Identification of compounds with binding affinity to proteins via magnetization transfer from bulk water

International Nuclear Information System (INIS)

Dalvit, Claudio; Pevarello, Paolo; Tato, Marco; Veronesi, Marina; Vulpetti, Anna; Sundstroem, Michael

2000-01-01

A powerful screening by NMR methodology (WaterLOGSY), based on transfer of magnetization from bulk water, for the identification of compounds that interact with target biomolecules (proteins, RNA and DNA fragments) is described. The method exploits efficiently the large reservoir of H 2 O magnetization. The high sensitivity of the technique reduces the amount of biomolecule and ligands needed for the screening, which constitutes an important requirement for high throughput screening by NMR of large libraries of compounds. Application of the method to a compound mixture against the cyclin-dependent kinase 2 (cdk2) protein is presented

Modeling protein structures: construction and their applications.

Science.gov (United States)

Ring, C S; Cohen, F E

1993-06-01

Although no general solution to the protein folding problem exists, the three-dimensional structures of proteins are being successfully predicted when experimentally derived constraints are used in conjunction with heuristic methods. In the case of interleukin-4, mutagenesis data and CD spectroscopy were instrumental in the accurate assignment of secondary structure. In addition, the tertiary structure was highly constrained by six cysteines separated by many residues that formed three disulfide bridges. Although the correct structure was a member of a short list of plausible structures, the "best" structure was the topological enantiomer of the experimentally determined conformation. For many proteases, other experimentally derived structures can be used as templates to identify the secondary structure elements. In a procedure called modeling by homology, the structure of a known protein is used as a scaffold to predict the structure of another related protein. This method has been used to model a serine and a cysteine protease that are important in the schistosome and malarial life cycles, respectively. The model structures were then used to identify putative small molecule enzyme inhibitors computationally. Experiments confirm that some of these nonpeptidic compounds are active at concentrations of less than 10 microM.

Automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

Science.gov (United States)

Bordoli, Lorenza; Schwede, Torsten

2012-01-01

Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of applications. Since the usefulness of a model for specific application is determined by its accuracy, model quality estimation is an essential component of protein structure prediction. Comparative protein modeling has become a routine approach in many areas of life science research since fully automated modeling systems allow also nonexperts to build reliable models. In this chapter, we describe practical approaches for automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

Integrated modelling of two xenobiotic organic compounds

DEFF Research Database (Denmark)

Lindblom, Erik Ulfson; Gernaey, K.V.; Henze, Mogens

2006-01-01

This paper presents a dynamic mathematical model that describes the fate and transport of two selected xenobiotic organic compounds (XOCs) in a simplified representation. of an integrated urban wastewater system. A simulation study, where the xenobiotics bisphenol A and pyrene are used as reference...... compounds, is carried out. Sorption and specific biological degradation processes are integrated with standardised water process models to model the fate of both compounds. Simulated mass flows of the two compounds during one dry weather day and one wet weather day are compared for realistic influent flow...... rate and concentration profiles. The wet weather day induces resuspension of stored sediments, which increases the pollutant load on the downstream system. The potential of the model to elucidate important phenomena related to origin and fate of the model compounds is demonstrated....

COMPOSITE PEPTIDE COMPOUNDS FOR DIAGNOSIS AND TREATMENT OF DISEASES CAUSED BY PRION PROTEINS

DEFF Research Database (Denmark)

2004-01-01

The present invention relates to diseases caused by prion proteins, Novel composite peptide compounds are disclosed which comprise two or more peptides or peptide fragments optionally linked to a backbone and the peptides or peptide fragments are spatially positioned relative to each other so tha....... Other uses of the composite peptide compounds are also disclosed, such as use in diagnostic assays, production of antibodies and uses as vaccine immunogens for the prophylactic protection and therapeutic treatment of subjects against transmissible prion disease.......The present invention relates to diseases caused by prion proteins, Novel composite peptide compounds are disclosed which comprise two or more peptides or peptide fragments optionally linked to a backbone and the peptides or peptide fragments are spatially positioned relative to each other so...

Automated Protein Structure Modeling with SWISS-MODEL Workspace and the Protein Model Portal

OpenAIRE

Bordoli, Lorenza; Schwede, Torsten

2012-01-01

Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of appl...

Compound semiconductor device modelling

CERN Document Server

Miles, Robert

1993-01-01

Compound semiconductor devices form the foundation of solid-state microwave and optoelectronic technologies used in many modern communication systems. In common with their low frequency counterparts, these devices are often represented using equivalent circuit models, but it is often necessary to resort to physical models in order to gain insight into the detailed operation of compound semiconductor devices. Many of the earliest physical models were indeed developed to understand the 'unusual' phenomena which occur at high frequencies. Such was the case with the Gunn and IMPATI diodes, which led to an increased interest in using numerical simulation methods. Contemporary devices often have feature sizes so small that they no longer operate within the familiar traditional framework, and hot electron or even quantum­ mechanical models are required. The need for accurate and efficient models suitable for computer aided design has increased with the demand for a wider range of integrated devices for operation at...

Modeling complexes of modeled proteins.

Science.gov (United States)

Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Structural analysis of protein-ligand interactions: the binding of endogenous compounds and of synthetic drugs.

Science.gov (United States)

Gallina, Anna M; Bork, Peer; Bordo, Domenico

2014-02-01

The large number of macromolecular structures deposited with the Protein Data Bank (PDB) describing complexes between proteins and either physiological compounds or synthetic drugs made it possible a systematic analysis of the interactions occurring between proteins and their ligands. In this work, the binding pockets of about 4000 PDB protein-ligand complexes were investigated and amino acid and interaction types were analyzed. The residues observed with lowest frequency in protein sequences, Trp, His, Met, Tyr, and Phe, turned out to be the most abundant in binding pockets. Significant differences between drug-like and physiological compounds were found. On average, physiological compounds establish with respect to drugs about twice as many hydrogen bonds with protein atoms, whereas drugs rely more on hydrophobic interactions to establish target selectivity. The large number of PDB structures describing homologous proteins in complex with the same ligand made it possible to analyze the conservation of binding pocket residues among homologous protein structures bound to the same ligand, showing that Gly, Glu, Arg, Asp, His, and Thr are more conserved than other amino acids. Also in the cases in which the same ligand is bound to unrelated proteins, the binding pockets showed significant conservation in the residue types. In this case, the probability of co-occurrence of the same amino acid type in the binding pockets could be up to thirteen times higher than that expected on a random basis. The trends identified in this study may provide an useful guideline in the process of drug design and lead optimization. Copyright © 2014 John Wiley & Sons, Ltd.

Active machine learning-driven experimentation to determine compound effects on protein patterns.

Science.gov (United States)

Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F

2016-02-03

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance.

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.

Compounds from silicones alter enzyme activity in curing barnacle glue and model enzymes.

Science.gov (United States)

Rittschof, Daniel; Orihuela, Beatriz; Harder, Tilmann; Stafslien, Shane; Chisholm, Bret; Dickinson, Gary H

2011-02-17

Attachment strength of fouling organisms on silicone coatings is low. We hypothesized that low attachment strength on silicones is, in part, due to the interaction of surface available components with natural glues. Components could alter curing of glues through bulk changes or specifically through altered enzyme activity. GC-MS analysis of silicone coatings showed surface-available siloxanes when the coatings were gently rubbed with a cotton swab for 15 seconds or given a 30 second rinse with methanol. Mixtures of compounds were found on 2 commercial and 8 model silicone coatings. The hypothesis that silicone components alter glue curing enzymes was tested with curing barnacle glue and with commercial enzymes. In our model, barnacle glue curing involves trypsin-like serine protease(s), which activate enzymes and structural proteins, and a transglutaminase which cross-links glue proteins. Transglutaminase activity was significantly altered upon exposure of curing glue from individual barnacles to silicone eluates. Activity of purified trypsin and, to a greater extent, transglutaminase was significantly altered by relevant concentrations of silicone polymer constituents. Surface-associated silicone compounds can disrupt glue curing and alter enzyme properties. Altered curing of natural glues has potential in fouling management.

Homology modeling and virtual screening to discover potent inhibitors targeting the imidazole glycerophosphate dehydratase protein in Staphylococcus xylosus

Science.gov (United States)

Chen, Xing-Ru; Wang, Xiao-Ting; Hao, Mei-Qi; Zhou, Yong-Hui; Cui, Wen-Qiang; Xing, Xiao-Xu; Xu, Chang-Geng; Bai, Jing-Wen; Li, Yan-Hua

2017-11-01

The imidazole glycerophosphate dehydratase (IGPD) protein is a therapeutic target for herbicide discovery. It is also regarded as a possible target in Staphylococcus xylosus (S. xylosus) for solving mastitis in the dairy cow. The 3D structure of IGPD protein is essential for discovering novel inhibitors during high-throughput virtual screening. However, to date, the 3D structure of IGPD protein of S. xylosus has not been solved. In this study, a series of computational techniques including homology modeling, Ramachandran Plots, and Verify 3D were performed in order to construct an appropriate 3D model of IGPD protein of S. xylosus. Nine hits were identified from 2500 compounds by docking studies. Then, these 9 compounds were first tested in vitro in S. xylosus biofilm formation using crystal violet staining. One of the potential compounds, baicalin was shown to significantly inhibit S. xylosus biofilm formation. Finally, the baicalin was further evaluated, which showed better inhibition of biofilm formation capability in S. xylosus by scanning electron microscopy. Hence, we have predicted the structure of IGPD protein of S. xylosus using computational techniques. We further discovered the IGPD protein was targeted by baicalin compound which inhibited the biofilm formation in S. xylosus. Our findings here would provide implications for the further development of novel IGPD inhibitors for the treatment of dairy mastitis.

Design of whey protein nanostructures for incorporation and release of nutraceutical compounds in food.

Science.gov (United States)

Ramos, Oscar L; Pereira, Ricardo N; Martins, Artur; Rodrigues, Rui; Fuciños, Clara; Teixeira, José A; Pastrana, Lorenzo; Malcata, F Xavier; Vicente, António A

2017-05-03

Whey proteins are widely used as nutritional and functional ingredients in formulated foods because they are relatively inexpensive, generally recognized as safe (GRAS) ingredient, and possess important biological, physical, and chemical functionalities. Denaturation and aggregation behavior of these proteins is of particular relevance toward manufacture of novel nanostructures with a number of potential uses. When these processes are properly engineered and controlled, whey proteins may be formed into nanohydrogels, nanofibrils, or nanotubes and be used as carrier of bioactive compounds. This review intends to discuss the latest understandings of nanoscale phenomena of whey protein denaturation and aggregation that may contribute for the design of protein nanostructures. Whey protein aggregation and gelation pathways under different processing and environmental conditions such as microwave heating, high voltage, and moderate electrical fields, high pressure, temperature, pH, and ionic strength were critically assessed. Moreover, several potential applications of nanohydrogels, nanofibrils, and nanotubes for controlled release of nutraceutical compounds (e.g. probiotics, vitamins, antioxidants, and peptides) were also included. Controlling the size of protein networks at nanoscale through application of different processing and environmental conditions can open perspectives for development of nanostructures with new or improved functionalities for incorporation and release of nutraceuticals in food matrices.

Crystal Structure of a Plant Multidrug and Toxic Compound Extrusion Family Protein.

Science.gov (United States)

Tanaka, Yoshiki; Iwaki, Shigehiro; Tsukazaki, Tomoya

2017-09-05

The multidrug and toxic compound extrusion (MATE) family of proteins consists of transporters responsible for multidrug resistance in prokaryotes. In plants, a number of MATE proteins were identified by recent genomic and functional studies, which imply that the proteins have substrate-specific transport functions instead of multidrug extrusion. The three-dimensional structure of eukaryotic MATE proteins, including those of plants, has not been reported, preventing a better understanding of the molecular mechanism of these proteins. Here, we describe the crystal structure of a MATE protein from the plant Camelina sativa at 2.9 Å resolution. Two sets of six transmembrane α helices, assembled pseudo-symmetrically, possess a negatively charged internal pocket with an outward-facing shape. The crystal structure provides insight into the diversity of plant MATE proteins and their substrate recognition and transport through the membrane. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Coarse-grain modelling of protein-protein interactions

NARCIS (Netherlands)

Baaden, Marc; Marrink, Siewert J.

2013-01-01

Here, we review recent advances towards the modelling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behaviour. PPI models of soluble proteins and membrane proteins are

Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target.

Science.gov (United States)

Chiba, Shuntaro; Ikeda, Kazuyoshi; Ishida, Takashi; Gromiha, M Michael; Taguchi, Y-H; Iwadate, Mitsuo; Umeyama, Hideaki; Hsin, Kun-Yi; Kitano, Hiroaki; Yamamoto, Kazuki; Sugaya, Nobuyoshi; Kato, Koya; Okuno, Tatsuya; Chikenji, George; Mochizuki, Masahiro; Yasuo, Nobuaki; Yoshino, Ryunosuke; Yanagisawa, Keisuke; Ban, Tomohiro; Teramoto, Reiji; Ramakrishnan, Chandrasekaran; Thangakani, A Mary; Velmurugan, D; Prathipati, Philip; Ito, Junichi; Tsuchiya, Yuko; Mizuguchi, Kenji; Honma, Teruki; Hirokawa, Takatsugu; Akiyama, Yutaka; Sekijima, Masakazu

2015-11-26

A search of broader range of chemical space is important for drug discovery. Different methods of computer-aided drug discovery (CADD) are known to propose compounds in different chemical spaces as hit molecules for the same target protein. This study aimed at using multiple CADD methods through open innovation to achieve a level of hit molecule diversity that is not achievable with any particular single method. We held a compound proposal contest, in which multiple research groups participated and predicted inhibitors of tyrosine-protein kinase Yes. This showed whether collective knowledge based on individual approaches helped to obtain hit compounds from a broad range of chemical space and whether the contest-based approach was effective.

Screening small-molecule compound microarrays for protein ligands without fluorescence labeling with a high-throughput scanning microscope.

Science.gov (United States)

Fei, Yiyan; Landry, James P; Sun, Yungshin; Zhu, Xiangdong; Wang, Xiaobing; Luo, Juntao; Wu, Chun-Yi; Lam, Kit S

2010-01-01

We describe a high-throughput scanning optical microscope for detecting small-molecule compound microarrays on functionalized glass slides. It is based on measurements of oblique-incidence reflectivity difference and employs a combination of a y-scan galvometer mirror and an x-scan translation stage with an effective field of view of 2 cm x 4 cm. Such a field of view can accommodate a printed small-molecule compound microarray with as many as 10,000 to 20,000 targets. The scanning microscope is capable of measuring kinetics as well as endpoints of protein-ligand reactions simultaneously. We present the experimental results on solution-phase protein reactions with small-molecule compound microarrays synthesized from one-bead, one-compound combinatorial chemistry and immobilized on a streptavidin-functionalized glass slide.

New potential nonsteroidal anti-inflammatory drugs with antileukotrienic effects: influence on model proteins with catalytic activity.

Science.gov (United States)

Netopilová, Miloslava; Drsata, Jaroslav; Beránek, Martin; Palicka, Vladimír

2002-01-01

Unspecific and side effects caused by interaction with proteins belong to common problems of many structures synthesized as potential medicaments. Possible in vitro interactions with proteins of a group of phenylsulfonyl benzoic acid derivatives (VUFB 19363, 19369, 19370, 19371, and 19760) as new potential anti-inflammatory compounds with anti-leukotrienic activities were studied in the present work. Three purified enzymes were used as model proteins with catalytic activities: Pig heart aspartate aminotransferase (AST, EC 2.6.1.1), alanine aminotransferase (ALT, EC 2.6.1.2), and glutamate decarboxylase (GAD, EC 4.1.1.15) from E. coli. Catalytic activities during incubation of individual compounds (6 x 10(-5) M solution to 5 x 10(-2) M suspension) at 37 degrees C with enzymes served as criteria of stability and function of the proteins. No immediate influence of any compound studied on enzyme activities was found. Aminotransferase activities were not affected even during incubation up to 20 d. In the case of GAD, the compounds VUFB 19369, 19370, 19371, and 19760 had stabilizing influence on GAD activity during incubation at enzyme concentrations of 11.25 and 5.62 mg prot/l. The lack of an immediate effect of compounds and the stability of enzymes during incubation them are favorable and support the prospective of the compounds as potential drugs.

Phosphorus compounds, proteins, nuclease and acid phosphatase activities in isolated spinach chloroplasts

Directory of Open Access Journals (Sweden)

E. Mikulska

2015-01-01

Full Text Available This paper deals with attempts to elaborate a simple method of spinach chloroplast isolation ensuring a high proportion of intact chloroplasts. We obtained 3 preparations of isolated chloroplasts. Several preliminary analyses of the obtained chloroplast fraction were also performed. Phosphorus compounds, total protein and the enzyme activities of RNase, DNase and GPase were determined. We found: 0,36-0,59% of RNA, 0,19-0,24% of DNA, 2,1-2,9% of phospholipids and 26-28% of protein. RNase activity was very high.

Modified expression of several sperm proteins after chronic exposure to the antiandrogenic compound vinclozolin.

Science.gov (United States)

Auger, Jacques; Eustache, Florence; Maceiras, Paula; Broussard, Cédric; Chafey, Philippe; Lesaffre, Corinne; Vaiman, Daniel; Camoin, Luc; Auer, Jana

2010-10-01

Little is known about the molecular impact of in vivo exposure to endocrine disruptors (EDs) on sperm structures and functions. We recently reported that the lifelong exposure of rats to the antiandrogenic compound vinclozolin results in low epididymal weight, changes in sperm kinematic parameters, and immature sperm chromatin condensation, together with the impairment of several fertility end points. These results led us to focus specifically on possible molecular abnormalities in sperm. Sperm samples were recovered from the frozen epididymides of rats exposed during the previous study. The proteins present in the samples from six exposed and six control rats were analyzed in pairs, by two-dimensional fluorescence difference gel electrophoresis, to investigate possible exposure-induced changes to sperm protein profiles. Twelve proteins, from the 380 matched spots observed in at least five gels, were present in larger or smaller amounts after vinclozolin exposure. These proteins were identified by mass spectrometry, and several are known to play a crucial role in the sperm fertilizing ability, among which, two mitochondrial enzymes, malate dehydrogenase 2 and aldehyde dehydrogenase (both of which were present in smaller amounts after treatment) and A-kinase anchor protein 4 (larger amounts of precursor after treatment). Finally, Ingenuity Pathway Analysis revealed highly significant interactions between proteins over- and underexpressed after treatment. This is the first study to show an association between in vivo exposure to an ED and changes to the sperm protein profile. These modifications may be at least partly responsible for the reproductive abnormalities and impaired fertility recently reported in this rat model of vinclozolin exposure.

The Protein Model Portal.

Science.gov (United States)

Arnold, Konstantin; Kiefer, Florian; Kopp, Jürgen; Battey, James N D; Podvinec, Michael; Westbrook, John D; Berman, Helen M; Bordoli, Lorenza; Schwede, Torsten

2009-03-01

Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploration of the protein structure space. One of the challenges in using model information effectively has been to access all models available for a specific protein in heterogeneous formats at different sites using various incompatible accession code systems. Often, structure models for hundreds of proteins can be derived from a given experimentally determined structure, using a variety of established methods. This has been done by all of the PSI centers, and by various independent modeling groups. The goal of the Protein Model Portal (PMP) is to provide a single portal which gives access to the various models that can be leveraged from PSI targets and other experimental protein structures. A single interface allows all existing pre-computed models across these various sites to be queried simultaneously, and provides links to interactive services for template selection, target-template alignment, model building, and quality assessment. The current release of the portal consists of 7.6 million model structures provided by different partner resources (CSMP, JCSG, MCSG, NESG, NYSGXRC, JCMM, ModBase, SWISS-MODEL Repository). The PMP is available at http://www.proteinmodelportal.org and from the PSI Structural Genomics Knowledgebase.

Efficient discovery of responses of proteins to compounds using active learning

Science.gov (United States)

2014-01-01

Background Drug discovery and development has been aided by high throughput screening methods that detect compound effects on a single target. However, when using focused initial screening, undesirable secondary effects are often detected late in the development process after significant investment has been made. An alternative approach would be to screen against undesired effects early in the process, but the number of possible secondary targets makes this prohibitively expensive. Results This paper describes methods for making this global approach practical by constructing predictive models for many target responses to many compounds and using them to guide experimentation. We demonstrate for the first time that by jointly modeling targets and compounds using descriptive features and using active machine learning methods, accurate models can be built by doing only a small fraction of possible experiments. The methods were evaluated by computational experiments using a dataset of 177 assays and 20,000 compounds constructed from the PubChem database. Conclusions An average of nearly 60% of all hits in the dataset were found after exploring only 3% of the experimental space which suggests that active learning can be used to enable more complete characterization of compound effects than otherwise affordable. The methods described are also likely to find widespread application outside drug discovery, such as for characterizing the effects of a large number of compounds or inhibitory RNAs on a large number of cell or tissue phenotypes. PMID:24884564

A Physiologically Based Pharmacokinetic Model to Predict the Pharmacokinetics of Highly Protein-Bound Drugs and Impact of Errors in Plasma Protein Binding

Science.gov (United States)

Ye, Min; Nagar, Swati; Korzekwa, Ken

2015-01-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057

The Protein Model Portal

OpenAIRE

Arnold, Konstantin; Kiefer, Florian; Kopp, J?rgen; Battey, James N. D.; Podvinec, Michael; Westbrook, John D.; Berman, Helen M.; Bordoli, Lorenza; Schwede, Torsten

2008-01-01

Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploratio...

Multivariate-parameter optimization of aroma compound release from carbohydrate-oil-protein model emulsions.

Science.gov (United States)

Samavati, Vahid; D-jomeh, Zahra Emam

2013-11-06

Optimization for retention and partition coefficient of ethyl acetate in emulsion model systems was investigated using response surface methodology in this paper. The effects of emulsion model ingredients, tragacanth gum (TG) (0.5-1 wt%), whey protein isolate (WPI) (2-4 wt%) and oleic acid (5-10%, v/v) on retention and partition coefficient of ethyl acetate were studied using a five-level three-factor central composite rotatable design (CCRD). Results showed that the regression models generated adequately explained the data variation and significantly represented the actual relationships between the independent and response parameters. The results showed that the highest retention (97.20±0.51%) and lowest partition coefficient (4.51±0.13%) of ethyl acetate were reached at the TG concentration 1 wt%, WPI concentration 4 wt% and oleic acid volume fraction 10% (v/v). Copyright © 2013 Elsevier Ltd. All rights reserved.

Reactions of Lignin Model Compounds in Ionic Liquids

Energy Technology Data Exchange (ETDEWEB)

Holladay, John E.; Binder, Joseph B.; Gray, Michel J.; White, James F.; Zhang, Z. Conrad

2009-09-15

Lignin, a readily available form of biomass, awaits novel chemistry for converting it to valuable aromatic chemicals. Recent work has demonstrated that ionic liquids are excellent solvents for processing woody biomass and lignin. Seeking to exploit ionic liquids as media for depolymerization of lignin, we investigated reactions of lignin model compounds in these solvents. Using Brønsted acid catalysts in 1-ethyl-3-methylimidazolium triflate at moderate temperatures, we obtained up to 11.6% yield of the dealkylation product guaiacol from the model compound eugenol and cleaved phenethyl phenyl ether, a model for lignin ethers. Despite these successes, acid catalysis failed in dealkylation of the unsaturated model compound 4-ethylguaiacol and did not produce monomeric products from organosolv lignin, demonstrating that further work is required to understand the complex chemistry of lignin depolymerization.

Behavior of asphaltene model compounds at w/o interfaces.

Science.gov (United States)

Nordgård, Erland L; Sørland, Geir; Sjöblom, Johan

2010-02-16

Asphaltenes, present in significant amounts in heavy crude oil, contains subfractions capable of stabilizing water-in-oil emulsions. Still, the composition of these subfractions is not known in detail, and the actual mechanism behind emulsion stability is dependent on perceived interfacial concentrations and compositions. This study aims at utilizing polyaromatic surfactants which contains an acidic moiety as model compounds for the surface-active subfraction of asphaltenes. A modified pulse-field gradient (PFG) NMR method has been used to study droplet sizes and stability of emulsions prepared with asphaltene model compounds. The method has been compared to the standard microscopy droplet counting method. Arithmetic and volumetric mean droplet sizes as a function of surfactant concentration and water content clearly showed that the interfacial area was dependent on the available surfactant at the emulsion interface. Adsorption of the model compounds onto hydrophilic silica has been investigated by UV depletion, and minor differences in the chemical structure of the model compounds caused significant differences in the affinity toward this highly polar surface. The cross-sectional areas obtained have been compared to areas from the surface-to-volume ratio found by NMR and gave similar results for one of the two model compounds. The mean molecular area for this compound suggested a tilted geometry of the aromatic core with respect to the interface, which has also been proposed for real asphaltenic samples. The film behavior was further investigated using a liquid-liquid Langmuir trough supporting the ability to form stable interfacial films. This study supports that acidic, or strong hydrogen-bonding fractions, can promote stable water-in-oil emulsion. The use of model compounds opens up for studying emulsion behavior and demulsifier efficiency based on true interfacial concentrations rather than perceived interfaces.

Organoselenium compounds prevent hyperphosphorylation of cytoskeletal proteins induced by the neurotoxic agent diphenyl ditelluride in cerebral cortex of young rats

International Nuclear Information System (INIS)

Moretto, M.B.; Funchal, C.; Zeni, G.; Rocha, J.B.T.; Pessoa-Pureur, R.

2005-01-01

In this work we investigated the protective ability of the selenium compounds ebselen and diphenyl diselenide against the effect of diphenyl ditelluride on the in vitro incorporation of 32 P into intermediate filament (IF) proteins from slices of cerebral cortex of 17-day-old rats. We observed that ditelluride in the concentrations of 1, 15 and 50 μM induced hyperphosphorylation of the high-salt Triton insoluble neurofilament subunits (NF-M and NF-L), glial fibrillary acidic protein (GFAP) and vimentin, without altering the immunocontent of these proteins. Concerning the selenium compounds, diselenide (1, 15 and 50 μM) did not induce alteration of the in vitro phosphorylation of the IF proteins. Otherwise, ebselen induced an altered in vitro phosphorylation of the cytoskeletal proteins in a dose-dependent manner. At intermediate concentrations (15 and 30 μM) it increased the in vitro phosphorylation even though, at low (5 μM) or high (50 and 100 μM) concentrations this compound was ineffective in altering the activity of the cytoskeletal-associated phosphorylating system. In addition, 15 μM diselenide and 5 μM ebselen, presented a protective effect against the action of ditelluride, on the phosphorylation of the proteins studied. Considering that hyperphosphorylation of cytoskeletal proteins is associated with neuronal dysfunction and neurodegeneration, it is probable that the effects of ditelluride could be related to the remarkable neurotoxicity of this organic form of tellurium. Furthermore the neuroprotective action of selenium compounds against tellurium effects could be a promising route to be exploited for a possible treatment of organic tellurium poisoning

A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim.

Science.gov (United States)

Niederalt, Christoph; Kuepfer, Lars; Solodenko, Juri; Eissing, Thomas; Siegmund, Hans-Ulrich; Block, Michael; Willmann, Stefan; Lippert, Jörg

2018-04-01

Proteins are an increasingly important class of drugs used as therapeutic as well as diagnostic agents. A generic physiologically based pharmacokinetic (PBPK) model was developed in order to represent at whole body level the fundamental mechanisms driving the distribution and clearance of large molecules like therapeutic proteins. The model was built as an extension of the PK-Sim model for small molecules incorporating (i) the two-pore formalism for drug extravasation from blood plasma to interstitial space, (ii) lymph flow, (iii) endosomal clearance and (iv) protection from endosomal clearance by neonatal Fc receptor (FcRn) mediated recycling as especially relevant for antibodies. For model development and evaluation, PK data was used for compounds with a wide range of solute radii. The model supports the integration of knowledge gained during all development phases of therapeutic proteins, enables translation from pre-clinical species to human and allows predictions of tissue concentration profiles which are of relevance for the analysis of on-target pharmacodynamic effects as well as off-target toxicity. The current implementation of the model replaces the generic protein PBPK model available in PK-Sim since version 4.2 and becomes part of the Open Systems Pharmacology Suite.

The Protein Model Portal--a comprehensive resource for protein structure and model information.

Science.gov (United States)

Haas, Juergen; Roth, Steven; Arnold, Konstantin; Kiefer, Florian; Schmidt, Tobias; Bordoli, Lorenza; Schwede, Torsten

2013-01-01

The Protein Model Portal (PMP) has been developed to foster effective use of 3D molecular models in biomedical research by providing convenient and comprehensive access to structural information for proteins. Both experimental structures and theoretical models for a given protein can be searched simultaneously and analyzed for structural variability. By providing a comprehensive view on structural information, PMP offers the opportunity to apply consistent assessment and validation criteria to the complete set of structural models available for proteins. PMP is an open project so that new methods developed by the community can contribute to PMP, for example, new modeling servers for creating homology models and model quality estimation servers for model validation. The accuracy of participating modeling servers is continuously evaluated by the Continuous Automated Model EvaluatiOn (CAMEO) project. The PMP offers a unique interface to visualize structural coverage of a protein combining both theoretical models and experimental structures, allowing straightforward assessment of the model quality and hence their utility. The portal is updated regularly and actively developed to include latest methods in the field of computational structural biology. Database URL: http://www.proteinmodelportal.org.

The Protein Model Portal—a comprehensive resource for protein structure and model information

Science.gov (United States)

Haas, Juergen; Roth, Steven; Arnold, Konstantin; Kiefer, Florian; Schmidt, Tobias; Bordoli, Lorenza; Schwede, Torsten

2013-01-01

The Protein Model Portal (PMP) has been developed to foster effective use of 3D molecular models in biomedical research by providing convenient and comprehensive access to structural information for proteins. Both experimental structures and theoretical models for a given protein can be searched simultaneously and analyzed for structural variability. By providing a comprehensive view on structural information, PMP offers the opportunity to apply consistent assessment and validation criteria to the complete set of structural models available for proteins. PMP is an open project so that new methods developed by the community can contribute to PMP, for example, new modeling servers for creating homology models and model quality estimation servers for model validation. The accuracy of participating modeling servers is continuously evaluated by the Continuous Automated Model EvaluatiOn (CAMEO) project. The PMP offers a unique interface to visualize structural coverage of a protein combining both theoretical models and experimental structures, allowing straightforward assessment of the model quality and hence their utility. The portal is updated regularly and actively developed to include latest methods in the field of computational structural biology. Database URL: http://www.proteinmodelportal.org PMID:23624946

Testing the compounding structure of the CP-INARCH model

OpenAIRE

Weiß, Christian H.; Gonçalves, Esmeralda; Lopes, Nazaré Mendes

2017-01-01

A statistical test to distinguish between a Poisson INARCH model and a Compound Poisson INARCH model is proposed, based on the form of the probability generating function of the compounding distribution of the conditional law of the model. For first-order autoregression, the normality of the test statistics’ asymptotic distribution is established, either in the case where the model parameters are specified, or when such parameters are consistently estimated. As the test statistics’ law involv...

A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

Science.gov (United States)

Ye, Min; Nagar, Swati; Korzekwa, Ken

2016-04-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Changes in volatile compounds in whey protein concentrate stored at elevated temperature and humidity

Science.gov (United States)

Whey protein concentrate (WPC) has been recommended for use in emergency aid programs, but it is often stored overseas without temperature and relative humidity (RH) control, which may cause it to be rejected because of yellowing, off-flavors, or clumping. Therefore, the volatile compounds present ...

The PMDB Protein Model Database

Science.gov (United States)

Castrignanò, Tiziana; De Meo, Paolo D'Onorio; Cozzetto, Domenico; Talamo, Ivano Giuseppe; Tramontano, Anna

2006-01-01

The Protein Model Database (PMDB) is a public resource aimed at storing manually built 3D models of proteins. The database is designed to provide access to models published in the scientific literature, together with validating experimental data. It is a relational database and it currently contains >74 000 models for ∼240 proteins. The system is accessible at and allows predictors to submit models along with related supporting evidence and users to download them through a simple and intuitive interface. Users can navigate in the database and retrieve models referring to the same target protein or to different regions of the same protein. Each model is assigned a unique identifier that allows interested users to directly access the data. PMID:16381873

Modeling Compound Flood Hazards in Coastal Embayments

Science.gov (United States)

Moftakhari, H.; Schubert, J. E.; AghaKouchak, A.; Luke, A.; Matthew, R.; Sanders, B. F.

2017-12-01

Coastal cities around the world are built on lowland topography adjacent to coastal embayments and river estuaries, where multiple factors threaten increasing flood hazards (e.g. sea level rise and river flooding). Quantitative risk assessment is required for administration of flood insurance programs and the design of cost-effective flood risk reduction measures. This demands a characterization of extreme water levels such as 100 and 500 year return period events. Furthermore, hydrodynamic flood models are routinely used to characterize localized flood level intensities (i.e., local depth and velocity) based on boundary forcing sampled from extreme value distributions. For example, extreme flood discharges in the U.S. are estimated from measured flood peaks using the Log-Pearson Type III distribution. However, configuring hydrodynamic models for coastal embayments is challenging because of compound extreme flood events: events caused by a combination of extreme sea levels, extreme river discharges, and possibly other factors such as extreme waves and precipitation causing pluvial flooding in urban developments. Here, we present an approach for flood risk assessment that coordinates multivariate extreme analysis with hydrodynamic modeling of coastal embayments. First, we evaluate the significance of correlation structure between terrestrial freshwater inflow and oceanic variables; second, this correlation structure is described using copula functions in unit joint probability domain; and third, we choose a series of compound design scenarios for hydrodynamic modeling based on their occurrence likelihood. The design scenarios include the most likely compound event (with the highest joint probability density), preferred marginal scenario and reproduced time series of ensembles based on Monte Carlo sampling of bivariate hazard domain. The comparison between resulting extreme water dynamics under the compound hazard scenarios explained above provides an insight to the

Double generalized linear compound poisson models to insurance claims data

DEFF Research Database (Denmark)

Andersen, Daniel Arnfeldt; Bonat, Wagner Hugo

2017-01-01

This paper describes the specification, estimation and comparison of double generalized linear compound Poisson models based on the likelihood paradigm. The models are motivated by insurance applications, where the distribution of the response variable is composed by a degenerate distribution...... implementation and illustrate the application of double generalized linear compound Poisson models using a data set about car insurances....

High Throughput, Label-free Screening Small Molecule Compound Libraries for Protein-Ligands using Combination of Small Molecule Microarrays and a Special Ellipsometry-based Optical Scanner.

Science.gov (United States)

Landry, James P; Fei, Yiyan; Zhu, X D

2011-12-01

Small-molecule compounds remain the major source of therapeutic and preventative drugs. Developing new drugs against a protein target often requires screening large collections of compounds with diverse structures for ligands or ligand fragments that exhibit sufficiently affinity and desirable inhibition effect on the target before further optimization and development. Since the number of small molecule compounds is large, high-throughput screening (HTS) methods are needed. Small-molecule microarrays (SMM) on a solid support in combination with a suitable binding assay form a viable HTS platform. We demonstrate that by combining an oblique-incidence reflectivity difference optical scanner with SMM we can screen 10,000 small-molecule compounds on a single glass slide for protein ligands without fluorescence labeling. Furthermore using such a label-free assay platform we can simultaneously acquire binding curves of a solution-phase protein to over 10,000 immobilized compounds, thus enabling full characterization of protein-ligand interactions over a wide range of affinity constants.

Identification and quantification of major maillard cross-links in human serum albumin and lens protein. Evidence for glucosepane as the dominant compound.

Science.gov (United States)

Biemel, Klaus M; Friedl, D Alexander; Lederer, Markus O

2002-07-12

Glycation reactions leading to protein modifications (advanced glycation end products) contribute to various pathologies associated with the general aging process and long term complications of diabetes. However, only few relevant compounds have so far been detected in vivo. We now report on the first unequivocal identification of the lysine-arginine cross-links glucosepane 5, DOGDIC 6, MODIC 7, and GODIC 8 in human material. For their accurate quantification by coupled liquid chromatography-electrospray ionization mass spectrometry, (13)C-labeled reference compounds were synthesized independently. Compounds 5-8 are formed via the alpha-dicarbonyl compounds N(6)-(2,3-dihydroxy-5,6-dioxohexyl)-l-lysinate (1a,b), 3-deoxyglucosone (), methylglyoxal (), and glyoxal (), respectively. The protein-bound dideoxyosone 1a,b seems to be of prime significance for cross-linking because it presumably is not detoxified by mammalian enzymes as readily as 2-4. Hence, the follow-up product glucosepane 5 was found to be the dominant compound. Up to 42.3 pmol of 5/mg of protein was identified in human serum albumin of diabetics; the level of 5 correlates markedly with the glycated hemoglobin HbA(1c). In the water-insoluble fraction of lens proteins from normoglycemics, concentration of 5 ranges between 132.3 and 241.7 pmol/mg. The advanced glycoxidation end product GODIC 8 is elevated significantly in brunescent lenses, indicating enhanced oxidative stress in this material. Compounds 5-8 thus appear predestined as markers for pathophysiological processes.

Statistical molecular design of balanced compound libraries for QSAR modeling.

Science.gov (United States)

Linusson, A; Elofsson, M; Andersson, I E; Dahlgren, M K

2010-01-01

A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.

Protein interactions in genome maintenance as novel antibacterial targets.

Directory of Open Access Journals (Sweden)

Aimee H Marceau

Full Text Available Antibacterial compounds typically act by directly inhibiting essential bacterial enzyme activities. Although this general mechanism of action has fueled traditional antibiotic discovery efforts for decades, new antibiotic development has not kept pace with the emergence of drug resistant bacterial strains. These limitations have severely restricted the therapeutic tools available for treating bacterial infections. Here we test an alternative antibacterial lead-compound identification strategy in which essential protein-protein interactions are targeted rather than enzymatic activities. Bacterial single-stranded DNA-binding proteins (SSBs form conserved protein interaction "hubs" that are essential for recruiting many DNA replication, recombination, and repair proteins to SSB/DNA nucleoprotein substrates. Three small molecules that block SSB/protein interactions are shown to have antibacterial activity against diverse bacterial species. Consistent with a model in which the compounds target multiple SSB/protein interactions, treatment of Bacillus subtilis cultures with the compounds leads to rapid inhibition of DNA replication and recombination, and ultimately to cell death. The compounds also have unanticipated effects on protein synthesis that could be due to a previously unknown role for SSB/protein interactions in translation or to off-target effects. Our results highlight the potential of targeting protein-protein interactions, particularly those that mediate genome maintenance, as a powerful approach for identifying new antibacterial compounds.

Molecular profiling of signalling proteins for effects induced by the anti-cancer compound GSAO with 400 antibodies

International Nuclear Information System (INIS)

Cadd, Verity A; Hogg, Philip J; Harris, Adrian L; Feller, Stephan M

2006-01-01

GSAO (4-[N-[S-glutathionylacetyl]amino] phenylarsenoxide) is a hydrophilic derivative of the protein tyrosine phosphatase inhibitor phenylarsine oxide (PAO). It inhibits angiogenesis and tumour growth in mouse models and may be evaluated in a phase I clinical trial in the near future. Initial experiments have implicated GSAO in perturbing mitochondrial function. Other molecular effects of GSAO in human cells, for example on the phosphorylation of proteins, are still largely unknown. Peripheral white blood cells (PWBC) from healthy volunteers were isolated and used to profile effects of GSAO vs. a control compound, GSCA. Changes in site-specific phosphorylations, other protein modifications and expression levels of many signalling proteins were analysed using more than 400 different antibodies in Western blots. PWBC were initially cultured in low serum conditions, with the aim to reduce basal protein phosphorylation and to increase detection sensitivity. Under these conditions pleiotropic intracellular signalling protein changes were induced by GSAO. Subsequently, PWBC were cultured in 100% donor serum to reflect more closely in vivo conditions. This eliminated detectable GSAO effects on most, but not all signalling proteins analysed. Activation of the MAP kinase Erk2 was still observed and the paxillin homologue Hic-5 still displayed a major shift in protein mobility upon GSAO-treatment. A GSAO induced change in Hic-5 mobility was also found in endothelial cells, which are thought to be the primary target of GSAO in vivo. Serum conditions greatly influence the molecular activity profile of GSAO in vitro. Low serum culture, which is typically used in experiments analysing protein phosphorylation, is not suitable to study GSAO activity in cells. The signalling proteins affected by GSAO under high serum conditions are candidate surrogate markers for GSAO bioactivity in vivo and can be analysed in future clinical trials. GSAO effects on Hic-5 in endothelial cells may

A Novel Benzodiazepine Compound Inhibits Yellow Fever Virus Infection by Specifically Targeting NS4B Protein.

Science.gov (United States)

Guo, Fang; Wu, Shuo; Julander, Justin; Ma, Julia; Zhang, Xuexiang; Kulp, John; Cuconati, Andrea; Block, Timothy M; Du, Yanming; Guo, Ju-Tao; Chang, Jinhong

2016-09-21

-risk regions. It has been estimated that up to 1.7 million YFV infections occur in Africa each year, resulting in 29,000 to 60,000 death. Thus far, there is no specific antiviral treatment for yellow fever. To cope with this medical challenge, we identified a benzodiazepine compound that selectively inhibits YFV by targeting the viral NS4B protein. To our knowledge, this is the first report demonstrating in vivo safety and antiviral efficacy of an YFV NS4B inhibitor in an animal model. We have thus reached a critical milestone toward the development of specific antiviral therapeutics for clinical management of yellow fever. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Molecular screening of compounds to the predicted Protein-Protein Interaction site of Rb1-E7 with p53- E6 in HPV

Science.gov (United States)

Shaikh, Faraz; Sanehi, Parvish; Rawal, Rakesh

2012-01-01

Cervical cancer is malignant neoplasm of the cervix uteri or cervical area. Human Papillomaviruses (HPVs) which are heterogeneous groups of small double stranded DNA viruses are considered as the primary cause of cervical cancer, involved in 90% of all Cervical Cancers. Two early HPV genes, E6 and E7, are known to play crucial role in tumor formation. E6 binds with p53 and prevents its translocation and thereby inhibit the ability of p53 to activate or repress target genes. E7 binds to hypophosphorylated Rb and thereby induces cells to enter into premature S-phase by disrupting Rb-E2F complexes. The strategy of the research work was to target the site of interaction of Rb1 -E7 & p53-E6. A total of 88 compounds were selected for molecular screening, based on comprehensive literature survey for natural compounds with anti-cancer activity. Molecular docking analysis was carried out with Molegro Virtual Docker, to screen the 88 chosen compounds and rank them according to their binding affinity towards the site of interaction of the viral oncoproteins and human tumor suppressor proteins. The docking result revealed that Nicandrenone a member of Withanolides family of chemical compounds as the most likely molecule that can be used as a candidate drug against HPV induced cervical cancer. Abbreviations HPV - Human Papiloma Virus, HTSP - Human Tumor Suppressor Proteins, VOP - Viral oncoproteins. PMID:22829740

Photolytic inhibition and labeling of proteins with aryl diazonium compounds

International Nuclear Information System (INIS)

Tometsko, A.M.; Turula, J.; Comstock, J.

1978-01-01

In the course of preparing aryl azide derivatives for use as photoprobes, we have observed significant light sensitivity in the precursor aryl diazonium compounds. The photosensitive properties of this class of compounds are of interest since they will seek out cationic binding sites in biological targets, and can be employed to inhibit complementary targets at acid pH. The relationship between photolytic change in the structure of diazonium compounds and the corresponding change in function of a biological target are presented. Experiments are described in which the dark and light sensitive properties of a model diazonium compound, diazobenzene sulfonate (DBS), were determined. The ultraviolet spectra were used to evaluate the dark stability and light sensitivity og DBS. Chymotrypsin and trypsin served as functioning targets for further evaluation of the photochemical properties. Both enzymes are stable to the probe in the dark at acid pH. A rapid loss of enzyme activity was observed following flash photolysis of DBS-enzyme solutions. Photolytic incorporation of radioactive DBS into chymotrypsin was observed. Aryl diazonium salts can be employed to probe the availability of complementary sites in biological targets at different acid pH values. (Author)

Fruit tree model for uptake of organic compounds from soil

DEFF Research Database (Denmark)

Trapp, Stefan; Rasmussen, D.; Samsoe-Petersen, L.

2003-01-01

-state, and an example calculation is given. The Fruit Tree Model is compared to the empirical equation of Travis and Arms (T&A), and to results from fruits, collected in contaminated areas. For polar compounds, both T&A and the Fruit Tree Model predict bioconcentration factors fruit to soil (BCF, wet weight based......) of > 1. No empirical data are available to support this prediction. For very lipophilic compounds (log K-OW > 5), T&A overestimates the uptake. The conclusion from the Fruit Tree Model is that the transfer of lipophilic compounds into fruits is not relevant. This was also found by an empirical study...... with PCDD/F. According to the Fruit Tree Model, polar chemicals are transferred efficiently into fruits, but empirical data to verify these predictions are lacking....

Effect of Dietary Protein Levels on Composition of Odorous Compounds and Bacterial Ecology in Pig Manure

Directory of Open Access Journals (Sweden)

Sungback Cho

2015-09-01

Full Text Available This study was performed to investigate the effect of different levels of dietary crude protein (CP on composition of odorous compounds and bacterial communities in pig manure. A total of 48 male pigs (average initial body weight 45 kg fed diets containing three levels of dietary CP (20%, 17.5%, and 15% and their slurry samples were collected from the pits under the floor every week for one month. Changes in composition of odorous compounds and bacterial communities were analyzed by gas chromatography and 454 FLX titanium pyrosequencing systems, respectively. Levels of phenols, indoles, short chain fatty acid and branched chain fatty acid were lowest (p<0.05 in CP 15% group among three CP levels. Relative abundance of Bacteroidetes phylum and bacterial genera including Leuconostoc, Bacillus, Atopostipes, Peptonphilus, Ruminococcaceae_uc, Bacteroides, and Pseudomonas was lower (p<0.05 in CP 15% than in CP 20% group. There was a positive correlation (p<0.05 between odorous compounds and bacterial genera: phenol, indole, iso-butyric acid, and iso-valeric acid with Atopostipes, p-cresol and skatole with Bacteroides, acetic acid and butyric acid with AM982595_g of Porphyromonadaceae family, and propionic acid with Tissierella. Taken together, administration of 15% CP showed less production of odorous compounds than 20% CP group and this result might be associated with the changes in bacterial communities especially whose roles in protein metabolism.

Discovery of a novel compound with anti-venezuelan equine encephalitis virus activity that targets the nonstructural protein 2.

Directory of Open Access Journals (Sweden)

Dong-Hoon Chung

2014-06-01

Full Text Available Alphaviruses present serious health threats as emerging and re-emerging viruses. Venezuelan equine encephalitis virus (VEEV, a New World alphavirus, can cause encephalitis in humans and horses, but there are no therapeutics for treatment. To date, compounds reported as anti-VEEV or anti-alphavirus inhibitors have shown moderate activity. To discover new classes of anti-VEEV inhibitors with novel viral targets, we used a high-throughput screen based on the measurement of cell protection from live VEEV TC-83-induced cytopathic effect to screen a 340,000 compound library. Of those, we identified five novel anti-VEEV compounds and chose a quinazolinone compound, CID15997213 (IC50 = 0.84 µM, for further characterization. The antiviral effect of CID15997213 was alphavirus-specific, inhibiting VEEV and Western equine encephalitis virus, but not Eastern equine encephalitis virus. In vitro assays confirmed inhibition of viral RNA, protein, and progeny synthesis. No antiviral activity was detected against a select group of RNA viruses. We found mutations conferring the resistance to the compound in the N-terminal domain of nsP2 and confirmed the target residues using a reverse genetic approach. Time of addition studies showed that the compound inhibits the middle stage of replication when viral genome replication is most active. In mice, the compound showed complete protection from lethal VEEV disease at 50 mg/kg/day. Collectively, these results reveal a potent anti-VEEV compound that uniquely targets the viral nsP2 N-terminal domain. While the function of nsP2 has yet to be characterized, our studies suggest that the protein might play a critical role in viral replication, and further, may represent an innovative opportunity to develop therapeutic interventions for alphavirus infection.

Rapid Diminution in the Level and Activity of DNA-Dependent Protein Kinase in Cancer Cells by a Reactive Nitro-Benzoxadiazole Compound

Directory of Open Access Journals (Sweden)

Viviane A. O. Silva

2016-05-01

Full Text Available The expression and activity of DNA-dependent protein kinase (DNA-PK is related to DNA repair status in the response of cells to exogenous and endogenous factors. Recent studies indicate that Epidermal Growth Factor Receptor (EGFR is involved in modulating DNA-PK. It has been shown that a compound 4-nitro-7-[(1-oxidopyridin-2-ylsulfanyl]-2,1,3-benzoxadiazole (NSC, bearing a nitro-benzoxadiazole (NBD scaffold, enhances tyrosine phosphorylation of EGFR and triggers downstream signaling pathways. Here, we studied the behavior of DNA-PK and other DNA repair proteins in prostate cancer cells exposed to compound NSC. We showed that both the expression and activity of DNA-PKcs (catalytic subunit of DNA-PK rapidly decreased upon exposure of cells to the compound. The decline in DNA-PKcs was associated with enhanced protein ubiquitination, indicating the activation of cellular proteasome. However, pretreatment of cells with thioglycerol abolished the action of compound NSC and restored the level of DNA-PKcs. Moreover, the decreased level of DNA-PKcs was associated with the production of intracellular hydrogen peroxide by stable dimeric forms of Cu/Zn SOD1 induced by NSC. Our findings indicate that reactive oxygen species and electrophilic intermediates, generated and accumulated during the redox transformation of NBD compounds, are primarily responsible for the rapid modulation of DNA-PKcs functions in cancer cells.

Photoreactivity of biologically active compounds. VIII. Photosensitized polymerization of lens proteins by antimalarial drugs in vitro.

Science.gov (United States)

Kristensen, S; Wang, R H; Tønnesen, H H; Dillon, J; Roberts, J E

1995-02-01

The drugs commonly used in the treatment of malaria are photochemically unstable. Several of these compounds cause dermal and ocular toxic reactions that may be light induced. The in vitro photopolymerization of calf lens proteins in the presence of antimalarial drugs was studied as part of a screening of the photochemical properties and phototoxic capabilities of these compounds. The pseudo-first-order rate constant for the reaction was calculated, and related to the amount of light absorbed by the compounds in order to determine the relative photosensitizing effect of each drug. The reaction mechanisms were evaluated by adding a variety of quenchers to the reaction medium during irradiation. Based on the results obtained in this study and previous knowledge about the pharmacokinetic behavior of these compounds, several of the drugs investigated have to be considered as potential photosensitizers in the human lens, the retina and the skin.

Multivariate characterisation and quantitative structure-property relationship modelling of nitroaromatic compounds

Energy Technology Data Exchange (ETDEWEB)

Joensson, S. [Man-Technology-Environment Research Centre, Department of Natural Sciences, Orebro University, 701 82 Orebro (Sweden)], E-mail: sofie.jonsson@nat.oru.se; Eriksson, L.A. [Department of Natural Sciences and Orebro Life Science Center, Orebro University, 701 82 Orebro (Sweden); Bavel, B. van [Man-Technology-Environment Research Centre, Department of Natural Sciences, Orebro University, 701 82 Orebro (Sweden)

2008-07-28

A multivariate model to characterise nitroaromatics and related compounds based on molecular descriptors was calculated. Descriptors were collected from literature and through empirical, semi-empirical and density functional theory-based calculations. Principal components were used to describe the distribution of the compounds in a multidimensional space. Four components described 76% of the variation in the dataset. PC1 separated the compounds due to molecular weight, PC2 separated the different isomers, PC3 arranged the compounds according to different functional groups such as nitrobenzoic acids, nitrobenzenes, nitrotoluenes and nitroesters and PC4 differentiated the compounds containing chlorine from other compounds. Quantitative structure-property relationship models were calculated using partial least squares (PLS) projection to latent structures to predict gas chromatographic (GC) retention times and the distribution between the water phase and air using solid-phase microextraction (SPME). GC retention time was found to be dependent on the presence of polar amine groups, electronic descriptors including highest occupied molecular orbital, dipole moments and the melting point. The model of GC retention time was good, but the precision was not precise enough for practical use. An important environmental parameter was measured using SPME, the distribution between headspace (air) and the water phase. This parameter was mainly dependent on Henry's law constant, vapour pressure, log P, content of hydroxyl groups and atmospheric OH rate constant. The predictive capacity of the model substantially improved when recalculating a model using these five descriptors only.

Stochastic interest rates model in compounding | Galadima ...

African Journals Online (AJOL)

Stochastic interest rates model in compounding. ... in finance, real estate, insurance, accounting and other areas of business administration. The assumption that future rates are fixed and known with certainty at the beginning of an investment, ...

AMPK modulatory activity of olive–tree leaves phenolic compounds: Bioassay-guided isolation on adipocyte model and in silico approach

Science.gov (United States)

Jiménez-Sánchez, Cecilia; Olivares-Vicente, Mariló; Rodríguez-Pérez, Celia; Herranz-López, María; Lozano-Sánchez, Jesús; Segura-Carretero, Antonio; Fernández-Gutiérrez, Alberto; Encinar, José Antonio; Micol, Vicente

2017-01-01

Scope Olive-tree polyphenols have demonstrated potential for the management of obesity-related pathologies. We aimed to explore the capacity of Olive-tree leaves extract to modulate triglyceride accumulation and AMP-activated protein kinase activity (AMPK) on a hypertrophic adipocyte model. Methods Intracellular triglycerides and AMPK activity were measured on the hypertrophic 3T3-L1 adipocyte model by AdipoRed and immunofluorescence microscopy, respectively. Reverse phase high performance liquid chromatography coupled to time-of-flight mass detection with electrospray ionization (RP-HPLC-ESI-TOF/MS) was used for the fractionation of the extract and the identification of the compounds. In-silico molecular docking of the AMPK alpha-2, beta and gamma subunits with the identified compounds was performed. Results Olive-tree leaves extract decreased the intracellular lipid accumulation through AMPK-dependent mechanisms in hypertrophic adipocytes. Secoiridoids, cinnamic acids, phenylethanoids and phenylpropanoids, flavonoids and lignans were the candidates predicted to account for this effect. Molecular docking revealed that some compounds may be AMPK-gamma modulators. The modulatory effects of compounds over the alpha and beta AMPK subunits appear to be less probable. Conclusions Olive-tree leaves polyphenols modulate AMPK activity, which may become a therapeutic aid in the management of obesity-associated disturbances. The natural occurrence of these compounds may have important nutritional implications for the design of functional ingredients. PMID:28278224

using stereochemistry models in teaching organic compounds

African Journals Online (AJOL)

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The purpose of the study was to find out the effect of stereochemistry models on students' ... consistent with the names given to organic compounds. Some of ... Considering class level, what is the performance of the students in naming organic.

Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining

Directory of Open Access Journals (Sweden)

Samer Haidar

2017-01-01

Full Text Available Protein kinase CK2, initially designated as casein kinase 2, is an ubiquitously expressed serine/threonine kinase. This enzyme, implicated in many cellular processes, is highly expressed and active in many tumor cells. A large number of compounds has been developed as inhibitors comprising different backbones. Beside others, structures with an indeno[1,2-b]indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors of human protein kinase CK2, we report here on the generation of common feature pharmacophore model to further explain the binding requirements for human CK2 inhibitors. Nine common chemical features of indeno[1,2-b]indole-type CK2 inhibitors were determined using MOE software (Chemical Computing Group, Montreal, Canada. This pharmacophore model was used for database mining with the aim to identify novel scaffolds for developing new potent and selective CK2 inhibitors. Using this strategy several structures were selected by searching inside the ZINC compound database. One of the selected compounds was bikaverin (6,11-dihydroxy-3,8-dimethoxy-1-methylbenzo[b]xanthene-7,10,12-trione, a natural compound which is produced by several kinds of fungi. This compound was tested on human recombinant CK2 and turned out to be an active inhibitor with an IC50 value of 1.24 µM.

Preparation, aroma characteristics and volatile compounds of flavorings from enzymatic hydrolyzed rice bran protein concentrate.

Science.gov (United States)

Arsa, Supeeraya; Theerakulkait, Chockchai

2018-02-19

Rice bran is a by-product obtained from the rice milling industry. The aims of this research were to add value to rice bran by preparation of enzymatic hydrolyzed rice bran protein concentrate (HRPC) as a flavoring agent and the flavoring which was produced by HRPC has not been investigated. Different drying methods (freeze-drying and spray-drying) and fructose additions were studied for improvement of rice bran protein sensorial aroma characteristics. The most abundant amino acids in liquid HRPC (LH) were glutamic acid, arginine, aspartic acid and leucine. The intensity of desirable aromas, such as cereal-like, nut-like, milk-powder-like, sweet, and cocoa-like aroma, were higher in spray-dried HRPC powder (SHP) than in LH and freeze-dried HRPC. Volatile compounds, such as aldehydes, pyrazines and ketones, were significantly increased in HRPC powders in which fructose was added before spray-drying (SHP-F). Higher amounts of 2-methylbutanal, 3-methylbutanal, phenylacetaldehyde, 2,5-dimethylpyrazine, vanillin, 2-acetylpyrrole and maltol were detected in SHP-F. Moreover, these compounds had high odor active values, which accounted for the cocoa-like, sweet, nut-like, and milk-powder-like characteristics of SHP-F. These findings could lead to the creation of desirable aroma characteristics of rice bran protein concentrate by different preparation methods. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Mathematical modeling of atmospheric fine particle-associated primary organic compound concentrations

Science.gov (United States)

Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

1996-08-01

An atmospheric transport model has been used to explore the relationship between source emissions and ambient air quality for individual particle phase organic compounds present in primary aerosol source emissions. An inventory of fine particulate organic compound emissions was assembled for the Los Angeles area in the year 1982. Sources characterized included noncatalyst- and catalyst-equipped autos, diesel trucks, paved road dust, tire wear, brake lining dust, meat cooking operations, industrial oil-fired boilers, roofing tar pots, natural gas combustion in residential homes, cigarette smoke, fireplaces burning oak and pine wood, and plant leaf abrasion products. These primary fine particle source emissions were supplied to a computer-based model that simulates atmospheric transport, dispersion, and dry deposition based on the time series of hourly wind observations and mixing depths. Monthly average fine particle organic compound concentrations that would prevail if the primary organic aerosol were transported without chemical reaction were computed for more than 100 organic compounds within an 80 km × 80 km modeling area centered over Los Angeles. The monthly average compound concentrations predicted by the transport model were compared to atmospheric measurements made at monitoring sites within the study area during 1982. The predicted seasonal variation and absolute values of the concentrations of the more stable compounds are found to be in reasonable agreement with the ambient observations. While model predictions for the higher molecular weight polycyclic aromatic hydrocarbons (PAH) are in agreement with ambient observations, lower molecular weight PAH show much higher predicted than measured atmospheric concentrations in the particle phase, indicating atmospheric decay by chemical reactions or evaporation from the particle phase. The atmospheric concentrations of dicarboxylic acids and aromatic polycarboxylic acids greatly exceed the contributions that

Completion of autobuilt protein models using a database of protein fragments

International Nuclear Information System (INIS)

Cowtan, Kevin

2012-01-01

Two developments in the process of automated protein model building in the Buccaneer software are described: the use of a database of protein fragments in improving the model completeness and the assembly of disconnected chain fragments into complete molecules. Two developments in the process of automated protein model building in the Buccaneer software are presented. A general-purpose library for protein fragments of arbitrary size is described, with a highly optimized search method allowing the use of a larger database than in previous work. The problem of assembling an autobuilt model into complete chains is discussed. This involves the assembly of disconnected chain fragments into complete molecules and the use of the database of protein fragments in improving the model completeness. Assembly of fragments into molecules is a standard step in existing model-building software, but the methods have not received detailed discussion in the literature

Semi classical model of the neutron resonance compound nucleus

International Nuclear Information System (INIS)

Ohkubo, Makio

1995-01-01

A Semi-classical model of compound nucleus is developed, where time evolution and recurrence for many degrees of freedom (oscillators) excited simultaneously are explicitly considered. The effective number of oscillators plays the role in the compound nucleus, and the nuclear temperatures are derived, which are in good agreement with the traditional values. Time structures of the compound nucleus at resonance are considered, from which equidistant level series with an envelope of strength function of giant resonance nature is obtained. S-matrix formulation for fine structure resonance is derived. (author)

Superior bactericidal activity of N-bromine compounds compared to their N-chlorine analogues can be reversed under protein load.

Science.gov (United States)

Gottardi, W; Klotz, S; Nagl, M

2014-06-01

To investigate and compare the bactericidal activity (BA) of active bromine and chlorine compounds in the absence and presence of protein load. Quantitative killing tests against Escherichia coli and Staphylococcus aureus were performed both in the absence and in the presence of peptone with pairs of isosteric active chlorine and bromine compounds: hypochlorous and hypobromous acid (HOCl and HOBr), dichloro- and dibromoisocyanuric acid, chlorantine and bromantine (1,3-dibromo- and 1,3 dichloro-5,5-dimethylhydantoine), chloramine T and bromamine T (N-chloro- and N-bromo-4-methylbenzenesulphonamide sodium), and N-chloro- and N-bromotaurine sodium. To classify the bactericidal activities on a quantitative basis, an empirical coefficient named specific bactericidal activity (SBA), founded on the parameters of killing curves, was defined: SBA= mean log reductions/(mean exposure times x concentration) [mmol 1(-1) min (-1)]. In the absence of peptone, tests with washed micro-organisms revealed a throughout higher BA of bromine compounds with only slight differences between single substances. This was in contrast to chlorine compounds, whose killing times differed by a factor of more than four decimal powers. As a consequence, also the isosteric pairs showed according differences. In the presence of peptone, however, bromine compounds showed an increased loss of BA, which partly caused a reversal of efficacy within isosteric pairs. In medical practice, weakly oxidizing active chlorine compounds like chloramines have the highest potential as topical anti-infectives in the presence of proteinaceous material (mucous membranes, open wounds). Active bromine compounds, on the other hand, have their chance at insensitive body regions with low organic matter, for example skin surfaces. The expected protein load is one of the most important parameters for selection of a suited active halogen compound. © 2014 The Society for Applied Microbiology.

Fate modelling of chemical compounds with incomplete data sets

DEFF Research Database (Denmark)

Birkved, Morten; Heijungs, Reinout

2011-01-01

Impact assessment of chemical compounds in Life Cycle Impact Assessment (LCIA) and Environmental Risk Assessment (ERA) requires a vast amount of data on the properties of the chemical compounds being assessed. These data are used in multi-media fate and exposure models, to calculate risk levels...... in an approximate way. The idea is that not all data needed in a multi-media fate and exposure model are completely independent and equally important, but that there are physical-chemical and biological relationships between sets of chemical properties. A statistical model is constructed to underpin this assumption...... and other indicators. ERA typically addresses one specific chemical, but in an LCIA, the number of chemicals encountered may be quite high, up to hundreds or thousands. This study explores the development of meta-models, which are supposed to reflect the “true”multi-media fate and exposure model...

Development and optimization of a cell-based assay for the selection of synthetic compounds that potentiate bone morphogenetic protein-2 activity.

Science.gov (United States)

Okada, Motohiro; Sangadala, Sreedhara; Liu, Yunshan; Yoshida, Munehito; Reddy, Boojala Vijay B; Titus, Louisa; Boden, Scott D

2009-12-01

reliability of our cell-based assay. Direct delivery of synthesized protein can be limited by high cost, instability or inadequate post-translational modifications. Thus, there would be a clear benefit for a low cost, cell penetrable chemical compound. We successfully used our gene expression-based assay to choose an active compound from a select group of compounds that were identified by computational screenings as the most likely candidates for mimicking the function of LMP-1. Among them, we selected SVAK-3, a compound that showed a dose-dependent potentiation of BMP-2 activity in inducing osteoblastic differentiation of C2C12 cells. We show that either the full length LMP-1 protein or its potential mimetic compound consistently exhibit similar potentiation of BMP-2 activity even when multiple markers of the osteoblastic phenotype were parallely monitored.

Classification of Beta-lactamases and penicillin binding proteins using ligand-centric network models.

Directory of Open Access Journals (Sweden)

Hakime Öztürk

Full Text Available β-lactamase mediated antibiotic resistance is an important health issue and the discovery of new β-lactam type antibiotics or β-lactamase inhibitors is an area of intense research. Today, there are about a thousand β-lactamases due to the evolutionary pressure exerted by these ligands. While β-lactamases hydrolyse the β-lactam ring of antibiotics, rendering them ineffective, Penicillin-Binding Proteins (PBPs, which share high structural similarity with β-lactamases, also confer antibiotic resistance to their host organism by acquiring mutations that allow them to continue their participation in cell wall biosynthesis. In this paper, we propose a novel approach to include ligand sharing information for classifying and clustering β-lactamases and PBPs in an effort to elucidate the ligand induced evolution of these β-lactam binding proteins. We first present a detailed summary of the β-lactamase and PBP families in the Protein Data Bank, as well as the compounds they bind to. Then, we build two different types of networks in which the proteins are represented as nodes, and two proteins are connected by an edge with a weight that depends on the number of shared identical or similar ligands. These models are analyzed under three different edge weight settings, namely unweighted, weighted, and normalized weighted. A detailed comparison of these six networks showed that the use of ligand sharing information to cluster proteins resulted in modules comprising proteins with not only sequence similarity but also functional similarity. Consideration of ligand similarity highlighted some interactions that were not detected in the identical ligand network. Analysing the β-lactamases and PBPs using ligand-centric network models enabled the identification of novel relationships, suggesting that these models can be used to examine other protein families to obtain information on their ligand induced evolutionary paths.

An elemental model of retrospective revaluation without within-compound associations.

Science.gov (United States)

Connor, Patrick C; Lolordo, Vincent M; Trappenberg, Thomas P

2014-03-01

When retrospective revaluation phenomena (e.g., unovershadowing: AB+, then A-, then test B) were discovered, simple elemental models were at a disadvantage because they could not explain such phenomena. Extensions of these models and novel models appealed to within-compound associations to accommodate these new data. Here, we present an elemental, neural network model of conditioning that explains retrospective revaluation apart from within-compound associations. In the model, previously paired stimuli (say, A and B, after AB+) come to activate similar ensembles of neurons, so that revaluation of one stimulus (A-) has the opposite effect on the other stimulus (B) through changes (decreases) in the strength of the inhibitory connections between neurons activated by B. The ventral striatum is discussed as a possible home for the structure and function of the present model.

In silico modeling of the yeast protein and protein family interaction network

Science.gov (United States)

Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

DNA-protein crosslinks in peripheral lymphocytes of individuals exposed to hexavalent chromium compounds.

Science.gov (United States)

Zhitkovich, A; Lukanova, A; Popov, T; Taioli, E; Cohen, H; Costa, M; Toniolo, P

1996-01-01

Abstract DNA-protein crosslinks were measured in peripheral blood lymphocytes of chrome-platers and controls from Bulgaria in order to evaluate a genotoxic effect of human exposure to carcinogenic Cr(VI) compounds. Chrome-platers and most of the unexposed controls were from the industrial city of Jambol; some additional controls were recruited from the seaside town of Burgas. The chrome-platers had significantly elevated levels of chromium in pre- and post-shift urine, erythrocytes and lymphocytes compared with the control subjects. The largest differences between the two groups were found in erythrocyte chromium concentrations which are considered to be indicative of Cr(VI) exposure. Despite the significant differences in internal chromium doses, levels of DNA-protein crosslinks were not significantly different between the combined controls and exposed workers. Individual DNA-protein crosslinks, however, correlated strongly with chromium in erythrocytes at low and moderate doses but at high exposures, such as among the majority of chrome-platers, these DNA adducts were saturated at maximum levels. The saturation of DNA-protein crosslinks seems to occur at 7-8 μg I-(1) chromium in erythrocytes whereas a mean erythrocyte chromium among the chrome platers was as high as 22.8 μg l(-1). Occupationally unexposed subjects exhibited a significant variability with respect to the erythrocyte chromium concentration, however erythrocyte chromium levels correlated closely with DNA-protein crosslinks in lymphocytes. The controls from Jambol had higher chromium concentrations in erythrocytes and elevated levels of DNA-protein crosslinks compared with Burgas controls. Occupational exposure to formaldehyde among furniture factory workers did not change levels of DNA-protein crosslinks in peripheral lymphocytes. DNA-protein crosslink measurements showed a low intraindividual variability and their levels among both controls and exposed indivduals were not affected by smoking, age

[Elimination of toxic compounds, biological evaluation and partial characterization of the protein from jojoba meal (Simmondsia chinensis [Link] Schneider].

Science.gov (United States)

Medina Juárez, L A; Trejo González, A

1989-12-01

The purpose of this study was to establish a new methodology to remove the toxic compounds present in jojoba meal and flour. Also, to perform the biological evaluation of the detoxified products and to chemically characterize the protein fractions. Jojoba meal and seed without testa were deffated with hexane and detoxified with a 7:3 isopropanol-water mixture which removed 86% of total phenolic compounds and 100% of simmondsins originally present, the resulting products had reduced bitterness and caused no deaths on experimental animals. NPR values obtained for diets containing such products were significantly different from those obtained with the casein control (p less than 0.05). Total protein was made up of three different fractions: the water-soluble fraction was the most abundant (61.8%), followed by the salt-soluble (23.6%), and the alkaline soluble fraction (14.6%). The nitrogen solubility curves showed that the isoelectric point for the water-soluble and salt-soluble fractions was pH 3.0, while that of the alkaline fraction fell in the range of 4.5-5.0. All fractions had a maximum solubility at pH 7.0. The methodology reported here, offers a viable solution to eliminate toxic compounds from jojoba meal or seeds, and upgrades the potential use of products such as animal feed or raw material for the production of protein isolates.

Discovery of rare protein-coding genes in model methylotroph Methylobacterium extorquens AM1.

Science.gov (United States)

Kumar, Dhirendra; Mondal, Anupam Kumar; Yadav, Amit Kumar; Dash, Debasis

2014-12-01

Proteogenomics involves the use of MS to refine annotation of protein-coding genes and discover genes in a genome. We carried out comprehensive proteogenomic analysis of Methylobacterium extorquens AM1 (ME-AM1) from publicly available proteomics data with a motive to improve annotation for methylotrophs; organisms capable of surviving in reduced carbon compounds such as methanol. Besides identifying 2482(50%) proteins, 29 new genes were discovered and 66 annotated gene models were revised in ME-AM1 genome. One such novel gene is identified with 75 peptides, lacks homolog in other methylobacteria but has glycosyl transferase and lipopolysaccharide biosynthesis protein domains, indicating its potential role in outer membrane synthesis. Many novel genes are present only in ME-AM1 among methylobacteria. Distant homologs of these genes in unrelated taxonomic classes and low GC-content of few genes suggest lateral gene transfer as a potential mode of their origin. Annotations of methylotrophy related genes were also improved by the discovery of a short gene in methylotrophy gene island and redefining a gene important for pyrroquinoline quinone synthesis, essential for methylotrophy. The combined use of proteogenomics and rigorous bioinformatics analysis greatly enhanced the annotation of protein-coding genes in model methylotroph ME-AM1 genome. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Protein expression changes induced in a malignant melanoma cell line by the curcumin analogue compound D6

International Nuclear Information System (INIS)

Pisano, Marina; Palomba, Antonio; Tanca, Alessandro; Pagnozzi, Daniela; Uzzau, Sergio; Addis, Maria Filippa; Dettori, Maria Antonietta; Fabbri, Davide; Palmieri, Giuseppe; Rozzo, Carla

2016-01-01

We have previously demonstrated that the hydroxylated biphenyl compound D6 (3E,3′E)-4,4′-(5,5′,6,6′-tetramethoxy-[1,1′-biphenyl]-3,3′-diyl)bis (but-3-en-2-one), a structural analogue of curcumin, exerts a strong antitumor activity on melanoma cells both in vitro and in vivo. Although the mechanism of action of D6 is yet to be clarified, this compound is thought to inhibit cancer cell growth by arresting the cell cycle in G2/M phase, and to induce apoptosis through the mitochondrial intrinsic pathway. To investigate the changes in protein expression induced by exposure of melanoma cells to D6, a differential proteomic study was carried out on D6-treated and untreated primary melanoma LB24Dagi cells. Proteins were fractionated by SDS-PAGE and subjected to in gel digestion. The peptide mixtures were analyzed by liquid chromatography coupled with tandem mass spectrometry. Proteins were identified and quantified using database search and spectral counting. Proteomic data were finally uploaded into the Ingenuity Pathway Analysis software to find significantly modulated networks and pathways. Analysis of the differentially expressed protein profiles revealed the activation of a strong cellular stress response, with overexpression of several HSPs and stimulation of ubiquitin-proteasome pathways. These were accompanied by a decrease of protein synthesis, evidenced by downregulation of proteins involved in mRNA processing and translation. These findings are consistent with our previous results on gene expression profiling in melanoma cells treated with D6. Our findings confirm that the curcumin analogue D6 triggers a strong stress response in melanoma cells, turning down majority of cell functions and finally driving cells to apoptosis. The online version of this article (doi:10.1186/s12885-016-2362-6) contains supplementary material, which is available to authorized users

A Mesoscopic Model for Protein-Protein Interactions in Solution

OpenAIRE

Lund, Mikael; Jönsson, Bo

2003-01-01

Protein self-association may be detrimental in biological systems, but can be utilized in a controlled fashion for protein crystallization. It is hence of considerable interest to understand how factors like solution conditions prevent or promote aggregation. Here we present a computational model describing interactions between protein molecules in solution. The calculations are based on a molecular description capturing the detailed structure of the protein molecule using x-ray or nuclear ma...

Binding Energy calculation of GSK-3 protein of Human against some anti-diabetic compounds of Momordica charantia linn (Bitter melon).

Science.gov (United States)

Hazarika, Ridip; Parida, Pratap; Neog, Bijoy; Yadav, Raj Narain Singh

2012-01-01

Diabetes is one of the major life threatening diseases worldwide. It creates major health problems in urban India. Glycogen Synthase Kinase-3 (GSK-3) protein of human is known for phosphorylating and inactivating glycogen synthase which also acts as a negative regulator in the hormonal control of glucose homeostasis. In traditional medicine, Momordica charantia is used as antidiabetic plant because of its hypoglycemic effect. Hence to block the active site of the GSK-3 protein three anti-diabetic compounds namely, charantin, momordenol & momordicilin were taken from Momordica charantia for docking study and calculation of binding energy. The aim of present investigation is to find the binding energy of three major insulin-like active compounds against glycogen synthase kinase-3 (GSK-3), one of the key proteins involved in carbohydrate metabolism, with the help of molecular docking using ExomeTM Horizon suite. The study recorded minimum binding energy by momordicilin in comparison to the others.

Computer modeling the boron compound factor in normal brain tissue

International Nuclear Information System (INIS)

Gavin, P.R.; Huiskamp, R.; Wheeler, F.J.; Griebenow, M.L.

1993-01-01

The macroscopic distribution of borocaptate sodium (Na 2 B 12 H 11 SH or BSH) in normal tissues has been determined and can be accurately predicted from the blood concentration. The compound para-borono-phenylalanine (p-BPA) has also been studied in dogs and normal tissue distribution has been determined. The total physical dose required to reach a biological isoeffect appears to increase directly as the proportion of boron capture dose increases. This effect, together with knowledge of the macrodistribution, led to estimates of the influence of the microdistribution of the BSH compound. This paper reports a computer model that was used to predict the compound factor for BSH and p-BPA and, hence, the equivalent radiation in normal tissues. The compound factor would need to be calculated for other compounds with different distributions. This information is needed to design appropriate normal tissue tolerance studies for different organ systems and/or different boron compounds

Prediction of protein-protein interactions between viruses and human by an SVM model

Directory of Open Access Journals (Sweden)

Cui Guangyu

2012-05-01

Full Text Available Abstract Background Several computational methods have been developed to predict protein-protein interactions from amino acid sequences, but most of those methods are intended for the interactions within a species rather than for interactions across different species. Methods for predicting interactions between homogeneous proteins are not appropriate for finding those between heterogeneous proteins since they do not distinguish the interactions between proteins of the same species from those of different species. Results We developed a new method for representing a protein sequence of variable length in a frequency vector of fixed length, which encodes the relative frequency of three consecutive amino acids of a sequence. We built a support vector machine (SVM model to predict human proteins that interact with virus proteins. In two types of viruses, human papillomaviruses (HPV and hepatitis C virus (HCV, our SVM model achieved an average accuracy above 80%, which is higher than that of another SVM model with a different representation scheme. Using the SVM model and Gene Ontology (GO annotations of proteins, we predicted new interactions between virus proteins and human proteins. Conclusions Encoding the relative frequency of amino acid triplets of a protein sequence is a simple yet powerful representation method for predicting protein-protein interactions across different species. The representation method has several advantages: (1 it enables a prediction model to achieve a better performance than other representations, (2 it generates feature vectors of fixed length regardless of the sequence length, and (3 the same representation is applicable to different types of proteins.

QSAR modeling and chemical space analysis of antimalarial compounds

Science.gov (United States)

Sidorov, Pavel; Viira, Birgit; Davioud-Charvet, Elisabeth; Maran, Uko; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2017-05-01

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including 3000 molecules tested in one or several of 17 anti- Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

Surface characterisation of synthetic coal chars made from model compounds

Energy Technology Data Exchange (ETDEWEB)

Arenillas, A.; Pevida, C.; Rubiera, F.; Palacios, J.M.; Navarrete, R.; Denoyel, R.; Rouquerol, J.; Pis, J.J. [Instituto Nacional del Carbon, CSIC, Oviedo (Spain)

2004-07-01

Knowledge of surface properties is essential for understanding the reaction mechanisms involved in several coal conversion processes. However, due to the complexity and heterogeneity of coal this is rather difficult and the use of known model compounds could be a valuable tool. Single model compounds have been widely used, but they give a quite simplified picture. In this work a mixture of model compounds in a phenol-formaldehyde matrix was cured in order to create cross-linked structures. The obtained synthetic coal was pyrolysed in a fixed bed reactor, under helium atmosphere. The surface composition of the chars was evaluated by XPS, adsorption gravimetry of water vapour, temperature-programmed desorption and potentiometric titration. Texture was characterised by N{sub 2} and CO{sub 2} adsorption isotherms at 77 and 273 K, respectively, and immersion calorimetry in benzene. The results obtained from the different techniques were contrasted in order to give an overview of the surface properties (chemical and physical) of the samples studied. Chars obtained under the same operating conditions from a high volatile bituminous coal were used as a reference.

Protein aggregates as depots for the release of biologically active compounds.

Science.gov (United States)

Artemova, Natalya V; Kasakov, Alexei S; Bumagina, Zoya M; Lyutova, Elena M; Gurvits, Bella Ya

2008-12-12

Protein misfolding and aggregation is one of the most serious problems in cell biology, molecular medicine, and biotechnology. Misfolded proteins interact with each other or with other proteins in non-productive or damaging ways. However, a new paradigm arises that protein aggregation may be exploited by nature to perform specific functions in different biological contexts. From this consideration, acceleration of stress-induced protein aggregation triggered by any factor resulting in the formation of soluble aggregates may have paradoxical positive consequences. Here, we suggest that amorphous aggregates can act as a source for the release of biologically active proteins after removal of stress conditions. To address this concept, we investigated the kinetics of thermal aggregation in vitro of yeast alcohol dehydrogenase (ADH) as a model substrate in the presence of two amphiphilic peptides: Arg-Phe or Ala-Phe-Lys. Using dynamic light scattering (DLS) and turbidimetry, we have demonstrated that under mild stress conditions the concentration-dependent acceleration of ADH aggregation by these peptides results in formation of large but soluble complexes of proteins prone to refolding.

Evidence for dynamic behavior of O2 in oxy-heme model compounds

International Nuclear Information System (INIS)

Montiel-Montoya, R.; Bill, E.; Trautwein, A.X.; Winkler, H.

1986-01-01

The authors have performed Moessbauer studies on several oxy-heme model compounds, and for two of them they have also derived the three dimensional structure from X-ray studies. The X-ray structure analysis of these model compounds provides the information that O 2 occupies three different sites in one and only two sites in the other. (Auth.)

Publicly available models to predict normal boiling point of organic compounds

International Nuclear Information System (INIS)

Oprisiu, Ioana; Marcou, Gilles; Horvath, Dragos; Brunel, Damien Bernard; Rivollet, Fabien; Varnek, Alexandre

2013-01-01

Quantitative structure–property models to predict the normal boiling point (T b ) of organic compounds were developed using non-linear ASNNs (associative neural networks) as well as multiple linear regression – ISIDA-MLR and SQS (stochastic QSAR sampler). Models were built on a diverse set of 2098 organic compounds with T b varying in the range of 185–491 K. In ISIDA-MLR and ASNN calculations, fragment descriptors were used, whereas fragment, FPTs (fuzzy pharmacophore triplets), and ChemAxon descriptors were employed in SQS models. Prediction quality of the models has been assessed in 5-fold cross validation. Obtained models were implemented in the on-line ISIDA predictor at (http://infochim.u-strasbg.fr/webserv/VSEngine.html)

Selective Oxidation of Lignin Model Compounds.

Science.gov (United States)

Gao, Ruili; Li, Yanding; Kim, Hoon; Mobley, Justin K; Ralph, John

2018-05-02

Lignin, the planet's most abundant renewable source of aromatic compounds, is difficult to degrade efficiently to welldefined aromatics. We developed a microwave-assisted catalytic Swern oxidation system using an easily prepared catalyst, MoO 2 Cl 2 (DMSO) 2 , and DMSO as the solvent and oxidant. It demonstrated high efficiency in transforming lignin model compounds containing the units and functional groups found in native lignins. The aromatic ring substituents strongly influenced the selectivity of β-ether phenolic dimer cleavage to generate sinapaldehyde and coniferaldehyde, monomers not usually produced by oxidative methods. Time-course studies on two key intermediates provided insight into the reaction pathway. Owing to the broad scope of this oxidation system and the insight gleaned with regard to its mechanism, this strategy could be adapted and applied in a general sense to the production of useful aromatic chemicals from phenolics and lignin. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Changes in the ionic and protein contents of adult Schistocerca Gregaria compound eyes due to He-Ne laser exposure

International Nuclear Information System (INIS)

El-Gindi, A.M.; Osiris, W.G.; El-kes, N.; Abd El-Meguid, A.

1996-01-01

The induced change in the concentration of the ionic content such as Na, K, and Ca in the compound eyes of Schistocerca Gregaria was carried out before and after exposure for different periodic times to He-Ne ;laser beam. Total protein and albumin contents in the compound eyes were also determined. The Data indicated that the ionic contents (Na, K and Ca) showed acceptable and significant changes in both the right (R) and left (L) eyes after exposure to different periodic times up to 60 minutes in comparison with the control ones. Moreover, very high significant increase in the total protein content (about 70.2%) as well as significant decrease in the albumin content (about 39.1%) in the right (R) eyes after exposure to He-Ne laser beam for 30 minutes in comparison with the control (unexposed) eyes, were detected. 2 tabs

The nested-doorway model of multistep compound processes

International Nuclear Information System (INIS)

Hussein, M.S.

1982-05-01

The multistep compound contribution to preequilibrium reaction are discussed within the nested-doorway model. Emphasis is placed on the generalized cross-section auto-correlation function. Several of the more widely used concepts in the conventional, one-class, statistical analysis are discussed and generalized to the multiclass case. A summary of the formal results of the nested-doorway model, obtained within Feshbach's projection operator theory is given. (Author) [pt

Laccase-mediator catalyzed conversion of model lignin compounds

Science.gov (United States)

Laccases play an important role in the biological breakdown of lignin and have great potential in the deconstruction of lignocellulosic feedstocks. We examined a variety of laccases, both commercially prepared and crude extracts, for their ability to oxidize three model lignol compounds (p-coumaryl...

Protein folding simulations: from coarse-grained model to all-atom model.

Science.gov (United States)

Zhang, Jian; Li, Wenfei; Wang, Jun; Qin, Meng; Wu, Lei; Yan, Zhiqiang; Xu, Weixin; Zuo, Guanghong; Wang, Wei

2009-06-01

Protein folding is an important and challenging problem in molecular biology. During the last two decades, molecular dynamics (MD) simulation has proved to be a paramount tool and was widely used to study protein structures, folding kinetics and thermodynamics, and structure-stability-function relationship. It was also used to help engineering and designing new proteins, and to answer even more general questions such as the minimal number of amino acid or the evolution principle of protein families. Nowadays, the MD simulation is still undergoing rapid developments. The first trend is to toward developing new coarse-grained models and studying larger and more complex molecular systems such as protein-protein complex and their assembling process, amyloid related aggregations, and structure and motion of chaperons, motors, channels and virus capsides; the second trend is toward building high resolution models and explore more detailed and accurate pictures of protein folding and the associated processes, such as the coordination bond or disulfide bond involved folding, the polarization, charge transfer and protonate/deprotonate process involved in metal coupled folding, and the ion permeation and its coupling with the kinetics of channels. On these new territories, MD simulations have given many promising results and will continue to offer exciting views. Here, we review several new subjects investigated by using MD simulations as well as the corresponding developments of appropriate protein models. These include but are not limited to the attempt to go beyond the topology based Gō-like model and characterize the energetic factors in protein structures and dynamics, the study of the thermodynamics and kinetics of disulfide bond involved protein folding, the modeling of the interactions between chaperonin and the encapsulated protein and the protein folding under this circumstance, the effort to clarify the important yet still elusive folding mechanism of protein BBL

Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

Science.gov (United States)

Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija

2018-01-01

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

DockQ: A Quality Measure for Protein-Protein Docking Models.

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Sankar Basu

Full Text Available The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (>10Å might still qualify as 'acceptable' with a descent Fnat (>0.50 and iRMS (<3.0Å. This is also the reason why the so called CAPRI criteria for assessing the quality of docking models is defined by applying various ad-hoc cutoffs on these measures to classify a docking model into the four classes: Incorrect, Acceptable, Medium, or High quality. This classification has been useful in CAPRI, but since models are grouped in only four bins it is also rather limiting, making it difficult to rank models, correlate with scoring functions or use it as target function in machine learning algorithms. Here, we present DockQ, a continuous protein-protein docking model quality measure derived by combining Fnat, LRMS, and iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for

Determination of the n-octanol/water partition coefficients of weakly ionizable basic compounds by reversed-phase high-performance liquid chromatography with neutral model compounds.

Science.gov (United States)

Liang, Chao; Han, Shu-ying; Qiao, Jun-qin; Lian, Hong-zhen; Ge, Xin

2014-11-01

A strategy to utilize neutral model compounds for lipophilicity measurement of ionizable basic compounds by reversed-phase high-performance liquid chromatography is proposed in this paper. The applicability of the novel protocol was justified by theoretical derivation. Meanwhile, the linear relationships between logarithm of apparent n-octanol/water partition coefficients (logKow '') and logarithm of retention factors corresponding to the 100% aqueous fraction of mobile phase (logkw ) were established for a basic training set, a neutral training set and a mixed training set of these two. As proved in theory, the good linearity and external validation results indicated that the logKow ''-logkw relationships obtained from a neutral model training set were always reliable regardless of mobile phase pH. Afterwards, the above relationships were adopted to determine the logKow of harmaline, a weakly dissociable alkaloid. As far as we know, this is the first report on experimental logKow data for harmaline (logKow = 2.28 ± 0.08). Introducing neutral compounds into a basic model training set or using neutral model compounds alone is recommended to measure the lipophilicity of weakly ionizable basic compounds especially those with high hydrophobicity for the advantages of more suitable model compound choices and convenient mobile phase pH control. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structural model of the hUbA1-UbcH10 quaternary complex: in silico and experimental analysis of the protein-protein interactions between E1, E2 and ubiquitin.

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Stefania Correale

Full Text Available UbcH10 is a component of the Ubiquitin Conjugation Enzymes (Ubc; E2 involved in the ubiquitination cascade controlling the cell cycle progression, whereby ubiquitin, activated by E1, is transferred through E2 to the target protein with the involvement of E3 enzymes. In this work we propose the first three dimensional model of the tetrameric complex formed by the human UbA1 (E1, two ubiquitin molecules and UbcH10 (E2, leading to the transthiolation reaction. The 3D model was built up by using an experimentally guided incremental docking strategy that combined homology modeling, protein-protein docking and refinement by means of molecular dynamics simulations. The structural features of the in silico model allowed us to identify the regions that mediate the recognition between the interacting proteins, revealing the active role of the ubiquitin crosslinked to E1 in the complex formation. Finally, the role of these regions involved in the E1-E2 binding was validated by designing short peptides that specifically interfere with the binding of UbcH10, thus supporting the reliability of the proposed model and representing valuable scaffolds for the design of peptidomimetic compounds that can bind selectively to Ubcs and inhibit the ubiquitylation process in pathological disorders.

Quantifying why urea is a protein denaturant, whereas glycine betaine is a protein stabilizer

Science.gov (United States)

Guinn, Emily J.; Pegram, Laurel M.; Capp, Michael W.; Pollock, Michelle N.; Record, M. Thomas

2011-01-01

To explain the large, opposite effects of urea and glycine betaine (GB) on stability of folded proteins and protein complexes, we quantify and interpret preferential interactions of urea with 45 model compounds displaying protein functional groups and compare with a previous analysis of GB. This information is needed to use urea as a probe of coupled folding in protein processes and to tune molecular dynamics force fields. Preferential interactions between urea and model compounds relative to their interactions with water are determined by osmometry or solubility and dissected using a unique coarse-grained analysis to obtain interaction potentials quantifying the interaction of urea with each significant type of protein surface (aliphatic, aromatic hydrocarbon (C); polar and charged N and O). Microscopic local-bulk partition coefficients Kp for the accumulation or exclusion of urea in the water of hydration of these surfaces relative to bulk water are obtained. Kp values reveal that urea accumulates moderately at amide O and weakly at aliphatic C, whereas GB is excluded from both. These results provide both thermodynamic and molecular explanations for the opposite effects of urea and glycine betaine on protein stability, as well as deductions about strengths of amide NH—amide O and amide NH—amide N hydrogen bonds relative to hydrogen bonds to water. Interestingly, urea, like GB, is moderately accumulated at aromatic C surface. Urea m-values for protein folding and other protein processes are quantitatively interpreted and predicted using these urea interaction potentials or Kp values. PMID:21930943

Consideration of the Verleur model of far-infrared spectroscopy of ternary compounds

International Nuclear Information System (INIS)

Robouch, B. V.; Kisiel, A.; Sheregii, E. M.

2001-01-01

The clustering model proposed by Verleur and Barker [Phys. Rev. 149, 715 (1966)] to interpret far infrared data for face-centered-cubic ternary compounds is critically analyzed. It is shown that their approach, satisfactory for fitting some ternary compound spectral curves, is too restricted by its one-parameter β model to be able to describe preferences (with respect to a random distribution case) for the five tetrahedron configurations

Adenosine Monophosphate (AMP)-Activated Protein Kinase: A New Target for Nutraceutical Compounds.

Science.gov (United States)

Marín-Aguilar, Fabiola; Pavillard, Luis E; Giampieri, Francesca; Bullón, Pedro; Cordero, Mario D

2017-01-29

Adenosine monophosphate-activated protein kinase (AMPK) is an important energy sensor which is activated by increases in adenosine monophosphate (AMP)/adenosine triphosphate (ATP) ratio and/or adenosine diphosphate (ADP)/ATP ratio, and increases different metabolic pathways such as fatty acid oxidation, glucose transport and mitochondrial biogenesis. In this sense, AMPK maintains cellular energy homeostasis by induction of catabolism and inhibition of ATP-consuming biosynthetic pathways to preserve ATP levels. Several studies indicate a reduction of AMPK sensitivity to cellular stress during aging and this could impair the downstream signaling and the maintenance of the cellular energy balance and the stress resistance. However, several diseases have been related with an AMPK dysfunction. Alterations in AMPK signaling decrease mitochondrial biogenesis, increase cellular stress and induce inflammation, which are typical events of the aging process and have been associated to several pathological processes. In this sense, in the last few years AMPK has been identified as a very interesting target and different nutraceutical compounds are being studied for an interesting potential effect on AMPK induction. In this review, we will evaluate the interaction of the different nutraceutical compounds to induce the AMPK phosphorylation and the applications in diseases such as cancer, type II diabetes, neurodegenerative diseases or cardiovascular diseases.

Modelling of proteins in membranes

DEFF Research Database (Denmark)

Sperotto, Maria Maddalena; May, S.; Baumgaertner, A.

2006-01-01

This review describes some recent theories and simulations of mesoscopic and microscopic models of lipid membranes with embedded or attached proteins. We summarize results supporting our understanding of phenomena for which the activities of proteins in membranes are expected to be significantly ...

Mathematical modeling of the mixing zone for getting bimetallic compound

Energy Technology Data Exchange (ETDEWEB)

Kim, Stanislav L. [Institute of Applied Mechanics, Ural Branch, Izhevsk (Russian Federation)

2011-07-01

A mathematical model of the formation of atomic bonds in metals and alloys, based on the electrostatic interaction between the outer electron shells of atoms of chemical elements. Key words: mathematical model, the interatomic bonds, the electron shell of atoms, the potential, the electron density, bimetallic compound.

Toxic Compound, Anti-Nutritional Factors and Functional Properties of Protein Isolated from Detoxified Jatropha curcas Seed Cake

Directory of Open Access Journals (Sweden)

Worapot Suntornsuk

2010-12-01

Full Text Available Jatropha curcas is a multipurpose tree, which has potential as an alternative source for biodiesel. All of its parts can also be used for human food, animal feed, fertilizer, fuel and traditional medicine. J. curcas seed cake is a low-value by-product obtained from biodiesel production. The seed cake, however, has a high amount of protein, with the presence of a main toxic compound: phorbol esters as well as anti-nutritional factors: trypsin inhibitors, phytic acid, lectin and saponin. The objective of this work was to detoxify J. curcas seed cake and study the toxin, anti-nutritional factors and also functional properties of the protein isolated from the detoxified seed cake. The yield of protein isolate was approximately 70.9%. The protein isolate was obtained without a detectable level of phorbol esters. The solubility of the protein isolate was maximal at pH 12.0 and minimal at pH 4.0. The water and oil binding capacities of the protein isolate were 1.76 g water/g protein and 1.07 mL oil/g protein, respectively. The foam capacity and stability, including emulsion activity and stability of protein isolate, had higher values in a range of basic pHs, while foam and emulsion stabilities decreased with increasing time. The results suggest that the detoxified J. curcas seed cake has potential to be exploited as a novel source of functional protein for food applications.

Toxic compound, anti-nutritional factors and functional properties of protein isolated from detoxified Jatropha curcas seed cake.

Science.gov (United States)

Saetae, Donlaporn; Suntornsuk, Worapot

2010-12-28

Jatropha curcas is a multipurpose tree, which has potential as an alternative source for biodiesel. All of its parts can also be used for human food, animal feed, fertilizer, fuel and traditional medicine. J. curcas seed cake is a low-value by-product obtained from biodiesel production. The seed cake, however, has a high amount of protein, with the presence of a main toxic compound: phorbol esters as well as anti-nutritional factors: trypsin inhibitors, phytic acid, lectin and saponin. The objective of this work was to detoxify J. curcas seed cake and study the toxin, anti-nutritional factors and also functional properties of the protein isolated from the detoxified seed cake. The yield of protein isolate was approximately 70.9%. The protein isolate was obtained without a detectable level of phorbol esters. The solubility of the protein isolate was maximal at pH 12.0 and minimal at pH 4.0. The water and oil binding capacities of the protein isolate were 1.76 g water/g protein and 1.07 mL oil/g protein, respectively. The foam capacity and stability, including emulsion activity and stability of protein isolate, had higher values in a range of basic pHs, while foam and emulsion stabilities decreased with increasing time. The results suggest that the detoxified J. curcas seed cake has potential to be exploited as a novel source of functional protein for food applications.

Gold(III) complexes with 2-substituted pyridines as experimental anticancer agents: solution behavior, reactions with model proteins, antiproliferative properties.

Science.gov (United States)

Maiore, Laura; Cinellu, Maria Agostina; Nobili, Stefania; Landini, Ida; Mini, Enrico; Gabbiani, Chiara; Messori, Luigi

2012-03-01

Gold(III) compounds form a family of promising cytotoxic and potentially anticancer agents that are currently undergoing intense preclinical investigations. Four recently synthesized and characterized gold(III) derivatives of 2-substituted pyridines are evaluated here for their biological and pharmacological behavior. These include two cationic adducts with 2-pyridinyl-oxazolines, [Au(pyox(R))Cl(2)][PF(6)], [pyox(R)=(S)-4-benzyl-2-(pyridin-2-yl)-4,5-dihydrooxazole, I; (S)-4-iso-propyl-2-(pyridin-2-yl)-4,5-dihydrooxazole, II] and two neutral complexes [Au(N,N'OH)Cl(2)], III, and [Au(N,N',O)Cl], IV, containing the deprotonated ligand N-(1-hydroxy-3-iso-propyl-2-yl)pyridine-2-carboxamide, N,N'H,OH, resulting from ring opening of bound pyox(R) ligand of complex II by hydroxide ions. The solution behavior of these compounds was analyzed. These behave as classical prodrugs: activation of the metal center typically takes place through release of the labile chloride ligands while the rest of the molecule is not altered; alternatively, activation may occur through gold(III) reduction. All compounds react eagerly with the model protein cyt c leading to extensive protein metalation. ESI MS experiments revealed details of gold-cyt c interactions and allowed us to establish the nature of protein bound metal containing fragments. The different behavior displayed by I and II compared to III and IV is highlighted. Remarkable cytotoxic properties, against the reference human ovarian carcinoma cell lines A2780/S and A2780/R were disclosed for all tested compounds with IC(50) values ranging from 1.43 to 6.18 μM in the sensitive cell line and from 1.59 to 10.86 μM in the resistant one. The common ability of these compounds to overcome cisplatin resistance is highlighted. The obtained results are thoroughly discussed in the frame of current knowledge on cytotoxic gold compounds. Copyright © 2011 Elsevier Inc. All rights reserved.

A DNA-Encoded Library of Chemical Compounds Based on Common Scaffolding Structures Reveals the Impact of Ligand Geometry on Protein Recognition.

Science.gov (United States)

Favalli, Nicholas; Biendl, Stefan; Hartmann, Marco; Piazzi, Jacopo; Sladojevich, Filippo; Gräslund, Susanne; Brown, Peter J; Näreoja, Katja; Schüler, Herwig; Scheuermann, Jörg; Franzini, Raphael; Neri, Dario

2018-06-01

A DNA-encoded chemical library (DECL) with 1.2 million compounds was synthesized by combinatorial reaction of seven central scaffolds with two sets of 343×492 building blocks. Library screening by affinity capture revealed that for some target proteins, the chemical nature of building blocks dominated the selection results, whereas for other proteins, the central scaffold also crucially contributed to ligand affinity. Molecules based on a 3,5-bis(aminomethyl)benzoic acid core structure were found to bind human serum albumin with a K d value of 6 nm, while compounds with the same substituents on an equidistant but flexible l-lysine scaffold showed 140-fold lower affinity. A 18 nm tankyrase-1 binder featured l-lysine as linking moiety, while molecules based on d-Lysine or (2S,4S)-amino-l-proline showed no detectable binding to the target. This work suggests that central scaffolds which predispose the orientation of chemical building blocks toward the protein target may enhance the screening productivity of encoded libraries. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Salivary protein levels as a predictor of perceived astringency in model systems and solid foods.

Science.gov (United States)

Fleming, Erin E; Ziegler, Gregory R; Hayes, John E

2016-09-01

Salivary protein difference value (SP D-value) is a quantitative measure of salivary protein replenishment, which reportedly relates to individual differences in perceived astringency. This in vitro measure is calculated as the difference in total salivary protein before (S1) and after (S2) stimulation with tannic acid, with a greater absolute value (S2-S1) indicating less protein replenishment. Others report that this measure predicts perceived astringency and liking of liquid model systems and beverages containing added polyphenols. Whether this relationship generalizes to astringent compounds other than polyphenols, or to solid foods is unknown. Here, the associations between SP D-values and perceived astringency and overall liking/disliking for alum and tannic acid (experiment 1) as well as solid chocolate-flavored compound coating with added tannic acid or grape seed extract (GSE) (experiment 2) were examined. In both experiments, participants (n=84 and 81, respectively) indicated perceived intensity of astringency, bitterness, sweetness, and sourness, and degree of liking of either aqueous solutions, or solid chocolate-flavored compound coating with added astringents. Data were analyzed via linear regression, and as discrete groups for comparison to prior work. Three discrete groups were formed based on first and third quartile splits of the SP D-value distribution: low (LR), medium (MR), and high responding (HR) individuals. In experiment 1, significantly higher mean astringency ratings were observed for the HR as compared to the LR/MR groups for alum and tannic acid, confirming and extending prior work. In experiment 2, significantly higher mean astringency ratings were also observed for HR as compared to LR groups in solid chocolate-flavored compound containing added tannic acid or GSE. Significant differences in liking were found between HR and LR groups for alum and tannic acid in water, but no significant differences in liking were observed for

Protein adsorption on nanoparticles: model development using computer simulation

International Nuclear Information System (INIS)

Shao, Qing; Hall, Carol K

2016-01-01

The adsorption of proteins on nanoparticles results in the formation of the protein corona, the composition of which determines how nanoparticles influence their biological surroundings. We seek to better understand corona formation by developing models that describe protein adsorption on nanoparticles using computer simulation results as data. Using a coarse-grained protein model, discontinuous molecular dynamics simulations are conducted to investigate the adsorption of two small proteins (Trp-cage and WW domain) on a model nanoparticle of diameter 10.0 nm at protein concentrations ranging from 0.5 to 5 mM. The resulting adsorption isotherms are well described by the Langmuir, Freundlich, Temkin and Kiselev models, but not by the Elovich, Fowler–Guggenheim and Hill–de Boer models. We also try to develop a generalized model that can describe protein adsorption equilibrium on nanoparticles of different diameters in terms of dimensionless size parameters. The simulation results for three proteins (Trp-cage, WW domain, and GB3) on four nanoparticles (diameter  =  5.0, 10.0, 15.0, and 20.0 nm) illustrate both the promise and the challenge associated with developing generalized models of protein adsorption on nanoparticles. (paper)

A prototypical non-malignant epithelial model to study genome dynamics and concurrently monitor micro-RNAs and proteins in situ during oncogene-induced senescence

DEFF Research Database (Denmark)

Komseli, Eirini Stavroula; Pateras, Ioannis S.; Krejsgaard, Thorbjørn

2018-01-01

limitations achieving for the first time simultaneous detection of both a micro-RNA and a protein in the biological context of cellular senescence, utilizing the new commercially available SenTraGorTM compound. The method was applied in a prototypical human non-malignant epithelial model of oncogene...

P-matrix in the quark compound bag model

International Nuclear Information System (INIS)

Kalashnikova, Yu.S.; Narodetskij, I.M.; Veselov, A.I.

1983-01-01

Meaning of the P-matrix analysis is discussed within the quark compound bag (QCB) model. The most general version of this model is considered including the arbitrary coupling between quark and hadronic channels and the arbitrary smearipg of the surface interection region. The behaviour of P-matrix poles as functions of matching radius r,L0 is discussed for r 0 > + . In conclusion are presented the parameters of an illustrative set of NN potentials that has been obtained from the P-matrix fit to experimental data

THREE DIMENSIONAL CFD MODELLING OF FLOW STRUCTURE IN COMPOUND CHANNELS

Directory of Open Access Journals (Sweden)

Usman Ghani

2010-10-01

Full Text Available The computational modeling of three dimensional flows in a meandering compound channel has been performed in this research work. The flow calculations are performed by solving 3D steady state continuity and Reynolds averaged Navier-Stokes equations. The turbulence closure is approximated with standard - turbulence model. The model equations are solved numerically with a general purpose software package. A comprehensive validation of the simulated results against the experimental data and a demonstration that the software used in this study has matured enough for investigating practical engineering problems are the major contributions of this paper. The model was initially validated. This was achieved by computing streamwise point velocities at different depths of various sections and depth averaged velocities at three cross sections along the main channel and comparing these results with experimental data. After the validation of the model, predictions were made for different flow parameters including velocity contours at the surface, pressure distribution, turbulence intensity etc. The results gave an overall understanding of these flow variables in meandering channels. The simulation also established the good prediction capability of the standard - turbulence model for flows in compound channels.

Phosphorus sorption on marine carbonate sediment: phosphonate as model organic compounds.

Science.gov (United States)

Huang, Xiao-Lan; Zhang, Jia-Zhong

2011-11-01

Organophosphonate, characterized by the presence of a stable, covalent, carbon to phosphorus (C-P) bond, is a group of synthetic or biogenic organophosphorus compounds. The fate of these organic phosphorus compounds in the environment is not well studied. This study presents the first investigation on the sorption of phosphorus (P) in the presence of two model phosphonate compounds, 2-aminothylphosphonoic acid (2-AEP) and phosphonoformic acid (PFA), on marine carbonate sediments. In contrast to other organic P compounds, no significant inorganic phosphate exchange was observed in seawater. P was found to adsorb on the sediment only in the presence of PFA, not 2-AEP. This indicated that sorption of P from phosphonate on marine sediment was compound specific. Compared with inorganic phosphate sorption on the same sediments, P sorption from organic phosphorus is much less in the marine environment. Further study is needed to understand the potential role of the organophosphonate compounds in biogeochemical cycle of phosphorus in the environment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Photobinding of tiaprofenic acid and suprofen to proteins and cells: a combined study using radiolabeling, antibodies and laser flash photolysis of model bichromophores.

Science.gov (United States)

Castell, J V; Hernández, D; Gómez-Lechón, M J; Lahoz, A; Miranda, M A; Morera, I M; Pérez-Prieto, J; Sarabia, Z

1998-11-01

Drug photoallergy is a matter of current concern. It involves the formation of drug-protein photoadducts (photoantigens) that may ultimately trigger an immunological response. Tyrosine residues appear to be key binding sites in proteins. The present work has investigated the photobinding of tiaprofenic and (TPA) and the closely related isomer suprofen (SUP) to proteins and cells by means of radioactive labelling and drug-directed antibodies. To ascertain whether preassociation with the protein may play a role in photoreactivity, two model bichromophoric compounds (TPA-Tyr and SUP-Tyr) have been prepared and studied by laser flash photolysis. The results of this work show that (a) TPA and SUP photobind to proteins with similar efficiencies, (b) both drugs form photoadducts that share a basic common structure, as they are recognized by the same antibody and (c) drug-protein preassociation must play a key role in photoreactivity, as indicated by the dramatic decrease in the triplet state lifetimes of the model bichromophores compared to the parent drugs.

Phenolic Compounds from Fermented Berry Beverages Modulated Gene and Protein Expression To Increase Insulin Secretion from Pancreatic β-Cells in Vitro.

Science.gov (United States)

Johnson, Michelle H; de Mejia, Elvira Gonzalez

2016-03-30

Berries are a rich source of bioactive phenolic compounds that are able to bind and inhibit the enzyme dipeptidyl peptidase-IV (DPP-IV), a current target for type-2 diabetes therapy. The objectives were to determine the role of berry phenolic compounds to modulate incretin-cleaving DPP-IV and its substrate glucagon-like peptide-1 (GLP-1), insulin secretion from pancreatic β-cells, and genes and proteins involved in the insulin secretion pathway using cell culture. Anthocyanins (ANC) from 50% blueberry-50% blackberry (Blu-Bla) and 100% blackberry (Bla) fermented beverages at 50 μM cyanidin-3-glucoside equivalents increased (p beverages have the potential to modulate DPP-IV and its substrate GLP-1, to increase insulin secretion, and to upregulate expression of mRNA of insulin-receptor associated genes and proteins in pancreatic β-cells.

Probing the molecular forces involved in binding of selected volatile flavour compounds to salt-extracted pea proteins.

Science.gov (United States)

Wang, Kun; Arntfield, Susan D

2016-11-15

Molecular interactions between heterologous classes of flavour compounds with salt-extracted pea protein isolates (PPIs) were determined using various bond disrupting agents followed by GC/MS analysis. Flavour bound by proteins decreased in the order: dibutyl disulfide>octanal>hexyl acetate>2-octanone=benzaldehyde. Benzaldehyde, 2-octanone and hexyl acetate interacted non-covalently with PPIs, whereas octanal bound PPIs via covalent and non-covalent forces. Dibutyl disulfide reacted with PPIs covalently, as its retention was not diminished by urea and guanidine hydrochloride. Using propylene glycol, H-bonding and ionic interactions were implicated for hexyl acetate, benzaldehyde, and 2-octanone. A protein-destabilising salt (Cl3CCOONa) reduced bindings for 2-octanone, hexyl acetate, and benzaldehyde; however, retention for octanal and dibutyl disulfide increased. Conversely, a protein-stabilising salt (Na2SO4) enhanced retention for benzaldehyde, 2-octanone, hexyl acetate and octanal. Formation of a volatile flavour by-product, 1-butanethiol, from dibutyl disulfide when PPIs were treated with dithiothreitol indicated occurrence of sulfhydryl-disulfide interchange reactions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular simulation of receptors of physiologically active compounds for purposes of medical chemistry

Science.gov (United States)

Baskin, Igor I.; Palyulin, Vladimir A.; Zefirov, Nikolai S.

2009-06-01

The general strategy of the molecular simulation of biological receptors and their interaction with ligands is considered. The procedures for construction of 3D protein models, molecular docking, evaluation of model quality, determination of the free energy of protein binding with ligands are discussed. The methods of molecular design of new medicaments based on molecular models of biological targets: virtual screening and de novo design, are presented. Examples of the above-listed approaches for the simulation of a number of pharmacologically significant receptors, analysis of receptor-ligand interactions and design of new biologically active organic compounds are given.

Molecular simulation of receptors of physiologically active compounds for purposes of medical chemistry

International Nuclear Information System (INIS)

Baskin, Igor I; Palyulin, Vladimir A; Zefirov, Nikolai S

2009-01-01

The general strategy of the molecular simulation of biological receptors and their interaction with ligands is considered. The procedures for construction of 3D protein models, molecular docking, evaluation of model quality, determination of the free energy of protein binding with ligands are discussed. The methods of molecular design of new medicaments based on molecular models of biological targets: virtual screening and de novo design, are presented. Examples of the above-listed approaches for the simulation of a number of pharmacologically significant receptors, analysis of receptor-ligand interactions and design of new biologically active organic compounds are given.

Molecular simulation of receptors of physiologically active compounds for purposes of medical chemistry

Energy Technology Data Exchange (ETDEWEB)

Baskin, Igor I; Palyulin, Vladimir A; Zefirov, Nikolai S [Department of Chemistry, M.V. Lomonosov Moscow State University, Moscow (Russian Federation)

2009-06-30

The general strategy of the molecular simulation of biological receptors and their interaction with ligands is considered. The procedures for construction of 3D protein models, molecular docking, evaluation of model quality, determination of the free energy of protein binding with ligands are discussed. The methods of molecular design of new medicaments based on molecular models of biological targets: virtual screening and de novo design, are presented. Examples of the above-listed approaches for the simulation of a number of pharmacologically significant receptors, analysis of receptor-ligand interactions and design of new biologically active organic compounds are given.

Quantitative chemogenomics: machine-learning models of protein-ligand interaction.

Science.gov (United States)

Andersson, Claes R; Gustafsson, Mats G; Strömbergsson, Helena

2011-01-01

Chemogenomics is an emerging interdisciplinary field that lies in the interface of biology, chemistry, and informatics. Most of the currently used drugs are small molecules that interact with proteins. Understanding protein-ligand interaction is therefore central to drug discovery and design. In the subfield of chemogenomics known as proteochemometrics, protein-ligand-interaction models are induced from data matrices that consist of both protein and ligand information along with some experimentally measured variable. The two general aims of this quantitative multi-structure-property-relationship modeling (QMSPR) approach are to exploit sparse/incomplete information sources and to obtain more general models covering larger parts of the protein-ligand space, than traditional approaches that focuses mainly on specific targets or ligands. The data matrices, usually obtained from multiple sparse/incomplete sources, typically contain series of proteins and ligands together with quantitative information about their interactions. A useful model should ideally be easy to interpret and generalize well to new unseen protein-ligand combinations. Resolving this requires sophisticated machine-learning methods for model induction, combined with adequate validation. This review is intended to provide a guide to methods and data sources suitable for this kind of protein-ligand-interaction modeling. An overview of the modeling process is presented including data collection, protein and ligand descriptor computation, data preprocessing, machine-learning-model induction and validation. Concerns and issues specific for each step in this kind of data-driven modeling will be discussed. © 2011 Bentham Science Publishers

Investigation on chemistry of model compounds of technetium radiopharmaceuticals

International Nuclear Information System (INIS)

Muenze, R.; Hartmann, E.

1983-01-01

The report summarized experimental and theoretical results concerning the chemical structures and the biodistribution of hydrophilic technetium chelates with hydroxycarboxylic and aminopolycarboxylic acids, thiol compounds and aliphatic and aromatic nitrogen compounds as ligands. Methods which are suitable for synthesizing and characterizing defined chelates of Tc(V), Tc(IV) and Tc(III) have been developed for crystlline substances and species in solution, respectively. For certain types of technetium chelates three dimensional structure models were calculated from atomic parameters. The electron energies and electron distribution of Tc(V) thiol compounds were calculated by quantum chemical methods in order to interprete physical properties of these substances. Biodistribution studies revealed relationships between the osteotropic behaviour and the structure of phosphorous and non-phosphorous technetium chelates and between the kidney uptake and ligand exchange ability of Tc(V) hydroxycarboxylates. Important parameters for the production of technetium-99m kits have been elaborated and used for the optimization of radiopharmaceuticals (bone-, kidney and hepatobiliaer agents). (author)

In search of new lead compounds for trypanosomiasis drug design: A protein structure-based linked-fragment approach

Science.gov (United States)

Verlinde, Christophe L. M. J.; Rudenko, Gabrielle; Hol, Wim G. J.

1992-04-01

A modular method for pursuing structure-based inhibitor design in the framework of a design cycle is presented. The approach entails four stages: (1) a design pathway is defined in the three-dimensional structure of a target protein; (2) this pathway is divided into subregions; (3) complementary building blocks, also called fragments, are designed in each subregion; complementarity is defined in terms of shape, hydrophobicity, hydrogen bond properties and electrostatics; and (4) fragments from different subregions are linked into potential lead compounds. Stages (3) and (4) are qualitatively guided by force-field calculations. In addition, the designed fragments serve as entries for retrieving existing compounds from chemical databases. This linked-fragment approach has been applied in the design of potentially selective inhibitors of triosephosphate isomerase from Trypanosoma brucei, the causative agent of sleeping sickness.

Some information needs for air quality modeling. [Environmental effects of sulfur compounds

Energy Technology Data Exchange (ETDEWEB)

Hill, F B

1975-09-01

The following topics were considered at the workshop: perturbation of the natural sulfur cycle by human activity; ecosystem responses to a given environmental dose of sulfur compounds; movement of sulfur compounds within the atmosphere; air quality models; contribution of biogenic sulfur compounds to atmospheric burden of sulfur; production of acid rain from sulfur dioxide; meteorological processes; and rates of oxidation of SO/sub 2/ via direct photo-oxidation, oxidation resulting from photo-induced free radical chemistry, and catalytic oxidation in cloud droplets and on dry particles. (HLW)

Physiologically Based Pharmacokinetic Modeling of Therapeutic Proteins.

Science.gov (United States)

Wong, Harvey; Chow, Timothy W

2017-09-01

Biologics or therapeutic proteins are becoming increasingly important as treatments for disease. The most common class of biologics are monoclonal antibodies (mAbs). Recently, there has been an increase in the use of physiologically based pharmacokinetic (PBPK) modeling in the pharmaceutical industry in drug development. We review PBPK models for therapeutic proteins with an emphasis on mAbs. Due to their size and similarity to endogenous antibodies, there are distinct differences between PBPK models for small molecules and mAbs. The high-level organization of a typical mAb PBPK model consists of a whole-body PBPK model with organ compartments interconnected by both blood and lymph flows. The whole-body PBPK model is coupled with tissue-level submodels used to describe key mechanisms governing mAb disposition including tissue efflux via the lymphatic system, elimination by catabolism, protection from catabolism binding to the neonatal Fc (FcRn) receptor, and nonlinear binding to specific pharmacological targets of interest. The use of PBPK modeling in the development of therapeutic proteins is still in its infancy. Further application of PBPK modeling for therapeutic proteins will help to define its developing role in drug discovery and development. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Toward the identification of a reliable 3D-QSAR model for the protein tyrosine phosphatase 1B inhibitors

Science.gov (United States)

Wang, Fangfang; Zhou, Bo

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) is an intracellular non-receptor phosphatase that is implicated in signal transduction of insulin and leptin pathways, thus PTP1B is considered as potential target for treating type II diabetes and obesity. The present article is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling of a series of compounds possessing PTP1B inhibitory activities using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The optimum template ligand-based models are statistically significant with great CoMFA (R2cv = 0.600, R2pred = 0.6760) and CoMSIA (R2cv = 0.624, R2pred = 0.8068) values. Molecular docking was employed to elucidate the inhibitory mechanisms of this series of compounds against PTP1B. In addition, the CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of PTP1B active site. The knowledge of structure-activity relationship and ligand-receptor interactions from 3D-QSAR model and molecular docking will be useful for better understanding the mechanism of ligand-receptor interaction and facilitating development of novel compounds as potent PTP1B inhibitors.

A study on superoxide dismutase activity of some model compounds.

Science.gov (United States)

Liao, Z; Liu, W; Liu, J; Jiang, Y; Shi, J; Liu, C

1994-08-15

The synthesis and characteristics of a binuclear ligand N,N,N',N'-tetrakis (2'-benzimidazolyl methyl)-1,4-diethylene amino glycol ether (EGTB) and its series of coordination compounds containing copper(II), iron(III), and manganese(II) with and without exogenous bridging ligand which was imidazolate ion (Im-), bipyridine (bpy), or 1,10-phenanthroline (phen) are reported. Depending on the redox potentials by cyclic voltammetry, the coordination compounds can act as catalysts for the dismutation of superoxide radicals (O2-). The detection of the rate constant of the reaction of superoxide ion with nitroblue tetrazolium (NBT) which is inhibited by superoxide dismutase (SOD) and its model compounds of the EGTB system has been performed by a modified illumination method. The rate constants kQ of the catalytic dismutation have been obtained.

Modelling uptake into roots and subsequent translocation of neutral and ionisable organic compounds

DEFF Research Database (Denmark)

Trapp, Stefan

2000-01-01

A study on uptake of neutral and dissociating organic compounds from soil solution into roots, and their subsequent translocation, was undertaken using model simulations. The model approach combines the processes of lipophilic sorption, electrochemical interactions, ion trap, advection in xylem...... and dilution by growth. It needs as input data, apart fromplant properties, log KOW, pKa and the valency number of the compound, and pH and chemical concentration in the soil solution. Equilibrium and dynamic (steady-state) models were tested against measured data from several authors, including non...

An in vitro transport model for rapid screening and predicting the permeability of candidate compounds at blood-brain barrier.

Science.gov (United States)

Yang, Zhi-Hong; Sun, Xiao; Mei, Chao; Sun, Xiao-Bo; Liu, Xiao-Dong; Chang, Qi

2011-12-01

The aim of this study was to design and develop a simple in vitro blood-brain barrier (BBB) permeation model for elementarily and rapidly predicting the permeability of candidate compounds at BBB and further evaluating whether P-glycoprotein (P-gp) affects them across BBB. The model was mainly composed of cultured rat brain microvascular endothelial cells (rBMECs), glass contraption, and micropore membrane. First, we evaluated the model by morphological observation. Second, the restriction effects of paracellular transport were verified by measuring marker probes transport, and monitoring transendothelial electrical resistance (TEER) and leakage. Finally, protein expression and activity of P-gp were confirmed by carrying out Western blot analysis and polarized transport of rhodamine-123 (Rho123) in rBMECs. The rBMECs retained both endothelial cells and BBB features. The rBMECs model reproducibly attained approximately 130 Ω cm² on the steady-state TEER value, and displayed a barrier function to marker probes transport by decreasing the permeability. Protein band of 170 kDa manifested the existence of P-gp in the rBMECs, and the findings of cyclosporin A-sensitive decrease of Rho123 efflux confirmed the presence of P-gp activity. A simple, rapid, and convenient in vitro BBB permeation model was successfully established and applied to evaluate the BBB transport profiles of three natural flavonoids: quercetin, naringenin, and rutin.

A hidden markov model derived structural alphabet for proteins.

Science.gov (United States)

Camproux, A C; Gautier, R; Tufféry, P

2004-06-04

Understanding and predicting protein structures depends on the complexity and the accuracy of the models used to represent them. We have set up a hidden Markov model that discretizes protein backbone conformation as series of overlapping fragments (states) of four residues length. This approach learns simultaneously the geometry of the states and their connections. We obtain, using a statistical criterion, an optimal systematic decomposition of the conformational variability of the protein peptidic chain in 27 states with strong connection logic. This result is stable over different protein sets. Our model fits well the previous knowledge related to protein architecture organisation and seems able to grab some subtle details of protein organisation, such as helix sub-level organisation schemes. Taking into account the dependence between the states results in a description of local protein structure of low complexity. On an average, the model makes use of only 8.3 states among 27 to describe each position of a protein structure. Although we use short fragments, the learning process on entire protein conformations captures the logic of the assembly on a larger scale. Using such a model, the structure of proteins can be reconstructed with an average accuracy close to 1.1A root-mean-square deviation and for a complexity of only 3. Finally, we also observe that sequence specificity increases with the number of states of the structural alphabet. Such models can constitute a very relevant approach to the analysis of protein architecture in particular for protein structure prediction.

DEVELOPMENT AND VALIDATION OF AN AIR-TO-BEEF FOOD CHAIN MODEL FOR DIOXIN-LIKE COMPOUNDS

Science.gov (United States)

A model for predicting concentrations of dioxin-like compounds in beef is developed and tested. The key premise of the model is that concentrations of these compounds in air are the source term, or starting point, for estimating beef concentrations. Vapor-phase concentrations t...

DockQ: A Quality Measure for Protein-Protein Docking Models

Science.gov (United States)

Basu, Sankar

2016-01-01

The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (>10Å) might still qualify as 'acceptable' with a descent Fnat (>0.50) and iRMS (iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for protein structure prediction, and DockQ should be useful in a similar development in the protein docking field. DockQ is available at http://github.com/bjornwallner/DockQ/ PMID:27560519

Association of protein structure, protein and carbohydrate subfractions with bioenergy profiles and biodegradation functions in modeled forage

Science.gov (United States)

Ji, Cuiying; Zhang, Xuewei; Yu, Peiqiang

2016-03-01

The objectives of this study were to detect unique aspects and association of forage protein inherent structure, biological compounds, protein and carbohydrate subfractions, bioenergy profiles, and biodegradation features. In this study, common available alfalfa hay from two different sourced-origins (FSO vs. CSO) was used as a modeled forage for inherent structure profile, bioenergy, biodegradation and their association between their structure and bio-functions. The molecular spectral profiles were determined using non-invasive molecular spectroscopy. The parameters included: protein structure amide I group, amide II group and their ratios; protein subfractions (PA1, PA2, PB1, PB2, PC); carbohydrate fractions (CA1, CA2, CA3, CA4, CB1, CB2, CC); biodegradable and undegradable fractions of protein (RDPA2, RDPB1, RDPB2, RDP; RUPA2 RUPB1, RUPB2, RUPC, RUP); biodegradable and undegradable fractions of carbohydrate (RDCA4, RDCB1, RDCB2, RDCB3, RDCHO; RUCA4, RUCB1; RUCB2; RUCB3 RUCC, RUCHO) and bioenergy profiles (tdNDF, tdFA, tdCP, tdNFC, TDN1 ×, DE3 ×, ME3 ×, NEL3 ×; NEm, NEg). The results show differences in protein and carbohydrate (CHO) subfractions in the moderately degradable true protein fraction (PB1: 502 vs. 420 g/kg CP, P = 0.09), slowly degraded true protein fraction (PB2: 45 vs. 96 g/kg CP, P = 0.02), moderately degradable CHO fraction (CB2: 283 vs. 223 g/kg CHO, P = 0.06) and slowly degraded CHO fraction (CB3: 369 vs. 408 g/kg CHO) between the two sourced origins. As to biodegradable (RD) fractions of protein and CHO in rumen, there were differences in RD of PB1 (417 vs. 349 g/kg CP, P = 0.09), RD of PB2 (29 vs. 62 g/kg CP, P = 0.02), RD of CB2 (251 vs. 198 g/kg DM, P = 0.06), RD of CB3 (236 vs. 261 g/kg CHO, P = 0.08). As to bioenergy profile, there were differences in total digestible nutrient (TDN: 551 vs. 537 g/kg DM, P = 0.06), and metabolic bioenergy (P = 0.095). As to protein molecular structure, there were differences in protein structure 1st

A credit-card library approach for disrupting protein-protein interactions.

Science.gov (United States)

Xu, Yang; Shi, Jin; Yamamoto, Noboru; Moss, Jason A; Vogt, Peter K; Janda, Kim D

2006-04-15

Protein-protein interfaces are prominent in many therapeutically important targets. Using small organic molecules to disrupt protein-protein interactions is a current challenge in chemical biology. An important example of protein-protein interactions is provided by the Myc protein, which is frequently deregulated in human cancers. Myc belongs to the family of basic helix-loop-helix leucine zipper (bHLH-ZIP) transcription factors. It is biologically active only as heterodimer with the bHLH-ZIP protein Max. Herein, we report a new strategy for the disruption of protein-protein interactions that has been corroborated through the design and synthesis of a small parallel library composed of 'credit-card' compounds. These compounds are derived from a planar, aromatic scaffold and functionalized with four points of diversity. From a 285 membered library, several hits were obtained that disrupted the c-Myc-Max interaction and cellular functions of c-Myc. The IC50 values determined for this small focused library for the disruption of Myc-Max dimerization are quite potent, especially since small molecule antagonists of protein-protein interactions are notoriously difficult to find. Furthermore, several of the compounds were active at the cellular level as shown by their biological effects on Myc action in chicken embryo fibroblast assays. In light of our findings, this approach is considered a valuable addition to the armamentarium of new molecules being developed to interact with protein-protein interfaces. Finally, this strategy for disrupting protein-protein interactions should prove applicable to other families of proteins.

Aromatic products from reaction of lignin model compounds with UV-alkaline peroxide

International Nuclear Information System (INIS)

Sun, Y.P.; Wallis, A.F.A.; Nguyen, K.L.

1997-01-01

A series of guaiacyl and syringyl lignin model compounds and their methylated analogues were reacted with alkaline hydrogen peroxide while irradiating with UV light at 254 nm. The aromatic products obtained were investigated by gas chromatography-mass spectrometry (GC-MS). Guaiacol, syringol and veratrol gave no detectable aromatic products. However, syringol methyl ether gave small amounts of aromatic products, resulting from ring substitution and methoxyl displacement by hydroxyl radicals. Reaction of vanillin and syringaldehyde gave the Dakin reaction products, methoxy-1,4-hydroquinones, while reaction of their methyl ethers yielded benzoic acids. Acetoguaiacone, acetosyringone and their methyl ethers afforded several hydroxylated aromatic products, but no aromatic products were identified in the reaction mixtures from guaiacylpropane and syringylpropane. In contrast, veratrylpropane gave a mixture from which 17 aromatic hydroxylated compounds were identified. It is concluded that for phenolic lignin model compounds, particularly those possessing electrondonating aromatic ring substituents, ring-cleavage reactions involving superoxide radical anions are dominant, whereas for non-phenolic lignin models, hydroxylation reactions through attack of hydroxyl radicals prevail

The rational design of a novel potent analogue of the 5’-AMP-activated protein kinase inhibitor compound C with improved selectivity and cellular activity

Science.gov (United States)

Machrouhi, Fouzia; Ouhamou, Nouara; Laderoute, Keith; Calaoagan, Joy; Bukhtiyarova, Marina; Ehrlich, Paula J.; Klon, Anthony E.

2010-01-01

We have designed and synthesized analogues of compound C, a non-specific inhibitor of 5’-AMP-activated protein kinase (AMPK), using a computational fragment-based drug design (FBDD) approach. Synthesizing only twenty-seven analogues yielded a compound that was equipotent to compound C in the inhibition of the human AMPK (hAMPK) α2 subunit in the heterotrimeric complex in vitro, exhibited significantly improved selectivity against a subset of relevant kinases, and demonstrated enhanced cellular inhibition of AMPK. PMID:20932747

Potential of chromatin modifying compounds for the treatment of Alzheimer's disease.

Science.gov (United States)

Karagiannis, Tom C; Ververis, Katherine

2012-01-01

Alzheimer's disease is a very common progressive neurodegenerative disorder affecting the learning and memory centers in the brain. The hallmarks of disease are the accumulation of β-amyloid neuritic plaques and neurofibrillary tangles formed by abnormally phosphorylated tau protein. Alzheimer's disease is currently incurable and there is an intense interest in the development of new potential therapies. Chromatin modifying compounds such as sirtuin modulators and histone deacetylase inhibitors have been evaluated in models of Alzheimer's disease with some promising results. For example, the natural antioxidant and sirtuin 1 activator resveratrol has been shown to have beneficial effects in animal models of disease. Similarly, numerous histone deacetylase inhibitors including Trichostatin A, suberoylanilide hydroxamic acid, valproic acid and phenylbutyrate reduction have shown promising results in models of Alzheimer's disease. These beneficial effects include a reduction of β-amyloid production and stabilization of tau protein. In this review we provide an overview of the histone deacetylase enzymes, with a focus on enzymes that have been identified to have an important role in the pathobiology of Alzheimer's disease. Further, we discuss the potential for pharmacological intervention with chromatin modifying compounds that modulate histone deacetylase enzymes.

Potential of chromatin modifying compounds for the treatment of Alzheimer's disease

Directory of Open Access Journals (Sweden)

Tom C. Karagiannis

2012-02-01

Full Text Available Alzheimer's disease is a very common progressive neurodegenerative disorder affecting the learning and memory centers in the brain. The hallmarks of disease are the accumulation of β-amyloid neuritic plaques and neurofibrillary tangles formed by abnormally phosphorylated tau protein. Alzheimer's disease is currently incurable and there is an intense interest in the development of new potential therapies. Chromatin modifying compounds such as sirtuin modulators and histone deacetylase inhibitors have been evaluated in models of Alzheimer's disease with some promising results. For example, the natural antioxidant and sirtuin 1 activator resveratrol has been shown to have beneficial effects in animal models of disease. Similarly, numerous histone deacetylase inhibitors including Trichostatin A, suberoylanilide hydroxamic acid, valproic acid and phenylbutyrate reduction have shown promising results in models of Alzheimer's disease. These beneficial effects include a reduction of β-amyloid production and stabilization of tau protein. In this review we provide an overview of the histone deacetylase enzymes, with a focus on enzymes that have been identified to have an important role in the pathobiology of Alzheimer's disease. Further, we discuss the potential for pharmacological intervention with chromatin modifying compounds that modulate histone deacetylase enzymes.

On the (R,s,Q) Inventory Model when Demand is Modelled as a Compound Process

NARCIS (Netherlands)

Janssen, F.B.S.L.P.; Heuts, R.M.J.; de Kok, T.

1996-01-01

In this paper we present an approximation method to compute the reorder point s in a (R; s; Q) inventory model with a service level restriction, where demand is modelled as a compound Bernoulli process, that is, with a xed probability there is positive demand during a time unit, otherwise demand is

Models of protein-ligand crystal structures: trust, but verify.

Science.gov (United States)

Deller, Marc C; Rupp, Bernhard

2015-09-01

X-ray crystallography provides the most accurate models of protein-ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein-ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein-ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein-ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein-ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein-ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein-ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.

Markov dynamic models for long-timescale protein motion.

KAUST Repository

Chiang, Tsung-Han

2010-06-01

Molecular dynamics (MD) simulation is a well-established method for studying protein motion at the atomic scale. However, it is computationally intensive and generates massive amounts of data. One way of addressing the dual challenges of computation efficiency and data analysis is to construct simplified models of long-timescale protein motion from MD simulation data. In this direction, we propose to use Markov models with hidden states, in which the Markovian states represent potentially overlapping probabilistic distributions over protein conformations. We also propose a principled criterion for evaluating the quality of a model by its ability to predict long-timescale protein motions. Our method was tested on 2D synthetic energy landscapes and two extensively studied peptides, alanine dipeptide and the villin headpiece subdomain (HP-35 NleNle). One interesting finding is that although a widely accepted model of alanine dipeptide contains six states, a simpler model with only three states is equally good for predicting long-timescale motions. We also used the constructed Markov models to estimate important kinetic and dynamic quantities for protein folding, in particular, mean first-passage time. The results are consistent with available experimental measurements.

Markov dynamic models for long-timescale protein motion.

KAUST Repository

Chiang, Tsung-Han; Hsu, David; Latombe, Jean-Claude

2010-01-01

Molecular dynamics (MD) simulation is a well-established method for studying protein motion at the atomic scale. However, it is computationally intensive and generates massive amounts of data. One way of addressing the dual challenges of computation efficiency and data analysis is to construct simplified models of long-timescale protein motion from MD simulation data. In this direction, we propose to use Markov models with hidden states, in which the Markovian states represent potentially overlapping probabilistic distributions over protein conformations. We also propose a principled criterion for evaluating the quality of a model by its ability to predict long-timescale protein motions. Our method was tested on 2D synthetic energy landscapes and two extensively studied peptides, alanine dipeptide and the villin headpiece subdomain (HP-35 NleNle). One interesting finding is that although a widely accepted model of alanine dipeptide contains six states, a simpler model with only three states is equally good for predicting long-timescale motions. We also used the constructed Markov models to estimate important kinetic and dynamic quantities for protein folding, in particular, mean first-passage time. The results are consistent with available experimental measurements.

Use of Shark Dental Protein to Estimate Trophic Position via Amino Acid Compound-Specific Isotope Analysis

Science.gov (United States)

Hayes, M.; Herbert, G.; Ellis, G.

2017-12-01

The diets of apex predators such as sharks are expected to change in response to overfishing of their mesopredator prey, but pre-anthropogenic baselines necessary to test for such changes are lacking. Stable isotope analysis (SIA) of soft tissues is commonly used to study diets in animals based on the bioaccumulation of heavier isotopes of carbon and nitrogen with increasing trophic level. In specimens representing pre-anthropogenic baselines, however, a modified SIA approach is needed to deal with taphonomic challenges, such as loss of soft tissues or selective loss of less stable amino acids (AAs) in other sources of organic compounds (e.g., teeth or bone) which can alter bulk isotope values. These challenges can be overcome with a compound-specific isotope analysis of individual AAs (AA-CSIA), but this first requires a thorough understanding of trophic enrichment factors for individual AAs within biomineralized tissues. In this study, we compare dental and muscle proteins of individual sharks via AA-CSIA to determine how trophic position is recorded within teeth and whether that information differs from that obtained from soft tissues. If skeletal organics reliably record information about shark ecology, then archaeological and perhaps paleontological specimens can be used to investigate pre-anthropogenic ecosystems. Preliminary experiments show that the commonly used glutamic acid/phenylalanine AA pairing may not be useful for establishing trophic position from dental proteins, but that estimated trophic position determined from alternate AA pairs are comparable to those from muscle tissue within the same species.

Effects of membrane composition on release of model hydrophilic compound from osmotic delivery systems.

Science.gov (United States)

Ozdemir, N; Ozalp, Y; Ozkan, Y

2000-01-01

In this study, the effects of surface-active agents in different types and concentrations, added into the coating solution, on release of model hydrophilic compound have been examined. For this purpose, the tablets, prepared with the use of methylene blue as a model substance, were coated by spray coating technique with cellulose acetate solution containing polyethylene glycol 400 as a plasticizer. In addition, cetylpyridinium chloride as cationic surface-active agent and sodium lauryl sulphate as anionic surface-active agent were added into coating solution in different concentrations. After creating a delivery orifice by a microdrill on the tablets, release of model hydrophilic compound was tested by the USP paddle method. The data obtained were evaluated according to the different kinetics and the mechanism of release from the preparations was examined. The surface properties of the coating material were investigated by scanning electron microscope taken before and after the contact with medium fluid, as well as the mechanical properties by tensile tests. In conclusion, it has been found that the cationic surface active agent, cetylpyridinium chloride reduced the lag time, observed during the release of model hydrophilic compound, as a result of its enhancing effect on wettability of tablets by reducing the contact angle between the medium fluid and the coating material. On the other hand, the anionic surface active agent, sodium lauryl sulphate has been inactivated possibly due to the interaction with model hydrophilic compound that has cationic properties and/or substances contained in membrane composition; thus, the lag time has not decreased and furthermore, a significant decrease in the delivery rate of model hydrophilic compound has been observed.

Modeling of iodine radiation chemistry in the presence of organic compounds

International Nuclear Information System (INIS)

Taghipour, Fariborz; Evans, Greg J.

2002-01-01

A kinetic-based model was developed that simulates the radiation chemistry of iodine in the presence of organic compounds. The model's mechanistic description of iodine chemistry and generic semi-mechanistic reactions for various classes of organics, provided a reasonable representation of experimental results. The majority of the model and experimental results of iodine volatilization rates were in agreement within an order of magnitude

Discovery of Novel Inhibitors for Nek6 Protein through Homology Model Assisted Structure Based Virtual Screening and Molecular Docking Approaches

Directory of Open Access Journals (Sweden)

P. Srinivasan

2014-01-01

Full Text Available Nek6 is a member of the NIMA (never in mitosis, gene A-related serine/threonine kinase family that plays an important role in the initiation of mitotic cell cycle progression. This work is an attempt to emphasize the structural and functional relationship of Nek6 protein based on homology modeling and binding pocket analysis. The three-dimensional structure of Nek6 was constructed by molecular modeling studies and the best model was further assessed by PROCHECK, ProSA, and ERRAT plot in order to analyze the quality and consistency of generated model. The overall quality of computed model showed 87.4% amino acid residues under the favored region. A 3 ns molecular dynamics simulation confirmed that the structure was reliable and stable. Two lead compounds (Binding database ID: 15666, 18602 were retrieved through structure-based virtual screening and induced fit docking approaches as novel Nek6 inhibitors. Hence, we concluded that the potential compounds may act as new leads for Nek6 inhibitors designing.

Thermal Decomposition Mechanisms of Lignin Model Compounds: From Phenol to Vanillin

Science.gov (United States)

Scheer, Adam Michael

Lignin is a complex, aromatic polymer abundant in cellulosic biomass (trees, switchgrass etc.). Thermochemical breakdown of lignin for liquid fuel production results in undesirable polycyclic aromatic hydrocarbons that lead to tar and soot byproducts. The fundamental chemistry governing these processes is not well understood. We have studied the unimolecular thermal decomposition mechanisms of aromatic lignin model compounds using a miniature SiC tubular reactor. Products are detected and characterized using time-of-flight mass spectrometry with both single photon (118.2 nm; 10.487 eV) and 1 + 1 resonance-enhanced multiphoton ionization (REMPI) as well as matrix isolation infrared spectroscopy. Gas exiting the heated reactor (300 K--1600 K) is subject to a free expansion after a residence time of approximately 100 micros. The expansion into vacuum rapidly cools the gas mixture and allows the detection of radicals and other highly reactive intermediates. By understanding the unimolecular fragmentation patterns of phenol (C6H5OH), anisole (C6H 5OCH3) and benzaldehyde (C6H5CHO), the more complicated thermocracking processes of the catechols (HO-C 6H4-OH), methoxyphenols (HO-C6H4-OCH 3) and hydroxybenzaldehydes (HO-C6H4-CHO) can be interpreted. These studies have resulted in a predictive model that allows the interpretation of vanillin, a complex phenolic ether containing methoxy, hydroxy and aldehyde functional groups. This model will serve as a guide for the pyrolyses of larger systems including lignin monomers such as coniferyl alcohol. The pyrolysis mechanisms of the dimethoxybenzenes (H3C-C 6H4-OCH3) and syringol, a hydroxydimethoxybenzene have also been studied. These results will aid in the understanding of the thermal fragmentation of sinapyl alcohol, the most complex lignin monomer. In addition to the model compound work, pyrolyisis of biomass has been studied via the pulsed laser ablation of poplar wood. With the REMPI scheme, aromatic lignin decomposition

Vanadium Compounds as PTP Inhibitors

Directory of Open Access Journals (Sweden)

Elsa Irving

2017-12-01

Full Text Available Phosphotyrosine signaling is regulated by the opposing actions of protein tyrosine kinases (PTKs and protein tyrosine phosphatases (PTPs. Here we discuss the potential of vanadium derivatives as PTP enzyme inhibitors and metallotherapeutics. We describe how vanadate in the V oxidized state is thought to inhibit PTPs, thus acting as a pan-inhibitor of this enzyme superfamily. We discuss recent developments in the biological and biochemical actions of more complex vanadium derivatives, including decavanadate and in particular the growing number of oxidovanadium compounds with organic ligands. Pre-clinical studies involving these compounds are discussed in the anti-diabetic and anti-cancer contexts. Although in many cases PTP inhibition has been implicated, it is also clear that many such compounds have further biochemical effects in cells. There also remain concerns surrounding off-target toxicities and long-term use of vanadium compounds in vivo in humans, hindering their progress through clinical trials. Despite these current misgivings, interest in these chemicals continues and many believe they could still have therapeutic potential. If so, we argue that this field would benefit from greater focus on improving the delivery and tissue targeting of vanadium compounds in order to minimize off-target toxicities. This may then harness their full therapeutic potential.

A Compound Model for the Origin of Earth's Water

Science.gov (United States)

Izidoro, A.; de Souza Torres, K.; Winter, O. C.; Haghighipour, N.

2013-04-01

One of the most important subjects of debate in the formation of the solar system is the origin of Earth's water. Comets have long been considered as the most likely source of the delivery of water to Earth. However, elemental and isotopic arguments suggest a very small contribution from these objects. Other sources have also been proposed, among which local adsorption of water vapor onto dust grains in the primordial nebula and delivery through planetesimals and planetary embryos have become more prominent. However, no sole source of water provides a satisfactory explanation for Earth's water as a whole. In view of that, using numerical simulations, we have developed a compound model incorporating both the principal endogenous and exogenous theories, and investigating their implications for terrestrial planet formation and water delivery. Comets are also considered in the final analysis, as it is likely that at least some of Earth's water has cometary origin. We analyze our results comparing two different water distribution models, and complement our study using the D/H ratio, finding possible relative contributions from each source and focusing on planets formed in the habitable zone. We find that the compound model plays an important role by showing greater advantage in the amount and time of water delivery in Earth-like planets.

A COMPOUND MODEL FOR THE ORIGIN OF EARTH'S WATER

International Nuclear Information System (INIS)

Izidoro, A.; Winter, O. C.; De Souza Torres, K.; Haghighipour, N.

2013-01-01

One of the most important subjects of debate in the formation of the solar system is the origin of Earth's water. Comets have long been considered as the most likely source of the delivery of water to Earth. However, elemental and isotopic arguments suggest a very small contribution from these objects. Other sources have also been proposed, among which local adsorption of water vapor onto dust grains in the primordial nebula and delivery through planetesimals and planetary embryos have become more prominent. However, no sole source of water provides a satisfactory explanation for Earth's water as a whole. In view of that, using numerical simulations, we have developed a compound model incorporating both the principal endogenous and exogenous theories, and investigating their implications for terrestrial planet formation and water delivery. Comets are also considered in the final analysis, as it is likely that at least some of Earth's water has cometary origin. We analyze our results comparing two different water distribution models, and complement our study using the D/H ratio, finding possible relative contributions from each source and focusing on planets formed in the habitable zone. We find that the compound model plays an important role by showing greater advantage in the amount and time of water delivery in Earth-like planets.

Adhesives from modified soy protein

Science.gov (United States)

Sun, Susan [Manhattan, KS; Wang, Donghai [Manhattan, KS; Zhong, Zhikai [Manhattan, KS; Yang, Guang [Shanghai, CN

2008-08-26

The present invention provides useful adhesive compositions having similar adhesive properties to conventional UF and PPF resins. The compositions generally include a protein portion and modifying ingredient portion selected from the group consisting of carboxyl-containing compounds, aldehyde-containing compounds, epoxy group-containing compounds, and mixtures thereof. The composition is preferably prepared at a pH level at or near the isoelectric point of the protein. In other preferred forms, the adhesive composition includes a protein portion and a carboxyl-containing group portion.

Participation of oxidized sulfur center in intramolecular free radical processes in the model organic compounds of biological importance

International Nuclear Information System (INIS)

Pogocki, D.M.

2004-01-01

The pathogenesis of neurodegenerative diseases such as prion diseases (Creutzfeldt-Jacob disease) and Alzheimer's disease is strongly associated with the presence of β-amyloid peptide (βA) and prion protein (hPrP) in the brain tissue. Both macromolecules contain methionine (Met) residues. Their presence seems to be responsible for unique redox properties of βA and hPrP. These residues may undergo relatively easy autooxidation and/or metal-catalysed oxidation. The presented studies were focused on the potential function of Met residues as antioxidants or pro-oxidants and on their role in radical-mediated oxidation of peptides and proteins. The role of S-, O-, N- and C-centered radicals generated in various oligopeptides containing Met and relevant model compounds has been examined in detail with respect to formation of 2c-3e bonds, redox processes, fragmentation and their mutual interconversion. In order to achieve these goals several experimental radiation, photochemical, and molecular modelling methods were applied. The experimental and molecular modelling results show significant influence of functional neighbouring groups and conformational flexibility of a peptide backbone on the oxidative reduction pathway in oligopeptides containing single and multiple Met residues. The results presented here allow for better understanding of the known propensities of βA and hPrP to reduce transition metals and to form reactive oxygen species and free radicals. (author)

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

Science.gov (United States)

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.

Toxic Compound, Anti-Nutritional Factors and Functional Properties of Protein Isolated from Detoxified Jatropha curcas Seed Cake

OpenAIRE

Worapot Suntornsuk; Donlaporn Saetae

2010-01-01

Jatropha curcas is a multipurpose tree, which has potential as an alternative source for biodiesel. All of its parts can also be used for human food, animal feed, fertilizer, fuel and traditional medicine. J. curcas seed cake is a low-value by-product obtained from biodiesel production. The seed cake, however, has a high amount of protein, with the presence of a main toxic compound: phorbol esters as well as anti-nutritional factors: trypsin inhibitors, phytic acid, lectin and saponin. The ob...

A compound memristive synapse model for statistical learning through STDP in spiking neural networks

Directory of Open Access Journals (Sweden)

Johannes eBill

2014-12-01

Full Text Available Memristors have recently emerged as promising circuit elements to mimic the function of biological synapses in neuromorphic computing. The fabrication of reliable nanoscale memristive synapses, that feature continuous conductance changes based on the timing of pre- and postsynaptic spikes, has however turned out to be challenging. In this article, we propose an alternative approach, the compound memristive synapse, that circumvents this problem by the use of memristors with binary memristive states. A compound memristive synapse employs multiple bistable memristors in parallel to jointly form one synapse, thereby providing a spectrum of synaptic efficacies. We investigate the computational implications of synaptic plasticity in the compound synapse by integrating the recently observed phenomenon of stochastic filament formation into an abstract model of stochastic switching. Using this abstract model, we first show how standard pulsing schemes give rise to spike-timing dependent plasticity (STDP with a stabilizing weight dependence in compound synapses. In a next step, we study unsupervised learning with compound synapses in networks of spiking neurons organized in a winner-take-all architecture. Our theoretical analysis reveals that compound-synapse STDP implements generalized Expectation-Maximization in the spiking network. Specifically, the emergent synapse configuration represents the most salient features of the input distribution in a Mixture-of-Gaussians generative model. Furthermore, the network’s spike response to spiking input streams approximates a well-defined Bayesian posterior distribution. We show in computer simulations how such networks learn to represent high-dimensional distributions over images of handwritten digits with high fidelity even in presence of substantial device variations and under severe noise conditions. Therefore, the compound memristive synapse may provide a synaptic design principle for future neuromorphic

A compound memristive synapse model for statistical learning through STDP in spiking neural networks.

Science.gov (United States)

Bill, Johannes; Legenstein, Robert

2014-01-01

Memristors have recently emerged as promising circuit elements to mimic the function of biological synapses in neuromorphic computing. The fabrication of reliable nanoscale memristive synapses, that feature continuous conductance changes based on the timing of pre- and postsynaptic spikes, has however turned out to be challenging. In this article, we propose an alternative approach, the compound memristive synapse, that circumvents this problem by the use of memristors with binary memristive states. A compound memristive synapse employs multiple bistable memristors in parallel to jointly form one synapse, thereby providing a spectrum of synaptic efficacies. We investigate the computational implications of synaptic plasticity in the compound synapse by integrating the recently observed phenomenon of stochastic filament formation into an abstract model of stochastic switching. Using this abstract model, we first show how standard pulsing schemes give rise to spike-timing dependent plasticity (STDP) with a stabilizing weight dependence in compound synapses. In a next step, we study unsupervised learning with compound synapses in networks of spiking neurons organized in a winner-take-all architecture. Our theoretical analysis reveals that compound-synapse STDP implements generalized Expectation-Maximization in the spiking network. Specifically, the emergent synapse configuration represents the most salient features of the input distribution in a Mixture-of-Gaussians generative model. Furthermore, the network's spike response to spiking input streams approximates a well-defined Bayesian posterior distribution. We show in computer simulations how such networks learn to represent high-dimensional distributions over images of handwritten digits with high fidelity even in presence of substantial device variations and under severe noise conditions. Therefore, the compound memristive synapse may provide a synaptic design principle for future neuromorphic architectures.

Comparing humic substance and protein compound effects on the bioaccumulation of perfluoroalkyl substances by Daphnia magna in water.

Science.gov (United States)

Xia, Xinghui; Dai, Zhineng; Rabearisoa, Andry Harinaina; Zhao, Pujun; Jiang, Xiaoman

2015-01-01

The influence of humic substances and protein compounds on the bioaccumulation of six types of perfluoroalkyl substances (PFASs) in Daphnia magna was compared. The humic substances included humic acid (HA) and fulvic acid (FA), the protein compounds included chicken egg albumin (albumin) and peptone, and the PFASs included perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid, perfluoroundecanoic acid, and perfluorododecanoic acid. Four concentrations (0, 1, 10, and 20 mg L(-1)) of the four dissolved organic matter (DOM) types were investigated. At the 1 mg L(-1) level, HA and albumin enhanced all tested PFAS bioaccumulation, whereas FA and peptone only enhanced the bioaccumulation of shorter-chain PFASs (PFOS, PFOA, and PFNA). However, all four DOM types decreased all tested PFAS bioaccumulation at the 20 mg L(-1) level, and the decreasing ratios of bioaccumulation factors caused by FA, HA, albumin, and peptone were 1-49%, 23-77%, 17-58%, and 8-56%, respectively compared with those without DOM. This is because DOM not only reduced the bioavailable concentrations and uptake rates of PFASs but also lowered the elimination rates of PFASs in D. magna, and these opposite effects would change with different DOM types and concentrations. Although the partition coefficients (L kg(-1)) of PFASs between HA and water (10(4.21)-10(4.98)) were much lower than those between albumin and water (10(4.92)-10(5.86)), their effects on PFAS bioaccumulation were comparable. This study suggests that although PFASs are a type of proteinophilic compounds, humic substances also have important effects on their bioavailability and bioaccumulation in aquatic organisms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Selective cleavage of the C(α)-C(β) linkage in lignin model compounds via Baeyer-Villiger oxidation.

Science.gov (United States)

Patil, Nikhil D; Yao, Soledad G; Meier, Mark S; Mobley, Justin K; Crocker, Mark

2015-03-21

Lignin is an amorphous aromatic polymer derived from plants and is a potential source of fuels and bulk chemicals. Herein, we present a survey of reagents for selective stepwise oxidation of lignin model compounds. Specifically, we have targeted the oxidative cleavage of Cα-Cβ bonds as a means to depolymerize lignin and obtain useful aromatic compounds. In this work, we prepared several lignin model compounds that possess structures, characteristic reactivity, and linkages closely related to the parent lignin polymer. We observed that selective oxidation of benzylic hydroxyl groups, followed by Baeyer-Villiger oxidation of the resulting ketones, successfully cleaves the Cα-Cβ linkage in these model compounds.

The Dangling model in the construction of compound sentences with regard to verb tenses

Directory of Open Access Journals (Sweden)

Mahmoud Mehravaran

2016-02-01

the mistakes of some of the grammars. This research project has for the first time introduced constructive models of compound sentences in a comprehensive research taking in to account the tense of the verbs. The primary question in this research project is which kind of sentences can be considered as compound and what is the constructive of such a sentence? When defining a compound sentences, grammarians either shave the same beliefs or differ in their ideas. But all grammarians agree to the fact that a compound sentences has more than one verb. Different definitions are due to different criteria adapted in constructing a compound sentences. To construct a noun, and adjective, a verb and a sentence we should take similar and precise criteria to our consideration. In the grammatical units of noun, adjectives, and verbs construction means connecting two or more parts that can convey one similar meaning and its parts are dependent upon one another.  In the construction of compound sentences there must be the same criteria so that its applications can be truly recognized and identified just like the previously mentioned grammatical units. The first step to arrive at a criterion in defining and identifying compound sentences, is to separate this discussion from connective sentences that are relate to each other with connectives are called connective sentences. But sentences which are constructed with dependent making connectives and their parts are dependent upon one another are called compound sentences. Therefore the signs of compound sentences with regard to constructions and the meaning of criterion are as follows: 1 They have more than one verb. 2 The consistence of two or more dependent phrases. 3 Phrases construct a complete sentences all together and convey one similar message. 4 One of the phrases is the main clause and the other one is the subordinate one. 5 The phrases or subordinate clauses can be related to one of the major parts and they can take a

Achievement report for fiscal 1999 on research and development of technologies for medical welfare equipment. Computer-assisted analysis system for medicinal compounds; 1999 nendo iryo fukushi kiki gijutsu kenkyu kaihatsu seika hokokusho. Iyo kagobutsu sukuriningu shien system

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-05-01

This system aims to support the selection and development of optimal compounds by resorting to compound classification, molecular superpositioning, acceptor model construction, etc., when information on the target protein structures of the numerous active compounds found by HTS (high throughput screening) is not available and, when available, by resorting to 3-dimensional protein structure modelling, docking study, etc. Investigated in this fiscal year for incorporation into the system are (1) a method of constructing a database of compounds, (2) method of classifying compounds, (3) method of molecular superpositioning, (4) development of a method of 3-dimensional protein structure modelling, and (5) a total system. In relation with item (1), investigations are conducted into the contents and management of HTS target compound data, and methods of incorporating the data into this system are studied. In relation with item (2), surveys and studies are conducted about methods of classification based on skeletal structures. In relation with item (3), application to the analysis of HTS active compounds is taken into consideration when problems are investigated relative to prior arts in molecular superpositioning. In relation with item (4), protein side chain conformation prediction methods are surveyed and studied. In relation with item (5), a user interface is developed and tentatively constructed for a total system. (NEDO)

Virtual Screening of M3 Protein Antagonists for Finding a Model to Study the Gammaherpesvirus Damaged Immune System and Chemokine Related Diseases

Directory of Open Access Journals (Sweden)

Ibrahim Torktaz

2013-12-01

Full Text Available Introduction: M3 protein is a chemokine decoy receptor involved in pathogenesis of persistent infection with gammaherpesvirus and complications related to the latency of this pathogen. We proposed that antagonists of the M3 would provide a unique opportunity for studying new therapeutic strategies in disordered immune system, immune-deficient states and role of chemokines in pathogenesis development. Methods: Comparative modeling and fold recognition algorithms have been used for prediction of M3 protein 3-D model. Evaluation of the models using Q-mean and ProSA-web score, has led to choosing predicted model by fold recognition algorithm as the best model which was minimized regarding energy level using Molegro Virtual Docker 2011.4.3.0 (MVD software. Pockets and active sites of model were recognized using MVD cavity detection, and MetaPocket algorithms. Ten thousand compounds accessible on KEGG database were screened; MVD was used for computer simulated docking study; MolDock SE was selected as docking scoring function and final results were evaluated based on MolDock and Re-rank score. Results: Docking data suggested that prilocaine, which is generally applied as a topical anesthetic, binds strongly to 3-D model of M3 protein. Conclusion: This study proposes that prilocaine is a potential inhibitor of M3 protein and possibly has immune enhancing properties.

Model for calculation of electrostatic contribution into protein stability

Science.gov (United States)

Kundrotas, Petras; Karshikoff, Andrey

2003-03-01

Existing models of the denatured state of proteins consider only one possible spatial distribution of protein charges and therefore are applicable to a limited number of cases. In this presentation a more general framework for the modeling of the denatured state is proposed. It is based on the assumption that the titratable groups of an unfolded protein can adopt a quasi-random distribution, restricted by the protein sequence. The model was tested on two proteins, barnase and N-terminal domain of the ribosomal protein L9. The calculated free energy of denaturation, Δ G( pH), reproduces the experimental data essentially better than the commonly used null approximation (NA). It was demonstrated that the seemingly good agreement with experimental data obtained by NA originates from the compensatory effect between the pair-wise electrostatic interactions and the desolvation energy of the individual sites. It was also found that the ionization properties of denatured proteins are influenced by the protein sequence.

In vivo stability and inertness of various direct labelled and chelate-tagged protein

International Nuclear Information System (INIS)

Janoki, A.; Korosi, L.; Klivenyi, G.; Spett, B.

1987-01-01

There were looking for methods giving precise information about composition and activity distribution of protein components, both in the initial samples and serum samples after intravenous administration. It was tested the applicability of electroimmunoassay, polyacrilamide gel electrophoresis and high performance liquid chromatography for the assessment of in vivo stability and labelled proteins. The model compound was human serum albumin (HSA) labelled with 99m Tc and 125 I, respectively. Bifunctional chelate labelling was done with desferrioxamine, in this case protein was labelled with 67 Ga. Biodistribution of the labelled compounds and their elimination from the blood were studied in rabbits. Experience with various labelling proteins, especially with Tc-Sn-HSA system indicate that in vivo stability of this compounds are generally low. Following intravenous injection of proteins labelled with metal isotopes, due to dilution and to the presence of considerable amount of compatitive protein in the serum, part of the label is being detached from the carrier protein. Distribution of the detached metal is different from the original distribution of the protein. This problem arises also with radiopharmaceuticals based on monoclonal antibodies. (M.E.L.) [es

Sampling and energy evaluation challenges in ligand binding protein design.

Science.gov (United States)

Dou, Jiayi; Doyle, Lindsey; Jr Greisen, Per; Schena, Alberto; Park, Hahnbeom; Johnsson, Kai; Stoddard, Barry L; Baker, David

2017-12-01

The steroid hormone 17α-hydroxylprogesterone (17-OHP) is a biomarker for congenital adrenal hyperplasia and hence there is considerable interest in development of sensors for this compound. We used computational protein design to generate protein models with binding sites for 17-OHP containing an extended, nonpolar, shape-complementary binding pocket for the four-ring core of the compound, and hydrogen bonding residues at the base of the pocket to interact with carbonyl and hydroxyl groups at the more polar end of the ligand. Eight of 16 designed proteins experimentally tested bind 17-OHP with micromolar affinity. A co-crystal structure of one of the designs revealed that 17-OHP is rotated 180° around a pseudo-two-fold axis in the compound and displays multiple binding modes within the pocket, while still interacting with all of the designed residues in the engineered site. Subsequent rounds of mutagenesis and binding selection improved the ligand affinity to nanomolar range, while appearing to constrain the ligand to a single bound conformation that maintains the same "flipped" orientation relative to the original design. We trace the discrepancy in the design calculations to two sources: first, a failure to model subtle backbone changes which alter the distribution of sidechain rotameric states and second, an underestimation of the energetic cost of desolvating the carbonyl and hydroxyl groups of the ligand. The difference between design model and crystal structure thus arises from both sampling limitations and energy function inaccuracies that are exacerbated by the near two-fold symmetry of the molecule. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Development of corresponding states model for estimation of the surface tension of chemical compounds

DEFF Research Database (Denmark)

Gharagheizi, Farhad; Eslamimanesh, Ali; Sattari, Mehdi

2013-01-01

include critical temperature or temperature/critical volume/acentric factor/critical pressure/reduced temperature/reduced normal boiling point temperature/molecular weight of the compounds. Around 1,300 surface tension data of 118 random compounds are used for developing the first model (a four...

Repair of model compounds of photoinduced lesions in DNA. Electrochemical approaches

International Nuclear Information System (INIS)

Boussicault, F.

2006-09-01

The goal of this work is to better understand the repair mechanism of photoinduced lesions in DNA (cyclobutane dimers and pyrimidine (6-4) pyrimidone adducts) by photolyase redox enzymes, using tools and concepts of molecular electrochemistry. Thanks to the study of model compounds of cyclobutane lesions by cyclic voltametry, we have been able to mimic the key step of the enzymatic repair (dissociative electron transfer) and to monitor the repair of model compounds by Escherichia coli DNA photolyase. From these results, we have discussed the repair mechanism, especially the stepwise or concerted character of the process. Repair mechanism of (6-4) adducts is not known now, but a possible pathway implies an electron transfer coupled to the cleavage of two bonds in the closed form of the lesions (oxetanes). Voltammetric study of reduction and oxidation of model oxetanes and their repair by E. coli DNA photolyase gave some experimental evidence confirming the proposed mechanism and allowing a better understanding of it. (author)

Discrete persistent-chain model for protein binding on DNA.

Science.gov (United States)

Lam, Pui-Man; Zhen, Yi

2011-04-01

We describe and solve a discrete persistent-chain model of protein binding on DNA, involving an extra σ(i) at a site i of the DNA. This variable takes the value 1 or 0, depending on whether or not the site is occupied by a protein. In addition, if the site is occupied by a protein, there is an extra energy cost ɛ. For a small force, we obtain analytic expressions for the force-extension curve and the fraction of bound protein on the DNA. For higher forces, the model can be solved numerically to obtain force-extension curves and the average fraction of bound proteins as a function of applied force. Our model can be used to analyze experimental force-extension curves of protein binding on DNA, and hence deduce the number of bound proteins in the case of nonspecific binding. ©2011 American Physical Society

Selecting a Response in Task Switching: Testing a Model of Compound Cue Retrieval

Science.gov (United States)

Schneider, Darryl W.; Logan, Gordon D.

2009-01-01

How can a task-appropriate response be selected for an ambiguous target stimulus in task-switching situations? One answer is to use compound cue retrieval, whereby stimuli serve as joint retrieval cues to select a response from long-term memory. In the present study, the authors tested how well a model of compound cue retrieval could account for a…

Chemical-genetic profile analysis of five inhibitory compounds in yeast.

Science.gov (United States)

Alamgir, Md; Erukova, Veronika; Jessulat, Matthew; Azizi, Ali; Golshani, Ashkan

2010-08-06

Chemical-genetic profiling of inhibitory compounds can lead to identification of their modes of action. These profiles can help elucidate the complex interactions between small bioactive compounds and the cell machinery, and explain putative gene function(s). Colony size reduction was used to investigate the chemical-genetic profile of cycloheximide, 3-amino-1,2,4-triazole, paromomycin, streptomycin and neomycin in the yeast Saccharomyces cerevisiae. These compounds target the process of protein biosynthesis. More than 70,000 strains were analyzed from the array of gene deletion mutant yeast strains. As expected, the overall profiles of the tested compounds were similar, with deletions for genes involved in protein biosynthesis being the major category followed by metabolism. This implies that novel genes involved in protein biosynthesis could be identified from these profiles. Further investigations were carried out to assess the activity of three profiled genes in the process of protein biosynthesis using relative fitness of double mutants and other genetic assays. Chemical-genetic profiles provide insight into the molecular mechanism(s) of the examined compounds by elucidating their potential primary and secondary cellular target sites. Our follow-up investigations into the activity of three profiled genes in the process of protein biosynthesis provided further evidence concerning the usefulness of chemical-genetic analyses for annotating gene functions. We termed these genes TAE2, TAE3 and TAE4 for translation associated elements 2-4.

The effect of high pressure on nitrogen compounds of milk

International Nuclear Information System (INIS)

Kielczewska, Katarzyna; Czerniewicz, Maria; Michalak, Joanna; Brandt, Waldemar

2004-01-01

The effect of pressurization at different pressures (from 200 to 1000 MPa, at 200 MPa intervals, t const. = 15 min) and periods of time (from 15 to 35 min, at 10 min intervals, p const. = 800 MPa) on the changes of proteins and nitrogen compounds of skimmed milk was studied. The pressurization caused an increase in the amount of soluble casein and denaturation of whey proteins. The level of nonprotein nitrogen compounds and proteoso-peptone nitrogen compounds increased as a result of the high-pressure treatment. These changes increased with an increase in pressure and exposure time. High-pressure treatment considerably affected the changes in the conformation of milk proteins, which was reflected in the changes in the content of proteins sedimenting and an increase in their degree of hydration

The MCRA model for probabilistic single-compound and cumulative risk assessment of pesticides.

Science.gov (United States)

van der Voet, Hilko; de Boer, Waldo J; Kruisselbrink, Johannes W; Goedhart, Paul W; van der Heijden, Gerie W A M; Kennedy, Marc C; Boon, Polly E; van Klaveren, Jacob D

2015-05-01

Pesticide risk assessment is hampered by worst-case assumptions leading to overly pessimistic assessments. On the other hand, cumulative health effects of similar pesticides are often not taken into account. This paper describes models and a web-based software system developed in the European research project ACROPOLIS. The models are appropriate for both acute and chronic exposure assessments of single compounds and of multiple compounds in cumulative assessment groups. The software system MCRA (Monte Carlo Risk Assessment) is available for stakeholders in pesticide risk assessment at mcra.rivm.nl. We describe the MCRA implementation of the methods as advised in the 2012 EFSA Guidance on probabilistic modelling, as well as more refined methods developed in the ACROPOLIS project. The emphasis is on cumulative assessments. Two approaches, sample-based and compound-based, are contrasted. It is shown that additional data on agricultural use of pesticides may give more realistic risk assessments. Examples are given of model and software validation of acute and chronic assessments, using both simulated data and comparisons against the previous release of MCRA and against the standard software DEEM-FCID used by the Environmental Protection Agency in the USA. It is shown that the EFSA Guidance pessimistic model may not always give an appropriate modelling of exposure. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Comparison of Nitrogen Bioaccessibility from Salmon and Whey Protein Hydrolysates using a Human Gastrointestinal Model (TIM-1

Directory of Open Access Journals (Sweden)

Bomi Framroze

2014-05-01

Full Text Available Background: The TIM-1 system is a computer-controlled multi-compartmental dynamic model that closely simulates in vivo gastrointestinal tract digestion in humans. During digestion, the compounds released from meal matrix by gastric and intestinal secretions (enzymes are progressively absorbed through semipermeable membranes depending on their molecular weight. These absorbed (dialysed compounds are considered as bioaccessible, which means that they can be theoretically absorbed by the small intestine in the body. Methods: Salmon protein hydrolysate (SPH, whey protein hydrolysates extensively (WPHHigh or weakly (WPH-Low hydrolysed, non-hydrolysed whey protein isolate (WPI and mixtures of WPI:SPH (90:10, 80:20 were digested in TIM-1 using the conditions for a fast gastrointestinal transit that simulate the digestion of a liquid meal in human adults. During digestion (2 hours, samples were collected in intestinal compartments (duodenum, jejunum, and ileum and in both jejunal and ileal dialysates to determine their nitrogen content. All the products were compared in terms of kinetics of nitrogen absorption through the semipermeable membranes (bioaccessible nitrogen and nitrogen distribution throughout the intestinal compartments at the end of the 2 hour digestion. Results: After a 2 h-digestion in TIM-1, SPH was the protein substrate from which the highest amount of nitrogen (67.0% becomes available for the small intestine absorption. WPH-High had the second highest amount (56.0% of bioaccessible nitrogen while this amount decreased to 38.5–42.2% for the other protein substrates. The high nitrogen bioaccessibility of SPH is consistent with its richness in low molecular weight peptides (50% < 1000 Da. Conclusions: The results of this study indicate that SPH provides a higher proportion of bioaccessible nitrogen to a healthy adult compared to all forms of whey proteins, including extensively hydrolysed whey protein hydrolysate. The substitution of

Modeling Mercury in Proteins

Energy Technology Data Exchange (ETDEWEB)

Smith, Jeremy C [ORNL; Parks, Jerry M [ORNL

2016-01-01

Mercury (Hg) is a naturally occurring element that is released into the biosphere both by natural processes and anthropogenic activities. Although its reduced, elemental form Hg(0) is relatively non-toxic, other forms such as Hg2+ and, in particular, its methylated form, methylmercury, are toxic, with deleterious effects on both ecosystems and humans. Microorganisms play important roles in the transformation of mercury in the environment. Inorganic Hg2+ can be methylated by certain bacteria and archaea to form methylmercury. Conversely, bacteria also demethylate methylmercury and reduce Hg2+ to relatively inert Hg(0). Transformations and toxicity occur as a result of mercury interacting with various proteins. Clearly, then, understanding the toxic effects of mercury and its cycling in the environment requires characterization of these interactions. Computational approaches are ideally suited to studies of mercury in proteins because they can provide a detailed picture and circumvent issues associated with toxicity. Here we describe computational methods for investigating and characterizing how mercury binds to proteins, how inter- and intra-protein transfer of mercury is orchestrated in biological systems, and how chemical reactions in proteins transform the metal. We describe quantum chemical analyses of aqueous Hg(II), which reveal critical factors that determine ligand binding propensities. We then provide a perspective on how we used chemical reasoning to discover how microorganisms methylate mercury. We also highlight our combined computational and experimental studies of the proteins and enzymes of the mer operon, a suite of genes that confers mercury resistance in many bacteria. Lastly, we place work on mercury in proteins in the context of what is needed for a comprehensive multi-scale model of environmental mercury cycling.

Drosophila melanogaster as a model system for the evaluation of anti-aging compounds.

Science.gov (United States)

Jafari, Mahtab

2010-01-01

Understanding the causes of aging is a complex problem due to the multiple factors that influence aging, which include genetics, environment, metabolism and reproduction, among others. These multiple factors create logistical difficulties in the evaluation of anti-aging agents. There is a need for good model systems to evaluate potential anti-aging compounds. The model systems used should represent the complexities of aging in humans, so that the findings may be extrapolated to human studies, but they should also present an opportunity to minimize the variables so that the experimental results can be accurately interpreted. In addition to positively affecting lifespan, the impact of the compound on the physiologic confounders of aging, including fecundity and the health span--the period of life where an organism is generally healthy and free from serious or chronic illness--of the model organism needs to be evaluated. Fecundity is considered a major confounder of aging in fruit flies. It is well established that female flies that are exposed to toxic substances typically reduce their dietary intake and their reproductive output and display an artifactual lifespan extension. As a result, drugs that achieve longevity benefits by reducing fecundity as a result of diminished food intake are probably not useful candidates for eventual treatment of aging in humans and should be eliminated during the screening process. Drosophila melanogaster provides a suitable model system for the screening of anti-aging compounds as D. melanogaster and humans have many conserved physiological and biological pathways. In this paper, I propose an algorithm to screen anti-aging compounds using Drosophila melanogaster as a model system.

The use of quantum chemically derived descriptors for QSAR modelling of reductive dehalogenation of aromatic compounds

NARCIS (Netherlands)

Rorije E; Richter J; Peijnenburg WJGM; ECO; IHE Delft

1994-01-01

In this study, quantum-chemically derived parameters are developed for a limited number of halogenated aromatic compounds to model the anaerobic reductive dehalogenation reaction rate constants of these compounds. It is shown that due to the heterogeneity of the set of compounds used, no single

Using affinity capillary electrophoresis and computational models for binding studies of heparinoids with p-selectin and other proteins.

Science.gov (United States)

Mozafari, Mona; Balasupramaniam, Shantheya; Preu, Lutz; El Deeb, Sami; Reiter, Christian G; Wätzig, Hermann

2017-06-01

A fast and precise affinity capillary electrophoresis (ACE) method has been developed and applied for the investigation of the binding interactions between P-selectin and heparinoids as potential P-selectin inhibitors in the presence and absence of calcium ions. Furthermore, model proteins and vitronectin were used to appraise the binding behavior of P-selectin. The normalized mobility ratios (∆R/R f ), which provided information about the binding strength and the overall charge of the protein-ligand complex, were used to evaluate the binding affinities. It was found that P-selectin interacts more strongly with heparinoids in the presence of calcium ions. P-selectin was affected by heparinoids at the concentration of 3 mg/L. In addition, the results of the ACE experiments showed that among other investigated proteins, albumins and vitronectin exhibited strong interactions with heparinoids. Especially with P-selectin and vitronectin, the interaction may additionally induce conformational changes. Subsequently, computational models were applied to interpret the ACE experiments. Docking experiments explained that the binding of heparinoids on P-selectin is promoted by calcium ions. These docking models proved to be particularly well suited to investigate the interaction of charged compounds, and are therefore complementary to ACE experiments. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Neurotoxicity in Preclinical Models of Occupational Exposure to Organophosphorus Compounds

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Voorhees, Jaymie R.; Rohlman, Diane S.; Lein, Pamela J.; Pieper, Andrew A.

2017-01-01

Organophosphorus (OPs) compounds are widely used as insecticides, plasticizers, and fuel additives. These compounds potently inhibit acetylcholinesterase (AChE), the enzyme that inactivates acetylcholine at neuronal synapses, and acute exposure to high OP levels can cause cholinergic crisis in humans and animals. Evidence further suggests that repeated exposure to lower OP levels insufficient to cause cholinergic crisis, frequently encountered in the occupational setting, also pose serious risks to people. For example, multiple epidemiological studies have identified associations between occupational OP exposure and neurodegenerative disease, psychiatric illness, and sensorimotor deficits. Rigorous scientific investigation of the basic science mechanisms underlying these epidemiological findings requires valid preclinical models in which tightly-regulated exposure paradigms can be correlated with neurotoxicity. Here, we review the experimental models of occupational OP exposure currently used in the field. We found that animal studies simulating occupational OP exposures do indeed show evidence of neurotoxicity, and that utilization of these models is helping illuminate the mechanisms underlying OP-induced neurological sequelae. Still, further work is necessary to evaluate exposure levels, protection methods, and treatment strategies, which taken together could serve to modify guidelines for improving workplace conditions globally. PMID:28149268

DJ-1-dependent protective activity of DJ-1-binding compound no. 23 against neuronal cell death in MPTP-treated mouse model of Parkinson's disease

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Kazuko Takahashi-Niki

2015-03-01

Full Text Available Parkinson's disease (PD is caused by dopaminergic cell death in the substantia nigra, leading to a reduced level of dopamine in the striatum. Oxidative stress is one of the causes of PD. Since symptomatic PD therapies are used, identification of compounds or proteins that inhibit oxidative stress-induced neuronal cell death is necessary. DJ-1 is a causative gene product of familial PD and plays a role in anti-oxidative stress reaction. We have identified various DJ-1-binding compounds, including compound-23, that restored neuronal cell death and locomotion defects observed in neurotoxin-induced PD models. In this study, wild-type and DJ-1-knockout mice were injected intraperitoneally with 1 mg/kg of compound-23 and then with 30 mg/kg of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP at 1 h after injection. Five days after administration, the effects of compound-23 on MPTP-induced locomotion deficits, on dopaminergic cell death and on brain dopamine levels were analyzed by rotor rod tests, by staining cells with an anti-TH antibody and by an HPLC, respectively. The results showed that compound-23 inhibited MPTP-induced reduction of retention time on the rotor rod bar, neuronal cell death in the substantia nigra and striatum and dopamine content in wild-type mice but not in DJ-1-knockout mice, indicating a DJ-1-dependent effect of compound-23.

Protein Folding: Search for Basic Physical Models

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Ivan Y. Torshin

2003-01-01

Full Text Available How a unique three-dimensional structure is rapidly formed from the linear sequence of a polypeptide is one of the important questions in contemporary science. Apart from biological context of in vivo protein folding (which has been studied only for a few proteins, the roles of the fundamental physical forces in the in vitro folding remain largely unstudied. Despite a degree of success in using descriptions based on statistical and/or thermodynamic approaches, few of the current models explicitly include more basic physical forces (such as electrostatics and Van Der Waals forces. Moreover, the present-day models rarely take into account that the protein folding is, essentially, a rapid process that produces a highly specific architecture. This review considers several physical models that may provide more direct links between sequence and tertiary structure in terms of the physical forces. In particular, elaboration of such simple models is likely to produce extremely effective computational techniques with value for modern genomics.

Structural and vibrational study of 8-hydroxyquinoline-2-carboxaldehyde isonicotinoyl hydrazone - A potential metal-protein attenuating compound (MPAC) for the treatment of Alzheimer's disease

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de Freitas, Leonardo Viana; da Silva, Cecilia C. P.; Ellena, Javier; Costa, Luiz Antônio Sodré; Rey, Nicolás A.

2013-12-01

A comprehensive structural and vibrational study of the potential metal-protein attenuating compound 8-hydroxyquinoline-2-carboxaldehyde isonicotinoyl hydrazone is reported. X-ray diffraction data, as well as FT-IR and Raman frequencies, were compared with the respective theoretical values obtained from DFT calculations. Theory agrees well with experiment. In this context, an attempt of total assignment concerning the FT-IR and Raman spectra of the title compound was performed, shedding new light on previous partial assignments published elsewhere.

Models of crk adaptor proteins in cancer.

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Bell, Emily S; Park, Morag

2012-05-01

The Crk family of adaptor proteins (CrkI, CrkII, and CrkL), originally discovered as the oncogene fusion product, v-Crk, of the CT10 chicken retrovirus, lacks catalytic activity but engages with multiple signaling pathways through their SH2 and SH3 domains. Crk proteins link upstream tyrosine kinase and integrin-dependent signals to downstream effectors, acting as adaptors in diverse signaling pathways and cellular processes. Crk proteins are now recognized to play a role in the malignancy of many human cancers, stimulating renewed interest in their mechanism of action in cancer progression. The contribution of Crk signaling to malignancy has been predominantly studied in fibroblasts and in hematopoietic models and more recently in epithelial models. A mechanistic understanding of Crk proteins in cancer progression in vivo is still poorly understood in part due to the highly pleiotropic nature of Crk signaling. Recent advances in the structural organization of Crk domains, new roles in kinase regulation, and increased knowledge of the mechanisms and frequency of Crk overexpression in human cancers have provided an incentive for further study in in vivo models. An understanding of the mechanisms through which Crk proteins act as oncogenic drivers could have important implications in therapeutic targeting.

Modelling Protein Dynamics on the Microsecond Time Scale

DEFF Research Database (Denmark)

Siuda, Iwona Anna

Recent years have shown an increase in coarse-grained (CG) molecular dynamics simulations, providing structural and dynamic details of large proteins and enabling studies of self-assembly of biological materials. It is not easy to acquire such data experimentally, and access is also still limited...... in atomistic simulations. During her PhD studies, Iwona Siuda used MARTINI CG models to study the dynamics of different globular and membrane proteins. In several cases, the MARTINI model was sufficient to study conformational changes of small, purely alpha-helical proteins. However, in studies of larger......ELNEDIN was therefore proposed as part of the work. Iwona Siuda’s results from the CG simulations had biological implications that provide insights into possible mechanisms of the periplasmic leucine-binding protein, the sarco(endo)plasmic reticulum calcium pump, and several proteins from the saposin-like proteins...

The Dangling model in the construction of compound sentences with regard to verb tenses

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Mahmoud Mehravaran

2016-01-01

the mistakes of some of the grammars. This research project has for the first time introduced constructive models of compound sentences in a comprehensive research taking in to account the tense of the verbs. The primary question in this research project is which kind of sentences can be considered as compound and what is the constructive of such a sentence? When defining a compound sentences, grammarians either shave the same beliefs or differ in their ideas. But all grammarians agree to the fact that a compound sentences has more than one verb. Different definitions are due to different criteria adapted in constructing a compound sentences. To construct a noun, and adjective, a verb and a sentence we should take similar and precise criteria to our consideration. In the grammatical units of noun, adjectives, and verbs construction means connecting two or more parts that can convey one similar meaning and its parts are dependent upon one another.  In the construction of compound sentences there must be the same criteria so that its applications can be truly recognized and identified just like the previously mentioned grammatical units. The first step to arrive at a criterion in defining and identifying compound sentences, is to separate this discussion from connective sentences that are relate to each other with connectives are called connective sentences. But sentences which are constructed with dependent making connectives and their parts are dependent upon one another are called compound sentences. Therefore the signs of compound sentences with regard to constructions and the meaning of criterion are as follows: 1 They have more than one verb. 2 The consistence of two or more dependent phrases. 3 Phrases construct a complete sentences all together and convey one similar message. 4 One of the phrases is the main clause and the other one is the subordinate one. 5 The phrases or subordinate clauses can be related to one of the major parts and they can take a

Immunogenicity of therapeutic proteins: the use of animal models.

Science.gov (United States)

Brinks, Vera; Jiskoot, Wim; Schellekens, Huub

2011-10-01

Immunogenicity of therapeutic proteins lowers patient well-being and drastically increases therapeutic costs. Preventing immunogenicity is an important issue to consider when developing novel therapeutic proteins and applying them in the clinic. Animal models are increasingly used to study immunogenicity of therapeutic proteins. They are employed as predictive tools to assess different aspects of immunogenicity during drug development and have become vital in studying the mechanisms underlying immunogenicity of therapeutic proteins. However, the use of animal models needs critical evaluation. Because of species differences, predictive value of such models is limited, and mechanistic studies can be restricted. This review addresses the suitability of animal models for immunogenicity prediction and summarizes the insights in immunogenicity that they have given so far.

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

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Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

2015-11-01

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

Quark compound Bag model for NN scattering up to 1 GeV

International Nuclear Information System (INIS)

Fasano, C.; Lee, T.S.H.

1987-01-01

A Quark Compound Bag model has been constructed to describe NN s-wave scattering up to 1 GeV. The model contains a vertex interaction H/sub D/leftrightarrow/NN/ for describing the excitation of a confined six-quark Bag state, and a meson-exchange interaction obtained from modifying the phenomenological core of the Paris potential. Explicit formalisms and numerical results are presented to reveal the role of the Bag excitation mechanism in determining the relative wave function, P- and S-matrix of NN scattering. We explore the merit as well as the shortcoming of the Quark Compound Bag model developed by the ITEP group. It is shown that the parameters of the vertex interaction H/sub D/leftrightarrow/NN/ can be more rigorously determined from the data if the notation of the Chiral/Cloudy Bag model is used to allow the presence of the background meson-exchange interaction inside Bag excitation region. The application of the model in the study of quark degrees of freedom in nuclei is discussed. 41 refs., 6 figs., 3 tabs

Scoring predictive models using a reduced representation of proteins: model and energy definition.

Science.gov (United States)

Fogolari, Federico; Pieri, Lidia; Dovier, Agostino; Bortolussi, Luca; Giugliarelli, Gilberto; Corazza, Alessandra; Esposito, Gennaro; Viglino, Paolo

2007-03-23

Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available, with different representation detail. Although the usefulness of many such models for structural bioinformatics applications has been demonstrated in recent years, there are few intermediate resolution models endowed with an energy model capable, for instance, of detecting native or native-like structures among decoy sets. The aim of the present work is to provide a discrete empirical potential for a reduced protein model termed here PC2CA, because it employs a PseudoCovalent structure with only 2 Centers of interactions per Amino acid, suitable for protein model quality assessment. All protein structures in the set top500H have been converted in reduced form. The distribution of pseudobonds, pseudoangle, pseudodihedrals and distances between centers of interactions have been converted into potentials of mean force. A suitable reference distribution has been defined for non-bonded interactions which takes into account excluded volume effects and protein finite size. The correlation between adjacent main chain pseudodihedrals has been converted in an additional energetic term which is able to account for cooperative effects in secondary structure elements. Local energy surface exploration is performed in order to increase the robustness of the energy function. The model and the energy definition proposed have been tested on all the multiple decoys' sets in the Decoys'R'us database. The energetic model is able to recognize, for almost all sets, native-like structures (RMSD less than 2.0 A). These results and those obtained in the blind CASP7 quality assessment experiment suggest that the model compares well with scoring potentials with finer granularity and could be useful for fast exploration of conformational space. Parameters are available at the url: http://www.dstb.uniud.it/~ffogolari/download/.

Ozonisation of model compounds as a pretreatment step for the biological wastewater treatment

International Nuclear Information System (INIS)

Degen, U.

1979-11-01

Biological degradability and toxicity of organic substances are two basic criteria determining their behaviour in natural environment and during the biological treatment of waste waters. In this work oxidation products of model compounds (p-toluenesulfonic acid, benzenesulfonic acid and aniline) generated by ozonation were tested in a two step laboratory plant with activated sludge. The organic oxidation products and the initial compounds were the sole source of carbon for the microbes of the adapted activated sludge. The progress of elimination of the compounds was studied by measuring DOC, COD, UV-spectra of the initial compounds and sulfate. Initial concentrations of the model compounds were 2-4 mmole/1 with 25-75ion of sulfonic acids. As oxidation products of p-toluenesulfonic acid the following compounds were identified and quantitatively measured: methylglyoxal, pyruvic acid, oxalic acid, acetic acid, formic acid and sulfate. With all the various solutions with different concentrations of initial compounds and oxidation products the biological activity in the two step laboratory plant could maintain. p-Toluenesulfonic acid and the oxidation products are biologically degraded. The degradation of p-toluenesulfonic acid is measured by following the increasing of the sulfate concentration after biological treatment. This shows that the elimination of p-toluenesulfonic acid is not an adsorption but a mineralization step. At high p-toluenesulfonic acid concentration and low concentration of oxidation products p-toluenesulfonic acid is eliminated with a high efficiency (4.3 mole/d m 3 = 0.34 kg p-toluenesulfonic acid/d m 3 ). However at high concentration of oxidation products p-toluenesulfonic acid is less degraded. The oxidation products are always degraded with an elimination efficiency of 70%. A high load of biologically degradable oxidation products diminished the elimination efficiency of p-toluenesulfonic acid. (orig.) [de

Chemical-genetic profile analysis of five inhibitory compounds in yeast

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Alamgir Md

2010-08-01

Full Text Available Abstract Background Chemical-genetic profiling of inhibitory compounds can lead to identification of their modes of action. These profiles can help elucidate the complex interactions between small bioactive compounds and the cell machinery, and explain putative gene function(s. Results Colony size reduction was used to investigate the chemical-genetic profile of cycloheximide, 3-amino-1,2,4-triazole, paromomycin, streptomycin and neomycin in the yeast Saccharomyces cerevisiae. These compounds target the process of protein biosynthesis. More than 70,000 strains were analyzed from the array of gene deletion mutant yeast strains. As expected, the overall profiles of the tested compounds were similar, with deletions for genes involved in protein biosynthesis being the major category followed by metabolism. This implies that novel genes involved in protein biosynthesis could be identified from these profiles. Further investigations were carried out to assess the activity of three profiled genes in the process of protein biosynthesis using relative fitness of double mutants and other genetic assays. Conclusion Chemical-genetic profiles provide insight into the molecular mechanism(s of the examined compounds by elucidating their potential primary and secondary cellular target sites. Our follow-up investigations into the activity of three profiled genes in the process of protein biosynthesis provided further evidence concerning the usefulness of chemical-genetic analyses for annotating gene functions. We termed these genes TAE2, TAE3 and TAE4 for translation associated elements 2-4.

Predicting nucleic acid binding interfaces from structural models of proteins.

Science.gov (United States)

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

2012-02-01

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

Fast loop modeling for protein structures

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Zhang, Jiong; Nguyen, Son; Shang, Yi; Xu, Dong; Kosztin, Ioan

2015-03-01

X-ray crystallography is the main method for determining 3D protein structures. In many cases, however, flexible loop regions of proteins cannot be resolved by this approach. This leads to incomplete structures in the protein data bank, preventing further computational study and analysis of these proteins. For instance, all-atom molecular dynamics (MD) simulation studies of structure-function relationship require complete protein structures. To address this shortcoming, we have developed and implemented an efficient computational method for building missing protein loops. The method is database driven and uses deep learning and multi-dimensional scaling algorithms. We have implemented the method as a simple stand-alone program, which can also be used as a plugin in existing molecular modeling software, e.g., VMD. The quality and stability of the generated structures are assessed and tested via energy scoring functions and by equilibrium MD simulations. The proposed method can also be used in template-based protein structure prediction. Work supported by the National Institutes of Health [R01 GM100701]. Computer time was provided by the University of Missouri Bioinformatics Consortium.

New compounds from acid hydrolyzed products of the fruits of Momordica charantia L. and their inhibitory activity against protein tyrosine phosphatas 1B.

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Zeng, Ke; He, Yan-Ni; Yang, Di; Cao, Jia-Qing; Xia, Xi-Chun; Zhang, Shi-Jun; Bi, Xiu-Li; Zhao, Yu-Qing

2014-06-23

Four new cucurbitane-type triterpene sapogenins, compounds 1-4, together with other eight known compounds were isolated from the acid-hydrolyzed fruits extract of Momordica charantia L. Their chemical structures were established by NMR, mass spectrometry and X-ray crystallography. Compounds 1-7 and 9-12 were evaluated for their inhibitory activities toward protein tyrosine phosphatase 1B (PTP1B), a tyrosine phosphatase that has been implicated as a key target for therapy against type II diabetes. Compounds 1, 2, 4, 7 and 9 were shown inhibitory activities of 77%, 62%, 62% 60% and 68% against PTP1B, respectively. All of these tested compounds were exhibited higher PTP1B inhibition activities than that of the Na3VO4, a known PTP1B inhibitor used as positive control in present study. Structure activity relationship (SAR) analysis indicated that the inhibition activity of PTP1B was associated with the presence and number of -OH groups. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

A computational model of the LGI1 protein suggests a common binding site for ADAM proteins.

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Emanuela Leonardi

Full Text Available Mutations of human leucine-rich glioma inactivated (LGI1 gene encoding the epitempin protein cause autosomal dominant temporal lateral epilepsy (ADTLE, a rare familial partial epileptic syndrome. The LGI1 gene seems to have a role on the transmission of neuronal messages but the exact molecular mechanism remains unclear. In contrast to other genes involved in epileptic disorders, epitempin shows no homology with known ion channel genes but contains two domains, composed of repeated structural units, known to mediate protein-protein interactions.A three dimensional in silico model of the two epitempin domains was built to predict the structure-function relationship and propose a functional model integrating previous experimental findings. Conserved and electrostatic charged regions of the model surface suggest a possible arrangement between the two domains and identifies a possible ADAM protein binding site in the β-propeller domain and another protein binding site in the leucine-rich repeat domain. The functional model indicates that epitempin could mediate the interaction between proteins localized to different synaptic sides in a static way, by forming a dimer, or in a dynamic way, by binding proteins at different times.The model was also used to predict effects of known disease-causing missense mutations. Most of the variants are predicted to alter protein folding while several other map to functional surface regions. In agreement with experimental evidence, this suggests that non-secreted LGI1 mutants could be retained within the cell by quality control mechanisms or by altering interactions required for the secretion process.

Compound C prevents Hypoxia-Inducible Factor-1α protein stabilization by regulating the cellular oxygen availability via interaction with Mitochondrial Complex I

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Hagen Thilo

2011-04-01

Full Text Available Abstract The transcription factor Hypoxia-Inducible Factor-1α is a master regulator of the cellular response to low oxygen concentration. Compound C, an inhibitor of AMP-activated kinase, has been reported to inhibit hypoxia dependent Hypoxia-Inducible Factor-1α activation via a mechanism that is independent of AMP-activated kinase but dependent on its interaction with the mitochondrial electron transport chain. The objective of this study is to characterize the interaction of Compound C with the mitochondrial electron transport chain and to determine the mechanism through which the drug influences the stability of the Hypoxia-Inducible Factor-1α protein. We found that Compound C functions as an inhibitor of complex I of the mitochondrial electron transport chain as demonstrated by its effect on mitochondrial respiration. It also prevents hypoxia-induced Hypoxia-Inducible Factor-1α stabilization in a dose dependent manner. In addition, Compound C does not have significant effects on reactive oxygen species production from complex I via both forward and reverse electron flux. This study provides evidence that similar to other mitochondrial electron transport chain inhibitors, Compound C regulates Hypoxia-Inducible Factor-1α stability by controlling the cellular oxygen concentration.

Scalable rule-based modelling of allosteric proteins and biochemical networks.

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Julien F Ollivier

2010-11-01

Full Text Available Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

Lindley frailty model for a class of compound Poisson processes

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Kadilar, Gamze Özel; Ata, Nihal

2013-10-01

The Lindley distribution gain importance in survival analysis for the similarity of exponential distribution and allowance for the different shapes of hazard function. Frailty models provide an alternative to proportional hazards model where misspecified or omitted covariates are described by an unobservable random variable. Despite of the distribution of the frailty is generally assumed to be continuous, it is appropriate to consider discrete frailty distributions In some circumstances. In this paper, frailty models with discrete compound Poisson process for the Lindley distributed failure time are introduced. Survival functions are derived and maximum likelihood estimation procedures for the parameters are studied. Then, the fit of the models to the earthquake data set of Turkey are examined.

Folding 19 proteins to their native state and stability of large proteins from a coarse-grained model.

Science.gov (United States)

Kapoor, Abhijeet; Travesset, Alex

2014-03-01

We develop an intermediate resolution model, where the backbone is modeled with atomic resolution but the side chain with a single bead, by extending our previous model (Proteins (2013) DOI: 10.1002/prot.24269) to properly include proline, preproline residues and backbone rigidity. Starting from random configurations, the model properly folds 19 proteins (including a mutant 2A3D sequence) into native states containing β sheet, α helix, and mixed α/β. As a further test, the stability of H-RAS (a 169 residue protein, critical in many signaling pathways) is investigated: The protein is stable, with excellent agreement with experimental B-factors. Despite that proteins containing only α helices fold to their native state at lower backbone rigidity, and other limitations, which we discuss thoroughly, the model provides a reliable description of the dynamics as compared with all atom simulations, but does not constrain secondary structures as it is typically the case in more coarse-grained models. Further implications are described. Copyright © 2013 Wiley Periodicals, Inc.

Comparative proteomics and protein profile related to phenolic compounds and antioxidant activity in germinated Oryza sativa 'KDML105' and Thai brown rice 'Mali Daeng' for better nutritional value.

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Maksup, Sarunyaporn; Pongpakpian, Sarintip; Roytrakul, Sittiruk; Cha-Um, Suriyan; Supaibulwatana, Kanyaratt

2018-01-01

Brown rice (BR) and germinated brown rice (GBR) are considered as prime sources of carbohydrate and bioactive compounds for more than half of the populations worldwide. Several studies have reported on the proteomics of BR and GBR; however, the proteomic profiles related to the synthesis of bioactive compounds are less well documented. In the present study, BR and GBR were used in a comparative analysis of the proteomic and bioactive compound profiles for two famous Thai rice varieties: Khao Dawk Mali 105 (KDML) and Mali Daeng (MD). The proteomes of KDML and MD revealed differences in the expression patterns of proteins after germination. Total phenolic compound content, anthocyanin contents and antioxidant activity of red rice MD was approximately 2.6-, 2.2- and 9.2-fold higher, respectively, compared to that of the white rice KDML. Moreover, GBR of MD showed higher total anthocyanin content and greater antioxidant activity, which is consistent with the increase expression of several proteins involved in the biosynthesis of phenolic compounds and protection against oxidative stress. Red rice MD exhibits higher nutrient values compared to white rice KDML and the appropriate germination of brown rice could represent a method for improving health-related benefits. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Trade-off between positive and negative design of protein stability: from lattice models to real proteins.

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Orly Noivirt-Brik

2009-12-01

Full Text Available Two different strategies for stabilizing proteins are (i positive design in which the native state is stabilized and (ii negative design in which competing non-native conformations are destabilized. Here, the circumstances under which one strategy might be favored over the other are explored in the case of lattice models of proteins and then generalized and discussed with regard to real proteins. The balance between positive and negative design of proteins is found to be determined by their average "contact-frequency", a property that corresponds to the fraction of states in the conformational ensemble of the sequence in which a pair of residues is in contact. Lattice model proteins with a high average contact-frequency are found to use negative design more than model proteins with a low average contact-frequency. A mathematical derivation of this result indicates that it is general and likely to hold also for real proteins. Comparison of the results of correlated mutation analysis for real proteins with typical contact-frequencies to those of proteins likely to have high contact-frequencies (such as disordered proteins and proteins that are dependent on chaperonins for their folding indicates that the latter tend to have stronger interactions between residues that are not in contact in their native conformation. Hence, our work indicates that negative design is employed when insufficient stabilization is achieved via positive design owing to high contact-frequencies.

Roles of beta-turns in protein folding: from peptide models to protein engineering.

Science.gov (United States)

Marcelino, Anna Marie C; Gierasch, Lila M

2008-05-01

Reverse turns are a major class of protein secondary structure; they represent sites of chain reversal and thus sites where the globular character of a protein is created. It has been speculated for many years that turns may nucleate the formation of structure in protein folding, as their propensity to occur will favor the approximation of their flanking regions and their general tendency to be hydrophilic will favor their disposition at the solvent-accessible surface. Reverse turns are local features, and it is therefore not surprising that their structural properties have been extensively studied using peptide models. In this article, we review research on peptide models of turns to test the hypothesis that the propensities of turns to form in short peptides will relate to the roles of corresponding sequences in protein folding. Turns with significant stability as isolated entities should actively promote the folding of a protein, and by contrast, turn sequences that merely allow the chain to adopt conformations required for chain reversal are predicted to be passive in the folding mechanism. We discuss results of protein engineering studies of the roles of turn residues in folding mechanisms. Factors that correlate with the importance of turns in folding indeed include their intrinsic stability, as well as their topological context and their participation in hydrophobic networks within the protein's structure.

An Integrated Framework Advancing Membrane Protein Modeling and Design.

Directory of Open Access Journals (Sweden)

Rebecca F Alford

2015-09-01

Full Text Available Membrane proteins are critical functional molecules in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to determine their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1 prediction of free energy changes upon mutation; (2 high-resolution structural refinement; (3 protein-protein docking; and (4 assembly of symmetric protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.

Evolving trends in biosciences: Multi-purpose proteins - GFP and GFP-like proteins

Digital Repository Service at National Institute of Oceanography (India)

Krishna, K.; Ingole, B.S.

The sea is considered as holding a clue to many known and unknown biologically active compounds. A family of protein named Green Fluorescent Proteins (GFP)-like proteins, initially isolated from marine organisms, started a trend in biotechnological...

Polyphenol Compound as a Transcription Factor Inhibitor.

Science.gov (United States)

Park, Seyeon

2015-10-30

A target-based approach has been used to develop novel drugs in many therapeutic fields. In the final stage of intracellular signaling, transcription factor-DNA interactions are central to most biological processes and therefore represent a large and important class of targets for human therapeutics. Thus, we focused on the idea that the disruption of protein dimers and cognate DNA complexes could impair the transcriptional activation and cell transformation regulated by these proteins. Historically, natural products have been regarded as providing the primary leading compounds capable of modulating protein-protein or protein-DNA interactions. Although their mechanism of action is not fully defined, polyphenols including flavonoids were found to act mostly as site-directed small molecule inhibitors on signaling. There are many reports in the literature of screening initiatives suggesting improved drugs that can modulate the transcription factor interactions responsible for disease. In this review, we focus on polyphenol compound inhibitors against dimeric forms of transcription factor components of intracellular signaling pathways (for instance, c-jun/c-fos (Activator Protein-1; AP-1), c-myc/max, Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and β-catenin/T cell factor (Tcf)).

Protein (multi-)location prediction: utilizing interdependencies via a generative model.

Science.gov (United States)

Simha, Ramanuja; Briesemeister, Sebastian; Kohlbacher, Oliver; Shatkay, Hagit

2015-06-15

Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein's function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. We introduce a probabilistic generative model for protein localization, and develop a system based on it-which we call MDLoc-that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. © The Author 2015. Published by Oxford University Press.

Compound waves in a higher order nonlinear model of thermoviscous fluids

DEFF Research Database (Denmark)

Rønne Rasmussen, Anders; Sørensen, Mads Peter; Gaididei, Yuri B.

2016-01-01

A generalized traveling wave ansatz is used to investigate compound shock waves in a higher order nonlinear model of a thermoviscous fluid. The fluid velocity potential is written as a traveling wave plus a linear function of space and time. The latter offers the possibility of predicting...

Mathematical Modeling of a Transient Vibration Control Strategy Using a Switchable Mass Stiffness Compound System

Directory of Open Access Journals (Sweden)

Diego Francisco Ledezma-Ramirez

2014-01-01

Full Text Available A theoretical control strategy for residual vibration control resulting from a shock pulse is studied. The semiactive control strategy is applied in a piecewise linear compound model and involves an on-off logic to connect and disconnect a secondary mass stiffness system from the primary isolation device, with the aim of providing high energy dissipation for lightly damped systems. The compound model is characterized by an energy dissipation mechanism due to the inelastic collision between the two masses and then viscous damping is introduced and its effects are analyzed. The objective of the simulations is to evaluate the transient vibration response in comparison to the results for a passive viscously damped single degree-of-freedom system considered as the benchmark or reference case. Similarly the decay in the compound system is associated with an equivalent decay rate or logarithmic decrement for direct comparison. It is found how the compound system provides improved isolation compared to the passive system, and the damping mechanisms are explained.

Establishment of an intermittent cold stress model using Tupaia belangeri and evaluation of compound C737 targeting neuron-restrictive silencer factor

Science.gov (United States)

Hai-Ying, Chi; Nagano, Kiori; Ezzikouri, Sayeh; Yamaguchi, Chiho; Kayesh, Mohammad Enamul Hoque; Rebbani, Khadija; Kitab, Bouchra; Nakano, Hirohumi; Kouji, Hiroyuki; Kohara, Michinori; Tsukiyama-Kohara, Kyoko

2016-01-01

Previous studies have shown that intermittent cold stress (ICS) induces depression-like behaviors in mammals. Tupaia belangeri (the tree shrew) is the only experimental animal other than the chimpanzee that has been shown to be susceptible to infection by hepatitis B and C viruses. Moreover, full genome sequence analysis has revealed strong homology between host proteins in Tupaia and in humans and other primates. Tupaia neuromodulator receptor proteins are also known to have a high degree of homology with their corresponding primate proteins. Based on these similarities, we hypothesized that induction of ICS in Tupaia would provide a useful animal model of stress responses. We exposed young adult Tupaia to ICS and observed decreases in body temperature and body weight in both female and male Tupaia, suggesting that Tupaia are an appropriate animal model for ICS studies. We further examined the efficacy of a new small-molecule compound, C737, against the effects of ICS. C737 mimics the helical structure of neuron-restrictive silencer factor (NRSF/REST), which regulates a wide range of target genes involved in neuronal function and pain modulation. Treatment with C737 significantly reduced stress-induced weight loss in female Tupaia; these effects were stronger than those elicited by the antidepressant agomelatine. These results suggest that Tupaia represents a useful non-rodent ICS model. Our data also provide new insights into the function of NRSF/REST in stress-induced depression and other disorders with epigenetic influences or those with high prevalence in women. PMID:27041457

Mechanical Modeling and Computer Simulation of Protein Folding

Science.gov (United States)

Prigozhin, Maxim B.; Scott, Gregory E.; Denos, Sharlene

2014-01-01

In this activity, science education and modern technology are bridged to teach students at the high school and undergraduate levels about protein folding and to strengthen their model building skills. Students are guided from a textbook picture of a protein as a rigid crystal structure to a more realistic view: proteins are highly dynamic…

Molecular modeling of protein materials: case study of elastin

International Nuclear Information System (INIS)

Tarakanova, Anna; Buehler, Markus J

2013-01-01

Molecular modeling of protein materials is a quickly growing area of research that has produced numerous contributions in fields ranging from structural engineering to medicine and biology. We review here the history and methods commonly employed in molecular modeling of protein materials, emphasizing the advantages for using modeling as a complement to experimental work. We then consider a case study of the protein elastin, a critically important ‘mechanical protein’ to exemplify the approach in an area where molecular modeling has made a significant impact. We outline the progression of computational modeling studies that have considerably enhanced our understanding of this important protein which endows elasticity and recoil to the tissues it is found in, including the skin, lungs, arteries and the heart. A vast collection of literature has been directed at studying the structure and function of this protein for over half a century, the first molecular dynamics study of elastin being reported in the 1980s. We review the pivotal computational works that have considerably enhanced our fundamental understanding of elastin's atomistic structure and its extraordinary qualities—focusing on two in particular: elastin's superb elasticity and the inverse temperature transition—the remarkable ability of elastin to take on a more structured conformation at higher temperatures, suggesting its effectiveness as a biomolecular switch. Our hope is to showcase these methods as both complementary and enriching to experimental approaches that have thus far dominated the study of most protein-based materials. (topical review)

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

Science.gov (United States)

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O.; Sperandio, Olivier

2010-01-01

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

Directory of Open Access Journals (Sweden)

Christelle Reynès

2010-03-01

Full Text Available Protein-protein interactions (PPIs may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific. Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

Science.gov (United States)

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O; Sperandio, Olivier

2010-03-05

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is

Diazo Compounds: Versatile Tools for Chemical Biology.

Science.gov (United States)

Mix, Kalie A; Aronoff, Matthew R; Raines, Ronald T

2016-12-16

Diazo groups have broad and tunable reactivity. That and other attributes endow diazo compounds with the potential to be valuable reagents for chemical biologists. The presence of diazo groups in natural products underscores their metabolic stability and anticipates their utility in a biological context. The chemoselectivity of diazo groups, even in the presence of azido groups, presents many opportunities. Already, diazo compounds have served as chemical probes and elicited novel modifications of proteins and nucleic acids. Here, we review advances that have facilitated the chemical synthesis of diazo compounds, and we highlight applications of diazo compounds in the detection and modification of biomolecules.

Protein (multi-)location prediction: utilizing interdependencies via a generative model

Science.gov (United States)

Shatkay, Hagit

2015-01-01

Motivation: Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein’s function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. Results: We introduce a probabilistic generative model for protein localization, and develop a system based on it—which we call MDLoc—that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. Availability and implementation: MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. Contact: shatkay@udel.edu. PMID:26072505

Equation of state for neutron matter in the Quark Compound Bag model

Science.gov (United States)

Krivoruchenko, M. I.

2017-11-01

The equation of state for neutron matter is derived in the framework of the Quark Compound Bag model, in which the nucleon-nucleon interaction is generated by the s-channel exchange of six-quark Jaffe-Low primitives.

In silico modelling and validation of differential expressed proteins in lung cancer

Directory of Open Access Journals (Sweden)

Bhagavathi S

2012-05-01

Full Text Available Objective: The present study aims predict the three dimensional structure of three major proteins responsible for causing Lung cancer. Methods: These are the differentially expressed proteins in lung cancer dataset. Initially, the structural template for these proteins is identified from structural database using homology search and perform homology modelling approach to predict its native 3D structure. Three-dimensional model obtained was validated using Ramachandran plot analysis to find the reliability of the model. Results: Four proteins were differentially expressed and were significant proteins in causing lung cancer. Among the four proteins, Matrixmetallo proteinase (P39900 had a known 3D structure and hence was not considered for modelling. The remaining proteins Polo like kinase I Q58A51, Trophinin B1AKF1, Thrombomodulin P07204 were modelled and validated. Conclusions: The three dimensional structure of proteins provides insights about the functional aspect and regulatory aspect of the protein. Thus, this study will be a breakthrough for further lung cancer related studies.

Protein single-model quality assessment by feature-based probability density functions.

Science.gov (United States)

Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

Quality assessment of protein model-structures based on structural and functional similarities.

Science.gov (United States)

Konopka, Bogumil M; Nebel, Jean-Christophe; Kotulska, Malgorzata

2012-09-21

Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. GOBA--Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and

The effect of rabbit’s age on in vitro fermentation of starch, compound feed and its fibre

OpenAIRE

Kermauner, Ajda; Lavrenčić, Andrej

2006-01-01

In vitro gas production movement for three different substrates, starch, standard compound feed (20 % crude protein, 33 % NDF/kg DM) and neutral detergent fibre prepared from the standard compound feed (NDF), were determined using the caecum content of weaned rabbits (36 days of age) and of rabbits of slaughter age (78 days) as inoculum. Gas produced was fitted with the Gompertz model and the differences between parameters were calculated. The differences in fermentation kinetic parameters be...

Selenium-containing indolyl compounds

DEFF Research Database (Denmark)

Casaril, Angela M; Ignasiak, Marta T; Chuang, Christine Y

2017-01-01

materials, including extracellular matrix (ECM) proteins, within the artery wall. Here we investigated the potential of selenium-containing indoles to afford protection against these oxidants, by determining rate constants (k) for their reaction, and quantifying the extent of damage on isolated ECM proteins......Tyr on HCAEC-ECM were also reduced. These data demonstrate that the novel selenium-containing compounds show high reactivity with oxidants and may modulate oxidative and nitrosative damage at sites of inflammation, contributing to a reduction in tissue dysfunction and atherogenesis....

Simulation studies of protein-induced bilayer deformations, and lipid-induced protein tilting, on a mesoscopic model for lipid bilayers with embedded proteins

DEFF Research Database (Denmark)

Venturoli, M.; Smit, B.; Sperotto, Maria Maddalena

2005-01-01

membranes. Here we present a mesoscopic model for lipid bilayers with embedded proteins, which we have studied with the help of the dissipative particle dynamics simulation technique. Because hydrophobic matching is believed to be one of the main physical mechanisms regulating lipid-protein interactions......-induced protein tilt, with the hydrophobic mismatch ( positive and negative) between the protein hydrophobic length and the pure lipid bilayer hydrophobic thickness. The protein-induced bilayer perturbation was quantified in terms of a coherence length, xi(P), of the lipid bilayer hydrophobic thickness pro. le...... for positive values of mismatch; a dependence on the protein size appears as well. In the case of large model proteins experiencing extreme mismatch conditions, in the region next to the so-called lipid annulus, there appears an undershooting ( or overshooting) region where the bilayer hydrophobic thickness...

Positive modulator of bone morphogenic protein-2

Science.gov (United States)

Zamora, Paul O [Gaithersburg, MD; Pena, Louis A [Poquott, NY; Lin, Xinhua [Plainview, NY; Takahashi, Kazuyuki [Germantown, MD

2009-01-27

Compounds of the present invention of formula I and formula II are disclosed in the specification and wherein the compounds are modulators of Bone Morphogenic Protein activity. Compounds are synthetic peptides having a non-growth factor heparin binding region, a linker, and sequences that bind specifically to a receptor for Bone Morphogenic Protein. Uses of compounds of the present invention in the treatment of bone lesions, degenerative joint disease and to enhance bone formation are disclosed.

Positive modulator of bone morphogenic protein-2

Energy Technology Data Exchange (ETDEWEB)

Zamora, Paul O.; Pena, Louis A.; Lin, Xinhua; Kazuyuki, Takahashi

2017-06-06

Compounds of the present invention of formula I and formula II are disclosed in the specification and wherein the compounds are modulators of Bone Morphogenic Protein activity. Compounds are synthetic peptides having a non-growth factor heparin binding region, a linker, and sequences that bind specifically to a receptor for Bone Morphogenic Protein. Uses of compounds of the present invention in the treatment of bone lesions, degenerative joint disease and to enhance bone formation are disclosed.

SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803

OpenAIRE

Kim, Woo-Yeon; Kang, Sungsoo; Kim, Byoung-Chul; Oh, Jeehyun; Cho, Seongwoong; Bhak, Jong; Choi, Jong-Soon

2008-01-01

Background Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. Description We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactio...

Aquatic pathways model to predict the fate of phenolic compounds

Energy Technology Data Exchange (ETDEWEB)

Aaberg, R.L.; Peloquin, R.A.; Strenge, D.L.; Mellinger, P.J.

1983-04-01

Organic materials released from energy-related activities could affect human health and the environment. To better assess possible impacts, we developed a model to predict the fate of spills or discharges of pollutants into flowing or static bodies of fresh water. A computer code, Aquatic Pathways Model (APM), was written to implement the model. The computer programs use compartmental analysis to simulate aquatic ecosystems. The APM estimates the concentrations of chemicals in fish tissue, water and sediment, and is therefore useful for assessing exposure to humans through aquatic pathways. The APM will consider any aquatic pathway for which the user has transport data. Additionally, APM will estimate transport rates from physical and chemical properties of chemicals between several key compartments. The major pathways considered are biodegradation, fish and sediment uptake, photolysis, and evaporation. The model has been implemented with parameters for distribution of phenols, an important class of compounds found in the water-soluble fractions of coal liquids. Current modeling efforts show that, in comparison with many pesticides and polyaromatic hydrocarbons (PAH), the lighter phenolics (the cresols) are not persistent in the environment. The properties of heavier molecular weight phenolics (indanols, naphthols) are not well enough understood at this time to make similar judgements. For the twelve phenolics studied, biodegradation appears to be the major pathway for elimination from aquatic environments. A pond system simulation (using APM) of a spill of solvent refined coal (SRC-II) materials indicates that phenol, cresols, and other single cyclic phenolics are degraded to 16 to 25 percent of their original concentrations within 30 hours. Adsorption of these compounds into sediments and accumulation by fish was minor.

Marine Natural Products Acting on the Acetylcholine-Binding Protein and Nicotinic Receptors: From Computer Modeling to Binding Studies and Electrophysiology

Directory of Open Access Journals (Sweden)

Denis Kudryavtsev

2014-03-01

Full Text Available For a small library of natural products from marine sponges and ascidians, in silico docking to the Lymnaea stagnalis acetylcholine-binding protein (AChBP, a model for the ligand-binding domains of nicotinic acetylcholine receptors (nAChRs, was carried out and the possibility of complex formation was revealed. It was further experimentally confirmed via competition with radioiodinated α-bungarotoxin ([125I]-αBgt for binding to AChBP of the majority of analyzed compounds. Alkaloids pibocin, varacin and makaluvamines С and G had relatively high affinities (Ki 0.5–1.3 μM. With the muscle-type nAChR from Torpedo californica ray and human neuronal α7 nAChR, heterologously expressed in the GH4C1 cell line, no competition with [125I]-αBgt was detected in four compounds, while the rest showed an inhibition. Makaluvamines (Ki ~ 1.5 μM were the most active compounds, but only makaluvamine G and crambescidine 359 revealed a weak selectivity towards muscle-type nAChR. Rhizochalin, aglycone of rhizochalin, pibocin, makaluvamine G, monanchocidin, crambescidine 359 and aaptamine showed inhibitory activities in electrophysiology experiments on the mouse muscle and human α7 nAChRs, expressed in Xenopus laevis oocytes. Thus, our results confirm the utility of the modeling studies on AChBPs in a search for natural compounds with cholinergic activity and demonstrate the presence of the latter in the analyzed marine biological sources.

Nucleon-nucleon interaction in the quark-compound-bag model

International Nuclear Information System (INIS)

Simonov, Yu.A.

1982-01-01

The NN potential is investigated in the framework of the quark-compound-bag model. The cluster decomposition of the total six-quark wave function are obtained. The resulting potential is nonlocal and energy dependent with coefficients which can be derived both phenomenologically and theoretically. Stringent conditions exist for those coefficients. As an example the NN potentials for the 3 S 1 and 1 S 0 states are presented. The properties of the wave functions are studied both in the configurational and momentum space

Quantifying drug-protein binding in vivo

International Nuclear Information System (INIS)

Buchholz, B; Bench, G; Keating III, G; Palmblad, M; Vogel, J; Grant, P G; Hillegonds, D

2004-01-01

Accelerator mass spectrometry (AMS) provides precise quantitation of isotope labeled compounds that are bound to biological macromolecules such as DNA or proteins. The sensitivity is high enough to allow for sub-pharmacological (''micro-'') dosing to determine macromolecular targets without inducing toxicities or altering the system under study, whether it is healthy or diseased. We demonstrated an application of AMS in quantifying the physiologic effects of one dosed chemical compound upon the binding level of another compound in vivo at sub-toxic doses [4].We are using tissues left from this study to develop protocols for quantifying specific binding to isolated and identified proteins. We also developed a new technique to quantify nanogram to milligram amounts of isolated protein at precisions that are comparable to those for quantifying the bound compound by AMS

Hydrodeoxygenation of mono- and dimeric lignin model compounds on noble metal catalysts

NARCIS (Netherlands)

Guvenatam, Burcu; Kursun, Osman; Heeres, Hero; Pidko, Evgeny A.; Hensen, Emiel J. M.

2014-01-01

The influence of reaction conditions (temperature, acidity) on the catalytic performance of supported Pt, Pd and Ru catalysts for the aqueous phase hydrodeoxygenation (HDO) of lignin model compounds was systematically investigated. Phenol conversion proceeds via hydrogenation of the aromatic ring

Alkoxyl- and carbon-centered radicals as primary agents for degrading non-phenolic lignin-substructure model compounds.

Science.gov (United States)

Ohashi, Yasunori; Uno, Yukiko; Amirta, Rudianto; Watanabe, Takahito; Honda, Yoichi; Watanabe, Takashi

2011-04-07

Lignin degradation by white-rot fungi proceeds via free radical reaction catalyzed by oxidative enzymes and metabolites. Basidiomycetes called selective white-rot fungi degrade both phenolic and non-phenolic lignin substructures without penetration of extracellular enzymes into the cell wall. Extracellular lipid peroxidation has been proposed as a possible ligninolytic mechanism, and radical species degrading the recalcitrant non-phenolic lignin substructures have been discussed. Reactions between the non-phenolic lignin model compounds and radicals produced from azo compounds in air have previously been analysed, and peroxyl radical (PR) is postulated to be responsible for lignin degradation (Kapich et al., FEBS Lett., 1999, 461, 115-119). However, because the thermolysis of azo compounds in air generates both a carbon-centred radical (CR) and a peroxyl radical (PR), we re-examined the reactivity of the three radicals alkoxyl radical (AR), CR and PR towards non-phenolic monomeric and dimeric lignin model compounds. The dimeric lignin model compound is degraded by CR produced by reaction of 2,2'-azobis(2-amidinopropane) dihydrochloride (AAPH), which under N(2) atmosphere cleaves the α-β bond in 1-(4-ethoxy-3-methoxyphenyl)-2-(2-methoxyphenoxy)-1,3-propanediol to yield 4-ethoxy-3-methoxybenzaldehyde. However, it is not degraded by the PR produced by reaction of Ce(4+)/tert-BuOOH. In addition, it is degraded by AR produced by reaction of Ti(3+)/tert-BuOOH. PR and AR are generated in the presence and absence of veratryl alcohol, respectively. Rapid-flow ESR analysis of the radical species demonstrates that AR but not PR reacts with the lignin model compound. Thus, AR and CR are primary agents for the degradation of non-phenolic lignin substructures.

Study on fluorescence of Maillard reaction compounds in breakfast cereals.

Science.gov (United States)

Delgado-Andrade, Cristina; Rufián-Henares, José A; Morales, Francisco J

2006-09-01

During the advanced stage of the Maillard reaction (MR) in food processing and cooking, Amadori rearrangement products undergo dehydration and fission and fluorescent substances are formed. Free and total (free + linked to the protein backbone) fluorescence (FIC) due to Maillard compounds in 60 commercial breakfast cereals was evaluated. Pronase was used for efficient release of linked fluorescent Maillard compounds from the protein backbone. Results were correlated with some heat-induced markers of the extent of the MR or sugar caramelisation during cereal processing, such as hydroxymethylfurfural, furfural, glucosilisomaltol and furosine. The effect of sample composition (dietary-fibre added, protein, etc.) on levels of FIC, expressed as fluorescence intensity (FI) per milligram of sample, is discussed. FIC is significantly correlated to the protein content of the sample and fluorescent Maillard compounds are mainly linked to the protein backbone. The ratio of total-FIC to free-FIC was 10.4-fold for corn-based, wheat-based and multicereal-based breakfast cereals but significantly higher in rice-based samples. Addition of dietary fibre or honey increased the FIC values. Data support the usefulness of FIC measurement as an unspecific heat-induced marker in breakfast cereals.

Hydration dynamics near a model protein surface

International Nuclear Information System (INIS)

Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

2003-01-01

The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces

Hazard rate model and statistical analysis of a compound point process

Czech Academy of Sciences Publication Activity Database

Volf, Petr

2005-01-01

Roč. 41, č. 6 (2005), s. 773-786 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : couting process * compound process * Cox regression model * intensity Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.343, year: 2005

Kinetic analysis of polyoxometalate (POM) oxidation of non-phenolic lignin model compound

Science.gov (United States)

Tomoya Yokoyama; Hou-min Chang; Ira A. Weinstock; Richard S. Reiner; John F. Kadla

2003-01-01

Kinetic and reaction mechanism of non-phenolic lignin model compounds under anaerobic polyoxometalate (POM), Na5(+1.9)[SiV1(-0.1)MoW10(+0.1) 40], bleaching conditions were examined. Analyses using a syringyl type model, 1-(3,4,5-trimethoxyphenyl)ethanol (1), a guaiacyl type, 1-(3,4- imethoxyphenyl)ethanol (2), and 1- (4-ethoxy-3,5-dimethoxyphenyl)ethanol (3) suggest...

Legume bioactive compounds: influence of rhizobial inoculation

Directory of Open Access Journals (Sweden)

Luis R. Silva

2017-04-01

Full Text Available Legumes consumption has been recognized as beneficial for human health, due to their content in proteins, fiber, minerals and vitamins, and their cultivation as beneficial for sustainable agriculture due to their ability to fix atmospheric nitrogen in symbiosis with soil bacteria known as rhizobia. The inoculation with these baceria induces metabolic changes in the plant, from which the more studied to date are the increases in the nitrogen and protein contents, and has been exploited in agriculture to improve the crop yield of several legumes. Nevertheless, legumes also contain several bioactive compounds such as polysaccharides, bioactive peptides, isoflavones and other phenolic compounds, carotenoids, tocopherols and fatty acids, which makes them functional foods included into the nutraceutical products. Therefore, the study of the effect of the rhizobial inoculation in the legume bioactive compounds content is gaining interest in the last decade. Several works reported that the inoculation of different genera and species of rhizobia in several grain legumes, such as soybean, cowpea, chickpea, faba bean or peanut, produced increases in the antioxidant potential and in the content of some bioactive compounds, such as phenolics, flavonoids, organic acids, proteins and fatty acids. Therefore, the rhizobial inoculation is a good tool to enhance the yield and quality of legumes and further studies on this field will allow us to have plant probiotic bacteria that promote the plant growth of legumes improving their functionality.

Statistical-mechanical lattice models for protein-DNA binding in chromatin

International Nuclear Information System (INIS)

Teif, Vladimir B; Rippe, Karsten

2010-01-01

Statistical-mechanical lattice models for protein-DNA binding are well established as a method to describe complex ligand binding equilibria measured in vitro with purified DNA and protein components. Recently, a new field of applications has opened up for this approach since it has become possible to experimentally quantify genome-wide protein occupancies in relation to the DNA sequence. In particular, the organization of the eukaryotic genome by histone proteins into a nucleoprotein complex termed chromatin has been recognized as a key parameter that controls the access of transcription factors to the DNA sequence. New approaches have to be developed to derive statistical-mechanical lattice descriptions of chromatin-associated protein-DNA interactions. Here, we present the theoretical framework for lattice models of histone-DNA interactions in chromatin and investigate the (competitive) DNA binding of other chromosomal proteins and transcription factors. The results have a number of applications for quantitative models for the regulation of gene expression.

Polyphenol Compound as a Transcription Factor Inhibitor

Directory of Open Access Journals (Sweden)

Seyeon Park

2015-10-01

Full Text Available A target-based approach has been used to develop novel drugs in many therapeutic fields. In the final stage of intracellular signaling, transcription factor–DNA interactions are central to most biological processes and therefore represent a large and important class of targets for human therapeutics. Thus, we focused on the idea that the disruption of protein dimers and cognate DNA complexes could impair the transcriptional activation and cell transformation regulated by these proteins. Historically, natural products have been regarded as providing the primary leading compounds capable of modulating protein–protein or protein-DNA interactions. Although their mechanism of action is not fully defined, polyphenols including flavonoids were found to act mostly as site-directed small molecule inhibitors on signaling. There are many reports in the literature of screening initiatives suggesting improved drugs that can modulate the transcription factor interactions responsible for disease. In this review, we focus on polyphenol compound inhibitors against dimeric forms of transcription factor components of intracellular signaling pathways (for instance, c-jun/c-fos (Activator Protein-1; AP-1, c-myc/max, Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB and β-catenin/T cell factor (Tcf.

Preparation of 125I labelled compound

International Nuclear Information System (INIS)

Rafii, H.; Beiki, D.; Matlubi, M.; Jalilian, A.R.; Motamedi, F.; Karimian, A.R.; Najafi, R.; Babaei, M.; Kamali Dehghan, M.; Shah-Hossaini, G.R.; Shafahi, S.K.; Keshavarzi, F.

2002-01-01

Iodinated compounds with 131 I, 125 I and 123 I have been widely used for biochemical function studies. In conjunction with SPECT, [ 123 I] labelled proteins have various diagnostic and therapeutic applications in nuclear medicine. In this study, synthesis and quality control of [ 18 F]radiofluorinated and radioiodinated of some proteins and peptides as well as their biological behaviors are considered to be investigated. (author)

Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale

Science.gov (United States)

Kuzu, Guray; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2013-01-01

Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than ‘blind’ docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested ‘difficult’ cases in a docking-benchmark dataset, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26% to 66%, and 57% of the interactions were successfully predicted in an ‘unbiased’ scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome-scale. We constructed the structural network of ERK interacting proteins as a case study. PMID:23590674

Stochastic lattice model of synaptic membrane protein domains.

Science.gov (United States)

Li, Yiwei; Kahraman, Osman; Haselwandter, Christoph A

2017-05-01

Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.

CONFOLD2: improved contact-driven ab initio protein structure modeling.

Science.gov (United States)

Adhikari, Badri; Cheng, Jianlin

2018-01-25

Contact-guided protein structure prediction methods are becoming more and more successful because of the latest advances in residue-residue contact prediction. To support contact-driven structure prediction, effective tools that can quickly build tertiary structural models of good quality from predicted contacts need to be developed. We develop an improved contact-driven protein modelling method, CONFOLD2, and study how it may be effectively used for ab initio protein structure prediction with predicted contacts as input. It builds models using various subsets of input contacts to explore the fold space under the guidance of a soft square energy function, and then clusters the models to obtain the top five models. CONFOLD2 obtains an average reconstruction accuracy of 0.57 TM-score for the 150 proteins in the PSICOV contact prediction dataset. When benchmarked on the CASP11 contacts predicted using CONSIP2 and CASP12 contacts predicted using Raptor-X, CONFOLD2 achieves a mean TM-score of 0.41 on both datasets. CONFOLD2 allows to quickly generate top five structural models for a protein sequence when its secondary structures and contacts predictions at hand. The source code of CONFOLD2 is publicly available at https://github.com/multicom-toolbox/CONFOLD2/ .

Structure-Based Virtual Screening of Commercially Available Compound Libraries.

Science.gov (United States)

Kireev, Dmitri

2016-01-01

Virtual screening (VS) is an efficient hit-finding tool. Its distinctive strength is that it allows one to screen compound libraries that are not available in the lab. Moreover, structure-based (SB) VS also enables an understanding of how the hit compounds bind the protein target, thus laying ground work for the rational hit-to-lead progression. SBVS requires a very limited experimental effort and is particularly well suited for academic labs and small biotech companies that, unlike pharmaceutical companies, do not have physical access to quality small-molecule libraries. Here, we describe SBVS of commercial compound libraries for Mer kinase inhibitors. The screening protocol relies on the docking algorithm Glide complemented by a post-docking filter based on structural protein-ligand interaction fingerprints (SPLIF).

Bipolar Mass Spectrometry of Labile Coordination Complexes, Redox Active Inorganic Compounds, and Proteins Using a Glass Nebulizer for Sonic-Spray Ionization

Science.gov (United States)

Antonakis, Manolis M.; Tsirigotaki, Alexandra; Kanaki, Katerina; Milios, Constantinos J.; Pergantis, Spiros A.

2013-08-01

In this study, we report on the development of a novel nebulizer configuration for sonic-spray ionization (SSI) mass spectrometry (MS), more specifically for a version of SSI that is referred to as Venturi easy ambient sonic-spray ionization (V-EASI) MS. The developed nebulizer configuration is based on a commercially available pneumatic glass nebulizer that has been used extensively for aerosol formation in atomic spectrometry. In the present study, the nebulizer was modified in order to achieve efficient V-EASI-MS operation. Upon evaluating this system, it has been demonstrated that V-EASI-MS offers some distinct advantages for the analysis of coordination compounds and redox active inorganic compounds over the predominantly used electrospray ionization (ESI) technique. Such advantages, for this type of compounds, are demonstrated here for the first time. More specifically, a series of labile heptanuclear heterometallic [CuII 6LnIII] clusters held together with artificial amino acid ligands, in addition to easily oxidized inorganic oxyanions of selenium and arsenic, were analyzed. The observed advantages pertain to V-EASI appearing to be a "milder" ionization source than ESI, not requiring electrical potentials for gas phase ion formation, thus eliminating the possibility of unwanted redox transformations, allowing for the "simultaneous" detection of negative and positive ions (bipolar analysis) without the need to change source ionization conditions, and also not requiring the use of syringes and delivery pumps. Because of such features, especially because of the absence of ionization potentials, EASI can be operated with minimal requirements for source parameter optimization. We observed that source temperature and accelerating voltage do not seem to affect labile compounds to the extent they do in ESI-MS. In addition, bipolar analysis of proteins was demonstrated here by acquiring both positive and negative ion mass spectra from the same protein solutions

Are animal models predictive for human postmortem muscle protein degradation?

Science.gov (United States)

Ehrenfellner, Bianca; Zissler, Angela; Steinbacher, Peter; Monticelli, Fabio C; Pittner, Stefan

2017-11-01

A most precise determination of the postmortem interval (PMI) is a crucial aspect in forensic casework. Although there are diverse approaches available to date, the high heterogeneity of cases together with the respective postmortal changes often limit the validity and sufficiency of many methods. Recently, a novel approach for time since death estimation by the analysis of postmortal changes of muscle proteins was proposed. It is however necessary to improve the reliability and accuracy, especially by analysis of possible influencing factors on protein degradation. This is ideally investigated on standardized animal models that, however, require legitimization by a comparison of human and animal tissue, and in this specific case of protein degradation profiles. Only if protein degradation events occur in comparable fashion within different species, respective findings can sufficiently be transferred from the animal model to application in humans. Therefor samples from two frequently used animal models (mouse and pig), as well as forensic cases with representative protein profiles of highly differing PMIs were analyzed. Despite physical and physiological differences between species, western blot analysis revealed similar patterns in most of the investigated proteins. Even most degradation events occurred in comparable fashion. In some other aspects, however, human and animal profiles depicted distinct differences. The results of this experimental series clearly indicate the huge importance of comparative studies, whenever animal models are considered. Although animal models could be shown to reflect the basic principles of protein degradation processes in humans, we also gained insight in the difficulties and limitations of the applicability of the developed methodology in different mammalian species regarding protein specificity and methodic functionality.

Structures of endothiapepsin-fragment complexes from crystallographic fragment screening using a novel, diverse and affordable 96-compound fragment library.

Science.gov (United States)

Huschmann, Franziska U; Linnik, Janina; Sparta, Karine; Ühlein, Monika; Wang, Xiaojie; Metz, Alexander; Schiebel, Johannes; Heine, Andreas; Klebe, Gerhard; Weiss, Manfred S; Mueller, Uwe

2016-05-01

Crystallographic screening of the binding of small organic compounds (termed fragments) to proteins is increasingly important for medicinal chemistry-oriented drug discovery. To enable such experiments in a widespread manner, an affordable 96-compound library has been assembled for fragment screening in both academia and industry. The library is selected from already existing protein-ligand structures and is characterized by a broad ligand diversity, including buffer ingredients, carbohydrates, nucleotides, amino acids, peptide-like fragments and various drug-like organic compounds. When applied to the model protease endothiapepsin in a crystallographic screening experiment, a hit rate of nearly 10% was obtained. In comparison to other fragment libraries and considering that no pre-screening was performed, this hit rate is remarkably high. This demonstrates the general suitability of the selected compounds for an initial fragment-screening campaign. The library composition, experimental considerations and time requirements for a complete crystallographic fragment-screening campaign are discussed as well as the nine fully refined obtained endothiapepsin-fragment structures. While most of the fragments bind close to the catalytic centre of endothiapepsin in poses that have been observed previously, two fragments address new sites on the protein surface. ITC measurements show that the fragments bind to endothiapepsin with millimolar affinity.

Hidden Markov model-derived structural alphabet for proteins: the learning of protein local shapes captures sequence specificity.

Science.gov (United States)

Camproux, A C; Tufféry, P

2005-08-05

Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. We have recently set up a Hidden Markov Model to optimally compress protein three-dimensional conformations into a one-dimensional series of letters of a structural alphabet. Such a model learns simultaneously the shape of representative structural letters describing the local conformation and the logic of their connections, i.e. the transition matrix between the letters. Here, we move one step further and report some evidence that such a model of protein local architecture also captures some accurate amino acid features. All the letters have specific and distinct amino acid distributions. Moreover, we show that words of amino acids can have significant propensities for some letters. Perspectives point towards the prediction of the series of letters describing the structure of a protein from its amino acid sequence.

Hidden markov model for the prediction of transmembrane proteins using MATLAB.

Science.gov (United States)

Chaturvedi, Navaneet; Shanker, Sudhanshu; Singh, Vinay Kumar; Sinha, Dhiraj; Pandey, Paras Nath

2011-01-01

Since membranous proteins play a key role in drug targeting therefore transmembrane proteins prediction is active and challenging area of biological sciences. Location based prediction of transmembrane proteins are significant for functional annotation of protein sequences. Hidden markov model based method was widely applied for transmembrane topology prediction. Here we have presented a revised and a better understanding model than an existing one for transmembrane protein prediction. Scripting on MATLAB was built and compiled for parameter estimation of model and applied this model on amino acid sequence to know the transmembrane and its adjacent locations. Estimated model of transmembrane topology was based on TMHMM model architecture. Only 7 super states are defined in the given dataset, which were converted to 96 states on the basis of their length in sequence. Accuracy of the prediction of model was observed about 74 %, is a good enough in the area of transmembrane topology prediction. Therefore we have concluded the hidden markov model plays crucial role in transmembrane helices prediction on MATLAB platform and it could also be useful for drug discovery strategy. The database is available for free at bioinfonavneet@gmail.comvinaysingh@bhu.ac.in.

Review of Natural Compounds for Potential Skin Cancer Treatment

Directory of Open Access Journals (Sweden)

Tawona N. Chinembiri

2014-08-01

Full Text Available Most anti-cancer drugs are derived from natural resources such as marine, microbial and botanical sources. Cutaneous malignant melanoma is the most aggressive form of skin cancer, with a high mortality rate. Various treatments for malignant melanoma are available, but due to the development of multi-drug resistance, current or emerging chemotherapies have a relatively low success rates. This emphasizes the importance of discovering new compounds that are both safe and effective against melanoma. In vitro testing of melanoma cell lines and murine melanoma models offers the opportunity for identifying mechanisms of action of plant derived compounds and extracts. Common anti-melanoma effects of natural compounds include potentiating apoptosis, inhibiting cell proliferation and inhibiting metastasis. There are different mechanisms and pathways responsible for anti-melanoma actions of medicinal compounds such as promotion of caspase activity, inhibition of angiogenesis and inhibition of the effects of tumor promoting proteins such as PI3-K, Bcl-2, STAT3 and MMPs. This review thus aims at providing an overview of anti-cancer compounds, derived from natural sources, that are currently used in cancer chemotherapies, or that have been reported to show anti-melanoma, or anti-skin cancer activities. Phytochemicals that are discussed in this review include flavonoids, carotenoids, terpenoids, vitamins, sulforaphane, some polyphenols and crude plant extracts.

Pyrazoleamide compounds are potent antimalarials that target Na+ homeostasis in intraerythrocytic Plasmodium falciparum

Science.gov (United States)

Vaidya, Akhil B.; Morrisey, Joanne M.; Zhang, Zhongsheng; Das, Sudipta; Daly, Thomas M.; Otto, Thomas D.; Spillman, Natalie J.; Wyvratt, Matthew; Siegl, Peter; Marfurt, Jutta; Wirjanata, Grennady; Sebayang, Boni F.; Price, Ric N.; Chatterjee, Arnab; Nagle, Advait; Stasiak, Marcin; Charman, Susan A.; Angulo-Barturen, Iñigo; Ferrer, Santiago; Belén Jiménez-Díaz, María; Martínez, María Santos; Gamo, Francisco Javier; Avery, Vicky M.; Ruecker, Andrea; Delves, Michael; Kirk, Kiaran; Berriman, Matthew; Kortagere, Sandhya; Burrows, Jeremy; Fan, Erkang; Bergman, Lawrence W.

2014-01-01

The quest for new antimalarial drugs, especially those with novel modes of action, is essential in the face of emerging drug-resistant parasites. Here we describe a new chemical class of molecules, pyrazoleamides, with potent activity against human malaria parasites and showing remarkably rapid parasite clearance in an in vivo model. Investigations involving pyrazoleamide-resistant parasites, whole-genome sequencing and gene transfers reveal that mutations in two proteins, a calcium-dependent protein kinase (PfCDPK5) and a P-type cation-ATPase (PfATP4), are necessary to impart full resistance to these compounds. A pyrazoleamide compound causes a rapid disruption of Na+ regulation in blood-stage Plasmodium falciparum parasites. Similar effect on Na+ homeostasis was recently reported for spiroindolones, which are antimalarials of a chemical class quite distinct from pyrazoleamides. Our results reveal that disruption of Na+ homeostasis in malaria parasites is a promising mode of antimalarial action mediated by at least two distinct chemical classes. PMID:25422853

Adsorption of selected pharmaceuticals and an endocrine disrupting compound by granular activated carbon. 2. Model prediction

Energy Technology Data Exchange (ETDEWEB)

Yu, Z.; Peldszus, S.; Huck, P.M. [University of Waterloo, Waterloo, ON (Canada). NSERC Chair in Water Treatment

2009-03-01

The adsorption of two representative pharmaceutically active compounds (PhACs) naproxen and carbamazepine and one endocrine disrupting compound (EDC) nonylphenol was studied in pilot-scale granular activated carbon (GAC) adsorbers using post-sedimentation (PS) water from a full-scale drinking water treatment plant. The GAC adsorbents were coal-based Calgon Filtrasorb 400 and coconut shell-based PICA CTIF TE. Acidic naproxen broke through fastest while nonylphenol was removed best, which was consistent with the degree to which fouling affected compound removals. Model predictions and experimental data were generally in good agreement for all three compounds, which demonstrated the effectiveness and robustness of the pore and surface diffusion model (PSDM) used in combination with the time-variable parameter approach for predicting removals at environmentally relevant concentrations (i.e., ng/L range). Sensitivity analyses suggested that accurate determination of film diffusion coefficients was critical for predicting breakthrough for naproxen and carbamazepine, in particular when high removals are targeted. Model simulations demonstrated that GAC carbon usage rates (CURs) for naproxen were substantially influenced by the empty bed contact time (EBCT) at the investigated conditions. Model-based comparisons between GAC CURs and minimum CURs for powdered activated carbon (PAC) applications suggested that PAC would be most appropriate for achieving 90% removal of naproxen, whereas GAC would be more suitable for nonylphenol. 25 refs., 4 figs., 1 tab.

A systematic evaluation of solubility enhancing excipients to enable the generation of permeability data for poorly soluble compounds in Caco-2 model.

Science.gov (United States)

Shah, Devang; Paruchury, Sundeep; Matta, Muralikrishna; Chowan, Gajendra; Subramanian, Murali; Saxena, Ajay; Soars, Matthew G; Herbst, John; Haskell, Roy; Marathe, Punit; Mandlekar, Sandhya

2014-01-01

The study presented here identified and utilized a panel of solubility enhancing excipients to enable the generation of flux data in the Human colon carcinoma (Caco-2) system for compounds with poor solubility. Solubility enhancing excipients Dimethyl acetamide (DMA) 1 % v/v, polyethylene glycol (PEG) 400 1% v/v, povidone 1% w/v, poloxamer 188 2.5% w/v and bovine serum albumin (BSA) 4% w/v did not compromise Caco-2 monolayer integrity as assessed by trans-epithelial resistance measurement (TEER) and Lucifer yellow (LY) permeation. Further, these excipients did not affect P-glycoprotein (P-gp) mediated bidirectional transport of digoxin, permeabilities of high (propranolol) or low permeability (atenolol) compounds, and were found to be inert to Breast cancer resistant protein (BCRP) mediated transport of cladribine. This approach was validated further using poorly soluble tool compounds, atazanavir (poloxamer 188 2.5% w/v) and cyclosporine A (BSA 4% w/v) and also applied to new chemical entity (NCE) BMS-A in BSA 4% w/v, for which Caco-2 data could not be generated using the traditional methodology due to poor solubility (solubility of atazanavir by >8 fold whereas BSA 4% w/v increased the solubility of cyclosporine A and BMS-A by >2-4 fold thereby enabling permeability as well as efflux liability estimation in the Caco-2 model with reasonable recovery values. To conclude, addition of excipients such as poloxamer 188 2.5% w/v and BSA 4% w/v to HBSS leads to a significant improvement in the solubility of the poorly soluble compounds resulting in enhanced recoveries without modulating transporter-mediated efflux, expanding the applicability of Caco-2 assays to poorly soluble compounds.

The radiation chemistry of the purine bases within DNA and related model compounds

International Nuclear Information System (INIS)

Cadet, J.; Berger, M.; Shaw, A.

1986-01-01

Both the direct and indirect effects of ionizing radiations are believed to contribute to the chemical changes induced in cellular DNA. Relevant information on the possible degradation pathways has been provided by studies using DNA model compounds, the major proportion of which have focused on pyrimidine components and sugar derivatives. With the development of powerful analytical tools such as high performance liquid chromatography and soft ionization mass spectrometry techniques, progress has recently been made in the elucidation of the nature of the radiation-induced chemical modifications of purine bases in DNA and related nucleosides and nucleotides. This short review details recent aspects of the radiation-induced degradation of adenine and guanine bases in DNA and its model compounds as the result of both direct and indirect effects. 11 refs., 2 figs., 1 tab

Chapter 8: Pyrolysis Mechanisms of Lignin Model Compounds Using a Heated Micro-Reactor

Energy Technology Data Exchange (ETDEWEB)

Robichaud, David J.; Nimlos, Mark R.; Ellison, G. Barney

2015-10-03

Lignin is an important component of biomass, and the decomposition of its thermal deconstruction products is important in pyrolysis and gasification. In this chapter, we investigate the unimolecular pyrolysis chemistry through the use of singly and doubly substituted benzene molecules that are model compounds representative of lignin and its primary pyrolysis products. These model compounds are decomposed in a heated micro-reactor, and the products, including radicals and unstable intermediates, are measured using photoionization mass spectrometry and matrix isolation infrared spectroscopy. We show that the unimolecular chemistry can yield insight into the initial decomposition of these species. At pyrolysis and gasification severities, singly substituted benzenes typically undergo bond scission and elimination reactions to form radicals. Some require radical-driven chain reactions. For doubly substituted benzenes, proximity effects of the substituents can change the reaction pathways.

Modeling of axonal endoplasmic reticulum network by spastic paraplegia proteins.

Science.gov (United States)

Yalçın, Belgin; Zhao, Lu; Stofanko, Martin; O'Sullivan, Niamh C; Kang, Zi Han; Roost, Annika; Thomas, Matthew R; Zaessinger, Sophie; Blard, Olivier; Patto, Alex L; Sohail, Anood; Baena, Valentina; Terasaki, Mark; O'Kane, Cahir J

2017-07-25

Axons contain a smooth tubular endoplasmic reticulum (ER) network that is thought to be continuous with ER throughout the neuron; the mechanisms that form this axonal network are unknown. Mutations affecting reticulon or REEP proteins, with intramembrane hairpin domains that model ER membranes, cause an axon degenerative disease, hereditary spastic paraplegia (HSP). We show that Drosophila axons have a dynamic axonal ER network, which these proteins help to model. Loss of HSP hairpin proteins causes ER sheet expansion, partial loss of ER from distal motor axons, and occasional discontinuities in axonal ER. Ultrastructural analysis reveals an extensive ER network in axons, which shows larger and fewer tubules in larvae that lack reticulon and REEP proteins, consistent with loss of membrane curvature. Therefore HSP hairpin-containing proteins are required for shaping and continuity of axonal ER, thus suggesting roles for ER modeling in axon maintenance and function.

A model in which heat shock protein 90 targets protein-folding clefts: rationale for a new approach to neuroprotective treatment of protein folding diseases.

Science.gov (United States)

Pratt, William B; Morishima, Yoshihiro; Gestwicki, Jason E; Lieberman, Andrew P; Osawa, Yoichi

2014-11-01

In an EBM Minireview published in 2010, we proposed that the heat shock protein (Hsp)90/Hsp70-based chaperone machinery played a major role in determining the selection of proteins that have undergone oxidative or other toxic damage for ubiquitination and proteasomal degradation. The proposal was based on a model in which the Hsp90 chaperone machinery regulates signaling by modulating ligand-binding clefts. The model provides a framework for thinking about the development of neuroprotective therapies for protein-folding diseases like Alzheimer's disease (AD), Parkinson's disease (PD), and the polyglutamine expansion disorders, such as Huntington's disease (HD) and spinal and bulbar muscular atrophy (SBMA). Major aberrant proteins that misfold and accumulate in these diseases are "client" proteins of the abundant and ubiquitous stress chaperone Hsp90. These Hsp90 client proteins include tau (AD), α-synuclein (PD), huntingtin (HD), and the expanded glutamine androgen receptor (polyQ AR) (SBMA). In this Minireview, we update our model in which Hsp90 acts on protein-folding clefts and show how it forms a rational basis for developing drugs that promote the targeted elimination of these aberrant proteins. © 2014 by the Society for Experimental Biology and Medicine.

Models of protein and amino acid requirements for cattle

Directory of Open Access Journals (Sweden)

Luis Orlindo Tedeschi

2015-03-01

Full Text Available Protein supply and requirements by ruminants have been studied for more than a century. These studies led to the accumulation of lots of scientific information about digestion and metabolism of protein by ruminants as well as the characterization of the dietary protein in order to maximize animal performance. During the 1980s and 1990s, when computers became more accessible and powerful, scientists began to conceptualize and develop mathematical nutrition models, and to program them into computers to assist with ration balancing and formulation for domesticated ruminants, specifically dairy and beef cattle. The most commonly known nutrition models developed during this period were the National Research Council (NRC in the United States, Agricultural Research Council (ARC in the United Kingdom, Institut National de la Recherche Agronomique (INRA in France, and the Commonwealth Scientific and Industrial Research Organization (CSIRO in Australia. Others were derivative works from these models with different degrees of modifications in the supply or requirement calculations, and the modeling nature (e.g., static or dynamic, mechanistic, or deterministic. Circa 1990s, most models adopted the metabolizable protein (MP system over the crude protein (CP and digestible CP systems to estimate supply of MP and the factorial system to calculate MP required by the animal. The MP system included two portions of protein (i.e., the rumen-undegraded dietary CP - RUP - and the contributions of microbial CP - MCP as the main sources of MP for the animal. Some models would explicitly account for the impact of dry matter intake (DMI on the MP required for maintenance (MPm; e.g., Cornell Net Carbohydrate and Protein System - CNCPS, the Dutch system - DVE/OEB, while others would simply account for scurf, urinary, metabolic fecal, and endogenous contributions independently of DMI. All models included milk yield and its components in estimating MP required for lactation

Ligand based pharmacophore modelling of anticancer histone ...

African Journals Online (AJOL)

USER

2010-06-21

Jun 21, 2010 ... are useful in predicting the biological activity of the compound or compound library by screening it ... with high affinity of binding toward a given protein ..... High- throughput structure-based pharmacophore modelling as a basis for successful parallel virtual screening. J. Comp. Aided Mol. Design, 20:.

New Linear Partitioning Models Based on Experimental Water: Supercritical CO2 Partitioning Data of Selected Organic Compounds.

Science.gov (United States)

Burant, Aniela; Thompson, Christopher; Lowry, Gregory V; Karamalidis, Athanasios K

2016-05-17

Partitioning coefficients of organic compounds between water and supercritical CO2 (sc-CO2) are necessary to assess the risk of migration of these chemicals from subsurface CO2 storage sites. Despite the large number of potential organic contaminants, the current data set of published water-sc-CO2 partitioning coefficients is very limited. Here, the partitioning coefficients of thiophene, pyrrole, and anisole were measured in situ over a range of temperatures and pressures using a novel pressurized batch-reactor system with dual spectroscopic detectors: a near-infrared spectrometer for measuring the organic analyte in the CO2 phase and a UV detector for quantifying the analyte in the aqueous phase. Our measured partitioning coefficients followed expected trends based on volatility and aqueous solubility. The partitioning coefficients and literature data were then used to update a published poly parameter linear free-energy relationship and to develop five new linear free-energy relationships for predicting water-sc-CO2 partitioning coefficients. A total of four of the models targeted a single class of organic compounds. Unlike models that utilize Abraham solvation parameters, the new relationships use vapor pressure and aqueous solubility of the organic compound at 25 °C and CO2 density to predict partitioning coefficients over a range of temperature and pressure conditions. The compound class models provide better estimates of partitioning behavior for compounds in that class than does the model built for the entire data set.

A resource for benchmarking the usefulness of protein structure models.

Science.gov (United States)

Carbajo, Daniel; Tramontano, Anna

2012-08-02

Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by non-academics: No.

A resource for benchmarking the usefulness of protein structure models

Directory of Open Access Journals (Sweden)

Carbajo Daniel

2012-08-01

Full Text Available Abstract Background Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. Results This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. Conclusions The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. Implementation, availability and requirements Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php. Operating system(s: Platform independent. Programming language: Perl-BioPerl (program; mySQL, Perl DBI and DBD modules (database; php, JavaScript, Jmol scripting (web server. Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet and PSAIA. License: Free. Any

A resource for benchmarking the usefulness of protein structure models.

KAUST Repository

Carbajo, Daniel

2012-08-02

BACKGROUND: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. RESULTS: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. CONCLUSIONS: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by

A resource for benchmarking the usefulness of protein structure models.

KAUST Repository

Carbajo, Daniel; Tramontano, Anna

2012-01-01

BACKGROUND: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. RESULTS: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. CONCLUSIONS: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by

Linear and nonlinear methods in modeling the aqueous solubility of organic compounds.

Science.gov (United States)

Catana, Cornel; Gao, Hua; Orrenius, Christian; Stouten, Pieter F W

2005-01-01

Solubility data for 930 diverse compounds have been analyzed using linear Partial Least Square (PLS) and nonlinear PLS methods, Continuum Regression (CR), and Neural Networks (NN). 1D and 2D descriptors from MOE package in combination with E-state or ISIS keys have been used. The best model was obtained using linear PLS for a combination between 22 MOE descriptors and 65 ISIS keys. It has a correlation coefficient (r2) of 0.935 and a root-mean-square error (RMSE) of 0.468 log molar solubility (log S(w)). The model validated on a test set of 177 compounds not included in the training set has r2 0.911 and RMSE 0.475 log S(w). The descriptors were ranked according to their importance, and at the top of the list have been found the 22 MOE descriptors. The CR model produced results as good as PLS, and because of the way in which cross-validation has been done it is expected to be a valuable tool in prediction besides PLS model. The statistics obtained using nonlinear methods did not surpass those got with linear ones. The good statistic obtained for linear PLS and CR recommends these models to be used in prediction when it is difficult or impossible to make experimental measurements, for virtual screening, combinatorial library design, and efficient leads optimization.

Pea VEGETATIVE2 Is an FD Homolog That Is Essential for Flowering and Compound Inflorescence Development.

Science.gov (United States)

Sussmilch, Frances C; Berbel, Ana; Hecht, Valérie; Vander Schoor, Jacqueline K; Ferrándiz, Cristina; Madueño, Francisco; Weller, James L

2015-04-01

As knowledge of the gene networks regulating inflorescence development in Arabidopsis thaliana improves, the current challenge is to characterize this system in different groups of crop species with different inflorescence architecture. Pea (Pisum sativum) has served as a model for development of the compound raceme, characteristic of many legume species, and in this study, we characterize the pea VEGETATIVE2 (VEG2) locus, showing that it is critical for regulation of flowering and inflorescence development and identifying it as a homolog of the bZIP transcription factor FD. Through detailed phenotypic characterizations of veg2 mutants, expression analyses, and the use of protein-protein interaction assays, we find that VEG2 has important roles during each stage of development of the pea compound inflorescence. Our results suggest that VEG2 acts in conjunction with multiple FLOWERING LOCUS T (FT) proteins to regulate expression of downstream target genes, including TERMINAL FLOWER1, LEAFY, and MADS box homologs, and to facilitate cross-regulation within the FT gene family. These findings further extend our understanding of the mechanisms underlying compound inflorescence development in pea and may have wider implications for future manipulation of inflorescence architecture in related legume crop species. © 2015 American Society of Plant Biologists. All rights reserved.

Xyloketal-derived small molecules show protective effect by decreasing mutant Huntingtin protein aggregates in Caenorhabditis elegans model of Huntington’s disease

Directory of Open Access Journals (Sweden)

Zeng YX

2016-04-01

Full Text Available Yixuan Zeng,1,2,* Wenyuan Guo,1,* Guangqing Xu,3 Qinmei Wang,4 Luyang Feng,1,2 Simei Long,1 Fengyin Liang,1 Yi Huang,1 Xilin Lu,1 Shichang Li,5 Jiebin Zhou,5 Jean-Marc Burgunder,6 Jiyan Pang,5 Zhong Pei1,2 1Department of Neurology, National Key Clinical Department and Key Discipline of Neurology, Guangdong Key Laboratory for Diagnosis and Treatment of Major Neurological Disease, The First Affiliated Hospital, Sun Yat-sen University, 2Guangzhou Center, Chinese Huntington’s Disease Network, 3Department of Rehabilitation, The First Affiliated Hospital, 4Key laboratory on Assisted Circulation, Ministry of Health, Department of Cardiovascular Medicine of the First Affiliated Hospital, 5School of Chemistry and Chemical Engineering, Sun Yat-sen University, Guangzhou, Guangdong, People’s Republic of China; 6Swiss Huntington’s Disease Center, Department of Neurology, University of Bern, Bern, Switzerland *These authors contributed equally to this work Abstract: Huntington’s disease is an autosomal-dominant neurodegenerative disorder, with chorea as the most prominent manifestation. The disease is caused by abnormal expansion of CAG codon repeats in the IT15 gene, which leads to the expression of a glutamine-rich protein named mutant Huntingtin (Htt. Because of its devastating disease burden and lack of valid treatment, development of more effective therapeutics for Huntington’s disease is urgently required. Xyloketal B, a natural product from mangrove fungus, has shown protective effects against toxicity in other neurodegenerative disease models such as Parkinson’s and Alzheimer’s diseases. To identify potential neuroprotective molecules for Huntington’s disease, six derivatives of xyloketal B were screened in a Caenorhabditis elegans Huntington’s disease model; all six compounds showed a protective effect. Molecular docking studies indicated that compound 1 could bind to residues GLN369 and GLN393 of the mutant Htt protein, forming a

A novel inhibitor of dengue virus replication that targets the capsid protein.

Science.gov (United States)

Byrd, Chelsea M; Dai, Dongcheng; Grosenbach, Douglas W; Berhanu, Aklile; Jones, Kevin F; Cardwell, Kara B; Schneider, Christine; Wineinger, Kristin A; Page, Jessica M; Harver, Chris; Stavale, Eric; Tyavanagimatt, Shanthakumar; Stone, Melialani A; Bartenschlager, Ralf; Scaturro, Pietro; Hruby, Dennis E; Jordan, Robert

2013-01-01

Dengue viruses (DENV) infect 50 to 100 million people worldwide per year, of which 500,000 develop severe life-threatening disease. This mosquito-borne illness is endemic in most tropical and subtropical countries and has spread significantly over the last decade. While there are several promising vaccine candidates in clinical trials, there are currently no approved vaccines or therapeutics available for treatment of dengue infection. Here, we describe a novel small-molecule compound, ST-148, that is a potent inhibitor of all four serotypes of DENV in vitro. ST-148 significantly reduced viremia and viral load in vital organs and tended to lower cytokine levels in the plasma in a nonlethal model of DENV infection in AG129 mice. Compound resistance mapped to the DENV capsid (C) gene, and a direct interaction of ST-148 with C protein is suggested by alterations of the intrinsic fluorescence of the protein in the presence of compound. Thus, ST-148 appears to interact with the DENV C protein and inhibits a distinct step(s) of the viral replication cycle.

Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

Directory of Open Access Journals (Sweden)

Jung Me Hwang

2011-12-01

Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

Preclinical models used for immunogenicity prediction of therapeutic proteins.

Science.gov (United States)

Brinks, Vera; Weinbuch, Daniel; Baker, Matthew; Dean, Yann; Stas, Philippe; Kostense, Stefan; Rup, Bonita; Jiskoot, Wim

2013-07-01

All therapeutic proteins are potentially immunogenic. Antibodies formed against these drugs can decrease efficacy, leading to drastically increased therapeutic costs and in rare cases to serious and sometimes life threatening side-effects. Many efforts are therefore undertaken to develop therapeutic proteins with minimal immunogenicity. For this, immunogenicity prediction of candidate drugs during early drug development is essential. Several in silico, in vitro and in vivo models are used to predict immunogenicity of drug leads, to modify potentially immunogenic properties and to continue development of drug candidates with expected low immunogenicity. Despite the extensive use of these predictive models, their actual predictive value varies. Important reasons for this uncertainty are the limited/insufficient knowledge on the immune mechanisms underlying immunogenicity of therapeutic proteins, the fact that different predictive models explore different components of the immune system and the lack of an integrated clinical validation. In this review, we discuss the predictive models in use, summarize aspects of immunogenicity that these models predict and explore the merits and the limitations of each of the models.

Model test on the relationship feed energy and protein ratio to the production and quality of milk protein

Science.gov (United States)

Hartanto, R.; Jantra, M. A. C.; Santosa, S. A. B.; Purnomoadi, A.

2018-01-01

The purpose of this research was to find an appropriate relationship model between the feed energy and protein ratio with the amount of production and quality of milk proteins. This research was conducted at Getasan Sub-district, Semarang Regency, Central Java Province, Indonesia using 40 samples (Holstein Friesian cattle, lactation period II-III and lactation month 3-4). Data were analyzed using linear and quadratic regressions, to predict the production and quality of milk protein from feed energy and protein ratio that describe the diet. The significance of model was tested using analysis of variance. Coefficient of determination (R2), residual variance (RV) and root mean square prediction error (RMSPE) were reported for the developed equations as an indicator of the goodness of model fit. The results showed no relationship in milk protein (kg), milk casein (%), milk casein (kg) and milk urea N (mg/dl) as function of CP/TDN. The significant relationship was observed in milk production (L or kg) and milk protein (%) as function of CP/TDN, both in linear and quadratic models. In addition, a quadratic change in milk production (L) (P = 0.003), milk production (kg) (P = 0.003) and milk protein concentration (%) (P = 0.026) were observed with increase of CP/TDN. It can be concluded that quadratic equation was the good fitting model for this research, because quadratic equation has larger R2, smaller RV and smaller RMSPE than those of linear equation.

Tracking 20 years of compound-to-target output from literature and patents.

Directory of Open Access Journals (Sweden)

Christopher Southan

Full Text Available The statistics of drug development output and declining yield of approved medicines has been the subject of many recent reviews. However, assessing research productivity that feeds development is more difficult. Here we utilise an extensive database of structure-activity relationships extracted from papers and patents. We have used this database to analyse published compounds cumulatively linked to nearly 4000 protein target identifiers from multiple species over the last 20 years. The compound output increases up to 2005 followed by a decline that parallels a fall in pharmaceutical patenting. Counts of protein targets have plateaued but not fallen. We extended these results by exploring compounds and targets for one large pharmaceutical company. In addition, we examined collective time course data for six individual protease targets, including average molecular weight of the compounds. We also tracked the PubMed profile of these targets to detect signals related to changes in compound output. Our results show that research compound output had decreased 35% by 2012. The major causative factor is likely to be a contraction in the global research base due to mergers and acquisitions across the pharmaceutical industry. However, this does not rule out an increasing stringency of compound quality filtration and/or patenting cost control. The number of proteins mapped to compounds on a yearly basis shows less decline, indicating the cumulative published target capacity of global research is being sustained in the region of 300 proteins for large companies. The tracking of six individual targets shows uniquely detailed patterns not discernible from cumulative snapshots. These are interpretable in terms of events related to validation and de-risking of targets that produce detectable follow-on surges in patenting. Further analysis of the type we present here can provide unique insights into the process of drug discovery based on the data it actually

Targeting Hsp27/eIF4E interaction with phenazine compound: a promising alternative for castration-resistant prostate cancer treatment.

Science.gov (United States)

Hajer, Ziouziou; Claudia, Andrieu; Erik, Laurini; Sara, Karaki; Maurizio, Fermeglia; Ridha, Oueslati; David, Taieb; Michel, Camplo; Olivier, Siri; Sabrina, Pricl; Maria, Katsogiannou; Palma, Rocchi

2017-09-29

The actual strategy to improve current therapies in advanced prostate cancer involves targeting genes activated by androgen withdrawal, either to delay or prevent the emergence of the castration-refractory phenotype. However, these genes are often implicated in several physiological processes, and long-term inhibition of survival proteins might be accompanied with cytotoxic effects. To avoid this problem, an alternative therapeutic strategy relies on the identification and use of compounds that disrupt specific protein-protein interactions involved in androgen withdrawal. Specifically, the interaction of the chaperone protein Hsp27 with the initiation factor eIF4E leads to the protection of protein synthesis initiation process and enhances cell survival during cell stress induced by castration or chemotherapy. Thus, in this work we aimed at i) identifying the interaction site of the Hsp27/eIF4E complex and ii) interfere with the relevant protein/protein association mechanism involved in castration-resistant progression of prostate cancer. By a combination of experimental and modeling techniques, we proved that eIF4E interacts with the C-terminal part of Hsp27, preferentially when Hsp27 is phosphorylated. We also observed that the loss of this interaction increased cell chemo-and hormone-sensitivity. In order to find a potential inhibitor of Hsp27/eIF4E interaction, BRET assays in combination with molecular simulations identified the phenazine derivative 14 as the compound able to efficiently interfere with this protein/protein interaction, thereby inhibiting cell viability and increasing cell death in chemo- and castration-resistant prostate cancer models in vitro and in vivo .

Strategies in megasynthase engineering – fatty acid synthases (FAS as model proteins

Directory of Open Access Journals (Sweden)

Manuel Fischer

2017-06-01

Full Text Available Megasynthases are large multienzyme proteins that produce a plethora of important natural compounds by catalyzing the successive condensation and modification of precursor units. Within the class of megasynthases, polyketide synthases (PKS are responsible for the production of a large spectrum of bioactive polyketides (PK, which have frequently found their way into therapeutic applications. Rational engineering approaches have been performed during the last 25 years that seek to employ the “assembly-line synthetic concept” of megasynthases in order to deliver new bioactive compounds. Here, we highlight PKS engineering strategies in the light of the newly emerging structural information on megasynthases, and argue that fatty acid synthases (FAS are and will be valuable objects for further developing this field.

An array of Escherichia coli clones over-expressing essential proteins: A new strategy of identifying cellular targets of potent antibacterial compounds

International Nuclear Information System (INIS)

Xu, H. Howard; Real, Lilian; Bailey, Melissa Wu

2006-01-01

With the advancement of high throughput screening, it has become easier and faster to discover hit compounds that inhibit proliferation of bacterial cells. However, development in technologies used to identify cellular targets of potent antibacterial inhibitors has lagged behind. Here, we describe a novel strategy of target identification for antibacterial inhibitors using an array of Escherichia coli clones each over-expressing one essential protein. In a proof-of-concept study, eight essential genes were cloned into pLex5BA vector under the control of an inducible promoter. Over-expression of target proteins was confirmed. For two clones, one over-expressing FabI and the other over-expressing MurA enzymes, the host cells became 17- and 139-fold more resistant to the specific inhibitors triclosan and phosphomycin, respectively, while the susceptibility of other clones towards these inhibitors remained unchanged after induction of gene expression. Target identification via target protein over-expression was demonstrated using both mixed clone and individual clone assay formats

The reactivity of phenolic and non-phenolic residual kraft lignin model compounds with Mn(II)-peroxidase from Lentinula edodes.

Science.gov (United States)

Crestini, C; D'Annibale, A; Sermanni, G G; Saladino, R

2000-02-01

Three phenolic model compounds representing bonding patterns of residual kraft lignin were incubated with manganese peroxidase from Lentinula edodes. Extensive degradation of all the phenolic models, mainly occurring via side-chain benzylic oxidation, was observed. Among the tested model compounds the diphenylmethane alpha-5 phenolic model was found to be the most reactive, yielding several products showing oxidation and fragmentation at the bridging position. The non-phenolic 5-5' biphenyl and 5-5' diphenylmethane models were found unreactive.

Protein structure analysis using the resonant recognition model and wavelet transforms

International Nuclear Information System (INIS)

Fang, Q.; Cosic, I.

1998-01-01

An approach based on the resonant recognition model and the discrete wavelet transform is introduced here for characterising proteins' biological function. The protein sequence is converted into a numerical series by assigning the electron-ion interaction potential to each amino acid from N-terminal to C-terminal. A set of peaks is found after performing a wavelet transform onto a numerical series representing a group of homologous proteins. These peaks are related to protein structural and functional properties and named characteristic vector of that protein group. Further more, the amino acids contributing mostly to a protein's biological functions, the so-called 'hot spots' amino acids, are predicted by the continuous wavelet transform. It is found that the hot spots are clustered around the protein's cleft structure. The wavelets approach provides a novel methods for amino acid sequence analysis as well as an expansion for the newly established macromolecular interaction model: the resonant recognition model. Copyright (1998) Australasian Physical and Engineering Sciences in Medicine

A generative, probabilistic model of local protein structure

DEFF Research Database (Denmark)

Boomsma, Wouter; Mardia, Kanti V.; Taylor, Charles C.

2008-01-01

Despite significant progress in recent years, protein structure prediction maintains its status as one of the prime unsolved problems in computational biology. One of the key remaining challenges is an efficient probabilistic exploration of the structural space that correctly reflects the relative...... conformational stabilities. Here, we present a fully probabilistic, continuous model of local protein structure in atomic detail. The generative model makes efficient conformational sampling possible and provides a framework for the rigorous analysis of local sequence-structure correlations in the native state...

Inhibition of protein synthesis and malaria parasite development by drug targeting of methionyl-tRNA synthetases.

Science.gov (United States)

Hussain, Tahir; Yogavel, Manickam; Sharma, Amit

2015-04-01

Aminoacyl-tRNA synthetases (aaRSs) are housekeeping enzymes that couple cognate tRNAs with amino acids to transmit genomic information for protein translation. The Plasmodium falciparum nuclear genome encodes two P. falciparum methionyl-tRNA synthetases (PfMRS), termed PfMRS(cyt) and PfMRS(api). Phylogenetic analyses revealed that the two proteins are of primitive origin and are related to heterokonts (PfMRS(cyt)) or proteobacteria/primitive bacteria (PfMRS(api)). We show that PfMRS(cyt) localizes in parasite cytoplasm, while PfMRS(api) localizes to apicoplasts in asexual stages of malaria parasites. Two known bacterial MRS inhibitors, REP3123 and REP8839, hampered Plasmodium growth very effectively in the early and late stages of parasite development. Small-molecule drug-like libraries were screened against modeled PfMRS structures, and several "hit" compounds showed significant effects on parasite growth. We then tested the effects of the hit compounds on protein translation by labeling nascent proteins with (35)S-labeled cysteine and methionine. Three of the tested compounds reduced protein synthesis and also blocked parasite growth progression from the ring stage to the trophozoite stage. Drug docking studies suggested distinct modes of binding for the three compounds, compared with the enzyme product methionyl adenylate. Therefore, this study provides new targets (PfMRSs) and hit compounds that can be explored for development as antimalarial drugs. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Expression of renin-angiotensin system signalling compounds in maternal protein-restricted rats: effect on renal sodium excretion and blood pressure.

Science.gov (United States)

Mesquita, Flávia Fernandes; Gontijo, José Antonio Rocha; Boer, Patrícia Aline

2010-02-01

Intrauterine growth restriction due to low maternal dietary protein during pregnancy is associated with retardation of foetal growth, renal alterations and adult hypertension. The renin-angiotensin system (RAS) is a coordinated hormonal cascade in the control of cardiovascular, renal and adrenal function that governs body fluid and electrolyte balance, as well as arterial pressure. In the kidney, all the components of the renin-angiotensin system including angiotensin II type 1 (AT1) and type 2 (AT2) receptors are expressed locally during nephrogenesis. Hence, we investigated whether low protein diet intake during pregnancy altered kidney and adrenal expression of AT1(R) and AT2(R) receptors, their pathways and if the modified expression of the RAS compounds occurs associated with changes in urinary sodium and in arterial blood pressure in sixteen-week-old males' offspring of the underfed group. The pregnancy dams were divided in two groups: with normal protein diet (pups named NP) (17% protein) or low protein diet (pups LP) (6% protein) during all pregnancy. The present data confirm a significant enhancement in arterial pressure in the LP group. Furthermore, the study showed a significantly decreased expression of RAS pathway protein and Ang II receptors in the kidney and an increased expression in the adrenal of LP rats. The detailed immunohistochemical analysis of RAS signalling proteins in the kidney confirm the immunoblotting results for both groups. The present investigation also showed a pronounced decrease in fractional urinary sodium excretion in maternal protein-restricted offspring, compared with the NP age-matched group. This occurred despite unchanged creatinine clearance. The current data led us to hypothesize that foetal undernutrition could be associated with decreased kidney expression of AT(R) resulting in the inability of renal tubules to handle the hydro-electrolyte balance, consequently causing arterial hypertension.

Computational results on the compound binomial risk model with nonhomogeneous claim occurrences

NARCIS (Netherlands)

Tuncel, A.; Tank, F.

2013-01-01

The aim of this paper is to give a recursive formula for non-ruin (survival) probability when the claim occurrences are nonhomogeneous in the compound binomial risk model. We give recursive formulas for non-ruin (survival) probability and for distribution of the total number of claims under the

Molecular Docking Analysis of Ginger Active Compound on Transient Receptor Potential Cation Channel Subfamily V Member 1 (TRPV1

Directory of Open Access Journals (Sweden)

Fifteen Aprila Fajrin

2018-02-01

Full Text Available Ginger had been reported to ameliorate painful diabetic neuropathy (PDN in an animal model. Gingerol and shogaol were active compounds of ginger that potentially act on transient receptor potential cation channel subfamily V member 1 (TRPV1, a key receptor in PDN. This study aims to predict the binding of gingerol and shogaol to TRPV1 using an in silico model. The ligands of the docking study were 3 chemical compounds of each gingerol and shogaol, i.e. 6-shogaol, 8-shogaol, 10-shogaol, 6-gingerol, 8 gingerol and 10-gingerol. Capsaicin, a TRPV1 agonist, was used as a native ligand. The TRPV1 structure was taken from Protein Data Bank (ID 3J9J. The docking analysis was performed using Autodock Vina. The result showed that among the ginger active compounds, 6-shogaol had the strongest binding energy (-7.10 kcal/mol to TRPV1. The 6-shogaol lacked the potential hydrogen bond to Ile265 of TRPV1 protein, which capsacin had. However, it's binding energy towards TRPV1 was not significantly different compared to capsaicin. Therefore, 6-shogaol had potential to be developed as a treatment for PDN.

Compound immobilization and drug-affinity chromatography.

Science.gov (United States)

Rix, Uwe; Gridling, Manuela; Superti-Furga, Giulio

2012-01-01

Bioactive small molecules act through modulating a yet unpredictable number of targets. It is therefore of critical importance to define the cellular target proteins of a compound as an entry point to understanding its mechanism of action. Often, this can be achieved in a direct fashion by chemical proteomics. As with any affinity chromatography, immobilization of the bait to a solid support is one of the earliest and most crucial steps in the process. Interfering with structural features that are important for identification of a target protein will be detrimental to binding affinity. Also, many molecules are sensitive to heat or to certain chemicals, such as acid or base, and might be destroyed during the process of immobilization, which therefore needs to be not only efficient, but also mild. The subsequent affinity chromatography step needs to preserve molecular and conformational integrity of both bait compound and proteins in order to result in the desired specific enrichment while ensuring a high level of compatibility with downstream analysis by mass spectrometry. Thus, the right choice of detergent, buffer, and protease inhibitors is also essential. This chapter describes a widely applicable procedure for the immobilization of small molecule drugs and for drug-affinity chromatography with subsequent protein identification by mass spectrometry.

Effect of perioperative application of L-asrginine combined with intacted protein compound preparations on postoperative antitumor immunity and tumor load in patients with gastric cancer

Directory of Open Access Journals (Sweden)

Xiu-Lan Jiang

2016-10-01

Full Text Available Objective: To analyze the effect of perioperative application of L-arginine combined with intacted protein compound preparations on postoperative antitumor immunity and tumor load in patients with gastric cancer. Methods: A total of 68 patients with gastric cancer received radical operation, and according to different perioperative nutrition intervention, they were divided into control group (normal glucose saline enteral nutrition and observation group (L-arginine combined with intacted protein compound preparations enteral nutrition by half. Postoperative short-term antitumor immune cell levels and serum levels of illness-related indexes, nutrition and inflammation indexes of two groups were detected, patients were followed up for 3 years and the gastric stump MRI changes were observed. Results: Venous blood CD4+ T lymphocyte level and CD4+ /CD8+ ratio of observation group 3 months after treatment were higher than those of control group while CD8+ T lymphocyte and Treg cell levels were lower than those of control group; serum Pentraxin-3, CYFRA21-1, TTF-1 and HE4 levels were lower than those of control group; ALB, PA and IL-2 levels were higher than those of control group while IL-6 and IL-10 levels were lower than those of control group (P<0.05. Gastric stump MRI images 3 years after operation were significantly different between two groups. Conclusions: Perioperative application of L-arginine combined with intacted protein compound preparations can optimize postoperative immune and nutritional state in patients with gastric cancer, and it also has positive effect on reducing the incidence of long-term gastric stump carcinoma and other aspects.

Variation in predicted internal concentrations in relation to PBPK model complexity for rainbow trout

Energy Technology Data Exchange (ETDEWEB)

Salmina, E.S.; Wondrousch, D. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, 09596 Freiberg (Germany); Kühne, R. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Potemkin, V.A. [Department of Chemistry, South Ural State Medical University, Vorovskogo 64, 454048, Chelyabinsk (Russian Federation); Schüürmann, G. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, 09596 Freiberg (Germany)

2016-04-15

The present study is motivated by the increasing demand to consider internal partitioning into tissues instead of exposure concentrations for the environmental toxicity assessment. To this end, physiologically based pharmacokinetic (PBPK) models can be applied. We evaluated the variation in accuracy of PBPK model outcomes depending on tissue constituents modeled as sorptive phases and chemical distribution tendencies addressed by molecular descriptors. The model performance was examined using data from 150 experiments for 28 chemicals collected from US EPA databases. The simplest PBPK model is based on the “K{sub ow}-lipid content” approach as being traditional for environmental toxicology. The most elaborated one considers five biological sorptive phases (polar and non-polar lipids, water, albumin and the remaining proteins) and makes use of LSER (linear solvation energy relationship) parameters to describe the compound partitioning behavior. The “K{sub ow}-lipid content”-based PBPK model shows more than one order of magnitude difference in predicted and measured values for 37% of the studied exposure experiments while for the most elaborated model this happens only for 7%. It is shown that further improvements could be achieved by introducing corrections for metabolic biotransformation and compound transmission hindrance through a cellular membrane. The analysis of the interface distribution tendencies shows that polar tissue constituents, namely water, polar lipids and proteins, play an important role in the accumulation behavior of polar compounds with H-bond donating functional groups. For compounds without H-bond donating fragments preferable accumulation phases are storage lipids and water depending on compound polarity. - Highlights: • For reliable predictions, models of a certain complexity should be compared. • For reliable predictions non-lipid fish tissue constituents should be considered. • H-donor compounds preferably accumulate in water

Variation in predicted internal concentrations in relation to PBPK model complexity for rainbow trout

International Nuclear Information System (INIS)

Salmina, E.S.; Wondrousch, D.; Kühne, R.; Potemkin, V.A.; Schüürmann, G.

2016-01-01

The present study is motivated by the increasing demand to consider internal partitioning into tissues instead of exposure concentrations for the environmental toxicity assessment. To this end, physiologically based pharmacokinetic (PBPK) models can be applied. We evaluated the variation in accuracy of PBPK model outcomes depending on tissue constituents modeled as sorptive phases and chemical distribution tendencies addressed by molecular descriptors. The model performance was examined using data from 150 experiments for 28 chemicals collected from US EPA databases. The simplest PBPK model is based on the “K_o_w-lipid content” approach as being traditional for environmental toxicology. The most elaborated one considers five biological sorptive phases (polar and non-polar lipids, water, albumin and the remaining proteins) and makes use of LSER (linear solvation energy relationship) parameters to describe the compound partitioning behavior. The “K_o_w-lipid content”-based PBPK model shows more than one order of magnitude difference in predicted and measured values for 37% of the studied exposure experiments while for the most elaborated model this happens only for 7%. It is shown that further improvements could be achieved by introducing corrections for metabolic biotransformation and compound transmission hindrance through a cellular membrane. The analysis of the interface distribution tendencies shows that polar tissue constituents, namely water, polar lipids and proteins, play an important role in the accumulation behavior of polar compounds with H-bond donating functional groups. For compounds without H-bond donating fragments preferable accumulation phases are storage lipids and water depending on compound polarity. - Highlights: • For reliable predictions, models of a certain complexity should be compared. • For reliable predictions non-lipid fish tissue constituents should be considered. • H-donor compounds preferably accumulate in water, polar

Modeling disordered regions in proteins using Rosetta.

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Ray Yu-Ruei Wang

Full Text Available Protein structure prediction methods such as Rosetta search for the lowest energy conformation of the polypeptide chain. However, the experimentally observed native state is at a minimum of the free energy, rather than the energy. The neglect of the missing configurational entropy contribution to the free energy can be partially justified by the assumption that the entropies of alternative folded states, while very much less than unfolded states, are not too different from one another, and hence can be to a first approximation neglected when searching for the lowest free energy state. The shortcomings of current structure prediction methods may be due in part to the breakdown of this assumption. Particularly problematic are proteins with significant disordered regions which do not populate single low energy conformations even in the native state. We describe two approaches within the Rosetta structure modeling methodology for treating such regions. The first does not require advance knowledge of the regions likely to be disordered; instead these are identified by minimizing a simple free energy function used previously to model protein folding landscapes and transition states. In this model, residues can be either completely ordered or completely disordered; they are considered disordered if the gain in entropy outweighs the loss of favorable energetic interactions with the rest of the protein chain. The second approach requires identification in advance of the disordered regions either from sequence alone using for example the DISOPRED server or from experimental data such as NMR chemical shifts. During Rosetta structure prediction calculations the disordered regions make only unfavorable repulsive contributions to the total energy. We find that the second approach has greater practical utility and illustrate this with examples from de novo structure prediction, NMR structure calculation, and comparative modeling.

Protein adhesives

Science.gov (United States)

Charles R. Frihart; Linda F. Lorenz

2018-01-01

Nature uses a wide variety of chemicals for providing adhesion internally (e.g., cell to cell) and externally (e.g., mussels to ships and piers). This adhesive bonding is chemically and mechanically complex, involving a variety of proteins, carbohydrates, and other compounds.Consequently,the effect of protein structures on adhesive properties is only partially...

Radical transfer between proteins: role of tyrosine, tryptophan and protein peroxyl radicals

International Nuclear Information System (INIS)

Irwin, J.A.; Ostdal, H.; Davies, M.J.

1998-01-01

Reaction of the Fe(III) forms of the heme proteins myoglobin (Mb) and horseradish peroxidase (HRP) with H 2 O 2 gives rise to high-oxidation-state heme-derived species which can be described as a Fe(IV)-oxo porphyrin radical-cation ('Compound 1'). In the case of Mb, the Fe(IV)-oxo porphyrin radical-cation undergoes rapid electron transfer with the surrounding protein to give protein (globin)-derived radicals and an Fe(lV)-oxo species ('Compound 2'). The globin-derived radicals have been shown to be located at two (or more) sites: Tyr-103 or Trp-14, with the latter radical known to react with oxygen to give a Trp-derived peroxyl radical (Mb-Trp-OO*). With HRP, the Fe(lV)-oxo porphyrin radical-cation carries out two successive one-electron oxidation reactions at the exposed heme edge to give firstly 'Compound 2' [the Fe(lV)oxo species] and then the resting Fe(III) state of the enzyme. n this study we have investigated whether the Trp-14 peroxyl radical from Mb and the Compound 1 and 2 species from HRP (in the absence and presence of free Tyr) can oxidise amino acids, peptides and proteins. Such reactions constitute intermolecular protein-to-protein radical transfer reactions and hence protein chain-oxidation. We have also examined whether these oxidants react with antioxidants. Reaction of these heme-protein derived oxidants with amino acids, proteins and antioxidants has been carried out at room temperature for defined periods of time before freeze-quenching to 77K to halt reaction. The radical species present in the reaction system at the time of freezing were subsequently examined by EPR spectroscopy at 77K. Three free amino acids, Tyr, Trp and Cys (with Cys the least efficient) have been shown to react rapidly with Mb-Trp-OO*, as evidenced by the loss of the characteristic EPR features of Mb-Trp-OO* on inclusion of increasing concentrations of the amino acids. All other amino acids are much less reactive. Evidence has also been obtained for (inefficient) hydrogen

Identifying developmental vascular disruptor compounds using a predictive signature and alternative toxicity models

Science.gov (United States)

Identifying Developmental Vascular Disruptor Compounds Using a Predictive Signature and Alternative Toxicity Models Presenting Author: Tamara Tal Affiliation: U.S. EPA/ORD/ISTD, RTP, NC, USA Chemically induced vascular toxicity during embryonic development can result in a wide...

Conformational Sampling in Template-Free Protein Loop Structure Modeling: An Overview

OpenAIRE

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increas...

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z.; Gao, Xin

2017-01-01

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza

2017-02-08

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Phenotypic Screening Identifies Modulators of Amyloid Precursor Protein Processing in Human Stem Cell Models of Alzheimer’s Disease

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Philip W. Brownjohn

2017-04-01

Full Text Available Summary: Human stem cell models have the potential to provide platforms for phenotypic screens to identify candidate treatments and cellular pathways involved in the pathogenesis of neurodegenerative disorders. Amyloid precursor protein (APP processing and the accumulation of APP-derived amyloid β (Aβ peptides are key processes in Alzheimer's disease (AD. We designed a phenotypic small-molecule screen to identify modulators of APP processing in trisomy 21/Down syndrome neurons, a complex genetic model of AD. We identified the avermectins, commonly used as anthelmintics, as compounds that increase the relative production of short Aβ peptides at the expense of longer, potentially more toxic peptides. Further studies demonstrated that this effect is not due to an interaction with the core γ-secretase responsible for Aβ production. This study demonstrates the feasibility of phenotypic drug screening in human stem cell models of Alzheimer-type dementia, and points to possibilities for indirectly modulating APP processing, independently of γ-secretase modulation. : In this article, Livesey and colleagues perform a phenotypic drug screen in a human stem cell model of Alzheimer's disease. The anthelminthic avermectins are identified as a family of compounds that increase the production of short Aβ peptides over longer more toxic Aβ forms. The effect is analogous to existing γ-secretase modulators, but is independent of the core γ-secretase complex. Keywords: neural stem cells, Alzheimer's disease, phenotypic screening, iPSCs, human neurons, dementia, Down syndrome, amyloid beta, ivermectin, selamectin

Influence of food matrix on absorption of flavour compounds by linear low-density polyethylene: proteins and carbohydrates

NARCIS (Netherlands)

Willige, van R.W.G.; Linssen, J.P.H.; Voragen, A.G.J.

2000-01-01

The influence of oil and food components in real food products on the absorption of four flavour compounds (limonene, decanal, linalool and ethyl 2-methyl butyrate) into linear low-density polyethylene (LLDPE) was studied using a large volume injection GC in vial extraction method. Model food

Retinoid-binding proteins: similar protein architectures bind similar ligands via completely different ways.

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Yu-Ru Zhang

Full Text Available BACKGROUND: Retinoids are a class of compounds that are chemically related to vitamin A, which is an essential nutrient that plays a key role in vision, cell growth and differentiation. In vivo, retinoids must bind with specific proteins to perform their necessary functions. Plasma retinol-binding protein (RBP and epididymal retinoic acid binding protein (ERABP carry retinoids in bodily fluids, while cellular retinol-binding proteins (CRBPs and cellular retinoic acid-binding proteins (CRABPs carry retinoids within cells. Interestingly, although all of these transport proteins possess similar structures, the modes of binding for the different retinoid ligands with their carrier proteins are different. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we analyzed the various retinoid transport mechanisms using structure and sequence comparisons, binding site analyses and molecular dynamics simulations. Our results show that in the same family of proteins and subcellular location, the orientation of a retinoid molecule within a binding protein is same, whereas when different families of proteins are considered, the orientation of the bound retinoid is completely different. In addition, none of the amino acid residues involved in ligand binding is conserved between the transport proteins. However, for each specific binding protein, the amino acids involved in the ligand binding are conserved. The results of this study allow us to propose a possible transport model for retinoids. CONCLUSIONS/SIGNIFICANCE: Our results reveal the differences in the binding modes between the different retinoid-binding proteins.

Isolation and Characterization of Protein Tyrosine Phosphatase 1B (PTP1B Inhibitory Polyphenolic Compounds From Dodonaea viscosa and Their Kinetic Analysis

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Zia Uddin

2018-03-01

Full Text Available Diabetes mellitus is one of a major worldwide concerns, regulated by either defects in secretion or action of insulin, or both. Insulin signaling down-regulation has been related with over activity of protein tyrosine phosphatase 1B (PTP1B enzyme, which has been a promising target for the treatment of diabetes mellitus. Herein, activity guided separation of methanol extract (95% of Dodonaea viscosa aerial parts afforded nine (1-9 polyphenolic compounds, all of them were identified through spectroscopic data including 2D NMR and HREIMS. Subsequently, their PTP1B inhibitory potentials were evaluated, in which all of the isolates exhibited significant dose-dependent inhibition with IC50 13.5–57.9 μM. Among them, viscosol (4 was found to be the most potent compound having IC50 13.5 μM. In order to unveil the mechanistic behavior, detailed kinetic study was carried out, in which compound 4 was observed as a reversible, and mixed type I inhibitor of PTP1B with inhibitory constant (Ki value of 4.6 μM. Furthermore, we annotated the major metabolites through HPLC-DAD-ESI/MS analysis, in which compounds 3, 6, 7, and 9 were found to be the most abundant metabolites in D. viscosa extract.

Isolation and characterization of protein tyrosine phosphatase 1B (PTP1B) inhibitory polyphenolic compounds from Dodonaea viscosa and their kinetic analysis

Science.gov (United States)

Uddin, Zia; Song, Yeong Hun; Ullah, Mahboob; Li, Zuopeng; Kim, Jeong Yoon; Park, Ki Hun

2018-03-01

Diabetes mellitus is one of a major worldwide concerns, regulated by either defects in secretion or action of insulin, or both. Insulin signaling down-regulation has been related with over activity of protein tyrosine phosphatase 1B (PTP1B) enzyme, which has been a promising target for the treatment of diabetes mellitus. Herein, activity guided separation of methanol extract (95%) of Dodonaea viscosa aerial parts afforded nine (1-9) polyphenolic compounds, all of them were identified through spectroscopic data including 2D NMR and HREIMS. Subsequently, their PTP1B inhibitory potentials were evaluated, in which all of the isolates exhibited significant dose-dependent inhibition with IC50 13.5-57.9 μM. Among them, viscosol (4) was found to be the most potent compound having IC50 13.5 μM. In order to unveil the mechanistic behavior, detailed kinetic study was carried out, in which compound 4 was observed as a reversible, and mixed type I inhibitor of PTP1B with inhibitory constant (Ki) value of 4.6 μM. Furthermore, we annotated the major metabolites through HPLC-DAD-ESI/MS analysis, in which compounds 3, 6, 7 and 9 were found to be the most abundant metabolites in D.viscosa extract.

Singlet oxygen-mediated protein oxidation

DEFF Research Database (Denmark)

Wright, Adam; Bubb, William A; Hawkins, Clare Louise

2002-01-01

Singlet oxygen (1O2) is generated by a number of enzymes as well as by UV or visible light in the presence of a sensitizer and has been proposed as a damaging agent in a number of pathologies including cataract, sunburn, and skin cancers. Proteins, and Cys, Met, Trp, Tyr and His side chains...... in particular, are major targets for 1O2 as a result of their abundance and high rate constants for reaction. In this study it is shown that long-lived peroxides are formed on free Tyr, Tyr residues in peptides and proteins, and model compounds on exposure to 1O2 generated by both photochemical and chemical....... These studies demonstrate that long-lived Tyr-derived peroxides are formed on proteins exposed to 1O2 and that these may promote damage to other targets via further radical generation....

The Action of Chain Extenders in Nylon-6, PET, and Model Compounds

NARCIS (Netherlands)

Loontjens, T.; Pauwels, K.; Derks, F.; Neilen, M.; Sham, C.K.; Serné, M.

1997-01-01

The action of two complementary chain extenders is studied in model systems as well as in poly(ethylene terephthalate) (PET) and nylon–6. Chain extenders are low molecular weight compounds that can be used to increase the molecular weight of polymers in a short time. The reaction must preferably be

Model of a DNA-protein complex of the architectural monomeric protein MC1 from Euryarchaea.

Directory of Open Access Journals (Sweden)

Françoise Paquet

Full Text Available In Archaea the two major modes of DNA packaging are wrapping by histone proteins or bending by architectural non-histone proteins. To supplement our knowledge about the binding mode of the different DNA-bending proteins observed across the three domains of life, we present here the first model of a complex in which the monomeric Methanogen Chromosomal protein 1 (MC1 from Euryarchaea binds to the concave side of a strongly bent DNA. In laboratory growth conditions MC1 is the most abundant architectural protein present in Methanosarcina thermophila CHTI55. Like most proteins that strongly bend DNA, MC1 is known to bind in the minor groove. Interaction areas for MC1 and DNA were mapped by Nuclear Magnetic Resonance (NMR data. The polarity of protein binding was determined using paramagnetic probes attached to the DNA. The first structural model of the DNA-MC1 complex we propose here was obtained by two complementary docking approaches and is in good agreement with the experimental data previously provided by electron microscopy and biochemistry. Residues essential to DNA-binding and -bending were highlighted and confirmed by site-directed mutagenesis. It was found that the Arg25 side-chain was essential to neutralize the negative charge of two phosphates that come very close in response to a dramatic curvature of the DNA.

Protein homology model refinement by large-scale energy optimization.

Science.gov (United States)

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

A Study on the Use of Compound and Extracted Models in the High Frequency Electromagnetic Exposure Assessment

Directory of Open Access Journals (Sweden)

Mario Cvetković

2017-01-01

Full Text Available The paper presents the numerical results for the induced electric field in the various models of the human eye and the head. The comparison between the extracted or the single organ models and the compound organ models placed inside realistic head models obtained from the magnetic resonance imaging scans is presented. The numerical results for several frequencies and polarizations of the incident electromagnetic (EM plane wave are obtained using the hybrid finite element method/boundary element method (FEM/BEM formulation and the surface integral equation (SIE based formulation featuring the use of method of moments, respectively. Although some previous analysis showed the similar distribution of the induced electric field along the pupillary axis obtained in both eye models, this study showed this not to be the case in general. The analysis showed that the compound eye model is much more suitable when taking into account the polarization of the incident EM wave. The numerical results for the brain models showed much better agreement in the maximum values and distributions of the induced surface field between detailed models, while homogeneous brain model showed better agreement with the compound model in the distribution along selected sagittal axis points. The analysis could provide some helpful insights when carrying out the dosimetric analysis of the human eye and the head/brain exposed to high frequency EM radiation.

Virtual screening using combinatorial cyclic peptide libraries reveals protein interfaces readily targetable by cyclic peptides.

Science.gov (United States)

Duffy, Fergal J; O'Donovan, Darragh; Devocelle, Marc; Moran, Niamh; O'Connell, David J; Shields, Denis C

2015-03-23

Protein-protein and protein-peptide interactions are responsible for the vast majority of biological functions in vivo, but targeting these interactions with small molecules has historically been difficult. What is required are efficient combined computational and experimental screening methods to choose among a number of potential protein interfaces worthy of targeting lead macrocyclic compounds for further investigation. To achieve this, we have generated combinatorial 3D virtual libraries of short disulfide-bonded peptides and compared them to pharmacophore models of important protein-protein and protein-peptide structures, including short linear motifs (SLiMs), protein-binding peptides, and turn structures at protein-protein interfaces, built from 3D models available in the Protein Data Bank. We prepared a total of 372 reference pharmacophores, which were matched against 108,659 multiconformer cyclic peptides. After normalization to exclude nonspecific cyclic peptides, the top hits notably are enriched for mimetics of turn structures, including a turn at the interaction surface of human α thrombin, and also feature several protein-binding peptides. The top cyclic peptide hits also cover the critical "hot spot" interaction sites predicted from the interaction crystal structure. We have validated our method by testing cyclic peptides predicted to inhibit thrombin, a key protein in the blood coagulation pathway of important therapeutic interest, identifying a cyclic peptide inhibitor with lead-like activity. We conclude that protein interfaces most readily targetable by cyclic peptides and related macrocyclic drugs may be identified computationally among a set of candidate interfaces, accelerating the choice of interfaces against which lead compounds may be screened.

Advanced Model Compounds for Understanding Acid-Catalyzed Lignin Depolymerization: Identification of Renewable Aromatics and a Lignin-Derived Solvent.

Science.gov (United States)

Lahive, Ciaran W; Deuss, Peter J; Lancefield, Christopher S; Sun, Zhuohua; Cordes, David B; Young, Claire M; Tran, Fanny; Slawin, Alexandra M Z; de Vries, Johannes G; Kamer, Paul C J; Westwood, Nicholas J; Barta, Katalin

2016-07-20

The development of fundamentally new approaches for lignin depolymerization is challenged by the complexity of this aromatic biopolymer. While overly simplified model compounds often lack relevance to the chemistry of lignin, the direct use of lignin streams poses significant analytical challenges to methodology development. Ideally, new methods should be tested on model compounds that are complex enough to mirror the structural diversity in lignin but still of sufficiently low molecular weight to enable facile analysis. In this contribution, we present a new class of advanced (β-O-4)-(β-5) dilinkage models that are highly realistic representations of a lignin fragment. Together with selected β-O-4, β-5, and β-β structures, these compounds provide a detailed understanding of the reactivity of various types of lignin linkages in acid catalysis in conjunction with stabilization of reactive intermediates using ethylene glycol. The use of these new models has allowed for identification of novel reaction pathways and intermediates and led to the characterization of new dimeric products in subsequent lignin depolymerization studies. The excellent correlation between model and lignin experiments highlights the relevance of this new class of model compounds for broader use in catalysis studies. Only by understanding the reactivity of the linkages in lignin at this level of detail can fully optimized lignin depolymerization strategies be developed.

Protein design for pathway engineering.

Science.gov (United States)

Eriksen, Dawn T; Lian, Jiazhang; Zhao, Huimin

2014-02-01

Design and construction of biochemical pathways has increased the complexity of biosynthetically-produced compounds when compared to single enzyme biocatalysis. However, the coordination of multiple enzymes can introduce a complicated set of obstacles to overcome in order to achieve a high titer and yield of the desired compound. Metabolic engineering has made great strides in developing tools to optimize the flux through a target pathway, but the inherent characteristics of a particular enzyme within the pathway can still limit the productivity. Thus, judicious protein design is critical for metabolic and pathway engineering. This review will describe various strategies and examples of applying protein design to pathway engineering to optimize the flux through the pathway. The proteins can be engineered for altered substrate specificity/selectivity, increased catalytic activity, reduced mass transfer limitations through specific protein localization, and reduced substrate/product inhibition. Protein engineering can also be expanded to design biosensors to enable high through-put screening and to customize cell signaling networks. These strategies have successfully engineered pathways for significantly increased productivity of the desired product or in the production of novel compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

Protein Folding and Aggregation into Amyloid: The Interference by Natural Phenolic Compounds

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Massimo Stefani

2013-06-01

Full Text Available Amyloid aggregation is a hallmark of several degenerative diseases affecting the brain or peripheral tissues, whose intermediates (oligomers, protofibrils and final mature fibrils display different toxicity. Consequently, compounds counteracting amyloid aggregation have been investigated for their ability (i to stabilize toxic amyloid precursors; (ii to prevent the growth of toxic oligomers or speed that of fibrils; (iii to inhibit fibril growth and deposition; (iv to disassemble preformed fibrils; and (v to favor amyloid clearance. Natural phenols, a wide panel of plant molecules, are one of the most actively investigated categories of potential amyloid inhibitors. They are considered responsible for the beneficial effects of several traditional diets being present in green tea, extra virgin olive oil, red wine, spices, berries and aromatic herbs. Accordingly, it has been proposed that some natural phenols could be exploited to prevent and to treat amyloid diseases, and recent studies have provided significant information on their ability to inhibit peptide/protein aggregation in various ways and to stimulate cell defenses, leading to identify shared or specific mechanisms. In the first part of this review, we will overview the significance and mechanisms of amyloid aggregation and aggregate toxicity; then, we will summarize the recent achievements on protection against amyloid diseases by many natural phenols.

The research methods and model of protein turnover in animal

International Nuclear Information System (INIS)

Wu Xilin; Yang Feng

2002-01-01

The author discussed the concept and research methods of protein turnover in animal body. The existing problems and the research results of animal protein turnover in recent years were presented. Meanwhile, the measures to improve the models of animal protein turnover were analyzed

A simple quantitative model of macromolecular crowding effects on protein folding: Application to the murine prion protein(121-231)

Science.gov (United States)

Bergasa-Caceres, Fernando; Rabitz, Herschel A.

2013-06-01

A model of protein folding kinetics is applied to study the effects of macromolecular crowding on protein folding rate and stability. Macromolecular crowding is found to promote a decrease of the entropic cost of folding of proteins that produces an increase of both the stability and the folding rate. The acceleration of the folding rate due to macromolecular crowding is shown to be a topology-dependent effect. The model is applied to the folding dynamics of the murine prion protein (121-231). The differential effect of macromolecular crowding as a function of protein topology suffices to make non-native configurations relatively more accessible.

Effects of Panax japonicus hypolipidemic compound on non-alcoholic fatty liver disease in mice and its mechanism

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Li DUAN

2017-10-01

Full Text Available Objective To investigate the effects of Panax japonicas hypolipidemic compound (ZDS on the lipid metabolism and its possible mechanism in non-alcoholic fatty liver disease (NAFLD mice induced by high sugar and fat diet. Methods The extracts of Panaax japonica rhizoma, Salviae Miltiorrhiz radix Et rhizoma and Crataegi Fructus were prepared, and ZDS compound was formulated according to their antioxidant activities. Forty SPF male Kunming mice were randomly divided into four groups (10 each: normal control group, model group, high-dose ZDS-treated group, and low-dose ZDS-treated group. In addition to the mice in normal control group were given conventional diet, the mice in other three groups were fed high-sugar high-fat diet. High-dose and low-dose ZDS-treated group were given 90mg/kg or 30mg/kg ZDS. After the treatment of five weeks, the histomorphology and lipid deposition of the liver were observed to confirm the establishment of mouse NAFLD model and the improvement of ZDS compound on lipid deposition. The relative expression of miR-34a, SIRT1, and lipid metabolism related genes (FASN, ACC1 was detected by RT-qPCR and RT-PCR. SIRT1 protein expression was detected by Western blotting. Results Compared with the normal group, the morphological results showed hepatic lipid accumulation in the model group was more serious, the levels of triglyceride (TG and miR- 34a in the liver tissue increased significantly (P<0.05, the expression levels of SIRT1 decreased, and the gene of lipid metabolism such as FASN, ACC1 significantly increased (P<0.05. However, compared with the model group, ZDS compound improve hepatic lipid accumulation, liver TG content significantly decreasd (P<0.05, liver tissue miR-34a, FASN and ACC1 expressions decreased, while SIRT1 expression increased (P<0.05. The protein expression of SIRT1 was consistent with its mRNA expression. Conclusion　ZDS compound can effectively improve liver cell steatosis through the miR-34a/SIRT1

Radiation chemistry of salicylic and methyl substituted salicylic acids: Models for the radiation chemistry of pharmaceutical compounds

International Nuclear Information System (INIS)

Ayatollahi, Shakiba; Kalnina, Daina; Song, Weihua; Turks, Maris; Cooper, William J.

2013-01-01

Salicylic acid and its derivatives are components of many medications and moieties found in numerous pharmaceutical compounds. They have been used as models for various pharmaceutical compounds in pharmacological studies, for the treatment of pharmaceuticals and personal care products (PPCPs), and, reactions with natural organic matter (NOM). In this study, the radiation chemistry of benzoic acid, salicylic acid and four methyl substituted salicylic acids (MSA) is reported. The absolute bimolecular reaction rate constants for hydroxyl radical reaction with benzoic and salicylic acids as well as 3-methyl-, 4-methyl-, 5-methyl-, and 6-methyl-salicylic acid were determined (5.86±0.54)×10 9 , (1.07±0.07)×10 10 , (7.48±0.17)×10 9 , (7.31±0.29)×10 9 , (5.47±0.25)×10 9 , (6.94±0.10)×10 9 (M −1 s −1 ), respectively. The hydrated electron reaction rate constants were measured (3.02±0.10)×10 9 , (8.98±0.27)×10 9 , (5.39±0.21)×10 9 , (4.33±0.17)×10 9 , (4.72±0.15)×10 9 , (1.42±0.02)×10 9 (M −1 s −1 ), respectively. The transient absorption spectra for the six model compounds were examined and their role as model compounds for the radiation chemistry of pharmaceuticals investigated. - Highlights: • Free radical chemistry of salicylic and 4 methyl salicylic acids is investigated. • The transient absorptions spectra for model compounds are measured. • Absolute bimolecular reaction rate constants for hydroxyl radical are determined. • Solvated electron reaction rate constants are calculated. • The use of salicylic acids as models for pharmaceuticals is explored

High-Throughput Screening to Identify Compounds That Increase Fragile X Mental Retardation Protein Expression in Neural Stem Cells Differentiated From Fragile X Syndrome Patient-Derived Induced Pluripotent Stem Cells.

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Kumari, Daman; Swaroop, Manju; Southall, Noel; Huang, Wenwei; Zheng, Wei; Usdin, Karen

2015-07-01

: Fragile X syndrome (FXS), the most common form of inherited cognitive disability, is caused by a deficiency of the fragile X mental retardation protein (FMRP). In most patients, the absence of FMRP is due to an aberrant transcriptional silencing of the fragile X mental retardation 1 (FMR1) gene. FXS has no cure, and the available treatments only provide symptomatic relief. Given that FMR1 gene silencing in FXS patient cells can be partially reversed by treatment with compounds that target repressive epigenetic marks, restoring FMRP expression could be one approach for the treatment of FXS. We describe a homogeneous and highly sensitive time-resolved fluorescence resonance energy transfer assay for FMRP detection in a 1,536-well plate format. Using neural stem cells differentiated from an FXS patient-derived induced pluripotent stem cell (iPSC) line that does not express any FMRP, we screened a collection of approximately 5,000 known tool compounds and approved drugs using this FMRP assay and identified 6 compounds that modestly increase FMR1 gene expression in FXS patient cells. Although none of these compounds resulted in clinically relevant levels of FMR1 mRNA, our data provide proof of principle that this assay combined with FXS patient-derived neural stem cells can be used in a high-throughput format to identify better lead compounds for FXS drug development. In this study, a specific and sensitive fluorescence resonance energy transfer-based assay for fragile X mental retardation protein detection was developed and optimized for high-throughput screening (HTS) of compound libraries using fragile X syndrome (FXS) patient-derived neural stem cells. The data suggest that this HTS format will be useful for the identification of better lead compounds for developing new therapeutics for FXS. This assay can also be adapted for FMRP detection in clinical and research settings. ©AlphaMed Press.

Possibilities of microscopic detection of isolated porcine proteins in model meat products

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Michaela Petrášová

2016-05-01

Full Text Available In recent years, various protein additives intended for manufacture of meat products have increasing importance in the food industry. These ingredients include both, plant-origin as well as animal-origin proteins. Among animal proteins, blood plasma, milk protein or collagen are used most commonly. Collagen is obtained from pork, beef, and poultry or fish skin. Collagen does not contain all the essential amino acids, thus it is not a full protein in terms of essential amino acids supply for one's organism. However, it is rather rich in amino acids of glycine, hydroxyproline and proline which are almost absent in other proteins and their synthesis is very energy intensive. Collagen, which is added to the soft and small meat products in the form of isolated porcine protein, significantly affects the organoleptic properties of these products. This work focused on detection of isolated porcine protein in model meat products where detection of isolated porcine protein was verified by histological staining and light microscopy. Seven model meat products from poultry meat and 7 model meat products from beef and pork in the ratio of 1:1, which contained 2.5% concentration of various commercially produced isolated porcine proteins, were examined. These model meat products were histologically processed by means of cryosections and stained with hematoxylin-eosin staining, toluidine blue staining and Calleja. For the validation phase, Calleja was utilized. To determine the sensitivity and specificity, five model meat products containing the addition of isolated porcine protein and five model meat products free of it were used. The sensitivity was determined for isolated porcine protein at 1.00 and specificity was determined at 1.00. The detection limit of the method was at the level of 0.001% addition. Repeatability of the method was carried out using products with addition as well as without addition of isolated porcine protein and detection was repeated

Mechanism-based strategies for protein thermostabilization.

Science.gov (United States)

Mozhaev, V V

1993-03-01

Strategies for stabilizing enzymes can be derived from a two-step model of irreversible inactivation that involves preliminary reversible unfolding, followed by an irreversible step. Reversible unfolding is best prevented by covalent immobilization, whereas methods such as covalent modification of amino acid residues or 'medium engineering' (by the addition of low-molecular-weight compounds) are effective against irreversible 'incorrect' refolding. Genetic modification of the protein sequence is the most effective approach for preventing chemical deterioration.

A linear programming model for protein inference problem in shotgun proteomics.

Science.gov (United States)

Huang, Ting; He, Zengyou

2012-11-15

Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/. zyhe@dlut.edu.cn. Supplementary data are available at Bioinformatics Online.

Development of a Model Protein Interaction Pair as a Benchmarking Tool for the Quantitative Analysis of 2-Site Protein-Protein Interactions.

Science.gov (United States)

Yamniuk, Aaron P; Newitt, John A; Doyle, Michael L; Arisaka, Fumio; Giannetti, Anthony M; Hensley, Preston; Myszka, David G; Schwarz, Fred P; Thomson, James A; Eisenstein, Edward

2015-12-01

A significant challenge in the molecular interaction field is to accurately determine the stoichiometry and stepwise binding affinity constants for macromolecules having >1 binding site. The mission of the Molecular Interactions Research Group (MIRG) of the Association of Biomolecular Resource Facilities (ABRF) is to show how biophysical technologies are used to quantitatively characterize molecular interactions, and to educate the ABRF members and scientific community on the utility and limitations of core technologies [such as biosensor, microcalorimetry, or analytic ultracentrifugation (AUC)]. In the present work, the MIRG has developed a robust model protein interaction pair consisting of a bivalent variant of the Bacillus amyloliquefaciens extracellular RNase barnase and a variant of its natural monovalent intracellular inhibitor protein barstar. It is demonstrated that this system can serve as a benchmarking tool for the quantitative analysis of 2-site protein-protein interactions. The protein interaction pair enables determination of precise binding constants for the barstar protein binding to 2 distinct sites on the bivalent barnase binding partner (termed binase), where the 2 binding sites were engineered to possess affinities that differed by 2 orders of magnitude. Multiple MIRG laboratories characterized the interaction using isothermal titration calorimetry (ITC), AUC, and surface plasmon resonance (SPR) methods to evaluate the feasibility of the system as a benchmarking model. Although general agreement was seen for the binding constants measured using solution-based ITC and AUC approaches, weaker affinity was seen for surface-based method SPR, with protein immobilization likely affecting affinity. An analysis of the results from multiple MIRG laboratories suggests that the bivalent barnase-barstar system is a suitable model for benchmarking new approaches for the quantitative characterization of complex biomolecular interactions.

Application of Artificial Neural Network and Support Vector Machines in Predicting Metabolizable Energy in Compound Feeds for Pigs.

Science.gov (United States)

Ahmadi, Hamed; Rodehutscord, Markus

2017-01-01

In the nutrition literature, there are several reports on the use of artificial neural network (ANN) and multiple linear regression (MLR) approaches for predicting feed composition and nutritive value, while the use of support vector machines (SVM) method as a new alternative approach to MLR and ANN models is still not fully investigated. The MLR, ANN, and SVM models were developed to predict metabolizable energy (ME) content of compound feeds for pigs based on the German energy evaluation system from analyzed contents of crude protein (CP), ether extract (EE), crude fiber (CF), and starch. A total of 290 datasets from standardized digestibility studies with compound feeds was provided from several institutions and published papers, and ME was calculated thereon. Accuracy and precision of developed models were evaluated, given their produced prediction values. The results revealed that the developed ANN [ R 2  = 0.95; root mean square error (RMSE) = 0.19 MJ/kg of dry matter] and SVM ( R 2  = 0.95; RMSE = 0.21 MJ/kg of dry matter) models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR ( R 2  = 0.89; RMSE = 0.27 MJ/kg of dry matter). The developed ANN and SVM models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR; however, there were not obvious differences between performance of ANN and SVM models. Thus, SVM model may also be considered as a promising tool for modeling the relationship between chemical composition and ME of compound feeds for pigs. To provide the readers and nutritionist with the easy and rapid tool, an Excel ® calculator, namely, SVM_ME_pig, was created to predict the metabolizable energy values in compound feeds for pigs using developed support vector machine model.

Identify High-Quality Protein Structural Models by Enhanced K-Means.

Science.gov (United States)

Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

Potential Compounds for Oral Cancer Treatment: Resveratrol, Nimbolide, Lovastatin, Bortezomib, Vorinostat, Berberine, Pterostilbene, Deguelin, Andrographolide, and Colchicine.

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Saurabh Bundela

Full Text Available Oral cancer is one of the main causes of cancer-related deaths in South-Asian countries. There are very limited treatment options available for oral cancer. Research endeavors focused on discovery and development of novel therapies for oral cancer, is necessary to control the ever rising oral cancer related mortalities. We mined the large pool of compounds from the publicly available compound databases, to identify potential therapeutic compounds for oral cancer. Over 84 million compounds were screened for the possible anti-cancer activity by custom build SVM classifier. The molecular targets of the predicted anti-cancer compounds were mined from reliable sources like experimental bioassays studies associated with the compound, and from protein-compound interaction databases. Therapeutic compounds from DrugBank, and a list of natural anti-cancer compounds derived from literature mining of published studies, were used for building partial least squares regression model. The regression model thus built, was used for the estimation of oral cancer specific weights based on the molecular targets. These weights were used to compute scores for screening the predicted anti-cancer compounds for their potential to treat oral cancer. The list of potential compounds was annotated with corresponding physicochemical properties, cancer specific bioactivity evidences, and literature evidences. In all, 288 compounds with the potential to treat oral cancer were identified in the current study. The majority of the compounds in this list are natural products, which are well-tolerated and have minimal side-effects compared to the synthetic counterparts. Some of the potential therapeutic compounds identified in the current study are resveratrol, nimbolide, lovastatin, bortezomib, vorinostat, berberine, pterostilbene, deguelin, andrographolide, and colchicine.

Potential Compounds for Oral Cancer Treatment: Resveratrol, Nimbolide, Lovastatin, Bortezomib, Vorinostat, Berberine, Pterostilbene, Deguelin, Andrographolide, and Colchicine

Science.gov (United States)

Bundela, Saurabh; Sharma, Anjana; Bisen, Prakash S.

2015-01-01

Oral cancer is one of the main causes of cancer-related deaths in South-Asian countries. There are very limited treatment options available for oral cancer. Research endeavors focused on discovery and development of novel therapies for oral cancer, is necessary to control the ever rising oral cancer related mortalities. We mined the large pool of compounds from the publicly available compound databases, to identify potential therapeutic compounds for oral cancer. Over 84 million compounds were screened for the possible anti-cancer activity by custom build SVM classifier. The molecular targets of the predicted anti-cancer compounds were mined from reliable sources like experimental bioassays studies associated with the compound, and from protein-compound interaction databases. Therapeutic compounds from DrugBank, and a list of natural anti-cancer compounds derived from literature mining of published studies, were used for building partial least squares regression model. The regression model thus built, was used for the estimation of oral cancer specific weights based on the molecular targets. These weights were used to compute scores for screening the predicted anti-cancer compounds for their potential to treat oral cancer. The list of potential compounds was annotated with corresponding physicochemical properties, cancer specific bioactivity evidences, and literature evidences. In all, 288 compounds with the potential to treat oral cancer were identified in the current study. The majority of the compounds in this list are natural products, which are well-tolerated and have minimal side-effects compared to the synthetic counterparts. Some of the potential therapeutic compounds identified in the current study are resveratrol, nimbolide, lovastatin, bortezomib, vorinostat, berberine, pterostilbene, deguelin, andrographolide, and colchicine. PMID:26536350

Parity violating NN forcES in the quark compound bag model

International Nuclear Information System (INIS)

Simonov, Yu.A.

1982-01-01

Parity violation (PV) in the interaction is considered as due to the Weinberg-Salam quark-quark interaction inside the six-quark bag. The initial and final strong interaction is described within the same quark compound bag (QCB) model, where the NN coupling to the six quark QCB is defined from the NN experimental data. The resulting PV amplitude contains no free parameters and allows therefore an unambiguous test of the QCB model. An estimate of the 1 S 0 → 3 P 0 contribution to the proton-proton asymmetry is in a rough agreement with experimental data [ru

Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.

Science.gov (United States)

Murrell, Daniel S; Cortes-Ciriano, Isidro; van Westen, Gerard J P; Stott, Ian P; Bender, Andreas; Malliavin, Thérèse E; Glen, Robert C

2015-01-01

In silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process. camb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both advanced and beginner R users. camb's capabilities include the standardisation of chemical structure representation, computation of 905 one-dimensional and 14 fingerprint type descriptors for small molecules, 8 types of amino acid descriptors, 13 whole protein sequence descriptors, filtering methods for feature selection, generation of predictive models (using an interface to the R package caret), as well as techniques to create model ensembles using techniques from the R package caretEnsemble). Results can be visualised through high-quality, customisable plots (R package ggplot2). Overall, camb constitutes an open-source framework to perform the following steps: (1) compound standardisation, (2) molecular and protein descriptor calculation, (3) descriptor pre-processing and model training, visualisation and validation, and (4) bioactivity/property prediction for new molecules. camb aims to speed model generation, in order to provide reproducibility and tests of robustness. QSPR and proteochemometric case studies are included which demonstrate camb's application.Graphical abstractFrom compounds and data to models: a complete model building workflow in one package.

Interactions between wine phenolic compounds and human saliva in astringency perception.

Science.gov (United States)

García-Estévez, Ignacio; Ramos-Pineda, Alba María; Escribano-Bailón, María Teresa

2018-03-01

Astringency is a complex perceptual phenomenon involving several sensations that are perceived simultaneously. The mechanism leading to these sensations has been thoroughly and controversially discussed in the literature and it is still not well understood since there are many contributing factors. Although we are still far from elucidating the mechanisms whereby astringency develops, the interaction between phenolic compounds and proteins (from saliva, oral mucosa or cells) seems to be most important. This review summarizes the recent trends in the protein-phenol interaction, focusing on the effect of the structure of the phenolic compound on the interaction with salivary proteins and on methodologies based on these interactions to determine astringency.

Model compounds of humic acid and oxovanadium cations. Potentiometric titration and EPR spectroscopy studies

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Mercê Ana Lucia Ramalho

1999-01-01

Full Text Available The stability constants and the isotropic EPR parameters Ao (hyperfine splitting constant and g o (g value were obtained by potentiometric titrations and EPR spectroscopy, respectively, of 85%v/v aqueous solutions of model compounds of humic acids - salicylic acid (SALA - and both nitrohumic acids, a laboratory artifact - nitrosalicylic acids, 3-nitrosalicylic acid (3-NSA, 5-nitrosalicylic acid (5-NSA and 3,5-dinitrosalicylic acid (3,5-DNSA and oxovanadium cations. It was possible to record EPR spectra of those model compounds and the ion VO2+ (V(IV, and the stability constants were obtained from a solution of VO3+ (V(V, the values for the logarithms of the stability constants ranging from 12.77 ± 0.04 to 7.06 ± 0.05 for the species ML, and from 9.90 ±0.04 to 4.06 ± 0.05 for the species ML2 according to the decrease in the acidity of the carboxylic and the hydroxyl groups in the aromatic ring of the model compounds studied as the -NO2 substituents were added. Species distribution diagrams were also obtained for the equilibria studied. The EPR parameters showed that as the logarithm of the overall stability constants increase, g o values also increase, while Ao values show a tendency to decrease.

Modelling of the Kinetics of Sulfure Compounds in Desulfurisation Processes Based on Industry Data of Plant

OpenAIRE

Krivtsova, Nadezhda Igorevna; Tataurshikov, A.; Kotkova, Elena

2016-01-01

Modelling of sulfur compounds kinetics was performed, including kinetics of benzothiophene and dibenzothiophene homologues. Modelling is based on experimental data obtained from monitoring of industrial hydrotreating set. Obtained results include kinetic parameters of reactions.

NASCENT: an automatic protein interaction network generation tool for non-model organisms.

Science.gov (United States)

Banky, Daniel; Ordog, Rafael; Grolmusz, Vince

2009-04-24

Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.

Hydrodeoxygenation of O-containing polycyclic model compounds using a novel organometallic catalyst-precursor

Energy Technology Data Exchange (ETDEWEB)

Kirby, S.R.; Song, C.S.; Schobert, H.H. [Pennsylvania State University, University Park, PA (United States). Dept. of Materials Science and Engineering

1996-09-05

Compounds containing oxygen functional groups, especially phenols, are undesirable components of coal-derived liquids. Removal of these compounds from the products of coal liquefaction is required. A beneficial alternative would be the removal of these compounds, or the prevention of their formation, during the liquefaction reaction itself, rather than as a separate processing step. A novel organometallic catalyst precursor containing Co and Mo has been studied as a potential hydrogenation catalyst for coal liquefaction. To ascertain the hydrodeoxygenation activity of this catalyst under liquefaction conditions, model compounds were investigated. Anthrone, 2,6-di-r-btuyl-4-methyl-phenol, dinaphthyl ether and xanthene were reacted in the presence of the Co-Mo catalyst precursor and a precursor containing only Mo over a range of temperatures, providing a comparison of conversions to deoxygenated products. These conversions give an indication of the hydrodeoxygenating abilities of organometallic catalyst precursors within a coal liquefaction system. For example, at 400{degree}C dinaphthyl ether was converted 100% (4.5% O-containing products) in the presence of the Co-Mo organometallic precursor, compared to 76.5% conversion (7.4% O-products) in the presence of the Mo catalyst.

DeepQA: Improving the estimation of single protein model quality with deep belief networks

OpenAIRE

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-01-01

Background Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. Results We introduce a novel single-model quality assessment method DeepQA based on deep belie...

A semi-nonparametric mixture model for selecting functionally consistent proteins.

Science.gov (United States)

Yu, Lianbo; Doerge, Rw

2010-09-28

High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

Fast Proton Titration Scheme for Multiscale Modeling of Protein Solutions.

Science.gov (United States)

Teixeira, Andre Azevedo Reis; Lund, Mikael; da Silva, Fernando Luís Barroso

2010-10-12

Proton exchange between titratable amino acid residues and the surrounding solution gives rise to exciting electric processes in proteins. We present a proton titration scheme for studying acid-base equilibria in Metropolis Monte Carlo simulations where salt is treated at the Debye-Hückel level. The method, rooted in the Kirkwood model of impenetrable spheres, is applied on the three milk proteins α-lactalbumin, β-lactoglobulin, and lactoferrin, for which we investigate the net-charge, molecular dipole moment, and charge capacitance. Over a wide range of pH and salt conditions, excellent agreement is found with more elaborate simulations where salt is explicitly included. The implicit salt scheme is orders of magnitude faster than the explicit analog and allows for transparent interpretation of physical mechanisms. It is shown how the method can be expanded to multiscale modeling of aqueous salt solutions of many biomolecules with nonstatic charge distributions. Important examples are protein-protein aggregation, protein-polyelectrolyte complexation, and protein-membrane association.

A single amino acid substitution in the core protein of West Nile virus increases resistance to acidotropic compounds.

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Miguel A Martín-Acebes

Full Text Available West Nile virus (WNV is a worldwide distributed mosquito-borne flavivirus that naturally cycles between birds and mosquitoes, although it can infect multiple vertebrate hosts including horses and humans. This virus is responsible for recurrent epidemics of febrile illness and encephalitis, and has recently become a global concern. WNV requires to transit through intracellular acidic compartments at two different steps to complete its infectious cycle. These include fusion between the viral envelope and the membrane of endosomes during viral entry, and virus maturation in the trans-Golgi network. In this study, we followed a genetic approach to study the connections between viral components and acidic pH. A WNV mutant with increased resistance to the acidotropic compound NH4Cl, which blocks organelle acidification and inhibits WNV infection, was selected. Nucleotide sequencing revealed that this mutant displayed a single amino acid substitution (Lys 3 to Glu on the highly basic internal capsid or core (C protein. The functional role of this replacement was confirmed by its introduction into a WNV infectious clone. This single amino acid substitution also increased resistance to other acidification inhibitor (concanamycin A and induced a reduction of the neurovirulence in mice. Interestingly, a naturally occurring accompanying mutation found on prM protein abolished the resistant phenotype, supporting the idea of a genetic crosstalk between the internal C protein and the external glycoproteins of the virion. The findings here reported unveil a non-previously assessed connection between the C viral protein and the acidic pH necessary for entry and proper exit of flaviviruses.

A single amino acid substitution in the core protein of West Nile virus increases resistance to acidotropic compounds.

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Martín-Acebes, Miguel A; Blázquez, Ana-Belén; de Oya, Nereida Jiménez; Escribano-Romero, Estela; Shi, Pei-Yong; Saiz, Juan-Carlos

2013-01-01

West Nile virus (WNV) is a worldwide distributed mosquito-borne flavivirus that naturally cycles between birds and mosquitoes, although it can infect multiple vertebrate hosts including horses and humans. This virus is responsible for recurrent epidemics of febrile illness and encephalitis, and has recently become a global concern. WNV requires to transit through intracellular acidic compartments at two different steps to complete its infectious cycle. These include fusion between the viral envelope and the membrane of endosomes during viral entry, and virus maturation in the trans-Golgi network. In this study, we followed a genetic approach to study the connections between viral components and acidic pH. A WNV mutant with increased resistance to the acidotropic compound NH4Cl, which blocks organelle acidification and inhibits WNV infection, was selected. Nucleotide sequencing revealed that this mutant displayed a single amino acid substitution (Lys 3 to Glu) on the highly basic internal capsid or core (C) protein. The functional role of this replacement was confirmed by its introduction into a WNV infectious clone. This single amino acid substitution also increased resistance to other acidification inhibitor (concanamycin A) and induced a reduction of the neurovirulence in mice. Interestingly, a naturally occurring accompanying mutation found on prM protein abolished the resistant phenotype, supporting the idea of a genetic crosstalk between the internal C protein and the external glycoproteins of the virion. The findings here reported unveil a non-previously assessed connection between the C viral protein and the acidic pH necessary for entry and proper exit of flaviviruses.

Identification of Compounds That Inhibit IGF-I Signaling in Hyperglycemia

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Laura A. Maile

2009-01-01

Full Text Available Increased responsiveness of vascular cells to the growth factor IGF-I has been implicated in complications associated with diabetes. Here we describe the development of an assay and screening of a library of compounds for their ability to accelerate cleavage of the transmembrane protein integrin-associated protein (IAP thereby disrupting the association between IAP and SHPS-1 which we have shown as critical for the enhanced response of vascular cells to IGF-I. The cell-based ELISA utilizes an antibody that specifically detects cleaved, but not intact, IAP. Of the 1040 compounds tested, 14 were considered active by virtue of their ability to stimulate an increase in antibody-binding indicative of IAP cleavage. In experiments with smooth muscle and retinal endothelial cell cultures in hyperglycemic conditions, each active compound was shown to accelerate the cleavage of IAP, and this was associated with a decrease in IAP association with SHPS-1 as determined by coimmunoprecipitation of the proteins from cell lysates. As a consequence of the acceleration in IAP cleavage, the compounds were shown to inhibit IGF-I-stimulated phosphorylation of key signaling molecules including Shc and ERK1/2, and this in turn was associated with a decrease in IGF-I-stimulated cell proliferation. Identification of these compounds that utilize this mechanism has the potential to yield novel therapeutic approaches for the prevention and treatment of vascular complications associated with diabetes.

Genome-scale modeling of the protein secretory machinery in yeast

DEFF Research Database (Denmark)

Feizi, Amir; Österlund, Tobias; Petranovic, Dina

2013-01-01

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking....... Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm...

Capture compound mass spectrometry sheds light on the molecular mechanisms of liver toxicity of two Parkinson drugs.

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Fischer, Jenny J; Michaelis, Simon; Schrey, Anna K; Graebner, Olivia Graebner nee; Glinski, Mirko; Dreger, Mathias; Kroll, Friedrich; Koester, Hubert

2010-01-01

Capture compound mass spectrometry (CCMS) is a novel technology that helps understand the molecular mechanism of the mode of action of small molecules. The Capture Compounds are trifunctional probes: A selectivity function (the drug) interacts with the proteins in a biological sample, a reactivity function (phenylazide) irreversibly forms a covalent bond, and a sorting function (biotin) allows the captured protein(s) to be isolated for mass spectrometric analysis. Tolcapone and entacapone are potent inhibitors of catechol-O-methyltransferase (COMT) for the treatment of Parkinson's disease. We aimed to understand the molecular basis of the difference of both drugs with respect to side effects. Using Capture Compounds with these drugs as selectivity functions, we were able to unambiguously and reproducibly isolate and identify their known target COMT. Tolcapone Capture Compounds captured five times more proteins than entacapone Capture Compounds. Moreover, tolcapone Capture Compounds isolated mitochondrial and peroxisomal proteins. The major tolcapone-protein interactions occurred with components of the respiratory chain and of the fatty acid beta-oxidation. Previously reported symptoms in tolcapone-treated rats suggested that tolcapone might act as decoupling reagent of the respiratory chain (Haasio et al., 2002b). Our results demonstrate that CCMS is an effective tool for the identification of a drug's potential off targets. It fills a gap in currently used in vitro screens for drug profiling that do not contain all the toxicologically relevant proteins. Thereby, CCMS has the potential to fill a technological need in drug safety assessment and helps reengineer or to reject drugs at an early preclinical stage.

[Protective effects of compound shenhua tablet on diabetic nephropathy rats].

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Geng, Wen-Jia; Wei, Ri-Bao; Mao, Wei

2012-03-01

To observe the renal protection effects of Compound Shenhua Tablet (CST) on diabetic nephropathy (DN) rats. DN rats were given a normal diet for 9 months after they were induced by intraperitoneal injection of STZ at the dose of 65 mg/kg after uninephrectomized. They were randomly divided into 4 groups, i. e., the normal control group, the model control group, the CST group, and the Irbesartan group. The intervention was given by gastrogavage for 6 weeks. The general state, 24 h urine protein, urine micro-albumin (mAlb), serum creatinine (SCr), blood urea nitrogen (BUN), glucose (GLU), triglyceride (TG), total cholesterol (TC), total protein (TP), and albumin (ALB) levels were observed before and after intervention. Renal pathological changes were observed by PAS staining and transmission electron microscope. After 6 weeks of drug intervention, when compared with the model control group, the general state was improved in the CST group and the Irbesartan group. The levels of 24 h urine protein, urine mAlb, SCr, BUN, GLU, TG, and TC were obviously lower in the CST group and the Irbesartan group than in the model group as well as in the same group before treatment (P0.05). The renal pathological changes and the renal ultrastructure were improved to some degree in the two groups when compared with those in the model control group. CST could attenuate the renal damage of diabetes and delay renal deterioration process. Its effectiveness was equivalent to that of Irbesartan.

High-intensity ultrasound production of Maillard reaction flavor compounds in a cysteine-xylose model system.

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Ong, Olivia X H; Seow, Yi-Xin; Ong, Peter K C; Zhou, Weibiao

2015-09-01

Application of high intensity ultrasound has shown potential in the production of Maillard reaction odor-active flavor compounds in model systems. The impact of initial pH, sonication duration, and ultrasound intensity on the production of Maillard reaction products (MRPs) by ultrasound processing in a cysteine-xylose model system were evaluated using Response Surface Methodology (RSM) with a modified mathematical model. Generation of selected MRPs, 2-methylthiophene and tetramethyl pyrazine, was optimal at an initial pH of 6.00, accompanied with 78.1 min of processing at an ultrasound intensity of 19.8 W cm(-2). However, identification of volatiles using gas chromatography-mass spectrometry (GC/MS) revealed that ultrasound-assisted Maillard reactions generated fewer sulfur-containing volatile flavor compounds as compared to conventional heat treatment of the model system. Likely reasons for this difference in flavor profile include the expulsion of H2S due to ultrasonic degassing and inefficient transmission of ultrasonic energy. Copyright © 2015 Elsevier B.V. All rights reserved.

[Assessment of the effect of selected mixture of food additives on the protein metabolism--model studies].

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Friedrich, Mariola; Kuchlewska, Magdalena

2012-01-01

Contemporarily, food production without food additives is very rare. Increasingly often, however, scientific works report on adverse effects of specified, single food additives on the body. Data is, in turn, lacking on the synergistic effect of a mixture of different food additives on body functions and its main metabolic pathways. The objective of this study, an animal model, was to evaluate if and in what way the compound of chosen and most frequently used and consumed food additives, along with the change of diet composition to processed, purified, influence the selected markers of protein metabolism. The animals were divided into four groups, which were fed with compound of feed pellets: group I and II with basic compound, group III and IV with modified compound in which part of the full grain was replaced by isocalorie wheat flour type 500 and saccharose. Animals from groups I and III received tap water, which was standing for some time, to drink. Animals from groups II and IV received solution of chosen additives to food and next they were given water to drink. The amount of given food additives was evaluated by taking into consideration their consumption by people recalculated to 1 kg of their body mass. The experiment spanned for 7 weeks. It was ascertained that the applied additives caused significant changes in total protein concentration and its fractions: albumin, alpha1-globulin, alpha2-globulin, beta-globulin and gamma-globulin in the blood serum of the animals under research, which can indicate and contribute to disclosure of creation of undesirable food reaction, especially when recommended levels of consumption of those additives are being exceeded. The organism response to the applied additives and accompanying it change of diet was essentially connected to sex of the animals. Undesirable character of changes taking place under the influence of applied additives, was observed both in animals fed with basic feed and modified feed with various

Modelling of the Kinetics of Sulfure Compounds in Desulfurisation Processes Based on Industry Data of Plant

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Krivtcova Nadezhda

2016-01-01

Full Text Available Modelling of sulfur compounds kinetics was performed, including kinetics of benzothiophene and dibenzothiophene homologues. Modelling is based on experimental data obtained from monitoring of industrial hydrotreating set. Obtained results include kinetic parameters of reactions.

Development of a canine model to enable the preclinical assessment of pH-dependent absorption of test compounds.

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Fancher, R Marcus; Zhang, Hongjian; Sleczka, Bogdan; Derbin, George; Rockar, Richard; Marathe, Punit

2011-07-01

A preclinical canine model capable of predicting a compound's potential for pH-dependent absorption in humans was developed. This involved the surgical insertion of a gastrostomy feeding tube into the stomach of a beagle dog. The tube was sutured in position to allow frequent withdrawal of gastric fluid for pH measurement. Therefore, it was possible to measure pH in the stomach and assess the effect of gastric pH-modifying agents on the absorption of various test compounds. Fasted gastric pH in the dog showed considerable inter- and intra-animal variability. Pretreatment of pentagastrin (6 µg/kg intramuscularly) 20 min prior to test compound administration was determined to be adequate for simulating fasting stomach pH in humans. Pretreatment with famotidine [40 mg orally] 1 h prior to test compound administration was determined to be adequate for simulating human gastric pH when acid-reducing agents are coadministered. Pentagastrin and famotidine pretreatments were used to test two discovery compounds and distinct differences in their potential for pH-dependent absorption were observed. The model described herein can be used preclinically to screen out compounds, differentiate compounds, and support the assessment of various formulation- and prodrug-based strategies to mitigate the pH effect. Copyright © 2011 Wiley-Liss, Inc. and the American Pharmacists Association

Metabolism of [14C]bicarbonate by Streptococcus lactis: identification and distribution of labelled compounds

International Nuclear Information System (INIS)

Hillier, A.J.; Jago, G.R.

1978-01-01

Streptococcus lactis C10, grown in tryptone-yeast extract-lactose broth containing [ 14 C] bicarbonate, incorporated radioactivity into the protein and nucleic acid fractions of the cell as well as into compounds which were excreted by the organism into the growth medium. Aspartic acid was the first compound to be labelled and was the only amino acid labelled in the cell protein. All 4 bases were labelled in the cell RNA. Aspartic, succunuc and lactic acids were the radioactive compounds excreted into the growth medium. (U.K.)

The Phyre2 web portal for protein modeling, prediction and analysis.

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Kelley, Lawrence A; Mezulis, Stefans; Yates, Christopher M; Wass, Mark N; Sternberg, Michael J E

2015-06-01

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.

Development of a general model for determination of thermal conductivity of liquid chemical compounds at atmospheric pressure

DEFF Research Database (Denmark)

Gharagheizi, Farhad; Ilani‐Kashkouli, Poorandokht; Sattari, Mehdi

2013-01-01

In this communication, a general model for representation/presentation of the liquid thermal conductivity of chemical compounds (mostly organic) at 1 atm pressure for temperatures below normal boiling point and at saturation pressure for temperatures above the normal boiling point is developed...... using the Gene Expression Programming algorithm. Approximately 19,000 liquid thermal conductivity data at different temperatures related to 1636 chemical compounds collected from the DIPPR 801 database are used to obtain the model as well as to assess its predictive capability. The parameters...

On the characterization and software implementation of general protein lattice models.

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Alessio Bechini

Full Text Available models of proteins have been widely used as a practical means to computationally investigate general properties of the system. In lattice models any sterically feasible conformation is represented as a self-avoiding walk on a lattice, and residue types are limited in number. So far, only two- or three-dimensional lattices have been used. The inspection of the neighborhood of alpha carbons in the core of real proteins reveals that also lattices with higher coordination numbers, possibly in higher dimensional spaces, can be adopted. In this paper, a new general parametric lattice model for simplified protein conformations is proposed and investigated. It is shown how the supporting software can be consistently designed to let algorithms that operate on protein structures be implemented in a lattice-agnostic way. The necessary theoretical foundations are developed and organically presented, pinpointing the role of the concept of main directions in lattice-agnostic model handling. Subsequently, the model features across dimensions and lattice types are explored in tests performed on benchmark protein sequences, using a Python implementation. Simulations give insights on the use of square and triangular lattices in a range of dimensions. The trend of potential minimum for sequences of different lengths, varying the lattice dimension, is uncovered. Moreover, an extensive quantitative characterization of the usage of the so-called "move types" is reported for the first time. The proposed general framework for the development of lattice models is simple yet complete, and an object-oriented architecture can be proficiently employed for the supporting software, by designing ad-hoc classes. The proposed framework represents a new general viewpoint that potentially subsumes a number of solutions previously studied. The adoption of the described model pushes to look at protein structure issues from a more general and essential perspective, making

Effect of Borax and cysteamine compound on finishing sheep growth performance, nitrogen retention, serum biochemical indices and body protein motabolism

International Nuclear Information System (INIS)

Chang Xinyao' Xie Hongbing; Wei Gangcai; Wang Hong

2009-01-01

Experiment was conducted to investigate the effects of borax, cysteamine and the mixture of two compounds on growth performance, serum biochemical indices, protein turn-over and nitrogen aggradation of sheep by using isotope ( 15 N-Gly) technique, nitrogen balance trial and serum testing. The results showed that both borax and cysteamine could increase the growth performance of sheep, especially the cysteamine and its mixture with borax, which increased average daily feed intake (P 3 ) and levothyroxine (T 4 ) of mixture were higher than that of control group (P<0.05), and the concentrations of growth hormone (GH) and insulin-like growth factors (IGF-1) were also significantly higher than those of control group (P<0.01). There was no significant difference of insulin (INS) between experiment groups and control group (P<0.05). Both mixture and borax contributed to increasing nitrogen retention, net nitrogen utilization, digestibility and biological value. Both borax and cysteamine accelerated protein degradation rate, apparent amino acid utilization rate and net amino acid utilization rate as well as biological value, body protein and oxidation rate, but the former was greater than the later. (authors)

Structure Based Virtual Screening Studies to Identify Novel Potential Compounds for GPR142 and Their Relative Dynamic Analysis for Study of Type 2 Diabetes

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Aman C. Kaushik

2018-02-01

Full Text Available GPR142 (G protein receptor 142 is a novel orphan GPCR (G protein coupled receptor belonging to “Class A” of GPCR family and expressed in β cells of pancreas. In this study, we reported the structure based virtual screening to identify the hit compounds which can be developed as leads for potential agonists. The results were validated through induced fit docking, pharmacophore modeling, and system biology approaches. Since, there is no solved crystal structure of GPR142, we attempted to predict the 3D structure followed by validation and then identification of active site using threading and ab initio methods. Also, structure based virtual screening was performed against a total of 1171519 compounds from different libraries and only top 20 best hit compounds were screened and analyzed. Moreover, the biochemical pathway of GPR142 complex with screened compound2 was also designed and compared with experimental data. Interestingly, compound2 showed an increase in insulin production via Gq mediated signaling pathway suggesting the possible role of novel GPR142 agonists in therapy against type 2 diabetes.

Structure Based Virtual Screening Studies to Identify Novel Potential Compounds for GPR142 and Their Relative Dynamic Analysis for Study of Type 2 Diabetes

Science.gov (United States)

Kaushik, Aman C.; Kumar, Sanjay; Wei, Dong Q.; Sahi, Shakti

2018-02-01

GPR142 (G protein receptor 142) is a novel orphan GPCR (G protein coupled receptor) belonging to ‘Class A’ of GPCR family and expressed in beta cells of pancreas. In this study, we reported the structure based virtual screening to identify the hit compounds which can be developed as leads for potential agonists. The results were validated through induced fit docking, pharmacophore modeling and system biology approaches. Since, there is no solved crystal structure of GPR142, we attempted to predict the 3D structure followed by validation and then identification of active site using threading and ab initio methods. Also, structure based virtual screening was performed against a total of 1171519 compounds from different libraries and only top 20 best hit compounds were screened and analyzed. Moreover, the biochemical pathway of GPR142 complex with screened compound2 was also designed and compared with experimental data. Interestingly, compound2 showed an increase in insulin production via Gq mediated signaling pathway suggesting the possible role of novel GPR142 agonists in therapy against type 2 diabetes.

Silencing the Odorant Binding Protein RferOBP1768 Reduces the Strong Preference of Palm Weevil for the Major Aggregation Pheromone Compound Ferrugineol

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Binu Antony

2018-03-01

Full Text Available In insects, perception of the environment—food, mates, and prey—is mainly guided by chemical signals. The dynamic process of signal perception involves transport to odorant receptors (ORs by soluble secretory proteins, odorant binding proteins (OBPs, which form the first stage in the process of olfactory recognition and are analogous to lipocalin family proteins in vertebrates. Although OBPs involved in the transport of pheromones to ORs have been functionally identified in insects, there is to date no report for Coleoptera. Furthermore, there is a lack of information on olfactory perception and the molecular mechanism by which OBPs participate in the transport of aggregation pheromones. We focus on the red palm weevil (RPW Rhynchophorus ferrugineus, the most devastating quarantine pest of palm trees worldwide. In this work, we constructed libraries of all OBPs and selected antenna-specific and highly expressed OBPs for silencing through RNA interference. Aggregation pheromone compounds, 4-methyl-5-nonanol (ferrugineol and 4-methyl-5-nonanone (ferruginone, and a kairomone, ethyl acetate, were then sequentially presented to individual RPWs. The results showed that antenna-specific RferOBP1768 aids in the capture and transport of ferrugineol to ORs. Silencing of RferOBP1768, which is responsible for pheromone binding, significantly disrupted pheromone communication. Study of odorant perception in palm weevil is important because the availability of literature regarding the nature and role of olfactory signaling in this insect may reveal likely candidates representative of animal olfaction and, more generally, of molecular recognition. Knowledge of OBPs recognizing the specific pheromone ferrugineol will allow for designing biosensors for the detection of this key compound in weevil monitoring in date palm fields.

Nanocarriers from GRAS Zein Proteins to Encapsulate Hydrophobic Actives.

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Weissmueller, Nikolas T; Lu, Hoang D; Hurley, Amanda; Prud'homme, Robert K

2016-11-14

One factor limiting the expansion of nanomedicines has been the high cost of the materials and processes required for their production. We present a continuous, scalable, low cost nanoencapsulation process, Flash Nanoprecipitation (FNP) that enables the production of nanocarriers (NCs) with a narrow size distribution using zein corn proteins. Zein is a low cost, GRAS protein (having the FDA status of "Generally Regarded as Safe") currently used in food applications, which acts as an effective encapsulant for hydrophobic compounds using FNP. The four-stream FNP configuration allows the encapsulation of very hydrophobic compounds in a way that is not possible with previous precipitation processes. We present the encapsulation of several model active compounds with as high as 45 wt % drug loading with respect to zein concentration into ∼100 nm nanocarriers. Three examples are presented: (1) the pro-drug antioxidant, vitamin E-acetate, (2) an anticholera quorum-sensing modulator CAI-1 ((S)-3-hydroxytridecan-4-one; CAI-1 that reduces Vibrio cholerae virulence by modulating cellular communication), and (3) hydrophobic fluorescent dyes with a range of hydrophobicities. The specific interaction between zein and the milk protein, sodium caseinate, provides stabilization of the NCs in PBS, LB medium, and in pH 2 solutions. The stability and size changes in the three media provide information on the mechanism of assembly of the zein/active/casein NC.

Tannin structural elucidation and quantitative ³¹P NMR analysis. 1. Model compounds.

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Melone, Federica; Saladino, Raffaele; Lange, Heiko; Crestini, Claudia

2013-10-02

Tannins and flavonoids are secondary metabolites of plants that display a wide array of biological activities. This peculiarity is related to the inhibition of extracellular enzymes that occurs through the complexation of peptides by tannins. Not only the nature of these interactions, but more fundamentally also the structure of these heterogeneous polyphenolic molecules are not completely clear. This first paper describes the development of a new analytical method for the structural characterization of tannins on the basis of tannin model compounds employing an in situ labeling of all labile H groups (aliphatic OH, phenolic OH, and carboxylic acids) with a phosphorus reagent. The ³¹P NMR analysis of ³¹P-labeled samples allowed the unprecedented quantitative and qualitative structural characterization of hydrolyzable tannins, proanthocyanidins, and catechin tannin model compounds, forming the foundations for the quantitative structural elucidation of a variety of actual tannin samples described in part 2 of this series.

Automated de novo phasing and model building of coiled-coil proteins.

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Rämisch, Sebastian; Lizatović, Robert; André, Ingemar

2015-03-01

Models generated by de novo structure prediction can be very useful starting points for molecular replacement for systems where suitable structural homologues cannot be readily identified. Protein-protein complexes and de novo-designed proteins are examples of systems that can be challenging to phase. In this study, the potential of de novo models of protein complexes for use as starting points for molecular replacement is investigated. The approach is demonstrated using homomeric coiled-coil proteins, which are excellent model systems for oligomeric systems. Despite the stereotypical fold of coiled coils, initial phase estimation can be difficult and many structures have to be solved with experimental phasing. A method was developed for automatic structure determination of homomeric coiled coils from X-ray diffraction data. In a benchmark set of 24 coiled coils, ranging from dimers to pentamers with resolutions down to 2.5 Å, 22 systems were automatically solved, 11 of which had previously been solved by experimental phasing. The generated models contained 71-103% of the residues present in the deposited structures, had the correct sequence and had free R values that deviated on average by 0.01 from those of the respective reference structures. The electron-density maps were of sufficient quality that only minor manual editing was necessary to produce final structures. The method, named CCsolve, combines methods for de novo structure prediction, initial phase estimation and automated model building into one pipeline. CCsolve is robust against errors in the initial models and can readily be modified to make use of alternative crystallographic software. The results demonstrate the feasibility of de novo phasing of protein-protein complexes, an approach that could also be employed for other small systems beyond coiled coils.

Validation of protein models by a neural network approach

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Fantucci Piercarlo

2008-01-01

Full Text Available Abstract Background The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure refinement, which has been recently identified as one of the bottlenecks limiting the quality and usefulness of protein structure prediction. Results In this contribution, we present a computational method (Artificial Intelligence Decoys Evaluator: AIDE which is able to consistently discriminate between correct and incorrect protein models. In particular, the method is based on neural networks that use as input 15 structural parameters, which include energy, solvent accessible surface, hydrophobic contacts and secondary structure content. The results obtained with AIDE on a set of decoy structures were evaluated using statistical indicators such as Pearson correlation coefficients, Znat, fraction enrichment, as well as ROC plots. It turned out that AIDE performances are comparable and often complementary to available state-of-the-art learning-based methods. Conclusion In light of the results obtained with AIDE, as well as its comparison with available learning-based methods, it can be concluded that AIDE can be successfully used to evaluate the quality of protein structures. The use of AIDE in combination with other evaluation tools is expected to further enhance protein refinement efforts.

Generic framework for mining cellular automata models on protein-folding simulations.

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Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

Development of Monopole Interaction Models for Ionic Compounds. Part I: Estimation of Aqueous Henry’s Law Constants for Ions and Gas Phase pKa Values for Acidic Compounds

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The SPARC (SPARC Performs Automated Reasoning in Chemistry) physicochemical mechanistic models for neutral compounds have been extended to estimate Henry’s Law Constant (HLC) for charged species by incorporating ionic electrostatic interaction models. Combinations of absolute aq...

Unravelling Protein-Protein Interaction Networks Linked to Aliphatic and Indole Glucosinolate Biosynthetic Pathways in Arabidopsis

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Sebastian J. Nintemann

2017-11-01

Full Text Available Within the cell, biosynthetic pathways are embedded in protein-protein interaction networks. In Arabidopsis, the biosynthetic pathways of aliphatic and indole glucosinolate defense compounds are well-characterized. However, little is known about the spatial orchestration of these enzymes and their interplay with the cellular environment. To address these aspects, we applied two complementary, untargeted approaches—split-ubiquitin yeast 2-hybrid and co-immunoprecipitation screens—to identify proteins interacting with CYP83A1 and CYP83B1, two homologous enzymes specific for aliphatic and indole glucosinolate biosynthesis, respectively. Our analyses reveal distinct functional networks with substantial interconnection among the identified interactors for both pathway-specific markers, and add to our knowledge about how biochemical pathways are connected to cellular processes. Specifically, a group of protein interactors involved in cell death and the hypersensitive response provides a potential link between the glucosinolate defense compounds and defense against biotrophic pathogens, mediated by protein-protein interactions.

Stochastic Interest Model Based on Compound Poisson Process and Applications in Actuarial Science

OpenAIRE

Li, Shilong; Yin, Chuancun; Zhao, Xia; Dai, Hongshuai

2017-01-01

Considering stochastic behavior of interest rates in financial market, we construct a new class of interest models based on compound Poisson process. Different from the references, this paper describes the randomness of interest rates by modeling the force of interest with Poisson random jumps directly. To solve the problem in calculation of accumulated interest force function, one important integral technique is employed. And a conception called the critical value is introduced to investigat...

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm.

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Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request.

DeepQA: improving the estimation of single protein model quality with deep belief networks.

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Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-12-05

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

Design of potentially active ligands for SH2 domains by molecular modeling methods

Directory of Open Access Journals (Sweden)

Hurmach V. V.

2014-07-01

Full Text Available Search for new chemical structures possessing specific biological activity is a complex problem that needs the use of the latest achievements of molecular modeling technologies. It is well known that SH2 domains play a major role in ontogenesis as intermediaries of specific protein-protein interactions. Aim. Developing an algorithm to investigate the properties of SH2 domain binding, search for new potential active compounds for the whole SH2 domains class. Methods. In this paper, we utilize a complex of computer modeling methods to create a generic set of potentially active compounds targeting universally at the whole class of SH2 domains. A cluster analysis of all available three-dimensional structures of SH2 domains was performed and general pharmacophore models were formulated. The models were used for virtual screening of collection of drug-like compounds provided by Enamine Ltd. Results. The design technique for library of potentially active compounds for SH2 domains class was proposed. Conclusions. The original algorithm of SH2 domains research with molecular docking method was developed. Using our algorithm, the active compounds for SH2 domains were found.

@TOME-2: a new pipeline for comparative modeling of protein-ligand complexes.

Science.gov (United States)

Pons, Jean-Luc; Labesse, Gilles

2009-07-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein-protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein-ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/

Data on coffee composition and mass spectrometry analysis of mixtures of coffee related carbohydrates, phenolic compounds and peptides

Directory of Open Access Journals (Sweden)

Ana S.P. Moreira

2017-08-01

Full Text Available The data presented here are related to the research paper entitled “Transglycosylation reactions, a main mechanism of phenolics incorporation in coffee melanoidins: inhibition by Maillard reaction” (Moreira et al., 2017 [1]. Methanolysis was applied in coffee fractions to quantify glycosidically-linked phenolics in melanoidins. Moreover, model mixtures mimicking coffee beans composition were roasted and analyzed using mass spectrometry-based approaches to disclose the regulatory role of proteins in transglycosylation reactions extension. This article reports the detailed chemical composition of coffee beans and derived fractions. In addition, it provides gas chromatography–mass spectrometry (GC–MS chromatograms and respective GC–MS spectra of silylated methanolysis products obtained from phenolic compounds standards, as well as the detailed identification of all compounds observed by electrospray mass spectrometry (ESI-MS analysis of roasted model mixtures, paving the way for the identification of the same type of compounds in other samples.

A lock-and-key model for protein–protein interactions

OpenAIRE

Morrison, Julie L.; Breitling, Rainer; Higham, Desmond J.; Gilbert, David R.

2006-01-01

Motivation: Protein–protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism’s proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs,...

Protein buffering in model systems and in whole human saliva.

Directory of Open Access Journals (Sweden)

Andreas Lamanda

Full Text Available The aim of this study was to quantify the buffer attributes (value, power, range and optimum of two model systems for whole human resting saliva, the purified proteins from whole human resting saliva and single proteins. Two model systems, the first containing amyloglucosidase and lysozyme, and the second containing amyloglucosidase and alpha-amylase, were shown to provide, in combination with hydrogencarbonate and di-hydrogenphosphate, almost identical buffer attributes as whole human resting saliva. It was further demonstrated that changes in the protein concentration as small as 0.1% may change the buffer value of a buffer solution up to 15 times. Additionally, it was shown that there was a protein concentration change in the same range (0.16% between saliva samples collected at the time periods of 13:00 and others collected at 9:00 am and 17:00. The mode of the protein expression changed between these samples corresponded to the change in basic buffer power and the change of the buffer value at pH 6.7. Finally, SDS Page and Ruthenium II tris (bathophenantroline disulfonate staining unveiled a constant protein expression in all samples except for one 50 kDa protein band. As the change in the expression pattern of that 50 kDa protein band corresponded to the change in basic buffer power and the buffer value at pH 6.7, it was reasonable to conclude that this 50 kDa protein band may contain the protein(s belonging to the protein buffer system of human saliva.

Effect of Selected Mercapto Flavor Compounds on Acrylamide Elimination in a Model System

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Zhiyong Xiong

2017-05-01

Full Text Available The effect of four mercapto flavor compounds (1,2-ethanedithiol, 1-butanethiol, 2-methyl-3-furanthiol, and 2-furanmethanethiol on acrylamide elimination were investigated in model systems. The obtained results showed that mercaptans assayed were effective in elimination arylamide in a model system. Their reactivities for decreasing acrylamide content depended on mercaptan’s molecular structure and acrylamide disappearance decreased in the following order: 1,2-ethanedithiol > 2-methyl-3-furanthiol > 1-butanethiol > 2-furanmethanethiol. Mercaptans were added to acrylamide to produce the corresponding 3-(alkylthio propionamides. This reaction was irreversible and only trace amounts of acrylamide were formed by thermal heating of 3-(alkylthio propanamide. Although a large amount disappeared, only part of the acrylamide conversed into 3-(alkylthio propionamides. All of these results constitute a fundamental proof of the complexity of the reactions involved in the removal of free acrylamide in foods. This implies mercapto flavor/aroma may directly or indirectly reduce the level of acrylamide in food processing. This study could be regarded as a pioneer contribution on acrylamide elimination in a model system by the addition of mercapto flavor compounds.

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

KAUST Repository

Oliva, Romina; Chermak, Edrisse; Cavallo, Luigi

2015-01-01

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

KAUST Repository

Oliva, Romina

2015-07-01

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

Activating AMP-activated protein kinase by an α1 selective activator compound 13 attenuates dexamethasone-induced osteoblast cell death

International Nuclear Information System (INIS)

Guo, Shiguang; Mao, Li; Ji, Feng; Wang, Shouguo; Xie, Yue; Fei, Haodong; Wang, Xiao-dong

2016-01-01

Excessive glucocorticoid (GC) usage may lead to non-traumatic femoral head osteonecrosis. Dexamethasone (Dex) exerts cytotoxic effect to cultured osteoblasts. Here, we investigated the potential activity of Compound 13 (C13), a novel α1 selective AMP-activated protein kinase (AMPK) activator, against the process. Our data revealed that C13 pretreatment significantly attenuated Dex-induced apoptosis and necrosis in both osteoblastic-like MC3T3-E1 cells and primary murine osteoblasts. AMPK activation mediated C13′ cytoprotective effect in osteoblasts. The AMPK inhibitor Compound C, shRNA-mediated knockdown of AMPKα1, or dominant negative mutation of AMPKα1 (T172A) almost abolished C13-induced AMPK activation and its pro-survival effect in osteoblasts. On the other hand, forced AMPK activation by adding AMPK activator A-769662 or exogenous expression a constitutively-active (ca) AMPKα1 (T172D) mimicked C13's actions and inhibited Dex-induced osteoblast cell death. Meanwhile, A-769662 or ca-AMPKα1 almost nullified C13's activity in osteoblast. Further studies showed that C13 activated AMPK-dependent nicotinamide adenine dinucleotide phosphate (NADPH) pathway to inhibit Dex-induced reactive oxygen species (ROS) production in MC3T3-E1 cells and primary murine osteoblasts. Such effects by C13 were almost reversed by Compound C or AMPKα1 depletion/mutation. Together, these results suggest that C13 alleviates Dex-induced osteoblast cell death via activating AMPK signaling pathway. - Highlights: • Compound 13 (C13) attenuates dexamethasone (Dex)-induced osteoblast cell death. • C13-induced cytoprotective effect against Dex in osteoblasts requires AMPK activation. • Forced AMPK activation protects osteoblasts from Dex, nullifying C13's activities. • C13 increases NADPH activity and inhibits Dex-induced oxidative stress in osteoblasts.

Activating AMP-activated protein kinase by an α1 selective activator compound 13 attenuates dexamethasone-induced osteoblast cell death

Energy Technology Data Exchange (ETDEWEB)

Guo, Shiguang [Department of Intensive Care Unit, Huai' an First People' s Hospital, Nanjing Medical University, Huai' an (China); Mao, Li [Department of Endocrinology, Huai' an First People' s Hospital, Nanjing Medical University, Huai' an (China); Ji, Feng, E-mail: huaiaifengjidr@163.com [Department of Orthopedics, Huai' an First People' s Hospital, Nanjing Medical University, Huai' an (China); Wang, Shouguo; Xie, Yue; Fei, Haodong [Department of Orthopedics, Huai' an First People' s Hospital, Nanjing Medical University, Huai' an (China); Wang, Xiao-dong, E-mail: xiaodongwangsz@163.com [The Center of Diagnosis and Treatment for Children' s Bone Diseases, The Children' s Hospital Affiliated to Soochow University, Suzhou (China)

2016-03-18

Excessive glucocorticoid (GC) usage may lead to non-traumatic femoral head osteonecrosis. Dexamethasone (Dex) exerts cytotoxic effect to cultured osteoblasts. Here, we investigated the potential activity of Compound 13 (C13), a novel α1 selective AMP-activated protein kinase (AMPK) activator, against the process. Our data revealed that C13 pretreatment significantly attenuated Dex-induced apoptosis and necrosis in both osteoblastic-like MC3T3-E1 cells and primary murine osteoblasts. AMPK activation mediated C13′ cytoprotective effect in osteoblasts. The AMPK inhibitor Compound C, shRNA-mediated knockdown of AMPKα1, or dominant negative mutation of AMPKα1 (T172A) almost abolished C13-induced AMPK activation and its pro-survival effect in osteoblasts. On the other hand, forced AMPK activation by adding AMPK activator A-769662 or exogenous expression a constitutively-active (ca) AMPKα1 (T172D) mimicked C13's actions and inhibited Dex-induced osteoblast cell death. Meanwhile, A-769662 or ca-AMPKα1 almost nullified C13's activity in osteoblast. Further studies showed that C13 activated AMPK-dependent nicotinamide adenine dinucleotide phosphate (NADPH) pathway to inhibit Dex-induced reactive oxygen species (ROS) production in MC3T3-E1 cells and primary murine osteoblasts. Such effects by C13 were almost reversed by Compound C or AMPKα1 depletion/mutation. Together, these results suggest that C13 alleviates Dex-induced osteoblast cell death via activating AMPK signaling pathway. - Highlights: • Compound 13 (C13) attenuates dexamethasone (Dex)-induced osteoblast cell death. • C13-induced cytoprotective effect against Dex in osteoblasts requires AMPK activation. • Forced AMPK activation protects osteoblasts from Dex, nullifying C13's activities. • C13 increases NADPH activity and inhibits Dex-induced oxidative stress in osteoblasts.

An acute rat in vivo screening model to predict compounds that alter blood glucose and/or insulin regulation.

Science.gov (United States)

Brott, David A; Diamond, Melody; Campbell, Pam; Zuvich, Andy; Cheatham, Letitia; Bentley, Patricia; Gorko, Mary Ann; Fikes, James; Saye, JoAnne

2013-01-01

Drug-induced glucose dysregulation and insulin resistance have been associated with weight gain and potential induction and/or exacerbation of diabetes mellitus in the clinic suggesting they may be safety biomarkers when developing antipsychotics. Glucose and insulin have also been suggested as potential efficacy biomarkers for some oncology compounds. The objective of this study was to qualify a medium throughput rat in vivo acute Intravenous Glucose Tolerance Test (IVGTT) for predicting compounds that will induce altered blood glucose and/or insulin levels. Acute and sub-chronic studies were performed to qualify an acute IVGTT model. Double cannulated male rats (Han-Wistar and Sprague-Dawley) were administered vehicle, olanzapine, aripiprazole or other compounds at t=-44min for acute studies and at time=-44min on the last day of dosing for sub-chronic studies, treated with dextrose (time=0min; i.v.) and blood collected using an automated Culex® system for glucose and insulin analysis (time=-45, -1, 2, 10, 15, 30, 45, 60, 75, 90, 120, 150 and 180min). Olanzapine significantly increased glucose and insulin area under the curve (AUC) values while aripiprazole AUC values were similar to control, in both acute and sub-chronic studies. All atypical antipsychotics evaluated were consistent with literature references of clinical weight gain. As efficacy biomarkers, insulin AUC but not glucose AUC values were increased with a compound known to have insulin growth factor-1 (IGF-1) activity, compared to control treatment. These studies qualified the medium throughput acute IVGTT model to more quickly screen compounds for 1) safety - the potential to elicit glucose dysregulation and/or insulin resistance and 2) efficacy - as a surrogate for compounds affecting the glucose and/or insulin regulatory pathways. These data demonstrate that the same in vivo rat model and assays can be used to predict both clinical safety and efficacy of compounds. © 2013.

Decomposition of lignin model compounds by Lewis acid catalysts in water and ethanol

NARCIS (Netherlands)

Guvenatam, Burcu; Heeres, Erik H.J.; Pidko, Evgeny A.; Hensen, Emiel J. M.

2015-01-01

The conversion of benzyl phenyl ether, diphenyl ether, diphenyl methane and biphenyl as representative model compounds for alpha-O-4, 5-O-4, alpha(1) (methylene bridges) and 5-5' lignin linkages was investigated. We compared the use of metal chlorides and acetates. The reactions were studied in sub-

Mechanical strength of 17,134 model proteins and cysteine slipknots.

Directory of Open Access Journals (Sweden)

Mateusz Sikora

2009-10-01

Full Text Available A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17,134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cysteine slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations.

Interaction of arsenic compounds with model phospholipid membranes

International Nuclear Information System (INIS)

Jemiola-Rzeminska, Malgorzata; Rivera, Cecilia; Suwalsky, Mario; Strzalka, Kazimierz

2007-01-01

This study is part of a project aimed at examining the influence of arsenic on biological membranes. By the use of differential scanning calorimetry (DSC) we have followed the thermotropic behavior of multilamellar vesicles prepared from dimyristoylphosphatidylcholine (DMPC) and dimyristoylphosphatidylethanolamine (DMPE) upon incorporation of sodium arsenite (AsI), disodium arsenate (AsII), cacodylic acid (AsIII) and disodium methyl arsenate (AsIV). The effectiveness of perturbations exerted by various arsenic compounds on thermotropic phase transition was further analysed in terms of thermodynamic parameters: transition temperature, enthalpy and molar heat capacity, determined for lipid/As systems on the basis of heating and cooling scans. It is found that while it only has a slight influence on the thermotropic properties of DMPC, arsenic is able to significantly modify DMPE model membranes