificial intelligence approaches.

Science.gov (United States)

Gupta, Shikha; Basant, Nikita; Rai, Premanjali; Singh, Kunwar P

2015-11-01

Binding affinity of chemical to carbon is an important characteristic as it finds vast industrial applications. Experimental determination of the adsorption capacity of diverse chemicals onto carbon is both time and resource intensive, and development of computational approaches has widely been advocated. In this study, artificial intelligence (AI)-based ten different qualitative and quantitative structure-property relationship (QSPR) models (MLPN, RBFN, PNN/GRNN, CCN, SVM, GEP, GMDH, SDT, DTF, DTB) were established for the prediction of the adsorption capacity of structurally diverse chemicals to activated carbon following the OECD guidelines. Structural diversity of the chemicals and nonlinear dependence in the data were evaluated using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. The generalization and prediction abilities of the constructed models were established through rigorous internal and external validation procedures performed employing a wide series of statistical checks. In complete dataset, the qualitative models rendered classification accuracies between 97.04 and 99.93%, while the quantitative models yielded correlation (R(2)) values of 0.877-0.977 between the measured and the predicted endpoint values. The quantitative prediction accuracies for the higher molecular weight (MW) compounds (class 4) were relatively better than those for the low MW compounds. Both in the qualitative and quantitative models, the Polarizability was the most influential descriptor. Structural alerts responsible for the extreme adsorption behavior of the compounds were identified. Higher number of carbon and presence of higher halogens in a molecule rendered higher binding affinity. Proposed QSPR models performed well and outperformed the previous reports. A relatively better performance of the ensemble learning models (DTF, DTB) may be attributed to the strengths of the bagging and boosting algorithms which enhance the predictive accuracies. The

Properties and crystal structure of methylenetetrahydrofolate reductase from Thermus thermophilus HB8.

Directory of Open Access Journals (Sweden)

Sayaka Igari

Full Text Available Methylenetetrahydrofolate reductase (MTHFR is one of the enzymes involved in homocysteine metabolism. Despite considerable genetic and clinical attention, the reaction mechanism and regulation of this enzyme are not fully understood because of difficult production and poor stability. While recombinant enzymes from thermophilic organisms are often stable and easy to prepare, properties of thermostable MTHFRs have not yet been reported.MTHFR from Thermus thermophilus HB8, a homologue of Escherichia coli MetF, has been expressed in E. coli and purified. The purified MTHFR was chiefly obtained as a heterodimer of apo- and holo-subunits, that is, one flavin adenine dinucleotide (FAD prosthetic group bound per dimer. The crystal structure of the holo-subunit was quite similar to the β(8α(8 barrel of E. coli MTHFR, while that of the apo-subunit was a previously unobserved closed form. In addition, the intersubunit interface of the dimer in the crystals was different from any of the subunit interfaces of the tetramer of E. coli MTHFR. Free FAD could be incorporated into the apo-subunit of the purified Thermus enzyme after purification, forming a homodimer of holo-subunits. Comparison of the crystal structures of the heterodimer and the homodimer revealed different intersubunit interfaces, indicating a large conformational change upon FAD binding. Most of the biochemical properties of the heterodimer and the homodimer were the same, except that the homodimer showed ≈50% activity per FAD-bound subunit in folate-dependent reactions.The different intersubunit interfaces and rearrangement of subunits of Thermus MTHFR may be related to human enzyme properties, such as the allosteric regulation by S-adenosylmethionine and the enhanced instability of the Ala222Val mutant upon loss of FAD. Whereas E. coli MTHFR was the only structural model for human MTHFR to date, our findings suggest that Thermus MTHFR will be another useful model for this important enzyme.

Solving the crystal structure of human calcium-free S100Z: the siege and conquer of one of the last S100 family strongholds.

Science.gov (United States)

Calderone, V; Fragai, M; Gallo, G; Luchinat, C

2017-06-01

The X-ray structure of human apo-S100Z has been solved and compared with that of the zebrafish calcium-bound S100Z, which is the closest in sequence. Human apo-S100A12, which shows only 43% sequence identity to human S100Z, has been used as template model to solve the crystallographic phase problem. Although a significant buried surface area between the two physiological dimers is present in the asymmetric unit of human apo-S100Z, the protein does not form the superhelical arrangement in the crystal as observed for the zebrafish calcium-bound S100Z and human calcium-bound S100A4. These findings further demonstrate that calcium plays a fundamental role in triggering quaternary structure formation in several S100s. Solving the X-ray structure of human apo-S100Z by standard molecular replacement procedures turned out to be a challenge and required trying different models and different software tools among which only one was successful. The model that allowed structure solution was that with one of the lowest sequence identity with the target protein among the S100 family in the apo state. Based on the previously solved zebrafish holo-S100Z, a putative human holo-S100Z structure has been then calculated through homology modeling; the differences between the experimental human apo and calculated holo structure have been compared to those existing for other members of the family.

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.

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.

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

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.

eMatchSite: sequence order-independent structure alignments of ligand binding pockets in protein models.

Directory of Open Access Journals (Sweden)

Michal Brylinski

2014-09-01

Full Text Available Detecting similarities between ligand binding sites in the absence of global homology between target proteins has been recognized as one of the critical components of modern drug discovery. Local binding site alignments can be constructed using sequence order-independent techniques, however, to achieve a high accuracy, many current algorithms for binding site comparison require high-quality experimental protein structures, preferably in the bound conformational state. This, in turn, complicates proteome scale applications, where only various quality structure models are available for the majority of gene products. To improve the state-of-the-art, we developed eMatchSite, a new method for constructing sequence order-independent alignments of ligand binding sites in protein models. Large-scale benchmarking calculations using adenine-binding pockets in crystal structures demonstrate that eMatchSite generates accurate alignments for almost three times more protein pairs than SOIPPA. More importantly, eMatchSite offers a high tolerance to structural distortions in ligand binding regions in protein models. For example, the percentage of correctly aligned pairs of adenine-binding sites in weakly homologous protein models is only 4-9% lower than those aligned using crystal structures. This represents a significant improvement over other algorithms, e.g. the performance of eMatchSite in recognizing similar binding sites is 6% and 13% higher than that of SiteEngine using high- and moderate-quality protein models, respectively. Constructing biologically correct alignments using predicted ligand binding sites in protein models opens up the possibility to investigate drug-protein interaction networks for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning. eMatchSite is freely available to the academic community as a web-server and a stand-alone software distribution at http://www.brylinski.org/ematchsite.

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...

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.

The structural flexibility of the human copper chaperone Atox1: Insights from combined pulsed EPR studies and computations.

Science.gov (United States)

Levy, Ariel R; Turgeman, Meital; Gevorkyan-Aiapetov, Lada; Ruthstein, Sharon

2017-08-01

Metallochaperones are responsible for shuttling metal ions to target proteins. Thus, a metallochaperone's structure must be sufficiently flexible both to hold onto its ion while traversing the cytoplasm and to transfer the ion to or from a partner protein. Here, we sought to shed light on the structure of Atox1, a metallochaperone involved in the human copper regulation system. Atox1 shuttles copper ions from the main copper transporter, Ctr1, to the ATP7b transporter in the Golgi apparatus. Conventional biophysical tools such as X-ray or NMR cannot always target the various conformational states of metallochaperones, owing to a requirement for crystallography or low sensitivity and resolution. Electron paramagnetic resonance (EPR) spectroscopy has recently emerged as a powerful tool for resolving biological reactions and mechanisms in solution. When coupled with computational methods, EPR with site-directed spin labeling and nanoscale distance measurements can provide structural information on a protein or protein complex in solution. We use these methods to show that Atox1 can accommodate at least four different conformations in the apo state (unbound to copper), and two different conformations in the holo state (bound to copper). We also demonstrate that the structure of Atox1 in the holo form is more compact than in the apo form. Our data provide insight regarding the structural mechanisms through which Atox1 can fulfill its dual role of copper binding and transfer. © 2017 The Protein Society.

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 .

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...

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity: in silico bioinformatic step-by-step guide using quantitative structure-activity relationships.

Science.gov (United States)

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

2007-01-01

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method

Concurrent Increases and Decreases in Local Stability and Conformational Heterogeneity in Cu, Zn Superoxide Dismutase Variants Revealed by Temperature-Dependence of Amide Chemical Shifts.

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Doyle, Colleen M; Rumfeldt, Jessica A; Broom, Helen R; Sekhar, Ashok; Kay, Lewis E; Meiering, Elizabeth M

2016-03-08

The chemical shifts of backbone amide protons in proteins are sensitive reporters of local structural stability and conformational heterogeneity, which can be determined from their readily measured linear and nonlinear temperature-dependences, respectively. Here we report analyses of amide proton temperature-dependences for native dimeric Cu, Zn superoxide dismutase (holo pWT SOD1) and structurally diverse mutant SOD1s associated with amyotrophic lateral sclerosis (ALS). Holo pWT SOD1 loses structure with temperature first at its periphery and, while having extremely high global stability, nevertheless exhibits extensive conformational heterogeneity, with ∼1 in 5 residues showing evidence for population of low energy alternative states. The holo G93A and E100G ALS mutants have moderately decreased global stability, whereas V148I is slightly stabilized. Comparison of the holo mutants as well as the marginally stable immature monomeric unmetalated and disulfide-reduced (apo(2SH)) pWT with holo pWT shows that changes in the local structural stability of individual amides vary greatly, with average changes corresponding to differences in global protein stability measured by differential scanning calorimetry. Mutants also exhibit altered conformational heterogeneity compared to pWT. Strikingly, substantial increases as well as decreases in local stability and conformational heterogeneity occur, in particular upon maturation and for G93A. Thus, the temperature-dependence of amide shifts for SOD1 variants is a rich source of information on the location and extent of perturbation of structure upon covalent changes and ligand binding. The implications for potential mechanisms of toxic misfolding of SOD1 in disease and for general aspects of protein energetics, including entropy-enthalpy compensation, are discussed.

Structure and Stability of Molecular Crystals with Many-Body Dispersion-Inclusive Density Functional Tight Binding.

Science.gov (United States)

Mortazavi, Majid; Brandenburg, Jan Gerit; Maurer, Reinhard J; Tkatchenko, Alexandre

2018-01-18

Accurate prediction of structure and stability of molecular crystals is crucial in materials science and requires reliable modeling of long-range dispersion interactions. Semiempirical electronic structure methods are computationally more efficient than their ab initio counterparts, allowing structure sampling with significant speedups. We combine the Tkatchenko-Scheffler van der Waals method (TS) and the many-body dispersion method (MBD) with third-order density functional tight-binding (DFTB3) via a charge population-based method. We find an overall good performance for the X23 benchmark database of molecular crystals, despite an underestimation of crystal volume that can be traced to the DFTB parametrization. We achieve accurate lattice energy predictions with DFT+MBD energetics on top of vdW-inclusive DFTB3 structures, resulting in a speedup of up to 3000 times compared with a full DFT treatment. This suggests that vdW-inclusive DFTB3 can serve as a viable structural prescreening tool in crystal structure prediction.

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

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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".

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/.

Structural characterization of the interactions between calmodulin and skeletal muscle myosin light chain kinase: Effect of peptide (576-594)G binding on the Ca2+-binding domains

International Nuclear Information System (INIS)

Seeholzer, S.H.; Wand, A.J.

1989-01-01

Calcium-containing calmodulin (CaM) and its complex with a peptide corresponding to the calmodulin-binding domain of skeletal muscle myosin light chain kinase [skMLCK(576-594)G] have been studied by one- and two-dimensional 1 H NMR techniques. Resonances arising from the antiparallel β-sheet structures associated with the calcium-binding domains of CaM and their counterparts in the CaM-skMLCK(576-594)G complex have been assigned. The assignments were initiated by application of the main chain directed assignment strategy. It is found that, despite significant changes in chemical shifts of resonances arising from amino acid residues in this region upon binding of the peptide, the β-sheets have virtually the same structure in the complex as in CaM. Hydrogen exchange rates of amide NH within the β-sheet structures are significantly slowed upon binding of peptide. These data, in conjunction with the observed nuclear Overhauser effect (NOE) patterns and relative intensities and the downfield shifts of associated amide and α resonances upon binding of peptide, show that the peptide stabilizes the Ca 2+ -bound state of calmodulin. The observed pattern of NOEs within the β-sheets and their structural similarity correspond closely to those predicted by the crystal structure. These findings imply that the apparent inconsistency of the crystal structure with recently reported low-angle X-ray scattering profiles of CaM may lie within the putative central helix bridging the globular domains

Plasticity of the Binding Site of Renin: Optimized Selection of Protein Structures for Ensemble Docking.

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Strecker, Claas; Meyer, Bernd

2018-05-02

Protein flexibility poses a major challenge to docking of potential ligands in that the binding site can adopt different shapes. Docking algorithms usually keep the protein rigid and only allow the ligand to be treated as flexible. However, a wrong assessment of the shape of the binding pocket can prevent a ligand from adapting a correct pose. Ensemble docking is a simple yet promising method to solve this problem: Ligands are docked into multiple structures, and the results are subsequently merged. Selection of protein structures is a significant factor for this approach. In this work we perform a comprehensive and comparative study evaluating the impact of structure selection on ensemble docking. We perform ensemble docking with several crystal structures and with structures derived from molecular dynamics simulations of renin, an attractive target for antihypertensive drugs. Here, 500 ns of MD simulations revealed binding site shapes not found in any available crystal structure. We evaluate the importance of structure selection for ensemble docking by comparing binding pose prediction, ability to rank actives above nonactives (screening utility), and scoring accuracy. As a result, for ensemble definition k-means clustering appears to be better suited than hierarchical clustering with average linkage. The best performing ensemble consists of four crystal structures and is able to reproduce the native ligand poses better than any individual crystal structure. Moreover this ensemble outperforms 88% of all individual crystal structures in terms of screening utility as well as scoring accuracy. Similarly, ensembles of MD-derived structures perform on average better than 75% of any individual crystal structure in terms of scoring accuracy at all inspected ensembles sizes.

Crystal structure of the gamma-2 herpesvirus LANA DNA binding domain identifies charged surface residues which impact viral latency.

Directory of Open Access Journals (Sweden)

Bruno Correia

Full Text Available Latency-associated nuclear antigen (LANA mediates γ2-herpesvirus genome persistence and regulates transcription. We describe the crystal structure of the murine gammaherpesvirus-68 LANA C-terminal domain at 2.2 Å resolution. The structure reveals an alpha-beta fold that assembles as a dimer, reminiscent of Epstein-Barr virus EBNA1. A predicted DNA binding surface is present and opposite this interface is a positive electrostatic patch. Targeted DNA recognition substitutions eliminated DNA binding, while certain charged patch mutations reduced bromodomain protein, BRD4, binding. Virus containing LANA abolished for DNA binding was incapable of viable latent infection in mice. Virus with mutations at the charged patch periphery exhibited substantial deficiency in expansion of latent infection, while central region substitutions had little effect. This deficiency was independent of BRD4. These results elucidate the LANA DNA binding domain structure and reveal a unique charged region that exerts a critical role in viral latent infection, likely acting through a host cell protein(s.

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

Science.gov (United States)

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

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

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.

Structure and self-assembly of the calcium binding matrix protein of human metapneumovirus.

Science.gov (United States)

Leyrat, Cedric; Renner, Max; Harlos, Karl; Huiskonen, Juha T; Grimes, Jonathan M

2014-01-07

The matrix protein (M) of paramyxoviruses plays a key role in determining virion morphology by directing viral assembly and budding. Here, we report the crystal structure of the human metapneumovirus M at 2.8 Å resolution in its native dimeric state. The structure reveals the presence of a high-affinity Ca²⁺ binding site. Molecular dynamics simulations (MDS) predict a secondary lower-affinity site that correlates well with data from fluorescence-based thermal shift assays. By combining small-angle X-ray scattering with MDS and ensemble analysis, we captured the structure and dynamics of M in solution. Our analysis reveals a large positively charged patch on the protein surface that is involved in membrane interaction. Structural analysis of DOPC-induced polymerization of M into helical filaments using electron microscopy leads to a model of M self-assembly. The conservation of the Ca²⁺ binding sites suggests a role for calcium in the replication and morphogenesis of pneumoviruses. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

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

Molecular basis of calcium-sensitizing and desensitizing mutations of the human cardiac troponin C regulatory domain: a multi-scale simulation study.

Directory of Open Access Journals (Sweden)

Peter Michael Kekenes-Huskey

Full Text Available Troponin C (TnC is implicated in the initiation of myocyte contraction via binding of cytosolic Ca²⁺ and subsequent recognition of the Troponin I switch peptide. Mutations of the cardiac TnC N-terminal regulatory domain have been shown to alter both calcium binding and myofilament force generation. We have performed molecular dynamics simulations of engineered TnC variants that increase or decrease Ca²⁺ sensitivity, in order to understand the structural basis of their impact on TnC function. We will use the distinction for mutants that are associated with increased Ca²⁺ affinity and for those mutants with reduced affinity. Our studies demonstrate that for GOF mutants V44Q and L48Q, the structure of the physiologically-active site II Ca²⁺ binding site in the Ca²⁺-free (apo state closely resembled the Ca²⁺-bound (holo state. In contrast, site II is very labile for LOF mutants E40A and V79Q in the apo form and bears little resemblance with the holo conformation. We hypothesize that these phenomena contribute to the increased association rate, k(on, for the GOF mutants relative to LOF. Furthermore, we observe significant positive and negative positional correlations between helices in the GOF holo mutants that are not found in the LOF mutants. We anticipate these correlations may contribute either directly to Ca²⁺ affinity or indirectly through TnI association. Our observations based on the structure and dynamics of mutant TnC provide rationale for binding trends observed in GOF and LOF mutants and will guide the development of inotropic drugs that target TnC.

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.

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

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.

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.

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.

Theoretical prediction of low-density hexagonal ZnO hollow structures

Energy Technology Data Exchange (ETDEWEB)

Tuoc, Vu Ngoc, E-mail: tuoc.vungoc@hust.edu.vn [Institute of Engineering Physics, Hanoi University of Science and Technology, 1 Dai Co Viet Road, Hanoi (Viet Nam); Huan, Tran Doan [Institute of Materials Science, University of Connecticut, Storrs, Connecticut 06269-3136 (United States); Thao, Nguyen Thi [Institute of Engineering Physics, Hanoi University of Science and Technology, 1 Dai Co Viet Road, Hanoi (Viet Nam); Hong Duc University, 307 Le Lai, Thanh Hoa City (Viet Nam); Tuan, Le Manh [Hong Duc University, 307 Le Lai, Thanh Hoa City (Viet Nam)

2016-10-14

Along with wurtzite and zinc blende, zinc oxide (ZnO) has been found in a large number of polymorphs with substantially different properties and, hence, applications. Therefore, predicting and synthesizing new classes of ZnO polymorphs are of great significance and have been gaining considerable interest. Herein, we perform a density functional theory based tight-binding study, predicting several new series of ZnO hollow structures using the bottom-up approach. The geometry of the building blocks allows for obtaining a variety of hexagonal, low-density nanoporous, and flexible ZnO hollow structures. Their stability is discussed by means of the free energy computed within the lattice-dynamics approach. Our calculations also indicate that all the reported hollow structures are wide band gap semiconductors in the same fashion with bulk ZnO. The electronic band structures of the ZnO hollow structures are finally examined in detail.

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.

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...

Subfamily-specific adaptations in the structures of two penicillin-binding proteins from Mycobacterium tuberculosis.

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Daniil M Prigozhin

Full Text Available Beta-lactam antibiotics target penicillin-binding proteins including several enzyme classes essential for bacterial cell-wall homeostasis. To better understand the functional and inhibitor-binding specificities of penicillin-binding proteins from the pathogen, Mycobacterium tuberculosis, we carried out structural and phylogenetic analysis of two predicted D,D-carboxypeptidases, Rv2911 and Rv3330. Optimization of Rv2911 for crystallization using directed evolution and the GFP folding reporter method yielded a soluble quadruple mutant. Structures of optimized Rv2911 bound to phenylmethylsulfonyl fluoride and Rv3330 bound to meropenem show that, in contrast to the nonspecific inhibitor, meropenem forms an extended interaction with the enzyme along a conserved surface. Phylogenetic analysis shows that Rv2911 and Rv3330 belong to different clades that emerged in Actinobacteria and are not represented in model organisms such as Escherichia coli and Bacillus subtilis. Clade-specific adaptations allow these enzymes to fulfill distinct physiological roles despite strict conservation of core catalytic residues. The characteristic differences include potential protein-protein interaction surfaces and specificity-determining residues surrounding the catalytic site. Overall, these structural insights lay the groundwork to develop improved beta-lactam therapeutics for tuberculosis.

STRUCTURAL FEATURES OF PLANT CHITINASES AND CHITIN-BINDING PROTEINS

NARCIS (Netherlands)

BEINTEMA, JJ

1994-01-01

Structural features of plant chitinases and chitin-binding proteins are discussed. Many of these proteins consist of multiple domains,of which the chitin-binding hevein domain is a predominant one. X-ray and NMR structures of representatives of the major classes of these proteins are available now,

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

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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.

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

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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.

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

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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.

Use of Spectroscopic, Zeta Potential and Molecular Dynamic Techniques to Study the Interaction between Human Holo-Transferrin and Two Antagonist Drugs: Comparison of Binary and Ternary Systems

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Mohammad Reza Saberi

2012-03-01

Full Text Available For the first time, the binding of ropinirole hydrochloride (ROP and aspirin (ASA to human holo-transferrin (hTf has been investigated by spectroscopic approaches (fluorescence quenching, synchronous fluorescence, time-resolved fluorescence, three-dimensional fluorescence, UV-vis absorption, circular dichroism, resonance light scattering, as well as zeta potential and molecular modeling techniques, under simulated physiological conditions. Fluorescence analysis was used to estimate the effect of the ROP and ASA drugs on the fluorescence of hTf as well as to define the binding and quenching properties of binary and ternary complexes. The synchronized fluorescence and three-dimensional fluorescence spectra demonstrated some micro-environmental and conformational changes around the Trp and Tyr residues with a faint red shift. Thermodynamic analysis displayed the van der Waals forces and hydrogen bonds interactions are the major acting forces in stabilizing the complexes. Steady-state and time-resolved fluorescence data revealed that the fluorescence quenching of complexes are static mechanism. The effect of the drugs aggregating on the hTf resulted in an enhancement of the resonance light scattering (RLS intensity. The average binding distance between were computed according to the forster non-radiation energy transfer theory. The circular dichroism (CD spectral examinations indicated that the binding of the drugs induced a conformational change of hTf. Measurements of the zeta potential indicated that the combination of electrostatic and hydrophobic interactions between ROP, ASA and hTf formed micelle-like clusters. The molecular modeling confirmed the experimental results. This study is expected to provide important insight into the interaction of hTf with ROP and ASA to use in various toxicological and therapeutic processes.

The necessity of connection structures in neural models of variable binding.

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van der Velde, Frank; de Kamps, Marc

2015-08-01

In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other ('connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

Specificity of anion-binding in the substrate-pocket ofbacteriorhodopsin

Energy Technology Data Exchange (ETDEWEB)

Facciotti, Marc T.; Cheung, Vincent S.; Lunde, Christopher S.; Rouhani, Shahab; Baliga, Nitin S.; Glaeser, Robert M.

2003-08-30

The structure of the D85S mutant of bacteriorhodopsin with a nitrate anion bound in the Schiff-base binding site, and the structure of the anion-free protein have been obtained in the same crystal form. Together with the previously solved structures of this anion pump, in both the anion-free state and bromide-bound state, these new structures provide insight into how this mutant of bacteriorhodopsin is able to bind a variety of different anions in the same binding pocket. The structural analysis reveals that the main structural change that accommodates different anions is the repositioning of the polar side-chain of S85. On the basis of these x-ray crystal structures, the prediction is then made that the D85S/D212N double mutant might bind similar anions and do so over a broader pH range than does the single mutant. Experimental comparison of the dissociation constants, K{sub d}, for a variety of anions confirms this prediction and demonstrates, in addition, that the binding affinity is dramatically improved by the D212N substitution.

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...

Prediction of Nucleotide Binding Peptides Using Star Graph Topological Indices.

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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.

Two unique ligand-binding clamps of Rhizopus oryzae starch binding domain for helical structure disruption of amylose.

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Ting-Ying Jiang

Full Text Available The N-terminal starch binding domain of Rhizopus oryzae glucoamylase (RoSBD has a high binding affinity for raw starch. RoSBD has two ligand-binding sites, each containing a ligand-binding clamp: a polyN clamp residing near binding site I is unique in that it is expressed in only three members of carbohydrate binding module family 21 (CBM21 members, and a Y32/F58 clamp located at binding site II is conserved in several CBMs. Here we characterized different roles of these sites in the binding of insoluble and soluble starches using an amylose-iodine complex assay, atomic force microscopy, isothermal titration calorimetry, site-directed mutagenesis, and structural bioinformatics. RoSBD induced the release of iodine from the amylose helical cavity and disrupted the helical structure of amylose type III, thereby significantly diminishing the thickness and length of the amylose type III fibrils. A point mutation in the critical ligand-binding residues of sites I and II, however, reduced both the binding affinity and amylose helix disruption. This is the first molecular model for structure disruption of the amylose helix by a non-hydrolytic CBM21 member. RoSBD apparently twists the helical amylose strands apart to expose more ligand surface for further SBD binding. Repeating the process triggers the relaxation and unwinding of amylose helices to generate thinner and shorter amylose fibrils, which are more susceptible to hydrolysis by glucoamylase. This model aids in understanding the natural roles of CBMs in protein-glycan interactions and contributes to potential molecular engineering of CBMs.

Positively-charged semi-tunnel is a structural and surface characteristic of polyphosphate-binding proteins: an in-silico study.

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Zheng Zachory Wei

Full Text Available Phosphate is essential for all major life processes, especially energy metabolism and signal transduction. A linear phosphate polymer, polyphosphate (polyP, linked by high-energy phosphoanhydride bonds, can interact with various proteins, playing important roles as an energy source and regulatory factor. However, polyP-binding structures are largely unknown. Here we proposed a putative polyP binding site, a positively-charged semi-tunnel (PCST, identified by surface electrostatics analyses in polyP kinases (PPKs and many other polyP-related proteins. We found that the PCSTs in varied proteins were folded in different secondary structure compositions. Molecular docking calculations revealed a significant value for binding affinity to polyP in PCST-containing proteins. Utilizing the PCST identified in the β subunit of PPK3, we predicted the potential polyP-binding domain of PPK3. The discovery of this feature facilitates future searches for polyP-binding proteins and discovery of the mechanisms for polyP-binding activities. This should greatly enhance the understanding of the many physiological functions of protein-bound polyP and the involvement of polyP and polyP-binding proteins in various human diseases.

Domain-based small molecule binding site annotation

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Dumontier Michel

2006-03-01

Full Text Available Abstract Background Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID, a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB. More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites. Description Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST algorithm. SMID records are available for viewing at http://smid.blueprint.org. The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60% of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. Conclusion By

Crystal structure of the botulinum neurotoxin type G binding domain: insight into cell surface binding.

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Stenmark, Pål; Dong, Min; Dupuy, Jérôme; Chapman, Edwin R; Stevens, Raymond C

2010-04-16

Botulinum neurotoxins (BoNTs) typically bind the neuronal cell surface via dual interactions with both protein receptors and gangliosides. We present here the 1.9-A X-ray structure of the BoNT serotype G (BoNT/G) receptor binding domain (residues 868-1297) and a detailed view of protein receptor and ganglioside binding regions. The ganglioside binding motif (SxWY) has a conserved structure compared to the corresponding regions in BoNT serotype A and BoNT serotype B (BoNT/B), but several features of interactions with the hydrophilic face of the ganglioside are absent at the opposite side of the motif in the BoNT/G ganglioside binding cleft. This may significantly reduce the affinity between BoNT/G and gangliosides. BoNT/G and BoNT/B share the protein receptor synaptotagmin (Syt) I/II. The Syt binding site has a conserved hydrophobic plateau located centrally in the proposed protein receptor binding interface (Tyr1189, Phe1202, Ala1204, Pro1205, and Phe1212). Interestingly, only 5 of 14 residues that are important for binding between Syt-II and BoNT/B are conserved in BoNT/G, suggesting that the means by which BoNT/G and BoNT/B bind Syt diverges more than previously appreciated. Indeed, substitution of Syt-II Phe47 and Phe55 with alanine residues had little effect on the binding of BoNT/G, but strongly reduced the binding of BoNT/B. Furthermore, an extended solvent-exposed hydrophobic loop, located between the Syt binding site and the ganglioside binding cleft, may serve as a third membrane association and binding element to contribute to high-affinity binding to the neuronal membrane. While BoNT/G and BoNT/B are homologous to each other and both utilize Syt-I/Syt-II as their protein receptor, the precise means by which these two toxin serotypes bind to Syt appears surprisingly divergent. Copyright (c) 2010. Published by Elsevier Ltd.

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

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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

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

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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

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

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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).

Evidence of chemical exchange in recombinant Major Urinary Protein and quenching thereof upon pheromone binding

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Perazzolo, Chiara, E-mail: Chiara.Perazzolo@epfl.ch; Verde, Mariachiara [Ecole Polytechnique Federale de Lausanne, Institut des Sciences et Ingenierie Chimiques (Switzerland); Homans, Steve W. [University of Leeds, Institute of Molecular and Cellular Biology (United Kingdom); Bodenhausen, Geoffrey [Ecole Polytechnique Federale de Lausanne, Institut des Sciences et Ingenierie Chimiques (Switzerland)

2007-05-15

The internal dynamics of recombinant Major Urinary Protein (rMUP) have been investigated by monitoring transverse nitrogen-15 relaxation using multiple-echo Carr-Purcell-Meiboom-Gill (CPMG) experiments. While the ligand-free protein (APO-rMUP) features extensive evidence of motions on the milliseconds time scale, the complex with 2-methoxy-3-isobutylpyrazine (HOLO-rMUP) appears to be much less mobile on this time scale. At 308 K, exchange rates k{sub ex} = 500-2000 s{sup -1} were typically observed in APO-rMUP for residues located adjacent to a {beta}-turn comprising residues 83-87. These residues occlude an entry to the binding pocket and have been proposed to be a portal for ligand entry in other members of the lipocalin family, such as the retinol binding protein and the human fatty-acid binding protein. Exchange rates and populations are largely uncorrelated, suggesting local 'breathing' motions rather than a concerted global conformational change.

Evidence of chemical exchange in recombinant Major Urinary Protein and quenching thereof upon pheromone binding

International Nuclear Information System (INIS)

Perazzolo, Chiara; Verde, Mariachiara; Homans, Steve W.; Bodenhausen, Geoffrey

2007-01-01

The internal dynamics of recombinant Major Urinary Protein (rMUP) have been investigated by monitoring transverse nitrogen-15 relaxation using multiple-echo Carr-Purcell-Meiboom-Gill (CPMG) experiments. While the ligand-free protein (APO-rMUP) features extensive evidence of motions on the milliseconds time scale, the complex with 2-methoxy-3-isobutylpyrazine (HOLO-rMUP) appears to be much less mobile on this time scale. At 308 K, exchange rates k ex = 500-2000 s -1 were typically observed in APO-rMUP for residues located adjacent to a β-turn comprising residues 83-87. These residues occlude an entry to the binding pocket and have been proposed to be a portal for ligand entry in other members of the lipocalin family, such as the retinol binding protein and the human fatty-acid binding protein. Exchange rates and populations are largely uncorrelated, suggesting local 'breathing' motions rather than a concerted global conformational change

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.

Structure-based function prediction of the expanding mollusk tyrosinase family

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Huang, Ronglian; Li, Li; Zhang, Guofan

2017-11-01

Tyrosinase (Ty) is a common enzyme found in many different animal groups. In our previous study, genome sequencing revealed that the Ty family is expanded in the Pacific oyster ( Crassostrea gigas). Here, we examine the larger number of Ty family members in the Pacific oyster by high-level structure prediction to obtain more information about their function and evolution, especially the unknown role in biomineralization. We verified 12 Ty gene sequences from Crassostrea gigas genome and Pinctada fucata martensii transcriptome. By using phylogenetic analysis of these Tys with functionally known Tys from other molluscan species, eight subgroups were identified (CgTy_s1, CgTy_s2, MolTy_s1, MolTy-s2, MolTy-s3, PinTy-s1, PinTy-s2 and PviTy). Structural data and surface pockets of the dinuclear copper center in the eight subgroups of molluscan Ty were obtained using the latest versions of prediction online servers. Structural comparison with other Ty proteins from the protein databank revealed functionally important residues (HA1, HA2, HA3, HB1, HB2, HB3, Z1-Z9) and their location within these protein structures. The structural and chemical features of these pockets which may related to the substrate binding showed considerable variability among mollusks, which undoubtedly defines Ty substrate binding. Finally, we discuss the potential driving forces of Ty family evolution in mollusks. Based on these observations, we conclude that the Ty family has rapidly evolved as a consequence of substrate adaptation in mollusks.

MCTBI: a web server for predicting metal ion effects in RNA structures.

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Sun, Li-Zhen; Zhang, Jing-Xiang; Chen, Shi-Jie

2017-08-01

Metal ions play critical roles in RNA structure and function. However, web servers and software packages for predicting ion effects in RNA structures are notably scarce. Furthermore, the existing web servers and software packages mainly neglect ion correlation and fluctuation effects, which are potentially important for RNAs. We here report a new web server, the MCTBI server (http://rna.physics.missouri.edu/MCTBI), for the prediction of ion effects for RNA structures. This server is based on the recently developed MCTBI, a model that can account for ion correlation and fluctuation effects for nucleic acid structures and can provide improved predictions for the effects of metal ions, especially for multivalent ions such as Mg 2+ effects, as shown by extensive theory-experiment test results. The MCTBI web server predicts metal ion binding fractions, the most probable bound ion distribution, the electrostatic free energy of the system, and the free energy components. The results provide mechanistic insights into the role of metal ions in RNA structure formation and folding stability, which is important for understanding RNA functions and the rational design of RNA structures. © 2017 Sun et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

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.

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

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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

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

Structural analysis of site-directed mutants of cellular retinoic acid-binding protein II addresses the relationship between structural integrity and ligand binding

International Nuclear Information System (INIS)

Vaezeslami, Soheila; Jia, Xiaofei; Vasileiou, Chrysoula; Borhan, Babak; Geiger, James H.

2008-01-01

A water network stabilizes the structure of cellular retionic acid binding protein II. The structural integrity of cellular retinoic acid-binding protein II (CRABPII) has been investigated using the crystal structures of CRABPII mutants. The overall fold was well maintained by these CRABPII mutants, each of which carried multiple different mutations. A water-mediated network is found to be present across the large binding cavity, extending from Arg111 deep inside the cavity to the α2 helix at its entrance. This chain of interactions acts as a ‘pillar’ that maintains the integrity of the protein. The disruption of the water network upon loss of Arg111 leads to decreased structural integrity of the protein. A water-mediated network can be re-established by introducing the hydrophilic Glu121 inside the cavity, which results in a rigid protein with the α2 helix adopting an altered conformation compared with wild-type CRABPII

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.

Mapping small molecule binding data to structural domains.

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Kruger, Felix A; Rostom, Raghd; Overington, John P

2012-01-01

Large-scale bioactivity/SAR Open Data has recently become available, and this has allowed new analyses and approaches to be developed to help address the productivity and translational gaps of current drug discovery. One of the current limitations of these data is the relative sparsity of reported interactions per protein target, and complexities in establishing clear relationships between bioactivity and targets using bioinformatics tools. We detail in this paper the indexing of targets by the structural domains that bind (or are likely to bind) the ligand within a full-length protein. Specifically, we present a simple heuristic to map small molecule binding to Pfam domains. This profiling can be applied to all proteins within a genome to give some indications of the potential pharmacological modulation and regulation of all proteins. In this implementation of our heuristic, ligand binding to protein targets from the ChEMBL database was mapped to structural domains as defined by profiles contained within the Pfam-A database. Our mapping suggests that the majority of assay targets within the current version of the ChEMBL database bind ligands through a small number of highly prevalent domains, and conversely the majority of Pfam domains sampled by our data play no currently established role in ligand binding. Validation studies, carried out firstly against Uniprot entries with expert binding-site annotation and secondly against entries in the wwPDB repository of crystallographic protein structures, demonstrate that our simple heuristic maps ligand binding to the correct domain in about 90 percent of all assessed cases. Using the mappings obtained with our heuristic, we have assembled ligand sets associated with each Pfam domain. Small molecule binding has been mapped to Pfam-A domains of protein targets in the ChEMBL bioactivity database. The result of this mapping is an enriched annotation of small molecule bioactivity data and a grouping of activity classes

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

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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.

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.

Activator Protein-1: redox switch controlling structure and DNA-binding

Energy Technology Data Exchange (ETDEWEB)

Yin, Zhou; Machius, Mischa; Nestler, Eric J.; Rudenko, Gabby (Texas-MED); (Icahn)

2017-09-07

The transcription factor, activator protein-1 (AP-1), binds to cognate DNA under redox control; yet, the underlying mechanism has remained enigmatic. A series of crystal structures of the AP-1 FosB/JunD bZIP domains reveal ordered DNA-binding regions in both FosB and JunD even in absence DNA. However, while JunD is competent to bind DNA, the FosB bZIP domain must undergo a large conformational rearrangement that is controlled by a ‘redox switch’ centered on an inter-molecular disulfide bond. Solution studies confirm that FosB/JunD cannot undergo structural transition and bind DNA when the redox-switch is in the ‘OFF’ state, and show that the mid-point redox potential of the redox switch affords it sensitivity to cellular redox homeostasis. The molecular and structural studies presented here thus reveal the mechanism underlying redox-regulation of AP-1 Fos/Jun transcription factors and provide structural insight for therapeutic interventions targeting AP-1 proteins.

Structural Analysis of Botulinum Neurotoxin Type G Receptor Binding

Energy Technology Data Exchange (ETDEWEB)

Schmitt, John; Karalewitz, Andrew; Benefield, Desire A.; Mushrush, Darren J.; Pruitt, Rory N.; Spiller, Benjamin W.; Barbieri, Joseph T.; Lacy, D. Borden (Vanderbilt); (MCW)

2010-10-19

Botulinum neurotoxin (BoNT) binds peripheral neurons at the neuromuscular junction through a dual-receptor mechanism that includes interactions with ganglioside and protein receptors. The receptor identities vary depending on BoNT serotype (A-G). BoNT/B and BoNT/G bind the luminal domains of synaptotagmin I and II, homologous synaptic vesicle proteins. We observe conditions under which BoNT/B binds both Syt isoforms, but BoNT/G binds only SytI. Both serotypes bind ganglioside G{sub T1b}. The BoNT/G receptor-binding domain crystal structure provides a context for examining these binding interactions and a platform for understanding the physiological relevance of different Syt receptor isoforms in vivo.

ANALYSIS OF STRUCTURAL ELEMENT OF FAMILY 6 CARBOHYDRATE BINDING MODULE (CTCBM6B OF ALPHA-L-ARABINOFURANOSIDASE FROM CLOSTRIDIUM THERMOCELLUM

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Shadab Ahmed

2013-06-01

Full Text Available The amino acid sequence of a family 6 carbohydrate binding module (CtCBM6B from Clostridium thermocellum alpha-L-arabinofuranosidase showed close evolutionary relationship with some other member of family 6 carbohydrate binding modules. The CD spectrum analysis confirmed the secondary structure prediction of CtCBM6B as both showed beta-sheets (44-48% and random coils (52-54% and no alpha-helix. The hydrogen bonding plot of CtCBM6B showed many segments of parallel and anti-parallel beta-strands which was similar to the secondary structure prediction by PSIPRED VIEW. The three dimensional structure of CtCBM6B generated by MODELLER revealed a typical beta-sandwich architecture at its core, characteristic of beta-jelly roll CBM superfamily. The Ramachandran plot analysis by PROCHECK showed that out of 134 residues, 92.9% were in most favoured region, 6.2% in additionally allowed region and only 0.9% in generously allowed region which indicated a stable conformation of 3D model of CtCBM6B. The docking analysis of CtCBM6B for finding putative ligand binding sites showed that it has high binding affinity for arabinobiose, beta-L-arabinofuranose and beta-D-xylopyranose indicated by lower ligand binding energy (-14.28 kcal mol–1, -12.5 kcal mol–1 and -11.3 kcal mol–1, respectively. CtCBM6B also showed appreciable binding affinity with alpha-D-xylopyranose (–10.8 kcal mol–1, beta-L-arabinopyranose (–10.2 kcal mol-1, alpha-L-arabinopyranose (–10.0 kcal mol–1 and alpha-L-arabinofuranose (–8.75 kcal mol–1. The results indicated that CtCBM6B has high potential for binding arabinan, xylans and substituted xylans.

Protein docking prediction using predicted protein-protein interface

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Li Bin

2012-01-01

Full Text Available Abstract Background Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. Results We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm, is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. Conclusion We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Protein docking prediction using predicted protein-protein interface.

Science.gov (United States)

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Insights on Structural Characteristics and Ligand Binding Mechanisms of CDK2

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Yan Li

2015-04-01

Full Text Available Cyclin-dependent kinase 2 (CDK2 is a crucial regulator of the eukaryotic cell cycle. However it is well established that monomeric CDK2 lacks regulatory activity, which needs to be aroused by its positive regulators, cyclins E and A, or be phosphorylated on the catalytic segment. Interestingly, these activation steps bring some dynamic changes on the 3D-structure of the kinase, especially the activation segment. Until now, in the monomeric CDK2 structure, three binding sites have been reported, including the adenosine triphosphate (ATP binding site (Site I and two non-competitive binding sites (Site II and III. In addition, when the kinase is subjected to the cyclin binding process, the resulting structural changes give rise to a variation of the ATP binding site, thus generating an allosteric binding site (Site IV. All the four sites are demonstrated as being targeted by corresponding inhibitors, as is illustrated by the allosteric binding one which is targeted by inhibitor ANS (fluorophore 8-anilino-1-naphthalene sulfonate. In the present work, the binding mechanisms and their fluctuations during the activation process attract our attention. Therefore, we carry out corresponding studies on the structural characterization of CDK2, which are expected to facilitate the understanding of the molecular mechanisms of kinase proteins. Besides, the binding mechanisms of CDK2 with its relevant inhibitors, as well as the changes of binding mechanisms following conformational variations of CDK2, are summarized and compared. The summary of the conformational characteristics and ligand binding mechanisms of CDK2 in the present work will improve our understanding of the molecular mechanisms regulating the bioactivities of CDK2.

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...

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.

Structural prediction in aphasia

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Tessa Warren

2015-05-01

Full Text Available There is considerable evidence that young healthy comprehenders predict the structure of upcoming material, and that their processing is facilitated when they encounter material matching those predictions (e.g., Staub & Clifton, 2006; Yoshida, Dickey & Sturt, 2013. However, less is known about structural prediction in aphasia. There is evidence that lexical prediction may be spared in aphasia (Dickey et al., 2014; Love & Webb, 1977; cf. Mack et al, 2013. However, predictive mechanisms supporting facilitated lexical access may not necessarily support structural facilitation. Given that many people with aphasia (PWA exhibit syntactic deficits (e.g. Goodglass, 1993, PWA with such impairments may not engage in structural prediction. However, recent evidence suggests that some PWA may indeed predict upcoming structure (Hanne, Burchert, De Bleser, & Vashishth, 2015. Hanne et al. tracked the eyes of PWA (n=8 with sentence-comprehension deficits while they listened to reversible subject-verb-object (SVO and object-verb-subject (OVS sentences in German, in a sentence-picture matching task. Hanne et al. manipulated case and number marking to disambiguate the sentences’ structure. Gazes to an OVS or SVO picture during the unfolding of a sentence were assumed to indicate prediction of the structure congruent with that picture. According to this measure, the PWA’s structural prediction was impaired compared to controls, but they did successfully predict upcoming structure when morphosyntactic cues were strong and unambiguous. Hanne et al.’s visual-world evidence is suggestive, but their forced-choice sentence-picture matching task places tight constraints on possible structural predictions. Clearer evidence of structural prediction would come from paradigms where the content of upcoming material is not as constrained. The current study used self-paced reading study to examine structural prediction among PWA in less constrained contexts. PWA (n=17 who

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.

Structural modeling and DNA binding autoinhibition analysis of Ergp55, a critical transcription factor in prostate cancer.

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Shanti P Gangwar

Full Text Available BACKGROUND: The Ergp55 protein belongs to Ets family of transcription factor. The Ets proteins are highly conserved in their DNA binding domain and involved in various development processes and regulation of cancer metabolism. To study the structure and DNA binding autoinhibition mechanism of Ergp55 protein, we have produced full length and smaller polypeptides of Ergp55 protein in E. coli and characterized using various biophysical techniques. RESULTS: The Ergp55 polypeptides contain large amount of α-helix and random coil structures as measured by circular dichorism spectroscopy. The full length Ergp55 forms a flexible and elongated molecule as revealed by molecular modeling, dynamics simulation and structural prediction algorithms. The binding analyses of Ergp55 polypeptides with target DNA sequences of E74 and cfos promoters indicate that longer fragments of Ergp55 (beyond the Ets domain showed the evidence of auto-inhibition. This study also revealed the parts of Ergp55 protein that mediate auto-inhibition. SIGNIFICANCE: The current study will aid in designing the compounds that stabilize the inhibited form of Ergp55 and inhibit its binding to promoter DNA. It will contribute in the development of drugs targeting Ergp55 for the prostate cancer treatment.

Recent improvements to Binding MOAD: a resource for protein–ligand binding affinities and structures

Science.gov (United States)

Ahmed, Aqeel; Smith, Richard D.; Clark, Jordan J.; Dunbar, James B.; Carlson, Heather A.

2015-01-01

For over 10 years, Binding MOAD (Mother of All Databases; http://www.BindingMOAD.org) has been one of the largest resources for high-quality protein–ligand complexes and associated binding affinity data. Binding MOAD has grown at the rate of 1994 complexes per year, on average. Currently, it contains 23 269 complexes and 8156 binding affinities. Our annual updates curate the data using a semi-automated literature search of the references cited within the PDB file, and we have recently upgraded our website and added new features and functionalities to better serve Binding MOAD users. In order to eliminate the legacy application server of the old platform and to accommodate new changes, the website has been completely rewritten in the LAMP (Linux, Apache, MySQL and PHP) environment. The improved user interface incorporates current third-party plugins for better visualization of protein and ligand molecules, and it provides features like sorting, filtering and filtered downloads. In addition to the field-based searching, Binding MOAD now can be searched by structural queries based on the ligand. In order to remove redundancy, Binding MOAD records are clustered in different families based on 90% sequence identity. The new Binding MOAD, with the upgraded platform, features and functionalities, is now equipped to better serve its users. PMID:25378330

Activator Protein-1: redox switch controlling structure and DNA-binding.

Science.gov (United States)

Yin, Zhou; Machius, Mischa; Nestler, Eric J; Rudenko, Gabby

2017-11-02

The transcription factor, activator protein-1 (AP-1), binds to cognate DNA under redox control; yet, the underlying mechanism has remained enigmatic. A series of crystal structures of the AP-1 FosB/JunD bZIP domains reveal ordered DNA-binding regions in both FosB and JunD even in absence DNA. However, while JunD is competent to bind DNA, the FosB bZIP domain must undergo a large conformational rearrangement that is controlled by a 'redox switch' centered on an inter-molecular disulfide bond. Solution studies confirm that FosB/JunD cannot undergo structural transition and bind DNA when the redox-switch is in the 'OFF' state, and show that the mid-point redox potential of the redox switch affords it sensitivity to cellular redox homeostasis. The molecular and structural studies presented here thus reveal the mechanism underlying redox-regulation of AP-1 Fos/Jun transcription factors and provide structural insight for therapeutic interventions targeting AP-1 proteins. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

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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.

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

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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.

Crystal structure of mouse coronavirus receptor-binding domain complexed with its murine receptor

Energy Technology Data Exchange (ETDEWEB)

Peng, Guiqing; Sun, Dawei; Rajashankar, Kanagalaghatta R.; Qian, Zhaohui; Holmes, Kathryn V.; Li, Fang (Cornell); (UMM-MED); (Colorado)

2011-09-28

Coronaviruses have evolved diverse mechanisms to recognize different receptors for their cross-species transmission and host-range expansion. Mouse hepatitis coronavirus (MHV) uses the N-terminal domain (NTD) of its spike protein as its receptor-binding domain. Here we present the crystal structure of MHV NTD complexed with its receptor murine carcinoembryonic antigen-related cell adhesion molecule 1a (mCEACAM1a). Unexpectedly, MHV NTD contains a core structure that has the same {beta}-sandwich fold as human galectins (S-lectins) and additional structural motifs that bind to the N-terminal Ig-like domain of mCEACAM1a. Despite its galectin fold, MHV NTD does not bind sugars, but instead binds mCEACAM1a through exclusive protein-protein interactions. Critical contacts at the interface have been confirmed by mutagenesis, providing a structural basis for viral and host specificities of coronavirus/CEACAM1 interactions. Sugar-binding assays reveal that galectin-like NTDs of some coronaviruses such as human coronavirus OC43 and bovine coronavirus bind sugars. Structural analysis and mutagenesis localize the sugar-binding site in coronavirus NTDs to be above the {beta}-sandwich core. We propose that coronavirus NTDs originated from a host galectin and retained sugar-binding functions in some contemporary coronaviruses, but evolved new structural features in MHV for mCEACAM1a binding.

Ligand binding and crystal structures of the substrate-binding domain of the ABC transporter OpuA.

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Justina C Wolters

2010-04-01

Full Text Available The ABC transporter OpuA from Lactococcus lactis transports glycine betaine upon activation by threshold values of ionic strength. In this study, the ligand binding characteristics of purified OpuA in a detergent-solubilized state and of its substrate-binding domain produced as soluble protein (OpuAC was characterized.The binding of glycine betaine to purified OpuA and OpuAC (K(D = 4-6 microM did not show any salt dependence or cooperative effects, in contrast to the transport activity. OpuAC is highly specific for glycine betaine and the related proline betaine. Other compatible solutes like proline and carnitine bound with affinities that were 3 to 4 orders of magnitude lower. The low affinity substrates were not noticeably transported by membrane-reconstituted OpuA. OpuAC was crystallized in an open (1.9 A and closed-liganded (2.3 A conformation. The binding pocket is formed by three tryptophans (Trp-prism coordinating the quaternary ammonium group of glycine betaine in the closed-liganded structure. Even though the binding site of OpuAC is identical to that of its B. subtilis homolog, the affinity for glycine betaine is 4-fold higher.Ionic strength did not affect substrate binding to OpuA, indicating that regulation of transport is not at the level of substrate binding, but rather at the level of translocation. The overlap between the crystal structures of OpuAC from L.lactis and B.subtilis, comprising the classical Trp-prism, show that the differences observed in the binding affinities originate from outside of the ligand binding site.

Crystallographic structure and substrate-binding interactions of the molybdate-binding protein of the phytopathogen Xanthomonas axonopodis pv. citri.

Science.gov (United States)

Balan, Andrea; Santacruz-Pérez, Carolina; Moutran, Alexandre; Ferreira, Luís Carlos Souza; Neshich, Goran; Gonçalves Barbosa, João Alexandre Ribeiro

2008-02-01

In Xanthomonas axonopodis pv. citri (Xac or X. citri), the modA gene codes for a periplasmic protein (ModA) that is capable of binding molybdate and tungstate as part of the ABC-type transporter required for the uptake of micronutrients. In this study, we report the crystallographic structure of the Xac ModA protein with bound molybdate. The Xac ModA structure is similar to orthologs with known three-dimensional structures and consists of two nearly symmetrical domains separated by a hinge region where the oxyanion-binding site lies. Phylogenetic analysis of different ModA orthologs based on sequence alignments revealed three groups of molybdate-binding proteins: bacterial phytopathogens, enterobacteria and soil bacteria. Even though the ModA orthologs are segregated into different groups, the ligand-binding hydrogen bonds are mostly conserved, except for Archaeglobus fulgidus ModA. A detailed discussion of hydrophobic interactions in the active site is presented and two new residues, Ala38 and Ser151, are shown to be part of the ligand-binding pocket.

Two distinct calmodulin binding sites in the third intracellular loop and carboxyl tail of angiotensin II (AT(1A receptor.

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Renwen Zhang

Full Text Available In this study, we present data that support the presence of two distinct calmodulin binding sites within the angiotensin II receptor (AT(1A, at juxtamembrane regions of the N-terminus of the third intracellular loop (i3, amino acids 214-231 and carboxyl tail of the receptor (ct, 302-317. We used bioluminescence resonance energy transfer assays to document interactions of calmodulin with the AT(1A holo-receptor and GST-fusion protein pull-downs to demonstrate that i3 and ct interact with calmodulin in a Ca²⁺-dependent fashion. The former is a 1-12 motif and the latter belongs to 1-5-10 calmodulin binding motif. The apparent Kd of calmodulin for i3 is 177.0±9.1 nM, and for ct is 79.4±7.9 nM as assessed by dansyl-calmodulin fluorescence. Replacement of the tryptophan (W219 for alanine in i3, and phenylalanine (F309 or F313 for alanine in ct reduced their binding affinities for calmodulin, as predicted by computer docking simulations. Exogenously applied calmodulin attenuated interactions between G protein βγ subunits and i3 and ct, somewhat more so for ct than i3. Mutations W219A, F309A, and F313A did not alter Gβγ binding, but reduced the ability of calmodulin to compete with Gβγ, suggesting that calmodulin and Gβγ have overlapping, but not identical, binding requirements for i3 and ct. Calmodulin interference with the Gβγ binding to i3 and ct regions of the AT(1A receptor strongly suggests that calmodulin plays critical roles in regulating Gβγ-dependent signaling of the receptor.

Two Distinct Calmodulin Binding Sites in the Third Intracellular Loop and Carboxyl Tail of Angiotensin II (AT1A) Receptor

Science.gov (United States)

Zhang, Renwen; Liu, Zhijie; Qu, Youxing; Xu, Ying; Yang, Qing

2013-01-01

In this study, we present data that support the presence of two distinct calmodulin binding sites within the angiotensin II receptor (AT1A), at juxtamembrane regions of the N-terminus of the third intracellular loop (i3, amino acids 214–231) and carboxyl tail of the receptor (ct, 302–317). We used bioluminescence resonance energy transfer assays to document interactions of calmodulin with the AT1A holo-receptor and GST-fusion protein pull-downs to demonstrate that i3 and ct interact with calmodulin in a Ca2+-dependent fashion. The former is a 1–12 motif and the latter belongs to 1-5-10 calmodulin binding motif. The apparent Kd of calmodulin for i3 is 177.0±9.1 nM, and for ct is 79.4±7.9 nM as assessed by dansyl-calmodulin fluorescence. Replacement of the tryptophan (W219) for alanine in i3, and phenylalanine (F309 or F313) for alanine in ct reduced their binding affinities for calmodulin, as predicted by computer docking simulations. Exogenously applied calmodulin attenuated interactions between G protein βγ subunits and i3 and ct, somewhat more so for ct than i3. Mutations W219A, F309A, and F313A did not alter Gβγ binding, but reduced the ability of calmodulin to compete with Gβγ, suggesting that calmodulin and Gβγ have overlapping, but not identical, binding requirements for i3 and ct. Calmodulin interference with the Gβγ binding to i3 and ct regions of the AT1A receptor strongly suggests that calmodulin plays critical roles in regulating Gβγ-dependent signaling of the receptor. PMID:23755207

Recent improvements to Binding MOAD: a resource for protein-ligand binding affinities and structures.

Science.gov (United States)

Ahmed, Aqeel; Smith, Richard D; Clark, Jordan J; Dunbar, James B; Carlson, Heather A

2015-01-01

For over 10 years, Binding MOAD (Mother of All Databases; http://www.BindingMOAD.org) has been one of the largest resources for high-quality protein-ligand complexes and associated binding affinity data. Binding MOAD has grown at the rate of 1994 complexes per year, on average. Currently, it contains 23,269 complexes and 8156 binding affinities. Our annual updates curate the data using a semi-automated literature search of the references cited within the PDB file, and we have recently upgraded our website and added new features and functionalities to better serve Binding MOAD users. In order to eliminate the legacy application server of the old platform and to accommodate new changes, the website has been completely rewritten in the LAMP (Linux, Apache, MySQL and PHP) environment. The improved user interface incorporates current third-party plugins for better visualization of protein and ligand molecules, and it provides features like sorting, filtering and filtered downloads. In addition to the field-based searching, Binding MOAD now can be searched by structural queries based on the ligand. In order to remove redundancy, Binding MOAD records are clustered in different families based on 90% sequence identity. The new Binding MOAD, with the upgraded platform, features and functionalities, is now equipped to better serve its users. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naïve Bayes.

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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

Effects of mutants in bHLH region on structure stability and protein-DNA binding energy in DECs.

Science.gov (United States)

Kong, Yi; Wang, Zhen; Jia, Yanfei; Li, Ping; Hao, Shuhua; Wang, Yunshan

2017-07-01

The human DEC subfamily contains two highly conserved members belonging to basic helix-loop-helix (bHLH) transcription factors. This conserved family is spread widely among various species with the function of regulating various crucial molecular signaling pathways. Due to the significance of DECs for important biological processes, their relationship with diseases and the lack of experimentally proven structures, we have implemented a comparative modeling for the bHLH region of DECs as homodimers with themselves and heterodimers with HES-1. Three mutants with predicted roles in reducing intramolecular binding (H57A, R65A, and LL7879AA in DEC1 and LL7071AA in DEC2) were investigated on DEC monomers. Molecular dynamics (MD) simulations were also employed to evaluate the behavior of the mutant molecules in aqueous solution. The monomer was divided into subregions for accurate investigation. The fluctuation in the basic region of mutants was higher than that of wild-type molecules. The binding energy value between protein and DNA obviously increased in the homodimer harboring R65A mutants, which led to more unstable status between protein and DNA. Thus, the mutant R65A interfered DNA-binding affinity. A study on the spatial structures of wild-type and mutant DECs may facilitate functional prediction for mutation effects and dynamic behavior under various conditions and may ultimately help in targeted drug design.

LigandRFs: random forest ensemble to identify ligand-binding residues from sequence information alone

KAUST Repository

Chen, Peng

2014-12-03

Background Protein-ligand binding is important for some proteins to perform their functions. Protein-ligand binding sites are the residues of proteins that physically bind to ligands. Despite of the recent advances in computational prediction for protein-ligand binding sites, the state-of-the-art methods search for similar, known structures of the query and predict the binding sites based on the solved structures. However, such structural information is not commonly available. Results In this paper, we propose a sequence-based approach to identify protein-ligand binding residues. We propose a combination technique to reduce the effects of different sliding residue windows in the process of encoding input feature vectors. Moreover, due to the highly imbalanced samples between the ligand-binding sites and non ligand-binding sites, we construct several balanced data sets, for each of which a random forest (RF)-based classifier is trained. The ensemble of these RF classifiers forms a sequence-based protein-ligand binding site predictor. Conclusions Experimental results on CASP9 and CASP8 data sets demonstrate that our method compares favorably with the state-of-the-art protein-ligand binding site prediction methods.

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…

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...

Solution structure of an archaeal DNA binding protein with an eukaryotic zinc finger fold.

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Florence Guillière

Full Text Available While the basal transcription machinery in archaea is eukaryal-like, transcription factors in archaea and their viruses are usually related to bacterial transcription factors. Nevertheless, some of these organisms show predicted classical zinc fingers motifs of the C2H2 type, which are almost exclusively found in proteins of eukaryotes and most often associated with transcription regulators. In this work, we focused on the protein AFV1p06 from the hyperthermophilic archaeal virus AFV1. The sequence of the protein consists of the classical eukaryotic C2H2 motif with the fourth histidine coordinating zinc missing, as well as of N- and C-terminal extensions. We showed that the protein AFV1p06 binds zinc and solved its solution structure by NMR. AFV1p06 displays a zinc finger fold with a novel structure extension and disordered N- and C-termini. Structure calculations show that a glutamic acid residue that coordinates zinc replaces the fourth histidine of the C2H2 motif. Electromobility gel shift assays indicate that the protein binds to DNA with different affinities depending on the DNA sequence. AFV1p06 is the first experimentally characterised archaeal zinc finger protein with a DNA binding activity. The AFV1p06 protein family has homologues in diverse viruses of hyperthermophilic archaea. A phylogenetic analysis points out a common origin of archaeal and eukaryotic C2H2 zinc fingers.

Structure solution of DNA-binding proteins and complexes with ARCIMBOLDO libraries

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Pröpper, Kevin [University of Göttingen, (Germany); Instituto de Biologia Molecular de Barcelona (IBMB-CSIC), (Spain); Meindl, Kathrin; Sammito, Massimo [Instituto de Biologia Molecular de Barcelona (IBMB-CSIC), (Spain); Dittrich, Birger; Sheldrick, George M. [University of Göttingen, (Germany); Pohl, Ehmke, E-mail: ehmke.pohl@durham.ac.uk [Durham University, (United Kingdom); Usón, Isabel, E-mail: ehmke.pohl@durham.ac.uk [Instituto de Biologia Molecular de Barcelona (IBMB-CSIC), (Spain); Institucio Catalana de Recerca i Estudis Avancats (ICREA), (Spain); University of Göttingen, (Germany)

2014-06-01

The structure solution of DNA-binding protein structures and complexes based on the combination of location of DNA-binding protein motif fragments with density modification in a multi-solution frame is described. Protein–DNA interactions play a major role in all aspects of genetic activity within an organism, such as transcription, packaging, rearrangement, replication and repair. The molecular detail of protein–DNA interactions can be best visualized through crystallography, and structures emphasizing insight into the principles of binding and base-sequence recognition are essential to understanding the subtleties of the underlying mechanisms. An increasing number of high-quality DNA-binding protein structure determinations have been witnessed despite the fact that the crystallographic particularities of nucleic acids tend to pose specific challenges to methods primarily developed for proteins. Crystallographic structure solution of protein–DNA complexes therefore remains a challenging area that is in need of optimized experimental and computational methods. The potential of the structure-solution program ARCIMBOLDO for the solution of protein–DNA complexes has therefore been assessed. The method is based on the combination of locating small, very accurate fragments using the program Phaser and density modification with the program SHELXE. Whereas for typical proteins main-chain α-helices provide the ideal, almost ubiquitous, small fragments to start searches, in the case of DNA complexes the binding motifs and DNA double helix constitute suitable search fragments. The aim of this work is to provide an effective library of search fragments as well as to determine the optimal ARCIMBOLDO strategy for the solution of this class of structures.

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....

Molecular simulations and Markov state modeling reveal the structural diversity and dynamics of a theophylline-binding RNA aptamer in its unbound state.

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Becka M Warfield

Full Text Available RNA aptamers are oligonucleotides that bind with high specificity and affinity to target ligands. In the absence of bound ligand, secondary structures of RNA aptamers are generally stable, but single-stranded and loop regions, including ligand binding sites, lack defined structures and exist as ensembles of conformations. For example, the well-characterized theophylline-binding aptamer forms a highly stable binding site when bound to theophylline, but the binding site is unstable and disordered when theophylline is absent. Experimental methods have not revealed at atomic resolution the conformations that the theophylline aptamer explores in its unbound state. Consequently, in the present study we applied 21 microseconds of molecular dynamics simulations to structurally characterize the ensemble of conformations that the aptamer adopts in the absence of theophylline. Moreover, we apply Markov state modeling to predict the kinetics of transitions between unbound conformational states. Our simulation results agree with experimental observations that the theophylline binding site is found in many distinct binding-incompetent states and show that these states lack a binding pocket that can accommodate theophylline. The binding-incompetent states interconvert with binding-competent states through structural rearrangement of the binding site on the nanosecond to microsecond timescale. Moreover, we have simulated the complete theophylline binding pathway. Our binding simulations supplement prior experimental observations of slow theophylline binding kinetics by showing that the binding site must undergo a large conformational rearrangement after the aptamer and theophylline form an initial complex, most notably, a major rearrangement of the C27 base from a buried to solvent-exposed orientation. Theophylline appears to bind by a combination of conformational selection and induced fit mechanisms. Finally, our modeling indicates that when Mg2+ ions are

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.

Integrating protein structures and precomputed genealogies in the Magnum database: Examples with cellular retinoid binding proteins

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Bradley Michael E

2006-02-01

Full Text Available Abstract Background When accurate models for the divergent evolution of protein sequences are integrated with complementary biological information, such as folded protein structures, analyses of the combined data often lead to new hypotheses about molecular physiology. This represents an excellent example of how bioinformatics can be used to guide experimental research. However, progress in this direction has been slowed by the lack of a publicly available resource suitable for general use. Results The precomputed Magnum database offers a solution to this problem for ca. 1,800 full-length protein families with at least one crystal structure. The Magnum deliverables include 1 multiple sequence alignments, 2 mapping of alignment sites to crystal structure sites, 3 phylogenetic trees, 4 inferred ancestral sequences at internal tree nodes, and 5 amino acid replacements along tree branches. Comprehensive evaluations revealed that the automated procedures used to construct Magnum produced accurate models of how proteins divergently evolve, or genealogies, and correctly integrated these with the structural data. To demonstrate Magnum's capabilities, we asked for amino acid replacements requiring three nucleotide substitutions, located at internal protein structure sites, and occurring on short phylogenetic tree branches. In the cellular retinoid binding protein family a site that potentially modulates ligand binding affinity was discovered. Recruitment of cellular retinol binding protein to function as a lens crystallin in the diurnal gecko afforded another opportunity to showcase the predictive value of a browsable database containing branch replacement patterns integrated with protein structures. Conclusion We integrated two areas of protein science, evolution and structure, on a large scale and created a precomputed database, known as Magnum, which is the first freely available resource of its kind. Magnum provides evolutionary and structural

A Structural Model for Binding of the Serine-Rich Repeat Adhesin GspB to Host Carbohydrate Receptors

Energy Technology Data Exchange (ETDEWEB)

Pyburn, Tasia M.; Bensing, Barbara A.; Xiong, Yan Q.; Melancon, Bruce J.; Tomasiak, Thomas M.; Ward, Nicholas J.; Yankovskaya, Victoria; Oliver, Kevin M.; Cecchini, Gary; Sulikowski, Gary A.; Tyska, Matthew J.; Sullam, Paul M.; Iverson, T.M. (VA); (UCLA); (Vanderbilt); (UCSF)

2014-10-02

GspB is a serine-rich repeat (SRR) adhesin of Streptococcus gordonii that mediates binding of this organism to human platelets via its interaction with sialyl-T antigen on the receptor GPIb{alpha}. This interaction appears to be a major virulence determinant in the pathogenesis of infective endocarditis. To address the mechanism by which GspB recognizes its carbohydrate ligand, we determined the high-resolution x-ray crystal structure of the GspB binding region (GspB{sub BR}), both alone and in complex with a disaccharide precursor to sialyl-T antigen. Analysis of the GspB{sub BR} structure revealed that it is comprised of three independently folded subdomains or modules: (1) an Ig-fold resembling a CnaA domain from prokaryotic pathogens; (2) a second Ig-fold resembling the binding region of mammalian Siglecs; (3) a subdomain of unique fold. The disaccharide was found to bind in a pocket within the Siglec subdomain, but at a site distinct from that observed in mammalian Siglecs. Confirming the biological relevance of this binding pocket, we produced three isogenic variants of S. gordonii, each containing a single point mutation of a residue lining this binding pocket. These variants have reduced binding to carbohydrates of GPIb{alpha}. Further examination of purified GspB{sub BR}-R484E showed reduced binding to sialyl-T antigen while S. gordonii harboring this mutation did not efficiently bind platelets and showed a significant reduction in virulence, as measured by an animal model of endocarditis. Analysis of other SRR proteins revealed that the predicted binding regions of these adhesins also had a modular organization, with those known to bind carbohydrate receptors having modules homologous to the Siglec and Unique subdomains of GspBBR. This suggests that the binding specificity of the SRR family of adhesins is determined by the type and organization of discrete modules within the binding domains, which may affect the tropism of organisms for different tissues.

Linguistic Structure Prediction

CERN Document Server

Smith, Noah A

2011-01-01

A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W

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

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate

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.

Expression, purification, crystallization and structure of human adipocyte lipid-binding protein (aP2)

International Nuclear Information System (INIS)

Marr, Eric; Tardie, Mark; Carty, Maynard; Brown Phillips, Tracy; Wang, Ing-Kae; Soeller, Walt; Qiu, Xiayang; Karam, George

2006-01-01

The crystal structure of human adipocyte lipid-binding protein (aP2) with a bound palmitate is reported at 1.5 Å resolution. Human adipocyte lipid-binding protein (aP2) belongs to a family of intracellular lipid-binding proteins involved in the transport and storage of lipids. Here, the crystal structure of human aP2 with a bound palmitate is described at 1.5 Å resolution. Unlike the known crystal structure of murine aP2 in complex with palmitate, this structure shows that the fatty acid is in a folded conformation and that the loop containing Phe57 acts as a lid to regulate ligand binding by excluding solvent exposure to the central binding cavity

Dynamic fluctuations provide the basis of a conformational switch mechanism in apo cyclic AMP receptor protein.

Directory of Open Access Journals (Sweden)

Burcu Aykaç Fas

Full Text Available Escherichia coli cyclic AMP Receptor Protein (CRP undergoes conformational changes with cAMP binding and allosterically promotes CRP to bind specifically to the DNA. In that, the structural and dynamic properties of apo CRP prior to cAMP binding are of interest for the comprehension of the activation mechanism. Here, the dynamics of apo CRP monomer/dimer and holo CRP dimer were studied by Molecular Dynamics (MD simulations and Gaussian Network Model (GNM. The interplay of the inter-domain hinge with the cAMP and DNA binding domains are pre-disposed in the apo state as a conformational switch in the CRP's allosteric communication mechanism. The hinge at L134-D138 displaying intra- and inter-subunit coupled fluctuations with the cAMP and DNA binding domains leads to the emergence of stronger coupled fluctuations between the two domains and describes an on state. The flexible regions at K52-E58, P154/D155 and I175 maintain the dynamic coupling of the two domains. With a shift in the inter-domain hinge position towards the N terminus, nevertheless, the latter correlations between the domains loosen and become disordered; L134-D138 dynamically interacts only with the cAMP and DNA binding domains of its own subunit, and an off state is assumed. We present a mechanistic view on how the structural dynamic units are hierarchically built for the allosteric functional mechanism; from apo CRP monomer to apo-to-holo CRP dimers.

Probing the structural basis of oxygen binding in a cofactor-independent dioxygenase.

Science.gov (United States)

Li, Kunhua; Fielding, Elisha N; Condurso, Heather L; Bruner, Steven D

2017-07-01

The enzyme DpgC is included in the small family of cofactor-independent dioxygenases. The chemistry of DpgC is uncommon as the protein binds and utilizes dioxygen without the aid of a metal or organic cofactor. Previous structural and biochemical studies identified the substrate-binding mode and the components of the active site that are important in the catalytic mechanism. In addition, the results delineated a putative binding pocket and migration pathway for the co-substrate dioxygen. Here, structural biology is utilized, along with site-directed mutagenesis, to probe the assigned dioxygen-binding pocket. The key residues implicated in dioxygen trafficking were studied to probe the process of binding, activation and chemistry. The results support the proposed chemistry and provide insight into the general mechanism of dioxygen binding and activation.

Nucleotide sequence of Phaseolus vulgaris L. alcohol dehydrogenase encoding cDNA and three-dimensional structure prediction of the deduced protein.

Science.gov (United States)

Amelia, Kassim; Khor, Chin Yin; Shah, Farida Habib; Bhore, Subhash J

2015-01-01

Common beans (Phaseolus vulgaris L.) are widely consumed as a source of proteins and natural products. However, its yield needs to be increased. In line with the agenda of Phaseomics (an international consortium), work of expressed sequence tags (ESTs) generation from bean pods was initiated. Altogether, 5972 ESTs have been isolated. Alcohol dehydrogenase (AD) encoding gene cDNA was a noticeable transcript among the generated ESTs. This AD is an important enzyme; therefore, to understand more about it this study was undertaken. The objective of this study was to elucidate P. vulgaris L. AD (PvAD) gene cDNA sequence and to predict the three-dimensional (3D) structure of deduced protein. positive and negative strands of the PvAD cDNA clone were sequenced using M13 forward and M13 reverse primers to elucidate the nucleotide sequence. Deduced PvAD cDNA and protein sequence was analyzed for their basic features using online bioinformatics tools. Sequence comparison was carried out using bl2seq program, and tree-view program was used to construct a phylogenetic tree. The secondary structures and 3D structure of PvAD protein were predicted by using the PHYRE automatic fold recognition server. The sequencing results analysis showed that PvAD cDNA is 1294 bp in length. It's open reading frame encodes for a protein that contains 371 amino acids. Deduced protein sequence analysis showed the presence of putative substrate binding, catalytic Zn binding, and NAD binding sites. Results indicate that the predicted 3D structure of PvAD protein is analogous to the experimentally determined crystal structure of s-nitrosoglutathione reductase from an Arabidopsis species. The 1294 bp long PvAD cDNA encodes for 371 amino acid long protein that contains conserved domains required for biological functions of AD. The predicted deduced PvAD protein's 3D structure reflects the analogy with the crystal structure of Arabidopsis thaliana s-nitrosoglutathione reductase. Further study is required

Phosphorus Binding Sites in Proteins: Structural Preorganization and Coordination

DEFF Research Database (Denmark)

Gruber, Mathias Felix; Greisen, Per Junior; Junker, Märta Caroline

2014-01-01

to individual structures that bind to phosphate groups; here, we investigate a total of 8307 structures obtained from the RCSB Protein Data Bank (PDB). An analysis of the binding site amino acid propensities reveals very characteristic first shell residue distributions, which are found to be influenced...... by the characteristics of the phosphorus compound and by the presence of cobound cations. The second shell, which supports the coordinating residues in the first shell, is found to consist mainly of protein backbone groups. Our results show how the second shell residue distribution is dictated mainly by the first shell...

An Augmented Pocketome: Detection and Analysis of Small-Molecule Binding Pockets in Proteins of Known 3D Structure.

Science.gov (United States)

Bhagavat, Raghu; Sankar, Santhosh; Srinivasan, Narayanaswamy; Chandra, Nagasuma

2018-03-06

Protein-ligand interactions form the basis of most cellular events. Identifying ligand binding pockets in proteins will greatly facilitate rationalizing and predicting protein function. Ligand binding sites are unknown for many proteins of known three-dimensional (3D) structure, creating a gap in our understanding of protein structure-function relationships. To bridge this gap, we detect pockets in proteins of known 3D structures, using computational techniques. This augmented pocketome (PocketDB) consists of 249,096 pockets, which is about seven times larger than what is currently known. We deduce possible ligand associations for about 46% of the newly identified pockets. The augmented pocketome, when subjected to clustering based on similarities among pockets, yielded 2,161 site types, which are associated with 1,037 ligand types, together providing fold-site-type-ligand-type associations. The PocketDB resource facilitates a structure-based function annotation, delineation of the structural basis of ligand recognition, and provides functional clues for domains of unknown functions, allosteric proteins, and druggable pockets. Copyright © 2018 Elsevier Ltd. All rights reserved.

Structural determination of functional units of the nucleotide binding domain (NBD94 of the reticulocyte binding protein Py235 of Plasmodium yoelii.

Directory of Open Access Journals (Sweden)

Ardina Grüber

2010-02-01

Full Text Available Invasion of the red blood cells (RBC by the merozoite of malaria parasites involves a large number of receptor ligand interactions. The reticulocyte binding protein homologue family (RH plays an important role in erythrocyte recognition as well as virulence. Recently, it has been shown that members of RH in addition to receptor binding may also have a role as ATP/ADP sensor. A 94 kDa region named Nucleotide-Binding Domain 94 (NBD94 of Plasmodium yoelii YM, representative of the putative nucleotide binding region of RH, has been demonstrated to bind ATP and ADP selectively. Binding of ATP or ADP induced nucleotide-dependent structural changes in the C-terminal hinge-region of NBD94, and directly impacted on the RBC binding ability of RH.In order to find the smallest structural unit, able to bind nucleotides, and its coupling module, the hinge region, three truncated domains of NBD94 have been generated, termed NBD94(444-547, NBD94(566-663 and NBD94(674-793, respectively. Using fluorescence correlation spectroscopy NBD94(444-547 has been identified to form the smallest nucleotide binding segment, sensitive for ATP and ADP, which became inhibited by 4-Chloro-7-nitrobenzofurazan. The shape of NBD94(444-547 in solution was calculated from small-angle X-ray scattering data, revealing an elongated molecule, comprised of two globular domains, connected by a spiral segment of about 73.1 A in length. The high quality of the constructs, forming the hinge-region, NBD94(566-663 and NBD94(674-793 enabled to determine the first crystallographic and solution structure, respectively. The crystal structure of NBD94(566-663 consists of two helices with 97.8 A and 48.6 A in length, linked by a loop. By comparison, the low resolution structure of NBD94(674-793 in solution represents a chair-like shape with three architectural segments.These structures give the first insight into how nucleotide binding impacts on the overall structure of RH and demonstrates the

Structural Changes of Creatine Kinase upon Substrate Binding

OpenAIRE

Forstner, Michael; Kriechbaum, Manfred; Laggner, Peter; Wallimann, Theo

1998-01-01

Small-angle x-ray scattering was used to investigate structural changes upon binding of individual substrates or a transition state analog complex (TSAC; Mg-ADP, creatine, and KNO3) to creatine kinase (CK) isoenzymes (dimeric muscle-type (M)-CK and octameric mitochondrial (Mi)-CK) and monomeric arginine kinase (AK). Considerable changes in the shape and the size of the molecules occurred upon binding of Mg-nucleotide or TSAC. The radius of gyration of Mi-CK was reduced from 55.6 A (free enzym...

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.

Structural Basis for Sialoglycan Binding by the Streptococcus sanguinis SrpA Adhesin.

Science.gov (United States)

Bensing, Barbara A; Loukachevitch, Lioudmila V; McCulloch, Kathryn M; Yu, Hai; Vann, Kendra R; Wawrzak, Zdzislaw; Anderson, Spencer; Chen, Xi; Sullam, Paul M; Iverson, T M

2016-04-01

Streptococcus sanguinisis a leading cause of infective endocarditis, a life-threatening infection of the cardiovascular system. An important interaction in the pathogenesis of infective endocarditis is attachment of the organisms to host platelets.S. sanguinisexpresses a serine-rich repeat adhesin, SrpA, similar in sequence to platelet-binding adhesins associated with increased virulence in this disease. In this study, we determined the first crystal structure of the putative binding region of SrpA (SrpABR) both unliganded and in complex with a synthetic disaccharide ligand at 1.8 and 2.0 Å resolution, respectively. We identified a conserved Thr-Arg motif that orients the sialic acid moiety and is required for binding to platelet monolayers. Furthermore, we propose that sequence insertions in closely related family members contribute to the modulation of structural and functional properties, including the quaternary structure, the tertiary structure, and the ligand-binding site. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Insight into mitochondrial structure and function from electron tomography.

Science.gov (United States)

Frey, T G; Renken, C W; Perkins, G A

2002-09-10

In recent years, electron tomography has provided detailed three-dimensional models of mitochondria that have redefined our concept of mitochondrial structure. The models reveal an inner membrane consisting of two components, the inner boundary membrane (IBM) closely apposed to the outer membrane and the cristae membrane that projects into the matrix compartment. These two components are connected by tubular structures of relatively uniform size called crista junctions. The distribution of crista junction sizes and shapes is predicted by a thermodynamic model based upon the energy of membrane bending, but proteins likely also play a role in determining the conformation of the inner membrane. Results of structural studies of mitochondria during apoptosis demonstrate that cytochrome c is released without detectable disruption of the outer membrane or extensive swelling of the mitochondrial matrix, suggesting the formation of an outer membrane pore large enough to allow passage of holo-cytochrome c. The possible compartmentation of inner membrane function between the IBM and the cristae membrane is also discussed.

Six independent fucose-binding sites in the crystal structure of Aspergillus oryzae lectin

Energy Technology Data Exchange (ETDEWEB)

Makyio, Hisayoshi [Structural Biology Research Center, Photon Factory, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK), 1-1 Oho, Tsukuba, Ibaraki, 305-0801 (Japan); Shimabukuro, Junpei; Suzuki, Tatsuya [Department of Applied Bioorganic Chemistry, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193 (Japan); Institute for Integrated Cell-Material Sciences (WPI-iCeMS), Kyoto University, Yoshida Ushinomiya-cho, Sakyo-ku, Kyoto 606-8501 (Japan); Imamura, Akihiro; Ishida, Hideharu [Department of Applied Bioorganic Chemistry, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193 (Japan); Kiso, Makoto [Department of Applied Bioorganic Chemistry, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193 (Japan); Institute for Integrated Cell-Material Sciences (WPI-iCeMS), Kyoto University, Yoshida Ushinomiya-cho, Sakyo-ku, Kyoto 606-8501 (Japan); Ando, Hiromune, E-mail: hando@gifu-u.ac.jp [Department of Applied Bioorganic Chemistry, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193 (Japan); Institute for Integrated Cell-Material Sciences (WPI-iCeMS), Kyoto University, Yoshida Ushinomiya-cho, Sakyo-ku, Kyoto 606-8501 (Japan); Kato, Ryuichi, E-mail: ryuichi.kato@kek.jp [Structural Biology Research Center, Photon Factory, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK), 1-1 Oho, Tsukuba, Ibaraki, 305-0801 (Japan)

2016-08-26

The crystal structure of AOL (a fucose-specific lectin of Aspergillus oryzae) has been solved by SAD (single-wavelength anomalous diffraction) and MAD (multi-wavelength anomalous diffraction) phasing of seleno-fucosides. The overall structure is a six-bladed β-propeller similar to that of other fucose-specific lectins. The fucose moieties of the seleno-fucosides are located in six fucose-binding sites. Although the Arg and Glu/Gln residues bound to the fucose moiety are common to all fucose-binding sites, the amino-acid residues involved in fucose binding at each site are not identical. The varying peak heights of the seleniums in the electron density map suggest that each fucose-binding site has a different carbohydrate binding affinity. - Highlights: • The six-bladed β-propeller structure of AOL was solved by seleno-sugar phasing. • The mode of fucose binding is essentially conserved at all six binding sites. • The seleno-fucosides exhibit slightly different interactions and electron densities. • These findings suggest that the affinity for fucose is not identical at each site.

Six independent fucose-binding sites in the crystal structure of Aspergillus oryzae lectin

International Nuclear Information System (INIS)

Makyio, Hisayoshi; Shimabukuro, Junpei; Suzuki, Tatsuya; Imamura, Akihiro; Ishida, Hideharu; Kiso, Makoto; Ando, Hiromune; Kato, Ryuichi

2016-01-01

The crystal structure of AOL (a fucose-specific lectin of Aspergillus oryzae) has been solved by SAD (single-wavelength anomalous diffraction) and MAD (multi-wavelength anomalous diffraction) phasing of seleno-fucosides. The overall structure is a six-bladed β-propeller similar to that of other fucose-specific lectins. The fucose moieties of the seleno-fucosides are located in six fucose-binding sites. Although the Arg and Glu/Gln residues bound to the fucose moiety are common to all fucose-binding sites, the amino-acid residues involved in fucose binding at each site are not identical. The varying peak heights of the seleniums in the electron density map suggest that each fucose-binding site has a different carbohydrate binding affinity. - Highlights: • The six-bladed β-propeller structure of AOL was solved by seleno-sugar phasing. • The mode of fucose binding is essentially conserved at all six binding sites. • The seleno-fucosides exhibit slightly different interactions and electron densities. • These findings suggest that the affinity for fucose is not identical at each site.

UPF201 Archaeal Specific Family Members Reveals Structural Similarity to RNA-Binding Proteins but Low Likelihood for RNA-Binding Function

Energy Technology Data Exchange (ETDEWEB)

Rao, K.N.; Swaminathan, S.; Burley, S. K.

2008-12-11

We have determined X-ray crystal structures of four members of an archaeal specific family of proteins of unknown function (UPF0201; Pfam classification: DUF54) to advance our understanding of the genetic repertoire of archaea. Despite low pairwise amino acid sequence identities (10-40%) and the absence of conserved sequence motifs, the three-dimensional structures of these proteins are remarkably similar to one another. Their common polypeptide chain fold, encompassing a five-stranded antiparallel {beta}-sheet and five {alpha}-helices, proved to be quite unexpectedly similar to that of the RRM-type RNA-binding domain of the ribosomal L5 protein, which is responsible for binding the 5S- rRNA. Structure-based sequence alignments enabled construction of a phylogenetic tree relating UPF0201 family members to L5 ribosomal proteins and other structurally similar RNA binding proteins, thereby expanding our understanding of the evolutionary purview of the RRM superfamily. Analyses of the surfaces of these newly determined UPF0201 structures suggest that they probably do not function as RNA binding proteins, and that this domain specific family of proteins has acquired a novel function in archaebacteria, which awaits experimental elucidation.

Structural and functional characterization of solute binding proteins for aromatic compounds derived from lignin: p-coumaric acid and related aromatic acids.

Science.gov (United States)

Tan, Kemin; Chang, Changsoo; Cuff, Marianne; Osipiuk, Jerzy; Landorf, Elizabeth; Mack, Jamey C; Zerbs, Sarah; Joachimiak, Andrzej; Collart, Frank R

2013-10-01

Lignin comprises 15-25% of plant biomass and represents a major environmental carbon source for utilization by soil microorganisms. Access to this energy resource requires the action of fungal and bacterial enzymes to break down the lignin polymer into a complex assortment of aromatic compounds that can be transported into the cells. To improve our understanding of the utilization of lignin by microorganisms, we characterized the molecular properties of solute binding proteins of ATP-binding cassette transporter proteins that interact with these compounds. A combination of functional screens and structural studies characterized the binding specificity of the solute binding proteins for aromatic compounds derived from lignin such as p-coumarate, 3-phenylpropionic acid and compounds with more complex ring substitutions. A ligand screen based on thermal stabilization identified several binding protein clusters that exhibit preferences based on the size or number of aromatic ring substituents. Multiple X-ray crystal structures of protein-ligand complexes for these clusters identified the molecular basis of the binding specificity for the lignin-derived aromatic compounds. The screens and structural data provide new functional assignments for these solute-binding proteins which can be used to infer their transport specificity. This knowledge of the functional roles and molecular binding specificity of these proteins will support the identification of the specific enzymes and regulatory proteins of peripheral pathways that funnel these compounds to central metabolic pathways and will improve the predictive power of sequence-based functional annotation methods for this family of proteins. Copyright © 2013 Wiley Periodicals, Inc.

The development of real-time stability supports visual working memory performance: Young children's feature binding can be improved through perceptual structure.

Science.gov (United States)

Simmering, Vanessa R; Wood, Chelsey M

2017-08-01

Working memory is a basic cognitive process that predicts higher-level skills. A central question in theories of working memory development is the generality of the mechanisms proposed to explain improvements in performance. Prior theories have been closely tied to particular tasks and/or age groups, limiting their generalizability. The cognitive dynamics theory of visual working memory development has been proposed to overcome this limitation. From this perspective, developmental improvements arise through the coordination of cognitive processes to meet demands of different behavioral tasks. This notion is described as real-time stability, and can be probed through experiments that assess how changing task demands impact children's performance. The current studies test this account by probing visual working memory for colors and shapes in a change detection task that compares detection of changes to new features versus swaps in color-shape binding. In Experiment 1, 3- to 4-year-old children showed impairments specific to binding swaps, as predicted by decreased real-time stability early in development; 5- to 6-year-old children showed a slight advantage on binding swaps, but 7- to 8-year-old children and adults showed no difference across trial types. Experiment 2 tested the proposed explanation of young children's binding impairment through added perceptual structure, which supported the stability and precision of feature localization in memory-a process key to detecting binding swaps. This additional structure improved young children's binding swap detection, but not new-feature detection or adults' performance. These results provide further evidence for the cognitive dynamics and real-time stability explanation of visual working memory development. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Neural Networks for protein Structure Prediction

DEFF Research Database (Denmark)

Bohr, Henrik

1998-01-01

This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

Structure and ligand-binding properties of the biogenic amine-binding protein from the saliva of a blood-feeding insect vector of Trypanosoma cruzi

Energy Technology Data Exchange (ETDEWEB)

Xu, Xueqing; Chang, Bianca W. [NIH/NIAID, 12735 Twinbrook Parkway, Rockville, MD 20852 (United States); Mans, Ben J. [NIH/NIAID, 12735 Twinbrook Parkway, Rockville, MD 20852 (United States); Agricultural Research Council, Onderstepoort 0110 (South Africa); Ribeiro, Jose M. C.; Andersen, John F., E-mail: jandersen@niaid.nih.gov [NIH/NIAID, 12735 Twinbrook Parkway, Rockville, MD 20852 (United States)

2013-01-01

Biogenic amine-binding proteins mediate the anti-inflammatory and antihemostatic activities of blood-feeding insect saliva. The structure of the amine-binding protein from R. prolixus reveals the interaction of biogenic amine ligands with the protein. Proteins that bind small-molecule mediators of inflammation and hemostasis are essential for blood-feeding by arthropod vectors of infectious disease. In ticks and triatomine insects, the lipocalin protein family is greatly expanded and members have been shown to bind biogenic amines, eicosanoids and ADP. These compounds are potent mediators of platelet activation, inflammation and vascular tone. In this paper, the structure of the amine-binding protein (ABP) from Rhodnius prolixus, a vector of the trypanosome that causes Chagas disease, is described. ABP binds the biogenic amines serotonin and norepinephrine with high affinity. A complex with tryptamine shows the presence of a binding site for a single ligand molecule in the central cavity of the β-barrel structure. The cavity contains significant additional volume, suggesting that this protein may have evolved from the related nitrophorin proteins, which bind a much larger heme ligand in the central cavity.

Structure and ligand-binding properties of the biogenic amine-binding protein from the saliva of a blood-feeding insect vector of Trypanosoma cruzi

International Nuclear Information System (INIS)

Xu, Xueqing; Chang, Bianca W.; Mans, Ben J.; Ribeiro, Jose M. C.; Andersen, John F.

2013-01-01

Biogenic amine-binding proteins mediate the anti-inflammatory and antihemostatic activities of blood-feeding insect saliva. The structure of the amine-binding protein from R. prolixus reveals the interaction of biogenic amine ligands with the protein. Proteins that bind small-molecule mediators of inflammation and hemostasis are essential for blood-feeding by arthropod vectors of infectious disease. In ticks and triatomine insects, the lipocalin protein family is greatly expanded and members have been shown to bind biogenic amines, eicosanoids and ADP. These compounds are potent mediators of platelet activation, inflammation and vascular tone. In this paper, the structure of the amine-binding protein (ABP) from Rhodnius prolixus, a vector of the trypanosome that causes Chagas disease, is described. ABP binds the biogenic amines serotonin and norepinephrine with high affinity. A complex with tryptamine shows the presence of a binding site for a single ligand molecule in the central cavity of the β-barrel structure. The cavity contains significant additional volume, suggesting that this protein may have evolved from the related nitrophorin proteins, which bind a much larger heme ligand in the central cavity

SCOWLP classification: Structural comparison and analysis of protein binding regions

Directory of Open Access Journals (Sweden)

Anders Gerd

2008-01-01

Full Text Available Abstract Background Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. Description Protein binding regions (PBRs might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed. We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions

Structural characterization of the binding interactions of various endogenous estrogen metabolites with human estrogen receptor α and β subtypes: a molecular modeling study.

Directory of Open Access Journals (Sweden)

Pan Wang

Full Text Available In the present study, we used the molecular docking approach to study the binding interactions of various derivatives of 17β-estradiol (E2 with human estrogen receptor (ER α and β. First, we determined the suitability of the molecular docking method to correctly predict the binding modes and interactions of two representative agonists (E2 and diethylstilbesterol in the ligand binding domain (LBD of human ERα. We showed that the docked structures of E2 and diethylstilbesterol in the ERα LBD were almost exactly the same as the known crystal structures of ERα in complex with these two estrogens. Using the same docking approach, we then characterized the binding interactions of 27 structurally similar E2 derivatives with the LBDs of human ERα and ERβ. While the binding modes of these E2 derivatives are very similar to that of E2, there are distinct subtle differences, and these small differences contribute importantly to their differential binding affinities for ERs. In the case of A-ring estrogen derivatives, there is a strong inverse relationship between the length of the hydrogen bonds formed with ERs and their binding affinity. We found that a better correlation between the computed binding energy values and the experimentally determined logRBA values could be achieved for various A-ring derivatives by re-adjusting the relative weights of the van der Waals interaction energy and the Coulomb interaction energy in computing the overall binding energy values.

Interleukin-11 binds specific EF-hand proteins via their conserved structural motifs.

Science.gov (United States)

Kazakov, Alexei S; Sokolov, Andrei S; Vologzhannikova, Alisa A; Permyakova, Maria E; Khorn, Polina A; Ismailov, Ramis G; Denessiouk, Konstantin A; Denesyuk, Alexander I; Rastrygina, Victoria A; Baksheeva, Viktoriia E; Zernii, Evgeni Yu; Zinchenko, Dmitry V; Glazatov, Vladimir V; Uversky, Vladimir N; Mirzabekov, Tajib A; Permyakov, Eugene A; Permyakov, Sergei E

2017-01-01

Interleukin-11 (IL-11) is a hematopoietic cytokine engaged in numerous biological processes and validated as a target for treatment of various cancers. IL-11 contains intrinsically disordered regions that might recognize multiple targets. Recently we found that aside from IL-11RA and gp130 receptors, IL-11 interacts with calcium sensor protein S100P. Strict calcium dependence of this interaction suggests a possibility of IL-11 interaction with other calcium sensor proteins. Here we probed specificity of IL-11 to calcium-binding proteins of various types: calcium sensors of the EF-hand family (calmodulin, S100B and neuronal calcium sensors: recoverin, NCS-1, GCAP-1, GCAP-2), calcium buffers of the EF-hand family (S100G, oncomodulin), and a non-EF-hand calcium buffer (α-lactalbumin). A specific subset of the calcium sensor proteins (calmodulin, S100B, NCS-1, GCAP-1/2) exhibits metal-dependent binding of IL-11 with dissociation constants of 1-19 μM. These proteins share several amino acid residues belonging to conservative structural motifs of the EF-hand proteins, 'black' and 'gray' clusters. Replacements of the respective S100P residues by alanine drastically decrease its affinity to IL-11, suggesting their involvement into the association process. Secondary structure and accessibility of the hinge region of the EF-hand proteins studied are predicted to control specificity and selectivity of their binding to IL-11. The IL-11 interaction with the EF-hand proteins is expected to occur under numerous pathological conditions, accompanied by disintegration of plasma membrane and efflux of cellular components into the extracellular milieu.

Discovery of novel membrane binding structures and functions

Science.gov (United States)

Kufareva, Irina; Lenoir, Marc; Dancea, Felician; Sridhar, Pooja; Raush, Eugene; Bissig, Christin; Gruenberg, Jean; Abagyan, Ruben; Overduin, Michael

2014-01-01

The function of a protein is determined by its intrinsic activity in the context of its subcellular distribution. Membranes localize proteins within cellular compartments and govern their specific activities. Discovering such membrane-protein interactions is important for understanding biological mechanisms, and could uncover novel sites for therapeutic intervention. Here we present a method for detecting membrane interactive proteins and their exposed residues that insert into lipid bilayers. Although the development process involved analysis of how C1b, C2, ENTH, FYVE, Gla, pleckstrin homology (PH) and PX domains bind membranes, the resulting Membrane Optimal Docking Area (MODA) method yields predictions for a given protein of known three dimensional structures without referring to canonical membrane-targeting modules. This approach was tested on the Arf1 GTPase, ATF2 acetyltransferase, von Willebrand factor A3 domain and Neisseria gonorrhoeae MsrB protein, and further refined with membrane interactive and non-interactive FAPP1 and PKD1 pleckstrin homology domains, respectively. Furthermore we demonstrate how this tool can be used to discover unprecedented membrane binding functions as illustrated by the Bro1 domain of Alix, which was revealed to recognize lysobisphosphatidic acid (LBPA). Validation of novel membrane-protein interactions relies on other techniques such as nuclear magnetic resonance spectroscopy (NMR) which was used here to map the sites of micelle interaction. Together this indicates that genome-wide identification of known and novel membrane interactive proteins and sites is now feasible, and provides a new tool for functional annotation of the proteome. PMID:25394204

Artemin Crystal Structure Reveals Insights into Heparan Sulfate Binding

Energy Technology Data Exchange (ETDEWEB)

Silvian,L.; Jin, P.; Carmillo, P.; Boriack-Sjodin, P.; Pelletier, C.; Rushe, M.; Gong, B.; Sah, D.; Pepinsky, B.; Rossomando, A.

2006-01-01

Artemin (ART) promotes the growth of developing peripheral neurons by signaling through a multicomponent receptor complex comprised of a transmembrane tyrosine kinase receptor (cRET) and a specific glycosylphosphatidylinositol-linked co-receptor (GFR{alpha}3). Glial cell line-derived neurotrophic factor (GDNF) signals through a similar ternary complex but requires heparan sulfate proteoglycans (HSPGs) for full activity. HSPG has not been demonstrated as a requirement for ART signaling. We crystallized ART in the presence of sulfate and solved its structure by isomorphous replacement. The structure reveals ordered sulfate anions bound to arginine residues in the pre-helix and amino-terminal regions that were organized in a triad arrangement characteristic of heparan sulfate. Three residues in the pre-helix were singly or triply substituted with glutamic acid, and the resulting proteins were shown to have reduced heparin-binding affinity that is partly reflected in their ability to activate cRET. This study suggests that ART binds HSPGs and identifies residues that may be involved in HSPG binding.

Structural basis for the ligand-binding specificity of fatty acid-binding proteins (pFABP4 and pFABP5) in gentoo penguin.

Science.gov (United States)

Lee, Chang Woo; Kim, Jung Eun; Do, Hackwon; Kim, Ryeo-Ok; Lee, Sung Gu; Park, Hyun Ho; Chang, Jeong Ho; Yim, Joung Han; Park, Hyun; Kim, Il-Chan; Lee, Jun Hyuck

2015-09-11

Fatty acid-binding proteins (FABPs) are involved in transporting hydrophobic fatty acids between various aqueous compartments of the cell by directly binding ligands inside their β-barrel cavities. Here, we report the crystal structures of ligand-unbound pFABP4, linoleate-bound pFABP4, and palmitate-bound pFABP5, obtained from gentoo penguin (Pygoscelis papua), at a resolution of 2.1 Å, 2.2 Å, and 2.3 Å, respectively. The pFABP4 and pFABP5 proteins have a canonical β-barrel structure with two short α-helices that form a cap region and fatty acid ligand binding sites in the hydrophobic cavity within the β-barrel structure. Linoleate-bound pFABP4 and palmitate-bound pFABP5 possess different ligand-binding modes and a unique ligand-binding pocket due to several sequence dissimilarities (A76/L78, T30/M32, underlining indicates pFABP4 residues) between the two proteins. Structural comparison revealed significantly different conformational changes in the β3-β4 loop region (residues 57-62) as well as the flipped Phe60 residue of pFABP5 than that in pFABP4 (the corresponding residue is Phe58). A ligand-binding study using fluorophore displacement assays shows that pFABP4 has a relatively strong affinity for linoleate as compared to pFABP5. In contrast, pFABP5 exhibits higher affinity for palmitate than that for pFABP4. In conclusion, our high-resolution structures and ligand-binding studies provide useful insights into the ligand-binding preferences of pFABPs based on key protein-ligand interactions. Copyright © 2015 Elsevier Inc. All rights reserved.

Inference of expanded Lrp-like feast/famine transcription factor targets in a non-model organism using protein structure-based prediction.

Science.gov (United States)

Ashworth, Justin; Plaisier, Christopher L; Lo, Fang Yin; Reiss, David J; Baliga, Nitin S

2014-01-01

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer.

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.

Molecular phylogeny and predicted 3D structure of plant beta-D-N-acetylhexosaminidase.

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Hossain, Md Anowar; Roslan, Hairul Azman

2014-01-01

beta-D-N-Acetylhexosaminidase, a family 20 glycosyl hydrolase, catalyzes the removal of β-1,4-linked N-acetylhexosamine residues from oligosaccharides and their conjugates. We constructed phylogenetic tree of β-hexosaminidases to analyze the evolutionary history and predicted functions of plant hexosaminidases. Phylogenetic analysis reveals the complex history of evolution of plant β-hexosaminidase that can be described by gene duplication events. The 3D structure of tomato β-hexosaminidase (β-Hex-Sl) was predicted by homology modeling using 1now as a template. Structural conformity studies of the best fit model showed that more than 98% of the residues lie inside the favoured and allowed regions where only 0.9% lie in the unfavourable region. Predicted 3D structure contains 531 amino acids residues with glycosyl hydrolase20b domain-I and glycosyl hydrolase20 superfamily domain-II including the (β/α)8 barrel in the central part. The α and β contents of the modeled structure were found to be 33.3% and 12.2%, respectively. Eleven amino acids were found to be involved in ligand-binding site; Asp(330) and Glu(331) could play important roles in enzyme-catalyzed reactions. The predicted model provides a structural framework that can act as a guide to develop a hypothesis for β-Hex-Sl mutagenesis experiments for exploring the functions of this class of enzymes in plant kingdom.

Stability of the octameric structure affects plasminogen-binding capacity of streptococcal enolase.

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Amanda J Cork

Full Text Available Group A Streptococcus (GAS is a human pathogen that has the potential to cause invasive disease by binding and activating human plasmin(ogen. Streptococcal surface enolase (SEN is an octameric α-enolase that is localized at the GAS cell surface. In addition to its glycolytic role inside the cell, SEN functions as a receptor for plasmin(ogen on the bacterial surface, but the understanding of the molecular basis of plasmin(ogen binding is limited. In this study, we determined the crystal and solution structures of GAS SEN and characterized the increased plasminogen binding by two SEN mutants. The plasminogen binding ability of SENK312A and SENK362A is ~2- and ~3.4-fold greater than for the wild-type protein. A combination of thermal stability assays, native mass spectrometry and X-ray crystallography approaches shows that increased plasminogen binding ability correlates with decreased stability of the octamer. We propose that decreased stability of the octameric structure facilitates the access of plasmin(ogen to its binding sites, leading to more efficient plasmin(ogen binding and activation.

Proteome scale identification, classification and structural analysis of iron-binding proteins in bread wheat.

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Verma, Shailender Kumar; Sharma, Ankita; Sandhu, Padmani; Choudhary, Neha; Sharma, Shailaja; Acharya, Vishal; Akhter, Yusuf

2017-05-01

Bread wheat is one of the major staple foods of worldwide population and iron plays a significant role in growth and development of the plant. In this report, we are presenting the genome wide identification of iron-binding proteins in bread wheat. The wheat genome derived putative proteome was screened for identification of iron-binding sequence motifs. Out of 602 putative iron-binding proteins, 130 were able to produce reliable structural models by homology techniques and further analyzed for the presence of iron-binding structural motifs. The computationally identified proteins appear to bind to ferrous and ferric ions and showed diverse coordination geometries. Glu, His, Asp and Cys amino acid residues were found to be mostly involved in iron binding. We have classified these proteins on the basis of their localization in the different cellular compartments. The identified proteins were further classified into their protein folds, families and functional classes ranging from structure maintenance of cellular components, regulation of gene expression, post translational modification, membrane proteins, enzymes, signaling and storage proteins. This comprehensive report regarding structural iron binding proteome provides useful insights into the diversity of iron binding proteins of wheat plants and further utilized to study their roles in plant growth, development and physiology. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Comparative structural analysis of lipid binding START domains.

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Ann-Gerd Thorsell

Full Text Available Steroidogenic acute regulatory (StAR protein related lipid transfer (START domains are small globular modules that form a cavity where lipids and lipid hormones bind. These domains can transport ligands to facilitate lipid exchange between biological membranes, and they have been postulated to modulate the activity of other domains of the protein in response to ligand binding. More than a dozen human genes encode START domains, and several of them are implicated in a disease.We report crystal structures of the human STARD1, STARD5, STARD13 and STARD14 lipid transfer domains. These represent four of the six functional classes of START domains.Sequence alignments based on these and previously reported crystal structures define the structural determinants of human START domains, both those related to structural framework and those involved in ligand specificity.This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1.

Conversion of pre-RISC to holo-RISC by Ago2 during assembly of RNAi complexes

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Kim, Kevin; Lee, Young Sik; Carthew, Richard W.

2007-01-01

In the Drosophila RNA interference (RNAi) pathway, small interfering RNAs (siRNAs) direct Argonaute2 (Ago2), an endonuclease, within the RNA-induced silencing complex (RISC) to cleave complementary mRNA targets. In vitro studies have shown that, for each siRNA duplex, RISC retains only one strand, the guide, and releases the other, the passenger, to form a holo-RISC complex. Here, we have isolated a new Ago2 mutant allele and provide, for the first time, in vivo evidence that endogenous Ago2 slicer activity is important to mount an RNAi response in Drosophila. We demonstrate in vivo that efficient removal of the passenger strand from RISC requires the cleavage activity of Ago2. We have also identified a new intermediate complex in the RISC assembly pathway, pre-RISC, in which Ago2 is stably bound to double-stranded siRNA. PMID:17123955

Visualizing RNA Secondary Structure Base Pair Binding Probabilities using Nested Concave Hulls

OpenAIRE

Sansen , Joris; Bourqui , Romain; Thebault , Patricia; Allali , Julien; Auber , David

2015-01-01

International audience; The challenge 1 of the BIOVIS 2015 design contest consists in designing an intuitive visual depiction of base pairs binding probabilities for secondary structure of ncRNA. Our representation depicts the potential nucleotide pairs binding using nested concave hulls over the computed MFE ncRNA secondary structure. Thus, it allows to identify regions with a high level of uncertainty in the MFE computation and the structures which seem to match to reality.

Molecular characterization of the receptor binding structure-activity relationships of influenza B virus hemagglutinin.

Science.gov (United States)

Carbone, V; Kim, H; Huang, J X; Baker, M A; Ong, C; Cooper, M A; Li, J; Rockman, S; Velkov, T

2013-01-01

Selectivity of α2,6-linked human-like receptors by B hemagglutinin (HA) is yet to be fully understood. This study integrates binding data with structure-recognition models to examine the impact of regional-specific sequence variations within the receptor-binding pocket on selectivity and structure activity relationships (SAR). The receptor-binding selectivity of influenza B HAs corresponding to either B/Victoria/2/1987 or the B/Yamagata/16/88 lineages was examined using surface plasmon resonance, solid-phase ELISA and gel-capture assays. Our SAR data showed that the presence of asialyl sugar units is the main determinant of receptor preference of α2,6 versus α2,3 receptor binding. Changes to the type of sialyl-glycan linkage present on receptors exhibit only a minor effect upon binding affinity. Homology-based structural models revealed that structural properties within the HA pocket, such as a glyco-conjugate at Asn194 on the 190-helix, sterically interfere with binding to avian receptor analogs by blocking the exit path of the asialyl sugars. Similarly, naturally occurring substitutions in the C-terminal region of the 190-helix and near the N-terminal end of the 140-loop narrows the horizontal borders of the binding pocket, which restricts access of the avian receptor analog LSTa. This study helps bridge the gap between ligand structure and receptor recognition for influenza B HA; and provides a consensus SAR model for the binding of human and avian receptor analogs to influenza B HA.

Key structural features of nonsteroidal ligands for binding and activation of the androgen receptor.

Science.gov (United States)

Yin, Donghua; He, Yali; Perera, Minoli A; Hong, Seoung Soo; Marhefka, Craig; Stourman, Nina; Kirkovsky, Leonid; Miller, Duane D; Dalton, James T

2003-01-01

The purposes of the present studies were to examine the androgen receptor (AR) binding ability and in vitro functional activity of multiple series of nonsteroidal compounds derived from known antiandrogen pharmacophores and to investigate the structure-activity relationships (SARs) of these nonsteroidal compounds. The AR binding properties of sixty-five nonsteroidal compounds were assessed by a radioligand competitive binding assay with the use of cytosolic AR prepared from rat prostates. The AR agonist and antagonist activities of high-affinity ligands were determined by the ability of the ligand to regulate AR-mediated transcriptional activation in cultured CV-1 cells, using a cotransfection assay. Nonsteroidal compounds with diverse structural features demonstrated a wide range of binding affinity for the AR. Ten compounds, mainly from the bicalutamide-related series, showed a binding affinity superior to the structural pharmacophore from which they were derived. Several SARs regarding nonsteroidal AR binding were revealed from the binding data, including stereoisomeric conformation, steric effect, and electronic effect. The functional activity of high-affinity ligands ranged from antagonist to full agonist for the AR. Several structural features were found to be determinative of agonist and antagonist activities. The nonsteroidal AR agonists identified from the present studies provided a pool of candidates for further development of selective androgen receptor modulators (SARMs) for androgen therapy. Also, these studies uncovered or confirmed numerous important SARs governing AR binding and functional properties by nonsteroidal molecules, which would be valuable in the future structural optimization of SARMs.

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

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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.

Probing binding hot spots at protein-RNA recognition sites.

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Barik, Amita; Nithin, Chandran; Karampudi, Naga Bhushana Rao; Mukherjee, Sunandan; Bahadur, Ranjit Prasad

2016-01-29

We use evolutionary conservation derived from structure alignment of polypeptide sequences along with structural and physicochemical attributes of protein-RNA interfaces to probe the binding hot spots at protein-RNA recognition sites. We find that the degree of conservation varies across the RNA binding proteins; some evolve rapidly compared to others. Additionally, irrespective of the structural class of the complexes, residues at the RNA binding sites are evolutionary better conserved than those at the solvent exposed surfaces. For recognitions involving duplex RNA, residues interacting with the major groove are better conserved than those interacting with the minor groove. We identify multi-interface residues participating simultaneously in protein-protein and protein-RNA interfaces in complexes where more than one polypeptide is involved in RNA recognition, and show that they are better conserved compared to any other RNA binding residues. We find that the residues at water preservation site are better conserved than those at hydrated or at dehydrated sites. Finally, we develop a Random Forests model using structural and physicochemical attributes for predicting binding hot spots. The model accurately predicts 80% of the instances of experimental ΔΔG values in a particular class, and provides a stepping-stone towards the engineering of protein-RNA recognition sites with desired affinity. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

SPOT-ligand 2: improving structure-based virtual screening by binding-homology search on an expanded structural template library.

Science.gov (United States)

Litfin, Thomas; Zhou, Yaoqi; Yang, Yuedong

2017-04-15

The high cost of drug discovery motivates the development of accurate virtual screening tools. Binding-homology, which takes advantage of known protein-ligand binding pairs, has emerged as a powerful discrimination technique. In order to exploit all available binding data, modelled structures of ligand-binding sequences may be used to create an expanded structural binding template library. SPOT-Ligand 2 has demonstrated significantly improved screening performance over its previous version by expanding the template library 15 times over the previous one. It also performed better than or similar to other binding-homology approaches on the DUD and DUD-E benchmarks. The server is available online at http://sparks-lab.org . yaoqi.zhou@griffith.edu.au or yuedong.yang@griffith.edu.au. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Secbase: database module to retrieve secondary structure elements with ligand binding motifs.

Science.gov (United States)

Koch, Oliver; Cole, Jason; Block, Peter; Klebe, Gerhard

2009-10-01

Secbase is presented as a novel extension module of Relibase. It integrates the information about secondary structure elements into the retrieval facilities of Relibase. The data are accessible via the extended Relibase user interface, and integrated retrieval queries can be addressed using an extended version of Reliscript. The primary information about alpha-helices and beta-sheets is used as provided by the PDB. Furthermore, a uniform classification of all turn families, based on recent clustering methods, and a new helix assignment that is based on this turn classification has been included. Algorithms to analyze the geometric features of helices and beta-strands were also implemented. To demonstrate the performance of the Secbase implementation, some application examples are given. They provide new insights into the involvement of secondary structure elements in ligand binding. A survey of water molecules detected next to the N-terminus of helices is analyzed to show their involvement in ligand binding. Additionally, the parallel oriented NH groups at the alpha-helix N-termini provide special binding motifs to bind particular ligand functional groups with two adjacent oxygen atoms, e.g., as found in negatively charged carboxylate or phosphate groups, respectively. The present study also shows that the specific structure of the first turn of alpha-helices provides a suitable explanation for stabilizing charged structures. The magnitude of the overall helix macrodipole seems to have no or only a minor influence on binding. Furthermore, an overview of the involvement of secondary structure elements with the recognition of some important endogenous ligands such as cofactors shows some distinct preference for particular binding motifs and amino acids.

Structural study of LEDGF/p75 binding partners

Czech Academy of Sciences Publication Activity Database

Těšina, Petr; Čermáková, Kateřina; Procházková, Kateřina; Hořejší, Magdalena; Christ, F.; De Rijck, J.; Veverka, Václav; Řezáčová, Pavlína

2013-01-01

Roč. 20, č. 1 (2013), s. 12-12 ISSN 1211-5894. [Discussions in Structural Molecular Biology. Annual Meeting of the Czech Society for Structural Biology /11./. 14.03.2013-16.03.2013, Nové Hrady] R&D Projects: GA MŠk(CZ) LK11205 Institutional support: RVO:61388963 ; RVO:68378050 Keywords : LEDGF/p75 * HIV * integrase-binding domain Subject RIV: EB - Genetics ; Molecular Biology

The Puf family of RNA-binding proteins in plants: phylogeny, structural modeling, activity and subcellular localization

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Tam Michael WC

2010-03-01

Full Text Available Abstract Background Puf proteins have important roles in controlling gene expression at the post-transcriptional level by promoting RNA decay and repressing translation. The Pumilio homology domain (PUM-HD is a conserved region within Puf proteins that binds to RNA with sequence specificity. Although Puf proteins have been well characterized in animal and fungal systems, little is known about the structural and functional characteristics of Puf-like proteins in plants. Results The Arabidopsis and rice genomes code for 26 and 19 Puf-like proteins, respectively, each possessing eight or fewer Puf repeats in their PUM-HD. Key amino acids in the PUM-HD of several of these proteins are conserved with those of animal and fungal homologs, whereas other plant Puf proteins demonstrate extensive variability in these amino acids. Three-dimensional modeling revealed that the predicted structure of this domain in plant Puf proteins provides a suitable surface for binding RNA. Electrophoretic gel mobility shift experiments showed that the Arabidopsis AtPum2 PUM-HD binds with high affinity to BoxB of the Drosophila Nanos Response Element I (NRE1 RNA, whereas a point mutation in the core of the NRE1 resulted in a significant reduction in binding affinity. Transient expression of several of the Arabidopsis Puf proteins as fluorescent protein fusions revealed a dynamic, punctate cytoplasmic pattern of localization for most of these proteins. The presence of predicted nuclear export signals and accumulation of AtPuf proteins in the nucleus after treatment of cells with leptomycin B demonstrated that shuttling of these proteins between the cytosol and nucleus is common among these proteins. In addition to the cytoplasmically enriched AtPum proteins, two AtPum proteins showed nuclear targeting with enrichment in the nucleolus. Conclusions The Puf family of RNA-binding proteins in plants consists of a greater number of members than any other model species studied to

Phocid seal leptin: tertiary structure and hydrophobic receptor binding site preservation during distinct leptin gene evolution.

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John A Hammond

Full Text Available The cytokine hormone leptin is a key signalling molecule in many pathways that control physiological functions. Although leptin demonstrates structural conservation in mammals, there is evidence of positive selection in primates, lagomorphs and chiropterans. We previously reported that the leptin genes of the grey and harbour seals (phocids have significantly diverged from other mammals. Therefore we further investigated the diversification of leptin in phocids, other marine mammals and terrestrial taxa by sequencing the leptin genes of representative species. Phylogenetic reconstruction revealed that leptin diversification was pronounced within the phocid seals with a high dN/dS ratio of 2.8, indicating positive selection. We found significant evidence of positive selection along the branch leading to the phocids, within the phocid clade, but not over the dataset as a whole. Structural predictions indicate that the individual residues under selection are away from the leptin receptor (LEPR binding site. Predictions of the surface electrostatic potential indicate that phocid seal leptin is notably different to other mammalian leptins, including the otariids. Cloning the grey seal leptin binding domain of LEPR confirmed that this was structurally conserved. These data, viewed in toto, support a hypothesis that phocid leptin divergence is unlikely to have arisen by random mutation. Based upon these phylogenetic and structural assessments, and considering the comparative physiology and varying life histories among species, we postulate that the unique phocid diving behaviour has produced this selection pressure. The Phocidae includes some of the deepest diving species, yet have the least modified lung structure to cope with pressure and volume changes experienced at depth. Therefore, greater surfactant production is required to facilitate rapid lung re-inflation upon surfacing, while maintaining patent airways. We suggest that this additional

Prediction of protein-protein interaction sites in sequences and 3D structures by random forests.

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Mile Sikić

2009-01-01

Full Text Available Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i a combination of sequence- and structure-derived parameters and (ii sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.

Structural Basis for Sialoglycan Binding by the Streptococcus sanguinis SrpA Adhesin*♦

Science.gov (United States)

Bensing, Barbara A.; Loukachevitch, Lioudmila V.; McCulloch, Kathryn M.; Yu, Hai; Vann, Kendra R.; Wawrzak, Zdzislaw; Anderson, Spencer; Chen, Xi; Sullam, Paul M.; Iverson, T. M.

2016-01-01

Streptococcus sanguinis is a leading cause of infective endocarditis, a life-threatening infection of the cardiovascular system. An important interaction in the pathogenesis of infective endocarditis is attachment of the organisms to host platelets. S. sanguinis expresses a serine-rich repeat adhesin, SrpA, similar in sequence to platelet-binding adhesins associated with increased virulence in this disease. In this study, we determined the first crystal structure of the putative binding region of SrpA (SrpABR) both unliganded and in complex with a synthetic disaccharide ligand at 1.8 and 2.0 Å resolution, respectively. We identified a conserved Thr-Arg motif that orients the sialic acid moiety and is required for binding to platelet monolayers. Furthermore, we propose that sequence insertions in closely related family members contribute to the modulation of structural and functional properties, including the quaternary structure, the tertiary structure, and the ligand-binding site. PMID:26833566

Membrane proteins bind lipids selectively to modulate their structure and function.

Science.gov (United States)

Laganowsky, Arthur; Reading, Eamonn; Allison, Timothy M; Ulmschneider, Martin B; Degiacomi, Matteo T; Baldwin, Andrew J; Robinson, Carol V

2014-06-05

Previous studies have established that the folding, structure and function of membrane proteins are influenced by their lipid environments and that lipids can bind to specific sites, for example, in potassium channels. Fundamental questions remain however regarding the extent of membrane protein selectivity towards lipids. Here we report a mass spectrometry approach designed to determine the selectivity of lipid binding to membrane protein complexes. We investigate the mechanosensitive channel of large conductance (MscL) from Mycobacterium tuberculosis and aquaporin Z (AqpZ) and the ammonia channel (AmtB) from Escherichia coli, using ion mobility mass spectrometry (IM-MS), which reports gas-phase collision cross-sections. We demonstrate that folded conformations of membrane protein complexes can exist in the gas phase. By resolving lipid-bound states, we then rank bound lipids on the basis of their ability to resist gas phase unfolding and thereby stabilize membrane protein structure. Lipids bind non-selectively and with high avidity to MscL, all imparting comparable stability; however, the highest-ranking lipid is phosphatidylinositol phosphate, in line with its proposed functional role in mechanosensation. AqpZ is also stabilized by many lipids, with cardiolipin imparting the most significant resistance to unfolding. Subsequently, through functional assays we show that cardiolipin modulates AqpZ function. Similar experiments identify AmtB as being highly selective for phosphatidylglycerol, prompting us to obtain an X-ray structure in this lipid membrane-like environment. The 2.3 Å resolution structure, when compared with others obtained without lipid bound, reveals distinct conformational changes that re-position AmtB residues to interact with the lipid bilayer. Our results demonstrate that resistance to unfolding correlates with specific lipid-binding events, enabling a distinction to be made between lipids that merely bind from those that modulate membrane

Convergence of Domain Architecture, Structure, and Ligand Affinity in Animal and Plant RNA-Binding Proteins.

Science.gov (United States)

Dias, Raquel; Manny, Austin; Kolaczkowski, Oralia; Kolaczkowski, Bryan

2017-06-01

Reconstruction of ancestral protein sequences using phylogenetic methods is a powerful technique for directly examining the evolution of molecular function. Although ancestral sequence reconstruction (ASR) is itself very efficient, downstream functional, and structural studies necessary to characterize when and how changes in molecular function occurred are often costly and time-consuming, currently limiting ASR studies to examining a relatively small number of discrete functional shifts. As a result, we have very little direct information about how molecular function evolves across large protein families. Here we develop an approach combining ASR with structure and function prediction to efficiently examine the evolution of ligand affinity across a large family of double-stranded RNA binding proteins (DRBs) spanning animals and plants. We find that the characteristic domain architecture of DRBs-consisting of 2-3 tandem double-stranded RNA binding motifs (dsrms)-arose independently in early animal and plant lineages. The affinity with which individual dsrms bind double-stranded RNA appears to have increased and decreased often across both animal and plant phylogenies, primarily through convergent structural mechanisms involving RNA-contact residues within the β1-β2 loop and a small region of α2. These studies provide some of the first direct information about how protein function evolves across large gene families and suggest that changes in molecular function may occur often and unassociated with major phylogenetic events, such as gene or domain duplications. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Module structure of interphotoreceptor retinoid-binding protein (IRBP may provide bases for its complex role in the visual cycle – structure/function study of Xenopus IRBP

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Ghosh Debashis

2007-08-01

Full Text Available Abstract Background Interphotoreceptor retinoid-binding protein's (IRBP remarkable module structure may be critical to its role in mediating the transport of all-trans and 11-cis retinol, and 11-cis retinal between rods, cones, RPE and Müller cells during the visual cycle. We isolated cDNAs for Xenopus IRBP, and expressed and purified its individual modules, module combinations, and the full-length polypeptide. Binding of all-trans retinol, 11-cis retinal and 9-(9-anthroyloxy stearic acid were characterized by fluorescence spectroscopy monitoring ligand-fluorescence enhancement, quenching of endogenous protein fluorescence, and energy transfer. Finally, the X-ray crystal structure of module-2 was used to predict the location of the ligand-binding sites, and compare their structures among modules using homology modeling. Results The full-length Xenopus IRBP cDNA codes for a polypeptide of 1,197 amino acid residues beginning with a signal peptide followed by four homologous modules each ~300 amino acid residues in length. Modules 1 and 3 are more closely related to each other than either is to modules 2 and 4. Modules 1 and 4 are most similar to the N- and C-terminal modules of the two module IRBP of teleosts. Our data are consistent with the model that vertebrate IRBPs arose through two genetic duplication events, but that the middle two modules were lost during the evolution of the ray finned fish. The sequence of the expressed full-length IRBP was confirmed by liquid chromatography-tandem mass spectrometry. The recombinant full-length Xenopus IRBP bound all-trans retinol and 11-cis retinaldehyde at 3 to 4 sites with Kd's of 0.2 to 0.3 μM, and was active in protecting all-trans retinol from degradation. Module 2 showed selectivity for all-trans retinol over 11-cis retinaldehyde. The binding data are correlated to the results of docking of all-trans-retinol to the crystal structure of Xenopus module 2 suggesting two ligand-binding sites

Intrinsic Thermodynamics and Structures of 2,4- and 3,4-Substituted Fluorinated Benzenesulfonamides Binding to Carbonic Anhydrases.

Science.gov (United States)

Zubrienė, Asta; Smirnov, Alexey; Dudutienė, Virginija; Timm, David D; Matulienė, Jurgita; Michailovienė, Vilma; Zakšauskas, Audrius; Manakova, Elena; Gražulis, Saulius; Matulis, Daumantas

2017-01-20

The goal of rational drug design is to understand structure-thermodynamics correlations in order to predict the chemical structure of a drug that would exhibit excellent affinity and selectivity for a target protein. In this study we explored the contribution of added functionalities of benzenesulfonamide inhibitors to the intrinsic binding affinity, enthalpy, and entropy for recombinant human carbonic anhydrases (CA) CA I, CA II, CA VII, CA IX, CA XII, and CA XIII. The binding enthalpies of compounds possessing similar chemical structures and affinities were found to be very different, spanning a range from -90 to +10 kJ mol -1 , and are compensated by a similar opposing entropy contribution. The intrinsic parameters of binding were determined by subtracting the linked protonation reactions. The sulfonamide group pK a values of the compounds were measured spectrophotometrically, and the protonation enthalpies were measured by isothermal titration calorimetry (ITC). Herein we describe the development of meta- or ortho-substituted fluorinated benzenesulfonamides toward the highly potent compound 10 h, which exhibits an observed dissociation constant value of 43 pm and an intrinsic dissociation constant value of 1.1 pm toward CA IX, an anticancer target that is highly overexpressed in various tumors. Fluorescence thermal shift assays, ITC, and X-ray crystallography were all applied in this work. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computational identification of antigen-binding antibody fragments.

Science.gov (United States)

Burkovitz, Anat; Leiderman, Olga; Sela-Culang, Inbal; Byk, Gerardo; Ofran, Yanay

2013-03-01

Determining which parts of the Ab are essential for Ag recognition and binding is crucial for understanding B cell-mediated immunity. Identification of fragments of Abs that maintain specificity to the Ag will also allow for the development of improved Ab-based therapy and diagnostics. In this article, we show that structural analysis of Ab-Ag complexes reveals which fragments of the Ab may bind the Ag on their own. In particular, it is possible to predict whether a given CDR is likely to bind the Ag as a peptide by analyzing the energetic contribution of each CDR to Ag binding and by assessing to what extent the interaction between that CDR and the Ag depends on other CDRs. To demonstrate this, we analyzed five Ab-Ag complexes and predicted for each of them which of the CDRs may bind the Ag on its own as a peptide. We then show that these predictions are in agreement with our experimental analysis and with previously published experimental results. These findings promote our understanding of the modular nature of Ab-Ag interactions and lay the foundation for the rational design of active CDR-derived peptides.

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

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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

Prediction of molecular crystal structures

International Nuclear Information System (INIS)

Beyer, Theresa

2001-01-01

The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol -1 of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

Prediction of molecular crystal structures

Energy Technology Data Exchange (ETDEWEB)

Beyer, Theresa

2001-07-01

The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol{sup -1} of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

Structure of the nucleotide-binding domain of a dipeptide ABC transporter reveals a novel iron-sulfur cluster-binding domain.

Science.gov (United States)

Li, Xiaolu; Zhuo, Wei; Yu, Jie; Ge, Jingpeng; Gu, Jinke; Feng, Yue; Yang, Maojun; Wang, Linfang; Wang, Na

2013-02-01

Dipeptide permease (Dpp), which belongs to an ABC transport system, imports peptides consisting of two or three L-amino acids from the matrix to the cytoplasm in microbes. Previous studies have indicated that haem competes with dipeptides to bind DppA in vitro and in vivo and that the Dpp system can also translocate haem. Here, the crystal structure of DppD, the nucleotide-binding domain (NBD) of the ABC-type dipeptide/oligopeptide/nickel-transport system from Thermoanaerobacter tengcongensis, bound with ATP, Mg(2+) and a [4Fe-4S] iron-sulfur cluster is reported. The N-terminal domain of DppD shares a similar structural fold with the NBDs of other ABC transporters. Interestingly, the C-terminal domain of DppD contains a [4Fe-4S] cluster. The UV-visible absorbance spectrum of DppD was consistent with the presence of a [4Fe-4S] cluster. A search with DALI revealed that the [4Fe-4S] cluster-binding domain is a novel structural fold. Structural analysis and comparisons with other ABC transporters revealed that this iron-sulfur cluster may act as a mediator in substrate (dipeptide or haem) binding by electron transfer and may regulate the transport process in Dpp ABC transport systems. The crystal structure provides a basis for understanding the properties of ABC transporters and will be helpful in investigating the functions of NBDs in the regulation of ABC transporter activity.

Crystal Structures and Binding Dynamics of Odorant-Binding Protein 3 from two aphid species Megoura viciae and Nasonovia ribisnigri.

Science.gov (United States)

Northey, Tom; Venthur, Herbert; De Biasio, Filomena; Chauviac, Francois-Xavier; Cole, Ambrose; Ribeiro, Karlos Antonio Lisboa; Grossi, Gerarda; Falabella, Patrizia; Field, Linda M; Keep, Nicholas H; Zhou, Jing-Jiang

2016-04-22

Aphids use chemical cues to locate hosts and find mates. The vetch aphid Megoura viciae feeds exclusively on the Fabaceae, whereas the currant-lettuce aphid Nasonovia ribisnigri alternates hosts between the Grossulariaceae and Asteraceae. Both species use alarm pheromones to warn of dangers. For N. ribisnigri this pheromone is a single component (E)-β-farnesene but M. viciae uses a mixture of (E)-β-farnesene, (-)-α-pinene, β-pinene, and limonene. Odorant-binding proteins (OBP) are believed to capture and transport such semiochemicals to their receptors. Here, we report the first aphid OBP crystal structures and examine their molecular interactions with the alarm pheromone components. Our study reveals some unique structural features: 1) the lack of an internal ligand binding site; 2) a striking groove in the surface of the proteins as a putative binding site; 3) the N-terminus rather than the C-terminus occupies the site closing off the conventional OBP pocket. The results from fluorescent binding assays, molecular docking and dynamics demonstrate that OBP3 from M. viciae can bind to all four alarm pheromone components and the differential ligand binding between these very similar OBP3s from the two aphid species is determined mainly by the direct π-π interactions between ligands and the aromatic residues of OBP3s in the binding pocket.

Structure of the C-terminal heme-binding domain of THAP domain containing protein 4 from Homo sapiens

Energy Technology Data Exchange (ETDEWEB)

Bianchetti, Christopher M.; Bingman, Craig A.; Phillips, Jr., George N. (UW)

2012-03-15

The thanatos (the Greek god of death)-associated protein (THAP) domain is a sequence-specific DNA-binding domain that contains a C2-CH (Cys-Xaa{sub 2-4}-Cys-Xaa{sub 35-50}-Cys-Xaa{sub 2}-His) zinc finger that is similar to the DNA domain of the P element transposase from Drosophila. THAP-containing proteins have been observed in the proteome of humans, pigs, cows, chickens, zebrafish, Drosophila, C. elegans, and Xenopus. To date, there are no known THAP domain proteins in plants, yeast, or bacteria. There are 12 identified human THAP domain-containing proteins (THAP0-11). In all human THAP protein, the THAP domain is located at the N-terminus and is {approx}90 residues in length. Although all of the human THAP-containing proteins have a homologous N-terminus, there is extensive variation in both the predicted structure and length of the remaining protein. Even though the exact function of these THAP proteins is not well defined, there is evidence that they play a role in cell proliferation, apoptosis, cell cycle modulation, chromatin modification, and transcriptional regulation. THAP-containing proteins have also been implicated in a number of human disease states including heart disease, neurological defects, and several types of cancers. Human THAP4 is a 577-residue protein of unknown function that is proposed to bind DNA in a sequence-specific manner similar to THAP1 and has been found to be upregulated in response to heat shock. THAP4 is expressed in a relatively uniform manner in a broad range of tissues and appears to be upregulated in lymphoma cells and highly expressed in heart cells. The C-terminal domain of THAP4 (residues 415-577), designated here as cTHAP4, is evolutionarily conserved and is observed in all known THAP4 orthologs. Several single-domain proteins lacking a THAP domain are found in plants and bacteria and show significant levels of homology to cTHAP4. It appears that cTHAP4 belongs to a large class of proteins that have yet to be fully

Binding of matrix metalloproteinase inhibitors to extracellular matrix: 3D-QSAR analysis.

Science.gov (United States)

Zhang, Yufen; Lukacova, Viera; Bartus, Vladimir; Nie, Xiaoping; Sun, Guorong; Manivannan, Ethirajan; Ghorpade, Sandeep R; Jin, Xiaomin; Manyem, Shankar; Sibi, Mukund P; Cook, Gregory R; Balaz, Stefan

2008-10-01

Binding to the extracellular matrix, one of the most abundant human protein complexes, significantly affects drug disposition. Specifically, the interactions with extracellular matrix determine the free concentrations of small molecules acting in tissues, including signaling peptides, inhibitors of tissue remodeling enzymes such as matrix metalloproteinases, and other drug candidates. The nature of extracellular matrix binding was elucidated for 63 matrix metalloproteinase inhibitors, for which the association constants to an extracellular matrix mimic were reported here. The data did not correlate with lipophilicity as a common determinant of structure-nonspecific, orientation-averaged binding. A hypothetical structure of the binding site of the solidified extracellular matrix surrogate was analyzed using the Comparative Molecular Field Analysis, which needed to be applied in our multi-mode variant. This fact indicates that the compounds bind to extracellular matrix in multiple modes, which cannot be considered as completely orientation-averaged and exhibit structural dependence. The novel comparative molecular field analysis models, exhibiting satisfactory descriptive and predictive abilities, are suitable for prediction of the extracellular matrix binding for the untested chemicals, which are within applicability domains. The results contribute to a better prediction of the pharmacokinetic parameters such as the distribution volume and the tissue-blood partition coefficients, in addition to a more imminent benefit for the development of more effective matrix metalloproteinase inhibitors.

Relationship of Structure and Function of DNA-Binding Domain in Vitamin D Receptor

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Lin-Yan Wan

2015-07-01

Full Text Available While the structure of the DNA-binding domain (DBD of the vitamin D receptor (VDR has been determined in great detail, the roles of its domains and how to bind the motif of its target genes are still under debate. The VDR DBD consists of two zinc finger modules and a C-terminal extension (CTE, at the end of the C-terminal of each structure presenting α-helix. For the first zinc finger structure, N37 and S-box take part in forming a dimer with 9-cis retinoid X receptor (RXR, while V26, R50, P-box and S-box participate in binding with VDR response elements (VDRE. For the second zinc finger structure, P61, F62 and H75 are essential in the structure of the VDR homodimer with the residues N37, E92 and F93 of the downstream of partner VDR, which form the inter-DBD interface. T-box of the CTE, especially the F93 and I94, plays a critical role in heterodimerization and heterodimers–VDRE binding. Six essential residues (R102, K103, M106, I107, K109, and R110 of the CTE α-helix of VDR construct one interaction face, which packs against the DBD core of the adjacent symmetry mate. In 1,25(OH2D3-activated signaling, the VDR-RXR heterodimer may bind to DR3-type VDRE and ER9-type VDREs of its target gene directly resulting in transactivation and also bind to DR3-liked nVDRE of its target gene directly resulting in transrepression. Except for this, 1α,25(OH2D3 ligand VDR-RXR may bind to 1αnVDRE indirectly through VDIR, resulting in transrepression of the target gene. Upon binding of 1α,25(OH2D3, VDR can transactivate and transrepress its target genes depending on the DNA motif that DBD binds.

Structural and mutational analyses of the receptor binding domain of botulinum D/C mosaic neurotoxin: Insight into the ganglioside binding mechanism

Energy Technology Data Exchange (ETDEWEB)

Nuemket, Nipawan [Graduate School of Life Sciences, Hokkaido University, Sapporo 060-0810 (Japan); Tanaka, Yoshikazu [Creative Research Institution ' Sousei,' Hokkaido University, Sapporo 001-0021 (Japan); Faculty of Advanced Life Science, Hokkaido University, Sapporo 060-0810 (Japan); Tsukamoto, Kentaro; Tsuji, Takao [Department of Microbiology, Fujita Health University School of Medicine, Toyoake, Aichi 470-1192 (Japan); Nakamura, Keiji; Kozaki, Shunji [Department of Veterinary Science, Graduate School of Life and Environmental Sciences, Osaka Prefecture University, Osaka 598-8531 (Japan); Yao, Min [Graduate School of Life Sciences, Hokkaido University, Sapporo 060-0810 (Japan); Faculty of Advanced Life Science, Hokkaido University, Sapporo 060-0810 (Japan); Tanaka, Isao, E-mail: tanaka@castor.sci.hokudai.ac.jp [Graduate School of Life Sciences, Hokkaido University, Sapporo 060-0810 (Japan); Faculty of Advanced Life Science, Hokkaido University, Sapporo 060-0810 (Japan)

2011-07-29

Highlights: {yields} We determined the crystal structure of the receptor binding domain of BoNT in complex with 3'-sialyllactose. {yields} An electron density derived from the 3'-sialyllactose was confirmed at the cleft in the C-terminal subdomain. {yields} Alanine site-directed mutagenesis showed that GBS and GBL are important for ganglioside binding. {yields} A cell binding mechanism, which involves cooperative contribution of two sites, was proposed. -- Abstract: Clostridium botulinum type D strain OFD05, which produces the D/C mosaic neurotoxin, was isolated from cattle killed by the recent botulism outbreak in Japan. The D/C mosaic neurotoxin is the most toxic of the botulinum neurotoxins (BoNT) characterized to date. Here, we determined the crystal structure of the receptor binding domain of BoNT from strain OFD05 in complex with 3'-sialyllactose at a resolution of 3.0 A. In the structure, an electron density derived from the 3'-sialyllactose was confirmed at the cleft in the C-terminal subdomain. Alanine site-directed mutagenesis showed the significant contribution of the residues surrounding the cleft to ganglioside recognition. In addition, a loop adjoining the cleft also plays an important role in ganglioside recognition. In contrast, little effect was observed when the residues located around the surface previously identified as the protein receptor binding site in other BoNTs were substituted. The results of cell binding analysis of the mutants were significantly correlated with the ganglioside binding properties. Based on these observations, a cell binding mechanism of BoNT from strain OFD05 is proposed, which involves cooperative contribution of two ganglioside binding sites.

Optimizing Stem Length To Improve Ligand Selectivity in a Structure-Switching Cocaine-Binding Aptamer.

Science.gov (United States)

Neves, Miguel A D; Shoara, Aron A; Reinstein, Oren; Abbasi Borhani, Okty; Martin, Taylor R; Johnson, Philip E

2017-10-27

Understanding how aptamer structure and function are related is crucial in the design and development of aptamer-based biosensors. We have analyzed a series of cocaine-binding aptamers with different lengths of their stem 1 in order to understand the role that this stem plays in the ligand-induced structure-switching binding mechanism utilized in many of the sensor applications of this aptamer. In the cocaine-binding aptamer, the length of stem 1 controls whether the structure-switching binding mechanism for this aptamer occurs or not. We varied the length of stem 1 from being one to seven base pairs long and found that the structural transition from unfolded to folded in the unbound aptamer is when the aptamer elongates from 3 to 4 base pairs in stem 1. We then used this knowledge to achieve new binding selectivity of this aptamer for quinine over cocaine by using an aptamer with a stem 1 two base pairs long. This selectivity is achieved by means of the greater affinity quinine has for the aptamer compared with cocaine. Quinine provides enough free energy to both fold and bind the 2-base pair-long aptamer while cocaine does not. This tuning of binding selectivity of an aptamer by reducing its stability is likely a general mechanism that could be used to tune aptamer specificity for tighter binding ligands.

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...

Atomic structure of nitrate-binding protein crucial for photosynthetic productivity

Energy Technology Data Exchange (ETDEWEB)

Koropatkin, Nicole M.; Pakrasi, Himadri B.; Smith, Thomas J.

2006-06-27

Cyanobacteria, blue-green algae, are the most abundant autotrophs in aquatic environments and form the base of all aquatic food chains by fixing carbon and nitrogen into cellular biomass. The single most important nutrient for photosynthesis and growth is nitrate, which is severely limiting in many aquatic environments particularly the open ocean (1, 2). It is therefore not surprising that NrtA, the solute-binding component of the high-affinity nitrate ABC transporter, is the single-most abundant protein in the plasma membrane of these bacteria (3). Here we describe the first structure of a nitratespecific receptor, NrtA from Synechocystis sp. PCC 6803, complexed with nitrate and determined to a resolution of 1.5Å. NrtA is significantly larger than other oxyanionbinding proteins, representing a new class of transport proteins. From sequence alignments, the only other solute-binding protein in this class is CmpA, a bicarbonatebinding protein. Therefore, these organisms created a novel solute-binding protein for two of the most important nutrients; inorganic nitrogen and carbon. The electrostatic charge distribution of NrtA appears to force the protein off of the membrane while the flexible tether facilitates the delivery of nitrate to the membrane pore. The structure not only details the determinants for nitrate selectivity in NrtA, but also the bicarbonate specificity in CmpA. Nitrate and bicarbonate transport are regulated by the cytoplasmic proteins NrtC and CmpC, respectively. Interestingly, the residues lining the ligand binding pockets suggest that they both bind nitrate. This implies that the nitrogen and carbon uptake pathways are synchronized by intracellular nitrate and nitrite.3 The nitrate ABC transporter of cyanobacteria is composed of four polypeptides (Figure 1): a high-affinity periplasmic solute-binding lipoprotein (NrtA), an integral membrane permease (NrtB), a cytoplasmic ATPase (NrtD), and a unique ATPase/solute-binding fusion protein (Nrt

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.

Molecular Phylogeny and Predicted 3D Structure of Plant beta-D-N-Acetylhexosaminidase

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Md. Anowar Hossain

2014-01-01

Full Text Available beta-D-N-Acetylhexosaminidase, a family 20 glycosyl hydrolase, catalyzes the removal of β-1,4-linked N-acetylhexosamine residues from oligosaccharides and their conjugates. We constructed phylogenetic tree of β-hexosaminidases to analyze the evolutionary history and predicted functions of plant hexosaminidases. Phylogenetic analysis reveals the complex history of evolution of plant β-hexosaminidase that can be described by gene duplication events. The 3D structure of tomato β-hexosaminidase (β-Hex-Sl was predicted by homology modeling using 1now as a template. Structural conformity studies of the best fit model showed that more than 98% of the residues lie inside the favoured and allowed regions where only 0.9% lie in the unfavourable region. Predicted 3D structure contains 531 amino acids residues with glycosyl hydrolase20b domain-I and glycosyl hydrolase20 superfamily domain-II including the (β/α8 barrel in the central part. The α and β contents of the modeled structure were found to be 33.3% and 12.2%, respectively. Eleven amino acids were found to be involved in ligand-binding site; Asp(330 and Glu(331 could play important roles in enzyme-catalyzed reactions. The predicted model provides a structural framework that can act as a guide to develop a hypothesis for β-Hex-Sl mutagenesis experiments for exploring the functions of this class of enzymes in plant kingdom.

Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops.

Science.gov (United States)

Phan, Andy; Mailey, Katherine; Saeki, Jessica; Gu, Xiaobo; Schroeder, Susan J

2017-05-01

Accurate thermodynamic parameters improve RNA structure predictions and thus accelerate understanding of RNA function and the identification of RNA drug binding sites. Many viral RNA structures, such as internal ribosome entry sites, have internal loops and bulges that are potential drug target sites. Current models used to predict internal loops are biased toward small, symmetric purine loops, and thus poorly predict asymmetric, pyrimidine-rich loops with >6 nucleotides (nt) that occur frequently in viral RNA. This article presents new thermodynamic data for 40 pyrimidine loops, many of which can form UU or protonated CC base pairs. Uracil and protonated cytosine base pairs stabilize asymmetric internal loops. Accurate prediction rules are presented that account for all thermodynamic measurements of RNA asymmetric internal loops. New loop initiation terms for loops with >6 nt are presented that do not follow previous assumptions that increasing asymmetry destabilizes loops. Since the last 2004 update, 126 new loops with asymmetry or sizes greater than 2 × 2 have been measured. These new measurements significantly deepen and diversify the thermodynamic database for RNA. These results will help better predict internal loops that are larger, pyrimidine-rich, and occur within viral structures such as internal ribosome entry sites. © 2017 Phan et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Homology modeling and docking analyses of M. leprae Mur ligases reveals the common binding residues for structure based drug designing to eradicate leprosy.

Science.gov (United States)

Shanmugam, Anusuya; Natarajan, Jeyakumar

2012-06-01

Multi drug resistance capacity for Mycobacterium leprae (MDR-Mle) demands the profound need for developing new anti-leprosy drugs. Since most of the drugs target a single enzyme, mutation in the active site renders the antibiotic ineffective. However, structural and mechanistic information on essential bacterial enzymes in a pathway could lead to the development of antibiotics that targets multiple enzymes. Peptidoglycan is an important component of the cell wall of M. leprae. The biosynthesis of bacterial peptidoglycan represents important targets for the development of new antibacterial drugs. Biosynthesis of peptidoglycan is a multi-step process that involves four key Mur ligase enzymes: MurC (EC:6.3.2.8), MurD (EC:6.3.2.9), MurE (EC:6.3.2.13) and MurF (EC:6.3.2.10). Hence in our work, we modeled the three-dimensional structure of the above Mur ligases using homology modeling method and analyzed its common binding features. The residues playing an important role in the catalytic activity of each of the Mur enzymes were predicted by docking these Mur ligases with their substrates and ATP. The conserved sequence motifs significant for ATP binding were predicted as the probable residues for structure based drug designing. Overall, the study was successful in listing significant and common binding residues of Mur enzymes in peptidoglycan pathway for multi targeted therapy.

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

Structure of Alzheimer’s disease amyloid precursor protein copper-binding domain at atomic resolution

Energy Technology Data Exchange (ETDEWEB)

Kong, Geoffrey Kwai-Wai; Adams, Julian J. [Biota Structural Biology Laboratory, St Vincent’s Institute, 9 Princes Street, Fitzroy, Victoria 3065 (Australia); Cappai, Roberto [Department of Pathology and Centre for Neuroscience, The University of Melbourne, Victoria 3010 (Australia); The Mental Health Research Institute of Victoria, Parkville, Victoria 3052 (Australia); Bio21 Institute, The University of Melbourne, Victoria 3010 (Australia); Parker, Michael W., E-mail: mparker@svi.edu.au [Biota Structural Biology Laboratory, St Vincent’s Institute, 9 Princes Street, Fitzroy, Victoria 3065 (Australia); Bio21 Institute, The University of Melbourne, Victoria 3010 (Australia)

2007-10-01

An atomic resolution structure of the copper-binding domain of the Alzheimer’s disease amyloid precursor protein is presented. Amyloid precursor protein (APP) plays a central role in the pathogenesis of Alzheimer’s disease, as its cleavage generates the Aβ peptide that is toxic to cells. APP is able to bind Cu{sup 2+} and reduce it to Cu{sup +} through its copper-binding domain (CuBD). The interaction between Cu{sup 2+} and APP leads to a decrease in Aβ production and to alleviation of the symptoms of the disease in mouse models. Structural studies of CuBD have been undertaken in order to better understand the mechanism behind the process. Here, the crystal structure of CuBD in the metal-free form determined to ultrahigh resolution (0.85 Å) is reported. The structure shows that the copper-binding residues of CuBD are rather rigid but that Met170, which is thought to be the electron source for Cu{sup 2+} reduction, adopts two different side-chain conformations. These observations shed light on the copper-binding and redox mechanisms of CuBD. The structure of CuBD at atomic resolution provides an accurate framework for structure-based design of molecules that will deplete Aβ production.

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)

Structural study and thermodynamic characterization of inhibitor binding to lumazine synthase from Bacillus anthracis

Energy Technology Data Exchange (ETDEWEB)

Morgunova, Ekaterina [Karolinska Institutet NOVUM, Center of Structural Biochemistry, Hälsovägen 7-9, 141 57 Huddinge (Sweden); Illarionov, Boris; Saller, Sabine [Institut für Lebensmittelchemie, Universität Hamburg, Grindelallee 117, 20146 Hamburg (Germany); Popov, Aleksander [European Synchrotron Radiation Facility, BP 220, F-38043 Grenoble CEDEX 09 (France); Sambaiah, Thota [Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University (United States); Bacher, Adelbert [Chemistry Department, Technical University of Munich, 85747 Garching (Germany); Cushman, Mark [Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University (United States); Fischer, Markus [Institut für Lebensmittelchemie, Universität Hamburg, Grindelallee 117, 20146 Hamburg (Germany); Ladenstein, Rudolf, E-mail: rudolf.ladenstein@ki.se [Karolinska Institutet NOVUM, Center of Structural Biochemistry, Hälsovägen 7-9, 141 57 Huddinge (Sweden)

2010-09-01

Crystallographic studies of lumazine synthase, the penultimate enzyme of the riboflavin-biosynthetic pathway in B. anthracis, provide a structural framework for the design of antibiotic inhibitors, together with calorimetric and kinetic investigations of inhibitor binding. The crystal structure of lumazine synthase from Bacillus anthracis was solved by molecular replacement and refined to R{sub cryst} = 23.7% (R{sub free} = 28.4%) at a resolution of 3.5 Å. The structure reveals the icosahedral symmetry of the enzyme and specific features of the active site that are unique in comparison with previously determined orthologues. The application of isothermal titration calorimetry in combination with enzyme kinetics showed that three designed pyrimidine derivatives bind to lumazine synthase with micromolar dissociation constants and competitively inhibit the catalytic reaction. Structure-based modelling suggested the binding modes of the inhibitors in the active site and allowed an estimation of the possible contacts formed upon binding. The results provide a structural framework for the design of antibiotics active against B. anthracis.

Structure and DNA-binding of meiosis-specific protein Hop2

Science.gov (United States)

Zhou, Donghua; Moktan, Hem; Pezza, Roberto

2014-03-01

Here we report structure elucidation of the DNA binding domain of homologous pairing protein 2 (Hop2), which is important to gene diversity when sperms and eggs are produced. Together with another protein Mnd1, Hop2 enhances the strand invasion activity of recombinase Dmc1 by over 30 times, facilitating proper synapsis of homologous chromosomes. However, the structural and biochemical bases for the function of Hop2 and Mnd1 have not been well understood. As a first step toward such understanding, we recently solved the structure for the N-terminus of Hop2 (1-84) using solution NMR. This fragment shows a typical winged-head conformation with recognized DNA binding activity. DNA interacting sites were then investigated by chemical shift perturbations in a titration experiment. Information of these sites was used to guide protein-DNA docking with MD simulation, revealing that helix 3 is stably lodged in the DNA major groove and that wing 1 (connecting strands 2 and 3) transiently comes in contact with the minor groove in nanosecond time scale. Mutagenesis analysis further confirmed the DNA binding sites in this fragment of the protein.

Structure of a retro-binding peptide inhibitor complexed with human alpha-thrombin.

Science.gov (United States)

Tabernero, L; Chang, C Y; Ohringer, S L; Lau, W F; Iwanowicz, E J; Han, W C; Wang, T C; Seiler, S M; Roberts, D G; Sack, J S

1995-02-10

The crystallographic structure of the ternary complex between human alpha-thrombin, hirugen and the peptidyl inhibitor Phe-alloThr-Phe-O-CH3, which is acylated at its N terminus with 4-guanidino butanoic acid (BMS-183507), has been determined at 2.6 A resolution. The structure reveals a unique "retro-binding" mode for this tripeptide active site inhibitor. The inhibitor binds with its alkyl-guanidine moiety in the primary specificity pocket and its two phenyl rings occupying the hydrophobic proximal and distal pockets of the thrombin active site. In this arrangement the backbone of the tripeptide forms a parallel beta-strand to the thrombin main-chain at the binding site. This is opposite to the orientation of the natural substrate, fibrinogen, and all the small active site-directed thrombin inhibitors whose bound structures have been previously reported. BMS-183507 is the first synthetic inhibitor proved to bind in a retro-binding fashion to thrombin, in a fashion similar to that of the N-terminal residues of the natural inhibitor hirudin. Furthermore, this new potent thrombin inhibitor (Ki = 17.2 nM) is selective for thrombin over other serine proteases tested and may be a template to be considered in designing hirudin-based thrombin inhibitors with interactions at the specificity pocket.

LIBRA: LIgand Binding site Recognition Application.

Science.gov (United States)

Hung, Le Viet; Caprari, Silvia; Bizai, Massimiliano; Toti, Daniele; Polticelli, Fabio

2015-12-15

In recent years, structural genomics and ab initio molecular modeling activities are leading to the availability of a large number of structural models of proteins whose biochemical function is not known. The aim of this study was the development of a novel software tool that, given a protein's structural model, predicts the presence and identity of active sites and/or ligand binding sites. The algorithm implemented by ligand binding site recognition application (LIBRA) is based on a graph theory approach to find the largest subset of similar residues between an input protein and a collection of known functional sites. The algorithm makes use of two predefined databases for active sites and ligand binding sites, respectively, derived from the Catalytic Site Atlas and the Protein Data Bank. Tests indicate that LIBRA is able to identify the correct binding/active site in 90% of the cases analyzed, 90% of which feature the identified site as ranking first. As far as ligand binding site recognition is concerned, LIBRA outperforms other structure-based ligand binding sites detection tools with which it has been compared. The application, developed in Java SE 7 with a Swing GUI embedding a JMol applet, can be run on any OS equipped with a suitable Java Virtual Machine (JVM), and is available at the following URL: http://www.computationalbiology.it/software/LIBRAv1.zip. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Structure of a periplasmic glucose-binding protein from Thermotoga maritima

International Nuclear Information System (INIS)

Palani, Kandavelu; Kumaran, Desigan; Burley, Stephen K.; Swaminathan, Subramanyam

2012-01-01

The periplasmic glucose-binding protein from T. maritima consists of two domains with the ligand β-d-glucose buried between them. The two domains adopt a closed conformation. ABC transport systems have been characterized in organisms ranging from bacteria to humans. In most bacterial systems, the periplasmic component is the primary determinant of specificity of the transport complex as a whole. Here, the X-ray crystal structure of a periplasmic glucose-binding protein (GBP) from Thermotoga maritima determined at 2.4 Å resolution is reported. The molecule consists of two similar α/β domains connected by a three-stranded hinge region. In the current structure, a ligand (β-d-glucose) is buried between the two domains, which have adopted a closed conformation. Details of the substrate-binding sites revealed features that determine substrate specificity. In toto, ten residues from both domains form eight hydrogen bonds to the bound sugar and four aromatic residues (two from each domain) stabilize the substrate through stacking interactions

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.

Science.gov (United States)

Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka

2018-05-08

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on

In Silico Mechanistic Profiling to Probe Small Molecule Binding to Sulfotransferases

Science.gov (United States)

Martiny, Virginie Y.; Carbonell, Pablo; Lagorce, David; Villoutreix, Bruno O.; Moroy, Gautier; Miteva, Maria A.

2013-01-01

Drug metabolizing enzymes play a key role in the metabolism, elimination and detoxification of xenobiotics, drugs and endogenous molecules. While their principal role is to detoxify organisms by modifying compounds, such as pollutants or drugs, for a rapid excretion, in some cases they render their substrates more toxic thereby inducing severe side effects and adverse drug reactions, or their inhibition can lead to drug–drug interactions. We focus on sulfotransferases (SULTs), a family of phase II metabolizing enzymes, acting on a large number of drugs and hormones and showing important structural flexibility. Here we report a novel in silico structure-based approach to probe ligand binding to SULTs. We explored the flexibility of SULTs by molecular dynamics (MD) simulations in order to identify the most suitable multiple receptor conformations for ligand binding prediction. Then, we employed structure-based docking-scoring approach to predict ligand binding and finally we combined the predicted interaction energies by using a QSAR methodology. The results showed that our protocol successfully prioritizes potent binders for the studied here SULT1 isoforms, and give new insights on specific molecular mechanisms for diverse ligands’ binding related to their binding sites plasticity. Our best QSAR models, introducing predicted protein-ligand interaction energy by using docking, showed accuracy of 67.28%, 78.00% and 75.46%, for the isoforms SULT1A1, SULT1A3 and SULT1E1, respectively. To the best of our knowledge our protocol is the first in silico structure-based approach consisting of a protein-ligand interaction analysis at atomic level that considers both ligand and enzyme flexibility, along with a QSAR approach, to identify small molecules that can interact with II phase dug metabolizing enzymes. PMID:24039991

In silico mechanistic profiling to probe small molecule binding to sulfotransferases.

Directory of Open Access Journals (Sweden)

Virginie Y Martiny

Full Text Available Drug metabolizing enzymes play a key role in the metabolism, elimination and detoxification of xenobiotics, drugs and endogenous molecules. While their principal role is to detoxify organisms by modifying compounds, such as pollutants or drugs, for a rapid excretion, in some cases they render their substrates more toxic thereby inducing severe side effects and adverse drug reactions, or their inhibition can lead to drug-drug interactions. We focus on sulfotransferases (SULTs, a family of phase II metabolizing enzymes, acting on a large number of drugs and hormones and showing important structural flexibility. Here we report a novel in silico structure-based approach to probe ligand binding to SULTs. We explored the flexibility of SULTs by molecular dynamics (MD simulations in order to identify the most suitable multiple receptor conformations for ligand binding prediction. Then, we employed structure-based docking-scoring approach to predict ligand binding and finally we combined the predicted interaction energies by using a QSAR methodology. The results showed that our protocol successfully prioritizes potent binders for the studied here SULT1 isoforms, and give new insights on specific molecular mechanisms for diverse ligands' binding related to their binding sites plasticity. Our best QSAR models, introducing predicted protein-ligand interaction energy by using docking, showed accuracy of 67.28%, 78.00% and 75.46%, for the isoforms SULT1A1, SULT1A3 and SULT1E1, respectively. To the best of our knowledge our protocol is the first in silico structure-based approach consisting of a protein-ligand interaction analysis at atomic level that considers both ligand and enzyme flexibility, along with a QSAR approach, to identify small molecules that can interact with II phase dug metabolizing enzymes.

RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information.

Science.gov (United States)

Ghosh, Pritha; Mathew, Oommen K; Sowdhamini, Ramanathan

2016-10-07

RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information. The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search. RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential

Structural Basis for a Ribofuranosyl Binding Protein: Insights into the Furanose Specific Transport

Energy Technology Data Exchange (ETDEWEB)

Bagaria, A.; Swaminathan, S.; Kumaran, D.; Burley, S. K.

2011-04-01

The ATP-binding cassette transporters (ABC-transporters) are members of one of the largest protein superfamilies, with representatives in all extant phyla. These integral membrane proteins utilize the energy of ATP hydrolysis to carry out certain biological processes, including translocation of various substrates across membranes and non-transport related processes such as translation of RNA and DNA repair. Typically, such transport systems in bacteria consist of an ATP binding component, a transmembrane permease, and a periplasmic receptor or binding protein. Soluble proteins found in the periplasm of gram-negative bacteria serve as the primary receptors for transport of many compounds, such as sugars, small peptides, and some ions. Ligand binding activates these periplasmic components, permitting recognition by the membrane spanning domain, which supports for transport and, in some cases, chemotaxis. Transport and chemotaxis processes appear to be independent of one another, and a few mutants of bifunctional periplasmic components reveal the absence of one or the other function. Previously published high-resolution X-ray structures of various periplasmic ligand binding proteins include Arabinose binding protein (ABP), Allose binding protein (ALBP), Glucose-galactose binding protein (GBP) and Ribose binding protein (RBP). Each of these proteins consists of two structurally similar domains connected by a three-stranded hinge region, with ligand buried between the domains. Upon ligand binding and release, various conformational changes have been observed. For RBP, open (apo) and closed (ligand bound) conformations have been reported and so for MBP. The closed/active form of the protein interacts with the integral membrane component of the system in both transport and chemotaxis. Herein, we report 1.9{angstrom} resolution X-ray structure of the R{sub f}BP periplasmic component of an ABC-type sugar transport system from Hahella chejuensis (UniProt Id Q2S7D2) bound to

Structural basis for ubiquitin recognition by ubiquitin-binding zinc finger of FAAP20.

Directory of Open Access Journals (Sweden)

Aya Toma

Full Text Available Several ubiquitin-binding zinc fingers (UBZs have been reported to preferentially bind K63-linked ubiquitin chains. In particular, the UBZ domain of FAAP20 (FAAP20-UBZ, a member of the Fanconi anemia core complex, seems to recognize K63-linked ubiquitin chains, in order to recruit the complex to DNA interstrand crosslinks and mediate DNA repair. By contrast, it is reported that the attachment of a single ubiquitin to Rev1, a translesion DNA polymerase, increases binding of Rev1 to FAAP20. To clarify the specificity of FAAP20-UBZ, we determined the crystal structure of FAAP20-UBZ in complex with K63-linked diubiquitin at 1.9 Å resolution. In this structure, FAAP20-UBZ interacts only with one of the two ubiquitin moieties. Consistently, binding assays using surface plasmon resonance spectrometry showed that FAAP20-UBZ binds ubiquitin and M1-, K48- and K63-linked diubiquitin chains with similar affinities. Residues in the vicinity of Ala168 within the α-helix and the C-terminal Trp180 interact with the canonical Ile44-centered hydrophobic patch of ubiquitin. Asp164 within the α-helix and the C-terminal loop mediate a hydrogen bond network, which reinforces ubiquitin-binding of FAAP20-UBZ. Mutations of the ubiquitin-interacting residues disrupted binding to ubiquitin in vitro and abolished the accumulation of FAAP20 to DNA damage sites in vivo. Finally, structural comparison among FAAP20-UBZ, WRNIP1-UBZ and RAD18-UBZ revealed distinct modes of ubiquitin binding. UBZ family proteins could be divided into at least three classes, according to their ubiquitin-binding modes.

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.

LDA+U and tight-binding electronic structure of InN nanowires

Science.gov (United States)

Molina-Sánchez, A.; García-Cristóbal, A.; Cantarero, A.; Terentjevs, A.; Cicero, G.

2010-10-01

In this paper we employ a combined ab initio and tight-binding approach to obtain the electronic and optical properties of hydrogenated Indium nitride (InN) nanowires. We first discuss InN band structure for the wurtzite structure calculated at the LDA+U level and use this information to extract the parameters needed for an empirical tight-binging implementation. These parameters are then employed to calculate the electronic and optical properties of InN nanowires in a diameter range that would not be affordable by ab initio techniques. The reliability of the large nanowires results is assessed by explicitly comparing the electronic structure of a small diameter wire studied both at LDA+U and tight-binding level.

Structural basis of nonribosomal peptide macrocyclization in fungi.

Science.gov (United States)

Zhang, Jinru; Liu, Nicholas; Cacho, Ralph A; Gong, Zhou; Liu, Zhu; Qin, Wenming; Tang, Chun; Tang, Yi; Zhou, Jiahai

2016-12-01

Nonribosomal peptide synthetases (NRPSs) in fungi biosynthesize important pharmaceutical compounds, including penicillin, cyclosporine and echinocandin. To understand the fungal strategy of forging the macrocyclic peptide linkage, we determined the crystal structures of the terminal condensation-like (C T ) domain and the holo thiolation (T)-C T complex of Penicillium aethiopicum TqaA. The first, to our knowledge, structural depiction of the terminal module in a fungal NRPS provides a molecular blueprint for generating new macrocyclic peptide natural products.

RNA-SSPT: RNA Secondary Structure Prediction Tools.

Science.gov (United States)

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

Acetylcholine-Binding Protein Engineered to Mimic the α4-α4 Binding Pocket in α4β2 Nicotinic Acetylcholine Receptors Reveals Interface Specific Interactions Important for Binding and Activity

DEFF Research Database (Denmark)

Shahsavar, Azadeh; Ahring, Philip K; Olsen, Jeppe A

2015-01-01

Neuronal α4β2 nicotinic acetylcholine receptors are attractive drug targets for psychiatric and neurodegenerative disorders and smoking cessation aids. Recently, a third agonist binding site between two α4 subunits in the (α4)(3)(β2)(2) receptor subpopulation was discovered. In particular, three......-yl)-1,4-diazepane], highlights the roles of the three residues in determining binding affinities and functional properties of ligands at the α4-α4 interface. Confirmed by mutational studies, our structures suggest a unique ligand-specific role of residue H142 on the α4 subunit. In the cocrystal...... that could not be predicted based on wild-type Ls-AChBP structures in complex with the same agonists. The results show that an unprecedented correlation between binding in engineered AChBPs and functional receptors can be obtained and provide new opportunities for structure-based design of drugs targeting...

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...

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...

The host-binding domain of the P2 phage tail spike reveals a trimeric iron-binding structure

International Nuclear Information System (INIS)

Yamashita, Eiki; Nakagawa, Atsushi; Takahashi, Junichi; Tsunoda, Kin-ichi; Yamada, Seiko; Takeda, Shigeki

2011-01-01

The C-terminal domain of a bacteriophage P2 tail-spike protein, gpV, was crystallized and its structure was solved at 1.27 Å resolution. The refined model showed a triple β-helix structure and the presence of iron, calcium and chloride ions. The adsorption and infection of bacteriophage P2 is mediated by tail fibres and tail spikes. The tail spikes on the tail baseplate are used to irreversibly adsorb to the host cells. Recently, a P2 phage tail-spike protein, gpV, was purified and it was shown that a C-terminal domain, Ser87–Leu211, is sufficient for the binding of gpV to host Escherichia coli membranes [Kageyama et al. (2009 ▶), Biochemistry, 48, 10129–10135]. In this paper, the crystal structure of the C-terminal domain of P2 gpV is reported. The structure is a triangular pyramid and looks like a spearhead composed of an intertwined β-sheet, a triple β-helix and a metal-binding region containing iron, calcium and chloride ions

Structural insights into human peroxisome proliferator activated receptor delta (PPAR-delta selective ligand binding.

Directory of Open Access Journals (Sweden)

Fernanda A H Batista

Full Text Available Peroxisome proliferator activated receptors (PPARs δ, α and γ are closely related transcription factors that exert distinct effects on fatty acid and glucose metabolism, cardiac disease, inflammatory response and other processes. Several groups developed PPAR subtype specific modulators to trigger desirable effects of particular PPARs without harmful side effects associated with activation of other subtypes. Presently, however, many compounds that bind to one of the PPARs cross-react with others and rational strategies to obtain highly selective PPAR modulators are far from clear. GW0742 is a synthetic ligand that binds PPARδ more than 300-fold more tightly than PPARα or PPARγ but the structural basis of PPARδ:GW0742 interactions and reasons for strong selectivity are not clear. Here we report the crystal structure of the PPARδ:GW0742 complex. Comparisons of the PPARδ:GW0742 complex with published structures of PPARs in complex with α and γ selective agonists and pan agonists suggests that two residues (Val312 and Ile328 in the buried hormone binding pocket play special roles in PPARδ selective binding and experimental and computational analysis of effects of mutations in these residues confirms this and suggests that bulky substituents that line the PPARα and γ ligand binding pockets as structural barriers for GW0742 binding. This analysis suggests general strategies for selective PPARδ ligand design.

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.

Modification of DNA radiolysis by DNA-binding proteins: Structural aspects

International Nuclear Information System (INIS)

Davidkova, M.; Stisova, V.; Goffinont, S.; Gillard, N.; Castaing, B.; Spotheim-Maurizot, M.

2006-01-01

Formation of specific complexes between proteins and their cognate DNA modulates the yields and the location of radiation damage on both partners of the complex. The radiolysis of DNA-protein complexes is studied for: (1) the Escherichia coli lactose operator-repressor complex, (2) the complex between DNA bearing an analogue of an abasic site and the repair protein Fpg of Lactococcus lactis. Experimental patterns of DNA damages are presented and compared to predicted damage distribution obtained using an improved version of the stochastic model RADACK. The same method is used for predicting the location of damages on the proteins. At doses lower than a threshold that depends on the system, proteins protect their specific binding site on DNA while at high doses, the studied complexes are disrupted mainly through protein damage. The loss of binding ability is the functional consequence of the amino-acids modification by OH . radicals. Many of the most probably damaged amino acids are essential for the DNA-protein interaction and within a complex are protected by DNA. (authors)

Isoforms of retinol binding protein 4 (RBP4) are increased in chronic diseases of the kidney but not of the liver

DEFF Research Database (Denmark)

Frey, Simone K; Nagl, Britta; Henze, Andrea

2008-01-01

disease (CLD) RBP4 levels decrease. Little is known about RBP4 isoforms including apo-RBP4, holo-RBP4 as well as RBP4 truncated at the C-terminus (RBP4-L and RBP4-LL) except that RBP4 isoforms have been reported to be increased in hemodialysis patients. Since it is not known whether CLD influence RBP4...... isoforms, we investigated RBP4 levels, apo- and holo-RBP4 as well as RBP4-L and RBP4-LL in plasma of 36 patients suffering from CKD, in 55 CLD patients and in 50 control subjects. RBP4 was determined by ELISA and apo- and holo-RBP4 by native polyacrylamide gel electrophoresis (PAGE). RBP4-L and RBP4-LL...

Structures of Orf Virus Chemokine Binding Protein in Complex with Host Chemokines Reveal Clues to Broad Binding Specificity.

Science.gov (United States)

Couñago, Rafael M; Knapp, Karen M; Nakatani, Yoshio; Fleming, Stephen B; Corbett, Michael; Wise, Lyn M; Mercer, Andrew A; Krause, Kurt L

2015-07-07

The chemokine binding protein (CKBP) from orf virus (ORFV) binds with high affinity to chemokines from three classes, C, CC, and CXC, making it unique among poxvirus CKBPs described to date. We present its crystal structure alone and in complex with three CC chemokines, CCL2, CCL3, and CCL7. ORFV CKBP possesses a β-sandwich fold that is electrostatically and sterically complementary to its binding partners. Chemokines bind primarily through interactions involving the N-terminal loop and a hydrophobic recess on the ORFV CKBP β-sheet II surface, and largely polar interactions between the chemokine 20s loop and a negatively charged surface groove located at one end of the CKBP β-sheet II surface. ORFV CKBP interacts with leukocyte receptor and glycosaminoglycan binding sites found on the surface of bound chemokines. SEC-MALLS and chromatographic evidence is presented supporting that ORFV CKBP is a dimer in solution over a broad range of protein concentrations. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.