Accounting for observed small angle X-ray scattering profile in the protein-protein docking server ClusPro.

PubMed

Xia, Bing; Mamonov, Artem; Leysen, Seppe; Allen, Karen N; Strelkov, Sergei V; Paschalidis, Ioannis Ch; Vajda, Sandor; Kozakov, Dima

2015-07-30

The protein-protein docking server ClusPro is used by thousands of laboratories, and models built by the server have been reported in over 300 publications. Although the structures generated by the docking include near-native ones for many proteins, selecting the best model is difficult due to the uncertainty in scoring. Small angle X-ray scattering (SAXS) is an experimental technique for obtaining low resolution structural information in solution. While not sufficient on its own to uniquely predict complex structures, accounting for SAXS data improves the ranking of models and facilitates the identification of the most accurate structure. Although SAXS profiles are currently available only for a small number of complexes, due to its simplicity the method is becoming increasingly popular. Since combining docking with SAXS experiments will provide a viable strategy for fairly high-throughput determination of protein complex structures, the option of using SAXS restraints is added to the ClusPro server. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Recent progress and future directions in protein-protein docking.

PubMed

Ritchie, David W

2008-02-01

This article gives an overview of recent progress in protein-protein docking and it identifies several directions for future research. Recent results from the CAPRI blind docking experiments show that docking algorithms are steadily improving in both reliability and accuracy. Current docking algorithms employ a range of efficient search and scoring strategies, including e.g. fast Fourier transform correlations, geometric hashing, and Monte Carlo techniques. These approaches can often produce a relatively small list of up to a few thousand orientations, amongst which a near-native binding mode is often observed. However, despite the use of improved scoring functions which typically include models of desolvation, hydrophobicity, and electrostatics, current algorithms still have difficulty in identifying the correct solution from the list of false positives, or decoys. Nonetheless, significant progress is being made through better use of bioinformatics, biochemical, and biophysical information such as e.g. sequence conservation analysis, protein interaction databases, alanine scanning, and NMR residual dipolar coupling restraints to help identify key binding residues. Promising new approaches to incorporate models of protein flexibility during docking are being developed, including the use of molecular dynamics snapshots, rotameric and off-rotamer searches, internal coordinate mechanics, and principal component analysis based techniques. Some investigators now use explicit solvent models in their docking protocols. Many of these approaches can be computationally intensive, although new silicon chip technologies such as programmable graphics processor units are beginning to offer competitive alternatives to conventional high performance computer systems. As cryo-EM techniques improve apace, docking NMR and X-ray protein structures into low resolution EM density maps is helping to bridge the resolution gap between these complementary techniques. The use of symmetry and fragment assembly constraints are also helping to make possible docking-based predictions of large multimeric protein complexes. In the near future, the closer integration of docking algorithms with protein interface prediction software, structural databases, and sequence analysis techniques should help produce better predictions of protein interaction networks and more accurate structural models of the fundamental molecular interactions within the cell.

Great interactions: How binding incorrect partners can teach us about protein recognition and function.

PubMed

Vamparys, Lydie; Laurent, Benoist; Carbone, Alessandra; Sacquin-Mora, Sophie

2016-10-01

Protein-protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross-docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein's binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross-docking predictions using the area under the specificity-sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on the binding patches that are scattered on the protein surface show that their distribution and growth will depend on the protein's functional group. Finally, in several cases, the binding-site predictions resulting from the cross-docking simulations will lead to the identification of an alternate interface, which corresponds to the interaction with a biomolecular partner that is not included in the original benchmark. Proteins 2016; 84:1408-1421. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

ClusPro: an automated docking and discrimination method for the prediction of protein complexes.

PubMed

Comeau, Stephen R; Gatchell, David W; Vajda, Sandor; Camacho, Carlos J

2004-01-01

Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. The fully automated docking and discrimination server ClusPro can be found at http://structure.bu.edu

Great interactions: How binding incorrect partners can teach us about protein recognition and function

PubMed Central

Vamparys, Lydie; Laurent, Benoist; Carbone, Alessandra

2016-01-01

ABSTRACT Protein–protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross‐docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein's binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross‐docking predictions using the area under the specificity‐sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on the binding patches that are scattered on the protein surface show that their distribution and growth will depend on the protein's functional group. Finally, in several cases, the binding‐site predictions resulting from the cross‐docking simulations will lead to the identification of an alternate interface, which corresponds to the interaction with a biomolecular partner that is not included in the original benchmark. Proteins 2016; 84:1408–1421. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:27287388

Performance of MDockPP in CAPRI rounds 28-29 and 31-35 including the prediction of water-mediated interactions.

PubMed

Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Ma, Zhiwei; Grinter, Sam Z; Zou, Xiaoqin

2017-03-01

Protein-protein interactions are either through direct contacts between two binding partners or mediated by structural waters. Both direct contacts and water-mediated interactions are crucial to the formation of a protein-protein complex. During the recent CAPRI rounds, a novel parallel searching strategy for predicting water-mediated interactions is introduced into our protein-protein docking method, MDockPP. Briefly, a FFT-based docking algorithm is employed in generating putative binding modes, and an iteratively derived statistical potential-based scoring function, ITScorePP, in conjunction with biological information is used to assess and rank the binding modes. Up to 10 binding modes are selected as the initial protein-protein complex structures for MD simulations in explicit solvent. Water molecules near the interface are clustered based on the snapshots extracted from independent equilibrated trajectories. Then, protein-ligand docking is employed for a parallel search for water molecules near the protein-protein interface. The water molecules generated by ligand docking and the clustered water molecules generated by MD simulations are merged, referred to as the predicted structural water molecules. Here, we report the performance of this protocol for CAPRI rounds 28-29 and 31-35 containing 20 valid docking targets and 11 scoring targets. In the docking experiments, we predicted correct binding modes for nine targets, including one high-accuracy, two medium-accuracy, and six acceptable predictions. Regarding the two targets for the prediction of water-mediated interactions, we achieved models ranked as "excellent" in accordance with the CAPRI evaluation criteria; one of these two targets is considered as a difficult target for structural water prediction. Proteins 2017; 85:424-434. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Application of Enhanced Sampling Monte Carlo Methods for High-Resolution Protein-Protein Docking in Rosetta

PubMed Central

Zhang, Zhe; Schindler, Christina E. M.; Lange, Oliver F.; Zacharias, Martin

2015-01-01

The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC) based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC) was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches. PMID:26053419

Utilizing Mechanistic Cross-Linking Technology to Study Protein-Protein Interactions: An Experiment Designed for an Undergraduate Biochemistry Lab

ERIC Educational Resources Information Center

Finzel, Kara; Beld, Joris; Burkart, Michael D.; Charkoudian, Louise K.

2017-01-01

Over the past decade, mechanistic cross-linking probes have been used to study protein-protein interactions in natural product biosynthetic pathways. This approach is highly interdisciplinary, combining elements of protein biochemistry, organic chemistry, and computational docking. Herein, we described the development of an experiment to engage…

Autogrid-based clustering of kinases: selection of representative conformations for docking purposes.

PubMed

Marzaro, Giovanni; Ferrarese, Alessandro; Chilin, Adriana

2014-08-01

The selection of the most appropriate protein conformation is a crucial aspect in molecular docking experiments. In order to reduce the errors arising from the use of a single protein conformation, several authors suggest the use of several tridimensional structures for the target. However, the selection of the most appropriate protein conformations still remains a challenging goal. The protein 3D-structures selection is mainly performed based on pairwise root-mean-square-deviation (RMSD) values computation, followed by hierarchical clustering. Herein we report an alternative strategy, based on the computation of only two atom affinity map for each protein conformation, followed by multivariate analysis and hierarchical clustering. This methodology was applied on seven different kinases of pharmaceutical interest. The comparison with the classical RMSD-based strategy was based on cross-docking of co-crystallized ligands. In the case of epidermal growth factor receptor kinase, also the docking performance on 220 known ligands were evaluated, followed by 3D-QSAR studies. In all the cases, the herein proposed methodology outperformed the RMSD-based one.

Lessons in molecular recognition. 2. Assessing and improving cross-docking accuracy.

PubMed

Sutherland, Jeffrey J; Nandigam, Ravi K; Erickson, Jon A; Vieth, Michal

2007-01-01

Docking methods are used to predict the manner in which a ligand binds to a protein receptor. Many studies have assessed the success rate of programs in self-docking tests, whereby a ligand is docked into the protein structure from which it was extracted. Cross-docking, or using a protein structure from a complex containing a different ligand, provides a more realistic assessment of a docking program's ability to reproduce X-ray results. In this work, cross-docking was performed with CDocker, Fred, and Rocs using multiple X-ray structures for eight proteins (two kinases, one nuclear hormone receptor, one serine protease, two metalloproteases, and two phosphodiesterases). While average cross-docking accuracy is not encouraging, it is shown that using the protein structure from the complex that contains the bound ligand most similar to the docked ligand increases docking accuracy for all methods ("similarity selection"). Identifying the most successful protein conformer ("best selection") and similarity selection substantially reduce the difference between self-docking and average cross-docking accuracy. We identify universal predictors of docking accuracy (i.e., showing consistent behavior across most protein-method combinations), and show that models for predicting docking accuracy built using these parameters can be used to select the most appropriate docking method.

A web interface for easy flexible protein-protein docking with ATTRACT.

PubMed

de Vries, Sjoerd J; Schindler, Christina E M; Chauvot de Beauchêne, Isaure; Zacharias, Martin

2015-02-03

Protein-protein docking programs can give valuable insights into the structure of protein complexes in the absence of an experimental complex structure. Web interfaces can facilitate the use of docking programs by structural biologists. Here, we present an easy web interface for protein-protein docking with the ATTRACT program. While aimed at nonexpert users, the web interface still covers a considerable range of docking applications. The web interface supports systematic rigid-body protein docking with the ATTRACT coarse-grained force field, as well as various kinds of protein flexibility. The execution of a docking protocol takes up to a few hours on a standard desktop computer. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening.

PubMed

Zhang, Changsheng; Tang, Bo; Wang, Qian; Lai, Luhua

2014-10-01

Target structure-based virtual screening, which employs protein-small molecule docking to identify potential ligands, has been widely used in small-molecule drug discovery. In the present study, we used a protein-protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all-to-all protein-protein docking run on a large dataset was performed. The three-dimensional rigid docking program SDOCK was used to examine protein-protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z-score, and convergency of the low-score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all-to-all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor-α (TNFα), which is a well-known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top-ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein-protein docking for the discovery of novel binding proteins for specific protein targets. © 2014 Wiley Periodicals, Inc.

Empirical entropic contributions in computational docking: evaluation in APS reductase complexes.

PubMed

Chang, Max W; Belew, Richard K; Carroll, Kate S; Olson, Arthur J; Goodsell, David S

2008-08-01

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments. 2008 Wiley Periodicals, Inc.

F2Dock: Fast Fourier Protein-Protein Docking

PubMed Central

Bajaj, Chandrajit; Chowdhury, Rezaul; Siddavanahalli, Vinay

2009-01-01

The functions of proteins is often realized through their mutual interactions. Determining a relative transformation for a pair of proteins and their conformations which form a stable complex, reproducible in nature, is known as docking. It is an important step in drug design, structure determination and understanding function and structure relationships. In this paper we extend our non-uniform fast Fourier transform docking algorithm to include an adaptive search phase (both translational and rotational) and thereby speed up its execution. We have also implemented a multithreaded version of the adaptive docking algorithm for even faster execution on multicore machines. We call this protein-protein docking code F2Dock (F2 = Fast Fourier). We have calibrated F2Dock based on an extensive experimental study on a list of benchmark complexes and conclude that F2Dock works very well in practice. Though all docking results reported in this paper use shape complementarity and Coulombic potential based scores only, F2Dock is structured to incorporate Lennard-Jones potential and re-ranking docking solutions based on desolvation energy. PMID:21071796

GalaxyDock BP2 score: a hybrid scoring function for accurate protein-ligand docking

NASA Astrophysics Data System (ADS)

Baek, Minkyung; Shin, Woong-Hee; Chung, Hwan Won; Seok, Chaok

2017-07-01

Protein-ligand docking is a useful tool for providing atomic-level understanding of protein functions in nature and design principles for artificial ligands or proteins with desired properties. The ability to identify the true binding pose of a ligand to a target protein among numerous possible candidate poses is an essential requirement for successful protein-ligand docking. Many previously developed docking scoring functions were trained to reproduce experimental binding affinities and were also used for scoring binding poses. However, in this study, we developed a new docking scoring function, called GalaxyDock BP2 Score, by directly training the scoring power of binding poses. This function is a hybrid of physics-based, empirical, and knowledge-based score terms that are balanced to strengthen the advantages of each component. The performance of the new scoring function exhibits significant improvement over existing scoring functions in decoy pose discrimination tests. In addition, when the score is used with the GalaxyDock2 protein-ligand docking program, it outperformed other state-of-the-art docking programs in docking tests on the Astex diverse set, the Cross2009 benchmark set, and the Astex non-native set. GalaxyDock BP2 Score and GalaxyDock2 with this score are freely available at http://galaxy.seoklab.org/softwares/galaxydock.html.

Docking and scoring protein complexes: CAPRI 3rd Edition.

PubMed

Lensink, Marc F; Méndez, Raúl; Wodak, Shoshana J

2007-12-01

The performance of methods for predicting protein-protein interactions at the atomic scale is assessed by evaluating blind predictions performed during 2005-2007 as part of Rounds 6-12 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). These Rounds also included a new scoring experiment, where a larger set of models contributed by the predictors was made available to groups developing scoring functions. These groups scored the uploaded set and submitted their own best models for assessment. The structures of nine protein complexes including one homodimer were used as targets. These targets represent biologically relevant interactions involved in gene expression, signal transduction, RNA, or protein processing and membrane maintenance. For all the targets except one, predictions started from the experimentally determined structures of the free (unbound) components or from models derived by homology, making it mandatory for docking methods to model the conformational changes that often accompany association. In total, 63 groups and eight automatic servers, a substantial increase from previous years, submitted docking predictions, of which 1994 were evaluated here. Fifteen groups submitted 305 models for five targets in the scoring experiment. Assessment of the predictions reveals that 31 different groups produced models of acceptable and medium accuracy-but only one high accuracy submission-for all the targets, except the homodimer. In the latter, none of the docking procedures reproduced the large conformational adjustment required for correct assembly, underscoring yet again that handling protein flexibility remains a major challenge. In the scoring experiment, a large fraction of the groups attained the set goal of singling out the correct association modes from incorrect solutions in the limited ensembles of contributed models. But in general they seemed unable to identify the best models, indicating that current scoring methods are probably not sensitive enough. With the increased focus on protein assemblies, in particular by structural genomics efforts, the growing community of CAPRI predictors is engaged more actively than ever in the development of better scoring functions and means of modeling conformational flexibility, which hold promise for much progress in the future. (c) 2007 Wiley-Liss, Inc.

Structure and Sequence Search on Aptamer-Protein Docking

NASA Astrophysics Data System (ADS)

Xiao, Jiajie; Bonin, Keith; Guthold, Martin; Salsbury, Freddie

2015-03-01

Interactions between proteins and deoxyribonucleic acid (DNA) play a significant role in the living systems, especially through gene regulation. However, short nucleic acids sequences (aptamers) with specific binding affinity to specific proteins exhibit clinical potential as therapeutics. Our capillary and gel electrophoresis selection experiments show that specific sequences of aptamers can be selected that bind specific proteins. Computationally, given the experimentally-determined structure and sequence of a thrombin-binding aptamer, we can successfully dock the aptamer onto thrombin in agreement with experimental structures of the complex. In order to further study the conformational flexibility of this thrombin-binding aptamer and to potentially develop a predictive computational model of aptamer-binding, we use GPU-enabled molecular dynamics simulations to both examine the conformational flexibility of the aptamer in the absence of binding to thrombin, and to determine our ability to fold an aptamer. This study should help further de-novo predictions of aptamer sequences by enabling the study of structural and sequence-dependent effects on aptamer-protein docking specificity.

InterEvDock2: an expanded server for protein docking using evolutionary and biological information from homology models and multimeric inputs.

PubMed

Quignot, Chloé; Rey, Julien; Yu, Jinchao; Tufféry, Pierre; Guerois, Raphaël; Andreani, Jessica

2018-05-08

Computational protein docking is a powerful strategy to predict structures of protein-protein interactions and provides crucial insights for the functional characterization of macromolecular cross-talks. We previously developed InterEvDock, a server for ab initio protein docking based on rigid-body sampling followed by consensus scoring using physics-based and statistical potentials, including the InterEvScore function specifically developed to incorporate co-evolutionary information in docking. InterEvDock2 is a major evolution of InterEvDock which allows users to submit input sequences - not only structures - and multimeric inputs and to specify constraints for the pairwise docking process based on previous knowledge about the interaction. For this purpose, we added modules in InterEvDock2 for automatic template search and comparative modeling of the input proteins. The InterEvDock2 pipeline was benchmarked on 812 complexes for which unbound homology models of the two partners and co-evolutionary information are available in the PPI4DOCK database. InterEvDock2 identified a correct model among the top 10 consensus in 29% of these cases (compared to 15-24% for individual scoring functions) and at least one correct interface residue among 10 predicted in 91% of these cases. InterEvDock2 is thus a unique protein docking server, designed to be useful for the experimental biology community. The InterEvDock2 web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock2/.

Multi-Conformer Ensemble Docking to Difficult Protein Targets

DOE PAGES

Ellingson, Sally R.; Miao, Yinglong; Baudry, Jerome; ...

2014-09-08

We investigate large-scale ensemble docking using five proteins from the Directory of Useful Decoys (DUD, dud.docking.org) for which docking to crystal structures has proven difficult. Molecular dynamics trajectories are produced for each protein and an ensemble of representative conformational structures extracted from the trajectories. Docking calculations are performed on these selected simulation structures and ensemble-based enrichment factors compared with those obtained using docking in crystal structures of the same protein targets or random selection of compounds. We also found simulation-derived snapshots with improved enrichment factors that increased the chemical diversity of docking hits for four of the five selected proteins.more » A combination of all the docking results obtained from molecular dynamics simulation followed by selection of top-ranking compounds appears to be an effective strategy for increasing the number and diversity of hits when using docking to screen large libraries of chemicals against difficult protein targets.« less

DOCKSCORE: a webserver for ranking protein-protein docked poses.

PubMed

Malhotra, Sony; Mathew, Oommen K; Sowdhamini, Ramanathan

2015-04-24

Proteins interact with a variety of other molecules such as nucleic acids, small molecules and other proteins inside the cell. Structure-determination of protein-protein complexes is challenging due to several reasons such as the large molecular weights of these macromolecular complexes, their dynamic nature, difficulty in purification and sample preparation. Computational docking permits an early understanding of the feasibility and mode of protein-protein interactions. However, docking algorithms propose a number of solutions and it is a challenging task to select the native or near native pose(s) from this pool. DockScore is an objective scoring scheme that can be used to rank protein-protein docked poses. It considers several interface parameters, namely, surface area, evolutionary conservation, hydrophobicity, short contacts and spatial clustering at the interface for scoring. We have implemented DockScore in form of a webserver for its use by the scientific community. DockScore webserver can be employed, subsequent to docking, to perform scoring of the docked solutions, starting from multiple poses as inputs. The results, on scores and ranks for all the poses, can be downloaded as a csv file and graphical view of the interface of best ranking poses is possible. The webserver for DockScore is made freely available for the scientific community at: http://caps.ncbs.res.in/dockscore/ .

PharmDock: a pharmacophore-based docking program

PubMed Central

2014-01-01

Background Protein-based pharmacophore models are enriched with the information of potential interactions between ligands and the protein target. We have shown in a previous study that protein-based pharmacophore models can be applied for ligand pose prediction and pose ranking. In this publication, we present a new pharmacophore-based docking program PharmDock that combines pose sampling and ranking based on optimized protein-based pharmacophore models with local optimization using an empirical scoring function. Results Tests of PharmDock on ligand pose prediction, binding affinity estimation, compound ranking and virtual screening yielded comparable or better performance to existing and widely used docking programs. The docking program comes with an easy-to-use GUI within PyMOL. Two features have been incorporated in the program suite that allow for user-defined guidance of the docking process based on previous experimental data. Docking with those features demonstrated superior performance compared to unbiased docking. Conclusion A protein pharmacophore-based docking program, PharmDock, has been made available with a PyMOL plugin. PharmDock and the PyMOL plugin are freely available from http://people.pharmacy.purdue.edu/~mlill/software/pharmdock. PMID:24739488

HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy.

PubMed

Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong; Huang, Sheng-You

2017-07-03

Protein-protein and protein-DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein-protein and protein-DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10-20 min for a docking run. Tested on the cases with weakly homologous complexes of <30% sequence identity from five docking benchmarks, the HDOCK pipeline tied with template-based modeling on the protein-protein and protein-DNA benchmarks and performed better than template-based modeling on the three protein-RNA benchmarks when the top 10 predictions were considered. The performance of HDOCK became better when more predictions were considered. Combining the results of HDOCK and template-based modeling by ranking first of the template-based model further improved the predictive power of the server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Improving Docking Performance Using Negative Image-Based Rescoring.

PubMed

Kurkinen, Sami T; Niinivehmas, Sanna; Ahinko, Mira; Lätti, Sakari; Pentikäinen, Olli T; Postila, Pekka A

2018-01-01

Despite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing the docking-based ligand conformers directly against the target protein's cavity shape and electrostatics. The similarity comparison of the conformers is performed without geometry optimization against the negative image of the target protein's ligand-binding cavity using the negative image-based (NIB) screening protocol. The viability of the NIB rescoring or the R-NiB, pioneered in this study, was tested with 11 target proteins using benchmark libraries. By focusing on the shape/electrostatics complementarity of the ligand-receptor association, the R-NiB is able to improve the early enrichment of docking essentially without adding to the computing cost. By implementing consensus scoring, in which the R-NiB and the original docking scoring are weighted for optimal outcome, the early enrichment is improved to a level that facilitates effective drug discovery. Moreover, the use of equal weight from the original docking scoring and the R-NiB scoring improves the yield in most cases.

pyDockWEB: a web server for rigid-body protein-protein docking using electrostatics and desolvation scoring.

PubMed

Jiménez-García, Brian; Pons, Carles; Fernández-Recio, Juan

2013-07-01

pyDockWEB is a web server for the rigid-body docking prediction of protein-protein complex structures using a new version of the pyDock scoring algorithm. We use here a new custom parallel FTDock implementation, with adjusted grid size for optimal FFT calculations, and a new version of pyDock, which dramatically speeds up calculations while keeping the same predictive accuracy. Given the 3D coordinates of two interacting proteins, pyDockWEB returns the best docking orientations as scored mainly by electrostatics and desolvation energy. The server does not require registration by the user and is freely accessible for academics at http://life.bsc.es/servlet/pydock. Supplementary data are available at Bioinformatics online.

Protein tyrosine phosphatases: Ligand interaction analysis and optimisation of virtual screening.

PubMed

Ghattas, Mohammad A; Atatreh, Noor; Bichenkova, Elena V; Bryce, Richard A

2014-07-01

Docking-based virtual screening is an established component of structure-based drug discovery. Nevertheless, scoring and ranking of computationally docked ligand libraries still suffer from many false positives. Identifying optimal docking parameters for a target protein prior to virtual screening can improve experimental hit rates. Here, we examine protocols for virtual screening against the important but challenging class of drug target, protein tyrosine phosphatases. In this study, common interaction features were identified from analysis of protein-ligand binding geometries of more than 50 complexed phosphatase crystal structures. It was found that two interactions were consistently formed across all phosphatase inhibitors: (1) a polar contact with the conserved arginine residue, and (2) at least one interaction with the P-loop backbone amide. In order to investigate the significance of these features on phosphatase-ligand binding, a series of seeded virtual screening experiments were conducted on three phosphatase enzymes, PTP1B, Cdc25b and IF2. It was observed that when the conserved arginine and P-loop amide interactions were used as pharmacophoric constraints during docking, enrichment of the virtual screen significantly increased in the three studied phosphatases, by up to a factor of two in some cases. Additionally, the use of such pharmacophoric constraints considerably improved the ability of docking to predict the inhibitor's bound pose, decreasing RMSD to the crystallographic geometry by 43% on average. Constrained docking improved enrichment of screens against both open and closed conformations of PTP1B. Incorporation of an ordered water molecule in PTP1B screening was also found to generally improve enrichment. The knowledge-based computational strategies explored here can potentially inform structure-based design of new phosphatase inhibitors using docking-based virtual screening. Copyright © 2014 Elsevier Inc. All rights reserved.

Structural Interface Parameters Are Discriminatory in Recognising Near-Native Poses of Protein-Protein Interactions

PubMed Central

Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

2014-01-01

Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets. PMID:24498255

Structural interface parameters are discriminatory in recognising near-native poses of protein-protein interactions.

PubMed

Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

2014-01-01

Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets.

Protein-protein docking using region-based 3D Zernike descriptors

PubMed Central

2009-01-01

Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods. PMID:20003235

Protein-protein docking using region-based 3D Zernike descriptors.

PubMed

Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD < or = 2.5 A) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

The pepATTRACT web server for blind, large-scale peptide-protein docking.

PubMed

de Vries, Sjoerd J; Rey, Julien; Schindler, Christina E M; Zacharias, Martin; Tuffery, Pierre

2017-07-03

Peptide-protein interactions are ubiquitous in the cell and form an important part of the interactome. Computational docking methods can complement experimental characterization of these complexes, but current protocols are not applicable on the proteome scale. pepATTRACT is a novel docking protocol that is fully blind, i.e. it does not require any information about the binding site. In various stages of its development, pepATTRACT has participated in CAPRI, making successful predictions for five out of seven protein-peptide targets. Its performance is similar or better than state-of-the-art local docking protocols that do require binding site information. Here we present a novel web server that carries out the rigid-body stage of pepATTRACT. On the peptiDB benchmark, the web server generates a correct model in the top 50 in 34% of the cases. Compared to the full pepATTRACT protocol, this leads to some loss of performance, but the computation time is reduced from ∼18 h to ∼10 min. Combined with the fact that it is fully blind, this makes the web server well-suited for large-scale in silico protein-peptide docking experiments. The rigid-body pepATTRACT server is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/services/pepATTRACT. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Constrained Photophysics of 5,7-dimethoxy-2,3,4,9-tetrahydro-1H-carbazol-1-one in the Bioenvironment of Serum Albumins: A Spectroscopic Endeavour Supported by Molecular Docking Analysis.

PubMed

Mitra, Amrit Krishna; Sau, Abhishek; Pal, Uttam; Saha, Chandan; Basu, Samita

2017-07-01

This paper vividly indicates that steady state as well as time-resolved fluorescence techniques can serve as highly sensitive monitors to explore the interactions of 5,7-dimethoxy-2,3,4,9-tetrahydro-1H-carbazol-1-one with model transport proteins, bovine serum albumin (BSA) and human serum albumin (HSA). Besides these, we have used fluorescence anisotropy study to assess the degree of restrictions imparted by the micro-environments of serum albumins. Again, to speculate the triplet excited state interaction between such fluorophore and albumin proteins (BSA& HSA), laser flash-photolysis experiments have been carried out. Molecular docking experiments have also been performed to support the conclusions obtained from steady state experiments.

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

PubMed

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.

DARC 2.0: Improved Docking and Virtual Screening at Protein Interaction Sites

PubMed Central

Gowthaman, Ragul; Lyskov, Sergey; Karanicolas, John

2015-01-01

Over the past decade, protein-protein interactions have emerged as attractive but challenging targets for therapeutic intervention using small molecules. Due to the relatively flat surfaces that typify protein interaction sites, modern virtual screening tools developed for optimal performance against “traditional” protein targets perform less well when applied instead at protein interaction sites. Previously, we described a docking method specifically catered to the shallow binding modes characteristic of small-molecule inhibitors of protein interaction sites. This method, called DARC (Docking Approach using Ray Casting), operates by comparing the topography of the protein surface when “viewed” from a vantage point inside the protein against the topography of a bound ligand when “viewed” from the same vantage point. Here, we present five key enhancements to DARC. First, we use multiple vantage points to more accurately determine protein-ligand surface complementarity. Second, we describe a new scheme for rapidly determining optimal weights in the DARC scoring function. Third, we incorporate sampling of ligand conformers “on-the-fly” during docking. Fourth, we move beyond simple shape complementarity and introduce a term in the scoring function to capture electrostatic complementarity. Finally, we adjust the control flow in our GPU implementation of DARC to achieve greater speedup of these calculations. At each step of this study, we evaluate the performance of DARC in a “pose recapitulation” experiment: predicting the binding mode of 25 inhibitors each solved in complex with its distinct target protein (a protein interaction site). Whereas the previous version of DARC docked only one of these inhibitors to within 2 Å RMSD of its position in the crystal structure, the newer version achieves this level of accuracy for 12 of the 25 complexes, corresponding to a statistically significant performance improvement (p < 0.001). Collectively then, we find that the five enhancements described here – which together make up DARC 2.0 – lead to dramatically improved speed and performance relative to the original DARC method. PMID:26181386

Monte Carlo replica-exchange based ensemble docking of protein conformations.

PubMed

Zhang, Zhe; Ehmann, Uwe; Zacharias, Martin

2017-05-01

A replica-exchange Monte Carlo (REMC) ensemble docking approach has been developed that allows efficient exploration of protein-protein docking geometries. In addition to Monte Carlo steps in translation and orientation of binding partners, possible conformational changes upon binding are included based on Monte Carlo selection of protein conformations stored as ordered pregenerated conformational ensembles. The conformational ensembles of each binding partner protein were generated by three different approaches starting from the unbound partner protein structure with a range spanning a root mean square deviation of 1-2.5 Å with respect to the unbound structure. Because MC sampling is performed to select appropriate partner conformations on the fly the approach is not limited by the number of conformations in the ensemble compared to ensemble docking of each conformer pair in ensemble cross docking. Although only a fraction of generated conformers was in closer agreement with the bound structure the REMC ensemble docking approach achieved improved docking results compared to REMC docking with only the unbound partner structures or using docking energy minimization methods. The approach has significant potential for further improvement in combination with more realistic structural ensembles and better docking scoring functions. Proteins 2017; 85:924-937. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Surflex-Dock: Docking benchmarks and real-world application

NASA Astrophysics Data System (ADS)

Spitzer, Russell; Jain, Ajay N.

2012-06-01

Benchmarks for molecular docking have historically focused on re-docking the cognate ligand of a well-determined protein-ligand complex to measure geometric pose prediction accuracy, and measurement of virtual screening performance has been focused on increasingly large and diverse sets of target protein structures, cognate ligands, and various types of decoy sets. Here, pose prediction is reported on the Astex Diverse set of 85 protein ligand complexes, and virtual screening performance is reported on the DUD set of 40 protein targets. In both cases, prepared structures of targets and ligands were provided by symposium organizers. The re-prepared data sets yielded results not significantly different than previous reports of Surflex-Dock on the two benchmarks. Minor changes to protein coordinates resulting from complex pre-optimization had large effects on observed performance, highlighting the limitations of cognate ligand re-docking for pose prediction assessment. Docking protocols developed for cross-docking, which address protein flexibility and produce discrete families of predicted poses, produced substantially better performance for pose prediction. Performance on virtual screening performance was shown to benefit by employing and combining multiple screening methods: docking, 2D molecular similarity, and 3D molecular similarity. In addition, use of multiple protein conformations significantly improved screening enrichment.

Ligand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach

NASA Astrophysics Data System (ADS)

Lam, Polo C.-H.; Abagyan, Ruben; Totrov, Maxim

2018-01-01

Ligand docking to flexible protein molecules can be efficiently carried out through ensemble docking to multiple protein conformations, either from experimental X-ray structures or from in silico simulations. The success of ensemble docking often requires the careful selection of complementary protein conformations, through docking and scoring of known co-crystallized ligands. False positives, in which a ligand in a wrong pose achieves a better docking score than that of native pose, arise as additional protein conformations are added. In the current study, we developed a new ligand-biased ensemble receptor docking method and composite scoring function which combine the use of ligand-based atomic property field (APF) method with receptor structure-based docking. This method helps us to correctly dock 30 out of 36 ligands presented by the D3R docking challenge. For the six mis-docked ligands, the cognate receptor structures prove to be too different from the 40 available experimental Pocketome conformations used for docking and could be identified only by receptor sampling beyond experimentally explored conformational subspace.

SDU: A Semidefinite Programming-Based Underestimation Method for Stochastic Global Optimization in Protein Docking

DTIC Science & Technology

2007-04-01

optimization methodology we introduce. State-of-the-art protein - protein docking approaches start by identifying conformations with good surface /chemical com...side-chains on the interface ). The protein - protein docking literature (e.g., [8] and the references therein) is predominantly treating the docking...mations by various measures of surface complementarity which can be efficiently computed using fast Fourier correlation tech- niques (FFTs). However, when

Protein-Protein Docking in Drug Design and Discovery.

PubMed

Kaczor, Agnieszka A; Bartuzi, Damian; Stępniewski, Tomasz Maciej; Matosiuk, Dariusz; Selent, Jana

2018-01-01

Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

Human and server docking prediction for CAPRI round 30-35 using LZerD with combined scoring functions.

PubMed

Peterson, Lenna X; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2017-03-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues' spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, that is whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. Proteins 2017; 85:513-527. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Human and Server Docking Prediction for CAPRI Round 30–35 Using LZerD with Combined Scoring Functions

PubMed Central

Peterson, Lenna X.; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2016-01-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues’ spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, i.e. whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. PMID:27654025

Influence of protonation, tautomeric, and stereoisomeric states on protein-ligand docking results.

PubMed

ten Brink, Tim; Exner, Thomas E

2009-06-01

In this work, we present a systematical investigation of the influence of ligand protonation states, stereoisomers, and tautomers on results obtained with the two protein-ligand docking programs GOLD and PLANTS. These different states were generated with a fully automated tool, called SPORES (Structure PrOtonation and Recognition System). First, the most probable protonations, as defined by this rule based system, were compared to the ones stored in the well-known, manually revised CCDC/ASTEX data set. Then, to investigate the influence of the ligand protonation state on the docking results, different protonation states were created. Redocking and virtual screening experiments were conducted demonstrating that both docking programs have problems in identifying the correct protomer for each complex. Therefore, a preselection of plausible protomers or the improvement of the scoring functions concerning their ability to rank different molecules/states is needed. Additionally, ligand stereoisomers were tested for a subset of the CCDC/ASTEX set, showing similar problems regarding the ranking of these stereoisomers as the ranking of the protomers.

wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model

PubMed Central

De Paris, Renata; Frantz, Fábio A.; Norberto de Souza, Osmar; Ruiz, Duncan D. A.

2013-01-01

Molecular docking simulations of fully flexible protein receptor (FFR) models are coming of age. In our studies, an FFR model is represented by a series of different conformations derived from a molecular dynamic simulation trajectory of the receptor. For each conformation in the FFR model, a docking simulation is executed and analyzed. An important challenge is to perform virtual screening of millions of ligands using an FFR model in a sequential mode since it can become computationally very demanding. In this paper, we propose a cloud-based web environment, called web Flexible Receptor Docking Workflow (wFReDoW), which reduces the CPU time in the molecular docking simulations of FFR models to small molecules. It is based on the new workflow data pattern called self-adaptive multiple instances (P-SaMIs) and on a middleware built on Amazon EC2 instances. P-SaMI reduces the number of molecular docking simulations while the middleware speeds up the docking experiments using a High Performance Computing (HPC) environment on the cloud. The experimental results show a reduction in the total elapsed time of docking experiments and the quality of the new reduced receptor models produced by discarding the nonpromising conformations from an FFR model ruled by the P-SaMI data pattern. PMID:23691504

Modeling complexes of modeled proteins.

PubMed

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.

CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site.

PubMed

Kurcinski, Mateusz; Jamroz, Michal; Blaszczyk, Maciej; Kolinski, Andrzej; Kmiecik, Sebastian

2015-07-01

Protein-peptide interactions play a key role in cell functions. Their structural characterization, though challenging, is important for the discovery of new drugs. The CABS-dock web server provides an interface for modeling protein-peptide interactions using a highly efficient protocol for the flexible docking of peptides to proteins. While other docking algorithms require pre-defined localization of the binding site, CABS-dock does not require such knowledge. Given a protein receptor structure and a peptide sequence (and starting from random conformations and positions of the peptide), CABS-dock performs simulation search for the binding site allowing for full flexibility of the peptide and small fluctuations of the receptor backbone. This protocol was extensively tested over the largest dataset of non-redundant protein-peptide interactions available to date (including bound and unbound docking cases). For over 80% of bound and unbound dataset cases, we obtained models with high or medium accuracy (sufficient for practical applications). Additionally, as optional features, CABS-dock can exclude user-selected binding modes from docking search or to increase the level of flexibility for chosen receptor fragments. CABS-dock is freely available as a web server at http://biocomp.chem.uw.edu.pl/CABSdock. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking.

PubMed

Heo, Lim; Lee, Hasup; Seok, Chaok

2016-08-18

Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex.

iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian

2011-06-01

The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.

iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan.

PubMed

Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian

2011-06-01

The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.

GPU.proton.DOCK: Genuine Protein Ultrafast proton equilibria consistent DOCKing.

PubMed

Kantardjiev, Alexander A

2011-07-01

GPU.proton.DOCK (Genuine Protein Ultrafast proton equilibria consistent DOCKing) is a state of the art service for in silico prediction of protein-protein interactions via rigorous and ultrafast docking code. It is unique in providing stringent account of electrostatic interactions self-consistency and proton equilibria mutual effects of docking partners. GPU.proton.DOCK is the first server offering such a crucial supplement to protein docking algorithms--a step toward more reliable and high accuracy docking results. The code (especially the Fast Fourier Transform bottleneck and electrostatic fields computation) is parallelized to run on a GPU supercomputer. The high performance will be of use for large-scale structural bioinformatics and systems biology projects, thus bridging physics of the interactions with analysis of molecular networks. We propose workflows for exploring in silico charge mutagenesis effects. Special emphasis is given to the interface-intuitive and user-friendly. The input is comprised of the atomic coordinate files in PDB format. The advanced user is provided with a special input section for addition of non-polypeptide charges, extra ionogenic groups with intrinsic pK(a) values or fixed ions. The output is comprised of docked complexes in PDB format as well as interactive visualization in a molecular viewer. GPU.proton.DOCK server can be accessed at http://gpudock.orgchm.bas.bg/.

DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.

PubMed

Xue, Li C; Jordan, Rafael A; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-02-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner-specific sequence homology-based protein-protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. Copyright © 2013 Wiley Periodicals, Inc.

ConsDock: A new program for the consensus analysis of protein-ligand interactions.

PubMed

Paul, Nicodème; Rognan, Didier

2002-06-01

Protein-based virtual screening of chemical libraries is a powerful technique for identifying new molecules that may interact with a macromolecular target of interest. Because of docking and scoring limitations, it is more difficult to apply as a lead optimization method because it requires that the docking/scoring tool is able to propose as few solutions as possible and all of them with a very good accuracy for both the protein-bound orientation and the conformation of the ligand. In the present study, we present a consensus docking approach (ConsDock) that takes advantage of three widely used docking tools (Dock, FlexX, and Gold). The consensus analysis of all possible poses generated by several docking tools is performed sequentially in four steps: (i) hierarchical clustering of all poses generated by a docking tool into families represented by a leader; (ii) definition of all consensus pairs from leaders generated by different docking programs; (iii) clustering of consensus pairs into classes, represented by a mean structure; and (iv) ranking the different means starting from the most populated class of consensus pairs. When applied to a test set of 100 protein-ligand complexes from the Protein Data Bank, ConsDock significantly outperforms single docking with respect to the docking accuracy of the top-ranked pose. In 60% of the cases investigated here, ConsDock was able to rank as top solution a pose within 2 A RMSD of the X-ray structure. It can be applied as a postprocessing filter to either single- or multiple-docking programs to prioritize three-dimensional guided lead optimization from the most likely docking solution. Copyright 2002 Wiley-Liss, Inc.

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.

PubMed

Sable, Rushikesh; Jois, Seetharama

2015-06-23

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

Evaluation of the novel algorithm of flexible ligand docking with moveable target-protein atoms.

PubMed

Sulimov, Alexey V; Zheltkov, Dmitry A; Oferkin, Igor V; Kutov, Danil C; Katkova, Ekaterina V; Tyrtyshnikov, Eugene E; Sulimov, Vladimir B

2017-01-01

We present the novel docking algorithm based on the Tensor Train decomposition and the TT-Cross global optimization. The algorithm is applied to the docking problem with flexible ligand and moveable protein atoms. The energy of the protein-ligand complex is calculated in the frame of the MMFF94 force field in vacuum. The grid of precalculated energy potentials of probe ligand atoms in the field of the target protein atoms is not used. The energy of the protein-ligand complex for any given configuration is computed directly with the MMFF94 force field without any fitting parameters. The conformation space of the system coordinates is formed by translations and rotations of the ligand as a whole, by the ligand torsions and also by Cartesian coordinates of the selected target protein atoms. Mobility of protein and ligand atoms is taken into account in the docking process simultaneously and equally. The algorithm is realized in the novel parallel docking SOL-P program and results of its performance for a set of 30 protein-ligand complexes are presented. Dependence of the docking positioning accuracy is investigated as a function of parameters of the docking algorithm and the number of protein moveable atoms. It is shown that mobility of the protein atoms improves docking positioning accuracy. The SOL-P program is able to perform docking of a flexible ligand into the active site of the target protein with several dozens of protein moveable atoms: the native crystallized ligand pose is correctly found as the global energy minimum in the search space with 157 dimensions using 4700 CPU ∗ h at the Lomonosov supercomputer.

Docking simulations and in vitro assay unveil potent inhibitory action of papaverine against protein tyrosine phosphatase 1B.

PubMed

Bustanji, Yasser; Taha, Mutasem Omar; Al-Masri, Ihab Mustafa; Mohammad, Mohammad Khalil

2009-04-01

The structural similarity between papaverine and berberine, a known inhibitor of human protein tyrosine phosphatase 1B (h-PTP 1B), prompted us to investigate the potential of papaverine as h-PTP 1B inhibitor. The investigation included simulated docking experiments to fit papaverine into the binding pocket of h-PTP 1B. Papaverine was found to readily dock within the binding pocket of h-PTP 1B in a low energy orientation via an optimal set of attractive interactions. Experimentally, papaverine illustrated potent in vitro inhibitory effect against recombinant h-PTP 1B (IC(50)=1.20 microM). In vivo, papaverine significantly decreased fasting blood glucose level of Balb/c mice. Our findings should encourage screening of other natural alkaloids for possible anti-h-PTP 1B activities.

AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking.

PubMed

Uehara, Shota; Tanaka, Shigenori

2016-11-23

Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters in the bulk region. The binding of a ligand to a protein causes a displacement of these waters from an active site to bulk, and this displacement process substantially contributes to the free energy change of protein-ligand binding. The free energy of active-site water molecules can be calculated by grid inhomogeneous solvation theory (GIST), using molecular dynamics (MD) and the trajectory of a target protein and water molecules. Here, we show a case study of the combination of GIST and a docking program and discuss the effectiveness of the displacing gain of unfavorable water in protein-ligand docking. We combined the GIST-based desolvation function with the scoring function of AutoDock4, which is called AutoDock-GIST. The proposed scoring function was assessed employing 51 ligands of coagulation factor Xa (FXa), and results showed that both scoring accuracy and docking success rate were improved. We also evaluated virtual screening performance of AutoDock-GIST using FXa ligands in the directory of useful decoys-enhanced (DUD-E), thus finding that the displacing gain of unfavorable water is effective for a successful docking campaign.

Discovery of Klotho peptide antagonists against Wnt3 and Wnt3a target proteins using combination of protein engineering, protein-protein docking, peptide docking and molecular dynamics simulations.

PubMed

Mirza, Shaher Bano; Ekhteiari Salmas, Ramin; Fatmi, M Qaiser; Durdagi, Serdar

2017-12-01

The Klotho is known as lifespan enhancing protein involved in antagonizing the effect of Wnt proteins. Wnt proteins are stem cell regulators, and uninterrupted exposure of Wnt proteins to the cell can cause stem and progenitor cell senescence, which may lead to aging. Keeping in mind the importance of Klotho in Wnt signaling, in silico approaches have been applied to study the important interactions between Klotho and Wnt3 and Wnt3a (wingless-type mouse mammary tumor virus (MMTV) integration site family members 3 and 3a). The main aim of the study is to identify important residues of the Klotho that help in designing peptides which can act as Wnt antagonists. For this aim, a protein engineering study is performed for Klotho, Wnt3 and Wnt3a. During the theoretical analysis of homology models, unexpected role of number of disulfide bonds and secondary structure elements has been witnessed in case of Wnt3 and Wnt3a proteins. Different in silico experiments were carried out to observe the effect of correct number of disulfide bonds on 3D protein models. For this aim, total of 10 molecular dynamics (MD) simulations were carried out for each system. Based on the protein-protein docking simulations of selected protein models of Klotho with Wnt3 and Wnt3a, different peptides derived from Klotho have been designed. Wnt3 and Wnt3a proteins have three important domains: Index finger, N-terminal domain and a patch of ∼10 residues on the solvent exposed surface of palm domain. Protein-peptide docking of designed peptides of Klotho against three important domains of palmitoylated Wnt3 and Wnt3a yields encouraging results and leads better understanding of the Wnt protein inhibition by proposed Klotho peptides. Further in vitro studies can be carried out to verify effects of novel designed peptides as Wnt antagonists.

Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein-Protein Encounters.

PubMed

Pallara, Chiara; Rueda, Manuel; Abagyan, Ruben; Fernández-Recio, Juan

2016-07-12

To understand cellular processes at the molecular level we need to improve our knowledge of protein-protein interactions, from a structural, mechanistic, and energetic point of view. Current theoretical studies and computational docking simulations show that protein dynamics plays a key role in protein association and support the need for including protein flexibility in modeling protein interactions. Assuming the conformational selection binding mechanism, in which the unbound state can sample bound conformers, one possible strategy to include flexibility in docking predictions would be the use of conformational ensembles originated from unbound protein structures. Here we present an exhaustive computational study about the use of precomputed unbound ensembles in the context of protein docking, performed on a set of 124 cases of the Protein-Protein Docking Benchmark 3.0. Conformational ensembles were generated by conformational optimization and refinement with MODELLER and by short molecular dynamics trajectories with AMBER. We identified those conformers providing optimal binding and investigated the role of protein conformational heterogeneity in protein-protein recognition. Our results show that a restricted conformational refinement can generate conformers with better binding properties and improve docking encounters in medium-flexible cases. For more flexible cases, a more extended conformational sampling based on Normal Mode Analysis was proven helpful. We found that successful conformers provide better energetic complementarity to the docking partners, which is compatible with recent views of binding association. In addition to the mechanistic considerations, these findings could be exploited for practical docking predictions of improved efficiency.

HSYMDOCK: a docking web server for predicting the structure of protein homo-oligomers with Cn or Dn symmetry.

PubMed

Yan, Yumeng; Tao, Huanyu; Huang, Sheng-You

2018-05-26

A major subclass of protein-protein interactions is formed by homo-oligomers with certain symmetry. Therefore, computational modeling of the symmetric protein complexes is important for understanding the molecular mechanism of related biological processes. Although several symmetric docking algorithms have been developed for Cn symmetry, few docking servers have been proposed for Dn symmetry. Here, we present HSYMDOCK, a web server of our hierarchical symmetric docking algorithm that supports both Cn and Dn symmetry. The HSYMDOCK server was extensively evaluated on three benchmarks of symmetric protein complexes, including the 20 CASP11-CAPRI30 homo-oligomer targets, the symmetric docking benchmark of 213 Cn targets and 35 Dn targets, and a nonredundant test set of 55 transmembrane proteins. It was shown that HSYMDOCK obtained a significantly better performance than other similar docking algorithms. The server supports both sequence and structure inputs for the monomer/subunit. Users have an option to provide the symmetry type of the complex, or the server can predict the symmetry type automatically. The docking process is fast and on average consumes 10∼20 min for a docking job. The HSYMDOCK web server is available at http://huanglab.phys.hust.edu.cn/hsymdock/.

CPdock: the complementarity plot for docking of proteins: implementing multi-dielectric continuum electrostatics.

PubMed

Basu, Sankar

2017-12-07

The complementarity plot (CP) is an established validation tool for protein structures, applicable to both globular proteins (folding) as well as protein-protein complexes (binding). It computes the shape and electrostatic complementarities (S m , E m ) for amino acid side-chains buried within the protein interior or interface and plots them in a two-dimensional plot having knowledge-based probabilistic quality estimates for the residues as well as for the whole structure. The current report essentially presents an upgraded version of the plot with the implementation of the advanced multi-dielectric functionality (as in Delphi version 6.2 or higher) in the computation of electrostatic complementarity to make the validation tool physico-chemically more realistic. The two methods (single- and multi-dielectric) agree decently in their resultant E m values, and hence, provisions for both methods have been kept in the software suite. So to speak, the global electrostatic balance within a well-folded protein and/or a well-packed interface seems only marginally perturbed by the choice of different internal dielectric values. However, both from theoretical as well as practical grounds, the more advanced multi-dielectric version of the plot is certainly recommended for potentially producing more reliable results. The report also presents a new methodology and a variant plot, namely CP dock , based on the same principles of complementarity specifically designed to be used in the docking of proteins. The efficacy of the method to discriminate between good and bad docked protein complexes has been tested on a recent state-of-the-art docking benchmark. The results unambiguously indicate that CP dock can indeed be effective in the initial screening phase of a docking scoring pipeline before going into more sophisticated and computationally expensive scoring functions. CP dock has been made available at https://github.com/nemo8130/CPdock . Graphical Abstract An example showing the efficacy of CP dock to be used in the initial screening phase of a protein-protein docking scoring pipeline.

Modeling of protein binary complexes using structural mass spectrometry data

PubMed Central

Kamal, J.K. Amisha; Chance, Mark R.

2008-01-01

In this article, we describe a general approach to modeling the structure of binary protein complexes using structural mass spectrometry data combined with molecular docking. In the first step, hydroxyl radical mediated oxidative protein footprinting is used to identify residues that experience conformational reorganization due to binding or participate in the binding interface. In the second step, a three-dimensional atomic structure of the complex is derived by computational modeling. Homology modeling approaches are used to define the structures of the individual proteins if footprinting detects significant conformational reorganization as a function of complex formation. A three-dimensional model of the complex is constructed from these binary partners using the ClusPro program, which is composed of docking, energy filtering, and clustering steps. Footprinting data are used to incorporate constraints—positive and/or negative—in the docking step and are also used to decide the type of energy filter—electrostatics or desolvation—in the successive energy-filtering step. By using this approach, we examine the structure of a number of binary complexes of monomeric actin and compare the results to crystallographic data. Based on docking alone, a number of competing models with widely varying structures are observed, one of which is likely to agree with crystallographic data. When the docking steps are guided by footprinting data, accurate models emerge as top scoring. We demonstrate this method with the actin/gelsolin segment-1 complex. We also provide a structural model for the actin/cofilin complex using this approach which does not have a crystal or NMR structure. PMID:18042684

GENIUS In Silico Screening Technology for HCV Drug Discovery.

PubMed

Patil, Vaishali M; Masand, Neeraj; Gupta, Satya P

2016-01-01

The various reported in silico screening protocols such as molecular docking are associated with various drawbacks as well as benefits. In molecular docking, on interaction with ligand, the protein or receptor molecule gets activated by adopting conformational changes. These conformational changes cannot be utilized to predict the 3D structure of a protein-ligand complex from unbound protein conformations rigid docking, which necessitates the demand for understanding protein flexibility. Therefore, efficiency and accuracy of docking should be achieved and various available/developed protocols may be adopted. One such protocol is GENIUS induced-fit docking and it is used effectively for the development of anti-HCV NS3-4A serine protease inhibitors. The present review elaborates the GENIUS docking protocol along with its benefits and drawbacks.

A scalable and accurate method for classifying protein-ligand binding geometries using a MapReduce approach.

PubMed

Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M

2012-07-01

We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking. Copyright © 2012 Elsevier Ltd. All rights reserved.

Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening

NASA Astrophysics Data System (ADS)

Zavodszky, Maria I.; Sanschagrin, Paul C.; Kuhn, Leslie A.; Korde, Rajesh S.

2002-12-01

For the successful identification and docking of new ligands to a protein target by virtual screening, the essential features of the protein and ligand surfaces must be captured and distilled in an efficient representation. Since the running time for docking increases exponentially with the number of points representing the protein and each ligand candidate, it is important to place these points where the best interactions can be made between the protein and the ligand. This definition of favorable points of interaction can also guide protein structure-based ligand design, which typically focuses on which chemical groups provide the most energetically favorable contacts. In this paper, we present an alternative method of protein template and ligand interaction point design that identifies the most favorable points for making hydrophobic and hydrogen-bond interactions by using a knowledge base. The knowledge-based protein and ligand representations have been incorporated in version 2.0 of SLIDE and resulted in dockings closer to the crystal structure orientations when screening a set of 57 known thrombin and glutathione S-transferase (GST) ligands against the apo structures of these proteins. There was also improved scoring enrichment of the dockings, meaning better differentiation between the chemically diverse known ligands and a ˜15,000-molecule dataset of randomly-chosen small organic molecules. This approach for identifying the most important points of interaction between proteins and their ligands can equally well be used in other docking and design techniques. While much recent effort has focused on improving scoring functions for protein-ligand docking, our results indicate that improving the representation of the chemistry of proteins and their ligands is another avenue that can lead to significant improvements in the identification, docking, and scoring of ligands.

Optimization of protein-protein docking for predicting Fc-protein interactions.

PubMed

Agostino, Mark; Mancera, Ricardo L; Ramsland, Paul A; Fernández-Recio, Juan

2016-11-01

The antibody crystallizable fragment (Fc) is recognized by effector proteins as part of the immune system. Pathogens produce proteins that bind Fc in order to subvert or evade the immune response. The structural characterization of the determinants of Fc-protein association is essential to improve our understanding of the immune system at the molecular level and to develop new therapeutic agents. Furthermore, Fc-binding peptides and proteins are frequently used to purify therapeutic antibodies. Although several structures of Fc-protein complexes are available, numerous others have not yet been determined. Protein-protein docking could be used to investigate Fc-protein complexes; however, improved approaches are necessary to efficiently model such cases. In this study, a docking-based structural bioinformatics approach is developed for predicting the structures of Fc-protein complexes. Based on the available set of X-ray structures of Fc-protein complexes, three regions of the Fc, loosely corresponding to three turns within the structure, were defined as containing the essential features for protein recognition and used as restraints to filter the initial docking search. Rescoring the filtered poses with an optimal scoring strategy provided a success rate of approximately 80% of the test cases examined within the top ranked 20 poses, compared to approximately 20% by the initial unrestrained docking. The developed docking protocol provides a significant improvement over the initial unrestrained docking and will be valuable for predicting the structures of currently undetermined Fc-protein complexes, as well as in the design of peptides and proteins that target Fc. Copyright © 2016 John Wiley & Sons, Ltd.

Template-based protein-protein docking exploiting pairwise interfacial residue restraints.

PubMed

Xue, Li C; Rodrigues, João P G L M; Dobbs, Drena; Honavar, Vasant; Bonvin, Alexandre M J J

2017-05-01

Although many advanced and sophisticated ab initio approaches for modeling protein-protein complexes have been proposed in past decades, template-based modeling (TBM) remains the most accurate and widely used approach, given a reliable template is available. However, there are many different ways to exploit template information in the modeling process. Here, we systematically evaluate and benchmark a TBM method that uses conserved interfacial residue pairs as docking distance restraints [referred to as alpha carbon-alpha carbon (CA-CA)-guided docking]. We compare it with two other template-based protein-protein modeling approaches, including a conserved non-pairwise interfacial residue restrained docking approach [referred to as the ambiguous interaction restraint (AIR)-guided docking] and a simple superposition-based modeling approach. Our results show that, for most cases, the CA-CA-guided docking method outperforms both superposition with refinement and the AIR-guided docking method. We emphasize the superiority of the CA-CA-guided docking on cases with medium to large conformational changes, and interactions mediated through loops, tails or disordered regions. Our results also underscore the importance of a proper refinement of superimposition models to reduce steric clashes. In summary, we provide a benchmarked TBM protocol that uses conserved pairwise interface distance as restraints in generating realistic 3D protein-protein interaction models, when reliable templates are available. The described CA-CA-guided docking protocol is based on the HADDOCK platform, which allows users to incorporate additional prior knowledge of the target system to further improve the quality of the resulting models. © The Author 2016. Published by Oxford University Press.

DockQ: A Quality Measure for Protein-Protein Docking Models

PubMed Central

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 (<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 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

Discover binding pathways using the sliding binding-box docking approach: application to binding pathways of oseltamivir to avian influenza H5N1 neuraminidase

NASA Astrophysics Data System (ADS)

Tran, Diem-Trang T.; Le, Ly T.; Truong, Thanh N.

2013-08-01

Drug binding and unbinding are transient processes which are hardly observed by experiment and difficult to analyze by computational techniques. In this paper, we employed a cost-effective method called "pathway docking" in which molecular docking was used to screen ligand-receptor binding free energy surface to reveal possible paths of ligand approaching protein binding pocket. A case study was applied on oseltamivir, the key drug against influenza a virus. The equilibrium pathways identified by this method are found to be similar to those identified in prior studies using highly expensive computational approaches.

Protein-ligand docking using fitness learning-based artificial bee colony with proximity stimuli.

PubMed

Uehara, Shota; Fujimoto, Kazuhiro J; Tanaka, Shigenori

2015-07-07

Protein-ligand docking is an optimization problem, which aims to identify the binding pose of a ligand with the lowest energy in the active site of a target protein. In this study, we employed a novel optimization algorithm called fitness learning-based artificial bee colony with proximity stimuli (FlABCps) for docking. Simulation results revealed that FlABCps improved the success rate of docking, compared to four state-of-the-art algorithms. The present results also showed superior docking performance of FlABCps, in particular for dealing with highly flexible ligands and proteins with a wide and shallow binding pocket.

Identifying Potential Protein Targets for Toluene Using a Molecular Similarity Search, in Silico Docking and in Vitro Validation

DTIC Science & Technology

2015-01-01

the Protein Data Bank (http://www.rcsb.org/ pdb /). These structures are the most accurate and can be used for molecular docking. Target flexibility is...crystallized with the different ligands. In total, 240 files with the structures of 37 proteins were downloaded from PDB and used for docking...total, 240 files with protein structures were downloaded from the PDB and used for protein–ligand docking. It is widely accepted that ligand binding

DockoMatic 2.0: high throughput inverse virtual screening and homology modeling.

PubMed

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T; McDougal, Owen M; Andersen, Timothy L

2013-08-26

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly graphical user interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to (1) conduct high throughput inverse virtual screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELER programs and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education.

Predicting bioactive conformations and binding modes of macrocycles

NASA Astrophysics Data System (ADS)

Anighoro, Andrew; de la Vega de León, Antonio; Bajorath, Jürgen

2016-10-01

Macrocyclic compounds experience increasing interest in drug discovery. It is often thought that these large and chemically complex molecules provide promising candidates to address difficult targets and interfere with protein-protein interactions. From a computational viewpoint, these molecules are difficult to treat. For example, flexible docking of macrocyclic compounds is hindered by the limited ability of current docking approaches to optimize conformations of extended ring systems for pose prediction. Herein, we report predictions of bioactive conformations of macrocycles using conformational search and binding modes using docking. Conformational ensembles generated using specialized search technique of about 70 % of the tested macrocycles contained accurate bioactive conformations. However, these conformations were difficult to identify on the basis of conformational energies. Moreover, docking calculations with limited ligand flexibility starting from individual low energy conformations rarely yielded highly accurate binding modes. In about 40 % of the test cases, binding modes were approximated with reasonable accuracy. However, when conformational ensembles were subjected to rigid body docking, an increase in meaningful binding mode predictions to more than 50 % of the test cases was observed. Electrostatic effects did not contribute to these predictions in a positive or negative manner. Rather, achieving shape complementarity at macrocycle-target interfaces was a decisive factor. In summary, a combined computational protocol using pre-computed conformational ensembles of macrocycles as a starting point for docking shows promise in modeling binding modes of macrocyclic compounds.

HDOCK: a web server for protein–protein and protein–DNA/RNA docking based on a hybrid strategy

PubMed Central

Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong

2017-01-01

Abstract Protein–protein and protein–DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein–protein and protein–DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10–20 min for a docking run. Tested on the cases with weakly homologous complexes of <30% sequence identity from five docking benchmarks, the HDOCK pipeline tied with template-based modeling on the protein–protein and protein–DNA benchmarks and performed better than template-based modeling on the three protein–RNA benchmarks when the top 10 predictions were considered. The performance of HDOCK became better when more predictions were considered. Combining the results of HDOCK and template-based modeling by ranking first of the template-based model further improved the predictive power of the server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. PMID:28521030

Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM

PubMed Central

Gagnon, Jessica K.; Law, Sean M.; Brooks, Charles L.

2016-01-01

Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an inter-converting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs. PMID:26691274

Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM.

PubMed

Gagnon, Jessica K; Law, Sean M; Brooks, Charles L

2016-03-30

Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an interconverting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs. © 2015 Wiley Periodicals, Inc.

PaFlexPepDock: parallel ab-initio docking of peptides onto their receptors with full flexibility based on Rosetta.

PubMed

Li, Haiou; Lu, Liyao; Chen, Rong; Quan, Lijun; Xia, Xiaoyan; Lü, Qiang

2014-01-01

Structural information related to protein-peptide complexes can be very useful for novel drug discovery and design. The computational docking of protein and peptide can supplement the structural information available on protein-peptide interactions explored by experimental ways. Protein-peptide docking of this paper can be described as three processes that occur in parallel: ab-initio peptide folding, peptide docking with its receptor, and refinement of some flexible areas of the receptor as the peptide is approaching. Several existing methods have been used to sample the degrees of freedom in the three processes, which are usually triggered in an organized sequential scheme. In this paper, we proposed a parallel approach that combines all the three processes during the docking of a folding peptide with a flexible receptor. This approach mimics the actual protein-peptide docking process in parallel way, and is expected to deliver better performance than sequential approaches. We used 22 unbound protein-peptide docking examples to evaluate our method. Our analysis of the results showed that the explicit refinement of the flexible areas of the receptor facilitated more accurate modeling of the interfaces of the complexes, while combining all of the moves in parallel helped the constructing of energy funnels for predictions.

InterEvDock: a docking server to predict the structure of protein–protein interactions using evolutionary information

PubMed Central

Yu, Jinchao; Vavrusa, Marek; Andreani, Jessica; Rey, Julien; Tufféry, Pierre; Guerois, Raphaël

2016-01-01

The structural modeling of protein–protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigid-body docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock/. PMID:27131368

AnchorDock for Blind Flexible Docking of Peptides to Proteins.

PubMed

Slutzki, Michal; Ben-Shimon, Avraham; Niv, Masha Y

2017-01-01

Due to increasing interest in peptides as signaling modulators and drug candidates, several methods for peptide docking to their target proteins are under active development. The "blind" docking problem, where the peptide-binding site on the protein surface is unknown, presents one of the current challenges in the field. AnchorDock protocol was developed by Ben-Shimon and Niv to address this challenge.This protocol narrows the docking search to the most relevant parts of the conformational space. This is achieved by pre-folding the free peptide and by computationally detecting anchoring spots on the surface of the unbound protein. Multiple flexible simulated annealing molecular dynamics (SAMD) simulations are subsequently carried out, starting from pre-folded peptide conformations, constrained to the various precomputed anchoring spots.Here, AnchorDock is demonstrated using two known protein-peptide complexes. A PDZ-peptide complex provides a relatively easy case due to the relatively small size of the protein, and a typical peptide conformation and binding region; a more challenging example is a complex between USP7 N-term and a p53-derived peptide, where the protein is larger, and the peptide conformation and a binding site are generally assumed to be unknown. AnchorDock returned native-like solutions ranked first and third for the PDZ and USP7 complexes, respectively. We describe the procedure step by step and discuss possible modifications where applicable.

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

PubMed

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.

Small-molecule ligand docking into comparative models with Rosetta

PubMed Central

Combs, Steven A; DeLuca, Samuel L; DeLuca, Stephanie H; Lemmon, Gordon H; Nannemann, David P; Nguyen, Elizabeth D; Willis, Jordan R; Sheehan, Jonathan H; Meiler, Jens

2017-01-01

Structure-based drug design is frequently used to accelerate the development of small-molecule therapeutics. Although substantial progress has been made in X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, the availability of high-resolution structures is limited owing to the frequent inability to crystallize or obtain sufficient NMR restraints for large or flexible proteins. Computational methods can be used to both predict unknown protein structures and model ligand interactions when experimental data are unavailable. This paper describes a comprehensive and detailed protocol using the Rosetta modeling suite to dock small-molecule ligands into comparative models. In the protocol presented here, we review the comparative modeling process, including sequence alignment, threading and loop building. Next, we cover docking a small-molecule ligand into the protein comparative model. In addition, we discuss criteria that can improve ligand docking into comparative models. Finally, and importantly, we present a strategy for assessing model quality. The entire protocol is presented on a single example selected solely for didactic purposes. The results are therefore not representative and do not replace benchmarks published elsewhere. We also provide an additional tutorial so that the user can gain hands-on experience in using Rosetta. The protocol should take 5–7 h, with additional time allocated for computer generation of models. PMID:23744289

DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction

PubMed Central

Xue, Li C.; Jordan, Rafael A.; EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2015-01-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. Dock-Rank uses interface residues predicted by partner-specific sequence homology-based protein–protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. PMID:23873600

Quantum.Ligand.Dock: protein-ligand docking with quantum entanglement refinement on a GPU system.

PubMed

Kantardjiev, Alexander A

2012-07-01

Quantum.Ligand.Dock (protein-ligand docking with graphic processing unit (GPU) quantum entanglement refinement on a GPU system) is an original modern method for in silico prediction of protein-ligand interactions via high-performance docking code. The main flavour of our approach is a combination of fast search with a special account for overlooked physical interactions. On the one hand, we take care of self-consistency and proton equilibria mutual effects of docking partners. On the other hand, Quantum.Ligand.Dock is the the only docking server offering such a subtle supplement to protein docking algorithms as quantum entanglement contributions. The motivation for development and proposition of the method to the community hinges upon two arguments-the fundamental importance of quantum entanglement contribution in molecular interaction and the realistic possibility to implement it by the availability of supercomputing power. The implementation of sophisticated quantum methods is made possible by parallelization at several bottlenecks on a GPU supercomputer. The high-performance implementation will be of use for large-scale virtual screening projects, structural bioinformatics, systems biology and fundamental research in understanding protein-ligand recognition. The design of the interface is focused on feasibility and ease of use. Protein and ligand molecule structures are supposed to be submitted as atomic coordinate files in PDB format. A customization section is offered for addition of user-specified charges, extra ionogenic groups with intrinsic pK(a) values or fixed ions. Final predicted complexes are ranked according to obtained scores and provided in PDB format as well as interactive visualization in a molecular viewer. Quantum.Ligand.Dock server can be accessed at http://87.116.85.141/LigandDock.html.

Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Kadukova, Maria; Grudinin, Sergei

2018-01-01

The 2016 D3R Grand Challenge 2 provided an opportunity to test multiple protein-ligand docking protocols on a set of ligands bound to farnesoid X receptor that has many available experimental structures. We participated in the Stage 1 of the Challenge devoted to the docking pose predictions, with the mean RMSD value of our submission poses of 2.9 Å. Here we present a thorough analysis of our docking predictions made with AutoDock Vina and the Convex-PL rescoring potential by reproducing our submission protocol and running a series of additional molecular docking experiments. We conclude that a correct receptor structure, or more precisely, the structure of the binding pocket, plays the crucial role in the success of our docking studies. We have also noticed the important role of a local ligand geometry, which seems to be not well discussed in literature. We succeed to improve our results up to the mean RMSD value of 2.15-2.33 Å dependent on the models of the ligands, if docking these to all available homologous receptors. Overall, for docking of ligands of diverse chemical series we suggest to perform docking of each of the ligands to a set of multiple receptors that are homologous to the target.

Rigid-Docking Approaches to Explore Protein-Protein Interaction Space.

PubMed

Matsuzaki, Yuri; Uchikoga, Nobuyuki; Ohue, Masahito; Akiyama, Yutaka

Protein-protein interactions play core roles in living cells, especially in the regulatory systems. As information on proteins has rapidly accumulated on publicly available databases, much effort has been made to obtain a better picture of protein-protein interaction networks using protein tertiary structure data. Predicting relevant interacting partners from their tertiary structure is a challenging task and computer science methods have the potential to assist with this. Protein-protein rigid docking has been utilized by several projects, docking-based approaches having the advantages that they can suggest binding poses of predicted binding partners which would help in understanding the interaction mechanisms and that comparing docking results of both non-binders and binders can lead to understanding the specificity of protein-protein interactions from structural viewpoints. In this review we focus on explaining current computational prediction methods to predict pairwise direct protein-protein interactions that form protein complexes.

ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.

PubMed

Wang, Nanyi; Wang, Lirong; Xie, Xiang-Qun

2017-11-27

Molecular docking is widely applied to computer-aided drug design and has become relatively mature in the recent decades. Application of docking in modeling varies from single lead compound optimization to large-scale virtual screening. The performance of molecular docking is highly dependent on the protein structures selected. It is especially challenging for large-scale target prediction research when multiple structures are available for a single target. Therefore, we have established ProSelection, a docking preferred-protein selection algorithm, in order to generate the proper structure subset(s). By the ProSelection algorithm, protein structures of "weak selectors" are filtered out whereas structures of "strong selectors" are kept. Specifically, the structure which has a good statistical performance of distinguishing active ligands from inactive ligands is defined as a strong selector. In this study, 249 protein structures of 14 autophagy-related targets are investigated. Surflex-dock was used as the docking engine to distinguish active and inactive compounds against these protein structures. Both t test and Mann-Whitney U test were used to distinguish the strong from the weak selectors based on the normality of the docking score distribution. The suggested docking score threshold for active ligands (SDA) was generated for each strong selector structure according to the receiver operating characteristic (ROC) curve. The performance of ProSelection was further validated by predicting the potential off-targets of 43 U.S. Federal Drug Administration approved small molecule antineoplastic drugs. Overall, ProSelection will accelerate the computational work in protein structure selection and could be a useful tool for molecular docking, target prediction, and protein-chemical database establishment research.

Modulation of interaction of mutant TP53 and wild type BRCA1 by alkaloids: a computational approach towards targeting protein-protein interaction as a futuristic therapeutic intervention strategy for breast cancer impediment.

PubMed

Tiwari, Sameeksha; Awasthi, Manika; Singh, Swati; Pandey, Veda P; Dwivedi, Upendra N

2017-10-23

Protein-protein interactions (PPI) are a new emerging class of novel therapeutic targets. In order to probe these interactions, computational tools provide a convenient and quick method towards the development of therapeutics. Keeping this in view the present study was initiated to analyse interaction of tumour suppressor protein p53 (TP53) and breast cancer associated protein (BRCA1) as promising target against breast cancer. Using computational approaches such as protein-protein docking, hot spot analyses, molecular docking and molecular dynamics simulation (MDS), stepwise analyses of the interactions of the wild type and mutant TP53 with that of wild type BRCA1 and their modulation by alkaloids were done. Protein-protein docking method was used to generate both wild type and mutant complexes of TP53-BRCA1. Subsequently, the complexes were docked using sixteen different alkaloids, fulfilling ADMET and Lipinski's rule of five criteria, and were compared with that of a well-known inhibitor of PPI, namely nutlin. The alkaloid dicentrine was found to be the best docked alkaloid among all the docked alklaloids as well as that of nutlin. Furthermore, MDS analyses of both wild type and mutant complexes with the best docked alkaloid i.e. dicentrine, revealed higher stability of mutant complex than that of the wild one, in terms of average RMSD, RMSF and binding free energy, corroborating the results of docking. Results suggested more pronounced interaction of BRCA1 with mutant TP53 leading to increased expression of mutated TP53 thus showing a dominant negative gain of function and hampering wild type TP53 function leading to tumour progression.

IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking.

PubMed

Su, Chinh; Nguyen, Thuy-Diem; Zheng, Jie; Kwoh, Chee-Keong

2014-01-01

Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations and water contribution is ignored or implicitly presented. Despite obtaining a number of acceptable complex predictions, it seems to-date that most initial rigid docking algorithms still find it difficult or even fail to discriminate successfully the correct predictions from the other incorrect or false positive ones. To improve the rigid docking results, re-ranking is one of the effective methods that help re-locate the correct predictions in top high ranks, discriminating them from the other incorrect ones. Our results showed that the IFACEwat increased both the numbers of the near-native structures and improved their ranks as compared to the initial rigid docking ZDOCK3.0.2. In fact, the IFACEwat achieved a success rate of 83.8% for Antigen/Antibody complexes, which is 10% better than ZDOCK3.0.2. As compared to another re-ranking technique ZRANK, the IFACEwat obtains success rates of 92.3% (8% better) and 90% (5% better) respectively for medium and difficult cases. When comparing with the latest published re-ranking method F2Dock, the IFACEwat performed equivalently well or even better for several Antigen/Antibody complexes. With the inclusion of interfacial water, the IFACEwat improves mostly results of the initial rigid docking, especially for Antigen/Antibody complexes. The improvement is achieved by explicitly taking into account the contribution of water during the protein interactions, which was ignored or not fully presented by the initial rigid docking and other re-ranking techniques. In addition, the IFACEwat maintains sufficient computational efficiency of the initial docking algorithm, yet improves the ranks as well as the number of the near native structures found. As our implementation so far targeted to improve the results of ZDOCK3.0.2, and particularly for the Antigen/Antibody complexes, it is expected in the near future that more implementations will be conducted to be applicable for other initial rigid docking algorithms.

DOCLASP - Docking ligands to target proteins using spatial and electrostatic congruence extracted from a known holoenzyme and applying simple geometrical transformations.

PubMed

Chakraborty, Sandeep

2014-01-01

The ability to accurately and effectively predict the interaction between proteins and small drug-like compounds has long intrigued researchers for pedagogic, humanitarian and economic reasons. Protein docking methods (AutoDock, GOLD, DOCK, FlexX and Glide to name a few) rank a large number of possible conformations of protein-ligand complexes using fast algorithms. Previously, it has been shown that structural congruence leading to the same enzymatic function necessitates the congruence of electrostatic properties (CLASP). The current work presents a methodology for docking a ligand into a target protein, provided that there is at least one known holoenzyme with ligand bound - DOCLASP (Docking using CLASP). The contact points of the ligand in the holoenzyme defines a motif, which is used to query the target enzyme using CLASP. If there are significant matches, the holoenzyme and the target protein are superimposed based on congruent atoms. The same linear and rotational transformations are also applied to the ligand, thus creating a unified coordinate framework having the holoenzyme, the ligand and the target enzyme. In the current work, the dipeptidyl peptidase-IV inhibitor vildagliptin was docked to the PI-PLC structure complexed with myo-inositol using DOCLASP. Also, corroboration of the docking of phenylthiourea to the modelled structure of polyphenol oxidase (JrPPO1) from walnut is provided based on the subsequently solved structure of JrPPO1 (PDBid:5CE9). Analysis of the binding of the antitrypanosomial drug suramin to nine non-homologous proteins in the PDB database shows a diverse set of binding motifs, and multiple binding sites in the phospholipase A2-likeproteins from the Bothrops genus of pitvipers. The conformational changes in the suramin molecule on binding highlights the challenges in docking flexible ligands into an already 'plastic' binding site. Thus, DOCLASP presents a method for 'soft docking' ligands to proteins with low computational requirements.

Building macromolecular assemblies by information-driven docking: introducing the HADDOCK multibody docking server.

PubMed

Karaca, Ezgi; Melquiond, Adrien S J; de Vries, Sjoerd J; Kastritis, Panagiotis L; Bonvin, Alexandre M J J

2010-08-01

Over the last years, large scale proteomics studies have generated a wealth of information of biomolecular complexes. Adding the structural dimension to the resulting interactomes represents a major challenge that classical structural experimental methods alone will have difficulties to confront. To meet this challenge, complementary modeling techniques such as docking are thus needed. Among the current docking methods, HADDOCK (High Ambiguity-Driven DOCKing) distinguishes itself from others by the use of experimental and/or bioinformatics data to drive the modeling process and has shown a strong performance in the critical assessment of prediction of interactions (CAPRI), a blind experiment for the prediction of interactions. Although most docking programs are limited to binary complexes, HADDOCK can deal with multiple molecules (up to six), a capability that will be required to build large macromolecular assemblies. We present here a novel web interface of HADDOCK that allows the user to dock up to six biomolecules simultaneously. This interface allows the inclusion of a large variety of both experimental and/or bioinformatics data and supports several types of cyclic and dihedral symmetries in the docking of multibody assemblies. The server was tested on a benchmark of six cases, containing five symmetric homo-oligomeric protein complexes and one symmetric protein-DNA complex. Our results reveal that, in the presence of either bioinformatics and/or experimental data, HADDOCK shows an excellent performance: in all cases, HADDOCK was able to generate good to high quality solutions and ranked them at the top, demonstrating its ability to model symmetric multicomponent assemblies. Docking methods can thus play an important role in adding the structural dimension to interactomes. However, although the current docking methodologies were successful for a vast range of cases, considering the variety and complexity of macromolecular assemblies, inclusion of some kind of experimental information (e.g. from mass spectrometry, nuclear magnetic resonance, cryoelectron microscopy, etc.) will remain highly desirable to obtain reliable results.

IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking

PubMed Central

2014-01-01

Background Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations and water contribution is ignored or implicitly presented. Despite obtaining a number of acceptable complex predictions, it seems to-date that most initial rigid docking algorithms still find it difficult or even fail to discriminate successfully the correct predictions from the other incorrect or false positive ones. To improve the rigid docking results, re-ranking is one of the effective methods that help re-locate the correct predictions in top high ranks, discriminating them from the other incorrect ones. In this paper, we propose a new re-ranking technique using a new energy-based scoring function, namely IFACEwat - a combined Interface Atomic Contact Energy (IFACE) and water effect. The IFACEwat aims to further improve the discrimination of the near-native structures of the initial rigid docking algorithm ZDOCK3.0.2. Unlike other re-ranking techniques, the IFACEwat explicitly implements interfacial water into the protein interfaces to account for the water-mediated contacts during the protein interactions. Results Our results showed that the IFACEwat increased both the numbers of the near-native structures and improved their ranks as compared to the initial rigid docking ZDOCK3.0.2. In fact, the IFACEwat achieved a success rate of 83.8% for Antigen/Antibody complexes, which is 10% better than ZDOCK3.0.2. As compared to another re-ranking technique ZRANK, the IFACEwat obtains success rates of 92.3% (8% better) and 90% (5% better) respectively for medium and difficult cases. When comparing with the latest published re-ranking method F2Dock, the IFACEwat performed equivalently well or even better for several Antigen/Antibody complexes. Conclusions With the inclusion of interfacial water, the IFACEwat improves mostly results of the initial rigid docking, especially for Antigen/Antibody complexes. The improvement is achieved by explicitly taking into account the contribution of water during the protein interactions, which was ignored or not fully presented by the initial rigid docking and other re-ranking techniques. In addition, the IFACEwat maintains sufficient computational efficiency of the initial docking algorithm, yet improves the ranks as well as the number of the near native structures found. As our implementation so far targeted to improve the results of ZDOCK3.0.2, and particularly for the Antigen/Antibody complexes, it is expected in the near future that more implementations will be conducted to be applicable for other initial rigid docking algorithms. PMID:25521441

Predicting protein interactions by Brownian dynamics simulations.

PubMed

Meng, Xuan-Yu; Xu, Yu; Zhang, Hong-Xing; Mezei, Mihaly; Cui, Meng

2012-01-01

We present a newly adapted Brownian-Dynamics (BD)-based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. In order to reduce the computational costs for energy evaluations, a shell-based grid force field was developed to represent the receptor protein and solvation effects. The performance of this BD protein docking approach has been evaluated on a test set of 24 crystal protein complexes. Reproduction of experimental structures in the test set indicates the adequate conformational sampling and accurate scoring of this BD protein docking approach. Furthermore, we have developed an approach to account for the flexibility of proteins, which has been successfully applied to reproduce the experimental complex structure from the structure of two unbounded proteins. These results indicate that this adapted BD protein docking approach can be useful for the prediction of protein-protein interactions.

DockoMatic 2.0: High Throughput Inverse Virtual Screening and Homology Modeling

PubMed Central

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T.; McDougal, Owen M.; Andersen, Timothy L.

2013-01-01

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly Graphical User Interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to: (1) conduct high throughput Inverse Virtual Screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying a receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories, and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELLER programs, and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education. PMID:23808933

Protein-protein docking on hardware accelerators: comparison of GPU and MIC architectures

PubMed Central

2015-01-01

Background The hardware accelerators will provide solutions to computationally complex problems in bioinformatics fields. However, the effect of acceleration depends on the nature of the application, thus selection of an appropriate accelerator requires some consideration. Results In the present study, we compared the effects of acceleration using graphics processing unit (GPU) and many integrated core (MIC) on the speed of fast Fourier transform (FFT)-based protein-protein docking calculation. The GPU implementation performed the protein-protein docking calculations approximately five times faster than the MIC offload mode implementation. The MIC native mode implementation has the advantage in the implementation costs. However, the performance was worse with larger protein pairs because of memory limitations. Conclusion The results suggest that GPU is more suitable than MIC for accelerating FFT-based protein-protein docking applications. PMID:25707855

GRAMM-X public web server for protein–protein docking

PubMed Central

Tovchigrechko, Andrey; Vakser, Ilya A.

2006-01-01

Protein docking software GRAMM-X and its web interface () extend the original GRAMM Fast Fourier Transformation methodology by employing smoothed potentials, refinement stage, and knowledge-based scoring. The web server frees users from complex installation of database-dependent parallel software and maintaining large hardware resources needed for protein docking simulations. Docking problems submitted to GRAMM-X server are processed by a 320 processor Linux cluster. The server was extensively tested by benchmarking, several months of public use, and participation in the CAPRI server track. PMID:16845016

Text Mining for Protein Docking

PubMed Central

Badal, Varsha D.; Kundrotas, Petras J.; Vakser, Ilya A.

2015-01-01

The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking). Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu). The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features) approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound benchmark set, significantly increasing the docking success rate. PMID:26650466

MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

PubMed Central

Ohue, Masahito; Matsuzaki, Yuri; Uchikoga, Nobuyuki; Ishida, Takashi; Akiyama, Yutaka

2014-01-01

The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure and function and structure-based drug design. However, the development of an effective method to conduct exhaustive PPI screening represents a computational challenge. We have been investigating a protein docking approach based on shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking software package “MEGADOCK” that samples an extremely large number of protein dockings at high speed. MEGADOCK reduces the calculation time required for docking by using several techniques such as a novel scoring function called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231 was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening problem with accuracy better than random. When our approach is combined with parallel high-performance computing systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock. PMID:23855673

Analysis of protein-protein docking decoys using interaction fingerprints: application to the reconstruction of CaM-ligand complexes.

PubMed

Uchikoga, Nobuyuki; Hirokawa, Takatsugu

2010-05-11

Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG), CaM kinase kinase (CaMKK) and the plasma membrane Ca2+ ATPase pump (PMCA), and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.

Application of a post-docking procedure based on MM-PBSA and MM-GBSA on single and multiple protein conformations.

PubMed

Sgobba, Miriam; Caporuscio, Fabiana; Anighoro, Andrew; Portioli, Corinne; Rastelli, Giulio

2012-12-01

In the last decades, molecular docking has emerged as an increasingly useful tool in the modern drug discovery process, but it still needs to overcome many hurdles and limitations such as how to account for protein flexibility and poor scoring function performance. For this reason, it has been recognized that in many cases docking results need to be post-processed to achieve a significant agreement with experimental activities. In this study, we have evaluated the performance of MM-PBSA and MM-GBSA scoring functions, implemented in our post-docking procedure BEAR, in rescoring docking solutions. For the first time, the performance of this post-docking procedure has been evaluated on six different biological targets (namely estrogen receptor, thymidine kinase, factor Xa, adenosine deaminase, aldose reductase, and enoyl ACP reductase) by using i) both a single and a multiple protein conformation approach, and ii) two different software, namely AutoDock and LibDock. The assessment has been based on two of the most important criteria for the evaluation of docking methods, i.e., the ability of known ligands to enrich the top positions of a ranked database with respect to molecular decoys, and the consistency of the docking poses with crystallographic binding modes. We found that, in many cases, MM-PBSA and MM-GBSA are able to yield higher enrichment factors compared to those obtained with the docking scoring functions alone. However, for only a minority of the cases, the enrichment factors obtained by using multiple protein conformations were higher than those obtained by using only one protein conformation. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Molecular docking.

PubMed

Morris, Garrett M; Lim-Wilby, Marguerita

2008-01-01

Molecular docking is a key tool in structural molecular biology and computer-assisted drug design. The goal of ligand-protein docking is to predict the predominant binding mode(s) of a ligand with a protein of known three-dimensional structure. Successful docking methods search high-dimensional spaces effectively and use a scoring function that correctly ranks candidate dockings. Docking can be used to perform virtual screening on large libraries of compounds, rank the results, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. The setting up of the input structures for the docking is just as important as the docking itself, and analyzing the results of stochastic search methods can sometimes be unclear. This chapter discusses the background and theory of molecular docking software, and covers the usage of some of the most-cited docking software.

PEPSI-Dock: a detailed data-driven protein-protein interaction potential accelerated by polar Fourier correlation.

PubMed

Neveu, Emilie; Ritchie, David W; Popov, Petr; Grudinin, Sergei

2016-09-01

Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expansion of Protein Structures and Interactions for Docking (PEPSI-Dock) improves the accuracy of the first stage of the docking pipeline, which will sharpen up the final predictions. Indeed, PEPSI-Dock benefits from the precision of a very detailed data-driven model of the binding free energy used with a global and exhaustive rigid-body search space. As well as being accurate, our computations are among the fastest by virtue of the sparse representation of the pre-computed potentials and FFT-accelerated sampling techniques. Overall, this is the first demonstration of a FFT-accelerated docking method coupled with an arbitrary-shaped distance-dependent interaction potential. First, we present a novel learning process to compute data-driven distant-dependent pairwise potentials, adapted from our previous method used for rescoring of putative protein-protein binding poses. The potential coefficients are learned by combining machine-learning techniques with physically interpretable descriptors. Then, we describe the integration of the deduced potentials into a FFT-accelerated spherical sampling provided by the Hex library. Overall, on a training set of 163 heterodimers, PEPSI-Dock achieves a success rate of 91% mid-quality predictions in the top-10 solutions. On a subset of the protein docking benchmark v5, it achieves 44.4% mid-quality predictions in the top-10 solutions when starting from bound structures and 20.5% when starting from unbound structures. The method runs in 5-15 min on a modern laptop and can easily be extended to other types of interactions. https://team.inria.fr/nano-d/software/PEPSI-Dock sergei.grudinin@inria.fr. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A systematic analysis of scoring functions in rigid-body protein docking: The delicate balance between the predictive rate improvement and the risk of overtraining.

PubMed

Barradas-Bautista, Didier; Moal, Iain H; Fernández-Recio, Juan

2017-07-01

Protein-protein interactions play fundamental roles in biological processes including signaling, metabolism, and trafficking. While the structure of a protein complex reveals crucial details about the interaction, it is often difficult to acquire this information experimentally. As the number of interactions discovered increases faster than they can be characterized, protein-protein docking calculations may be able to reduce this disparity by providing models of the interacting proteins. Rigid-body docking is a widely used docking approach, and is often capable of generating a pool of models within which a near-native structure can be found. These models need to be scored in order to select the acceptable ones from the set of poses. Recently, more than 100 scoring functions from the CCharPPI server were evaluated for this task using decoy structures generated with SwarmDock. Here, we extend this analysis to identify the predictive success rates of the scoring functions on decoys from three rigid-body docking programs, ZDOCK, FTDock, and SDOCK, allowing us to assess the transferability of the functions. We also apply set-theoretic measure to test whether the scoring functions are capable of identifying near-native poses within different subsets of the benchmark. This information can provide guides for the use of the most efficient scoring function for each docking method, as well as instruct future scoring functions development efforts. Proteins 2017; 85:1287-1297. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Naringenin and quercetin--potential anti-HCV agents for NS2 protease targets.

PubMed

Lulu, S Sajitha; Thabitha, A; Vino, S; Priya, A Mohana; Rout, Madhusmita

2016-01-01

Nonstructural proteins of hepatitis C virus had drawn much attention for the scientific fraternity in drug discovery due to its important role in the disease. 3D structure of the protein was predicted using molecular modelling protocol. Docking studies of 10 medicinal plant compounds and three drugs available in the market (control) with NS2 protease were employed by using rigid docking approach of AutoDock 4.2. Among the molecules tested for docking study, naringenin and quercetin revealed minimum binding energy of - 7.97 and - 7.95 kcal/mol with NS2 protease. All the ligands were docked deeply within the binding pocket region of the protein. The docking study results showed that these compounds are potential inhibitors of the target; and also all these docked compounds have good inhibition constant, vdW+Hbond+desolv energy with best RMSD value.

Assessment of CAPRI predictions in rounds 3-5 shows progress in docking procedures.

PubMed

Méndez, Raúl; Leplae, Raphaël; Lensink, Marc F; Wodak, Shoshana J

2005-08-01

The current status of docking procedures for predicting protein-protein interactions starting from their three-dimensional (3D) structure is reassessed by evaluating blind predictions, performed during 2003-2004 as part of Rounds 3-5 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Ten newly determined structures of protein-protein complexes were used as targets for these rounds. They comprised 2 enzyme-inhibitor complexes, 2 antigen-antibody complexes, 2 complexes involved in cellular signaling, 2 homo-oligomers, and a complex between 2 components of the bacterial cellulosome. For most targets, the predictors were given the experimental structures of 1 unbound and 1 bound component, with the latter in a random orientation. For some, the structure of the free component was derived from that of a related protein, requiring the use of homology modeling. In some of the targets, significant differences in conformation were displayed between the bound and unbound components, representing a major challenge for the docking procedures. For 1 target, predictions could not go to completion. In total, 1866 predictions submitted by 30 groups were evaluated. Over one-third of these groups applied completely novel docking algorithms and scoring functions, with several of them specifically addressing the challenge of dealing with side-chain and backbone flexibility. The quality of the predicted interactions was evaluated by comparison to the experimental structures of the targets, made available for the evaluation, using the well-agreed-upon criteria used previously. Twenty-four groups, which for the first time included an automatic Web server, produced predictions ranking from acceptable to highly accurate for all targets, including those where the structures of the bound and unbound forms differed substantially. These results and a brief survey of the methods used by participants of CAPRI Rounds 3-5 suggest that genuine progress in the performance of docking methods is being achieved, with CAPRI acting as the catalyst.

Intuitive, but not simple: including explicit water molecules in protein-protein docking simulations improves model quality.

PubMed

Parikh, Hardik I; Kellogg, Glen E

2014-06-01

Characterizing the nature of interaction between proteins that have not been experimentally cocrystallized requires a computational docking approach that can successfully predict the spatial conformation adopted in the complex. In this work, the Hydropathic INTeractions (HINT) force field model was used for scoring docked models in a data set of 30 high-resolution crystallographically characterized "dry" protein-protein complexes and was shown to reliably identify native-like models. However, most current protein-protein docking algorithms fail to explicitly account for water molecules involved in bridging interactions that mediate and stabilize the association of the protein partners, so we used HINT to illuminate the physical and chemical properties of bridging waters and account for their energetic stabilizing contributions. The HINT water Relevance metric identified the "truly" bridging waters at the 30 protein-protein interfaces and we utilized them in "solvated" docking by manually inserting them into the input files for the rigid body ZDOCK program. By accounting for these interfacial waters, a statistically significant improvement of ∼24% in the average hit-count within the top-10 predictions the protein-protein dataset was seen, compared to standard "dry" docking. The results also show scoring improvement, with medium and high accuracy models ranking much better than incorrect ones. These improvements can be attributed to the physical presence of water molecules that alter surface properties and better represent native shape and hydropathic complementarity between interacting partners, with concomitantly more accurate native-like structure predictions. © 2013 Wiley Periodicals, Inc.

A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking

PubMed Central

Trellet, Mikael; Melquiond, Adrien S. J.; Bonvin, Alexandre M. J. J.

2013-01-01

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking. PMID:23516555

A unified conformational selection and induced fit approach to protein-peptide docking.

PubMed

Trellet, Mikael; Melquiond, Adrien S J; Bonvin, Alexandre M J J

2013-01-01

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.

Evaluation of protein docking predictions using Hex 3.1 in CAPRI rounds 1 and 2.

PubMed

Ritchie, David W

2003-07-01

This article describes and reviews our efforts using Hex 3.1 to predict the docking modes of the seven target protein-protein complexes presented in the CAPRI (Critical Assessment of Predicted Interactions) blind docking trial. For each target, the structure of at least one of the docking partners was given in its unbound form, and several of the targets involved large multimeric structures (e.g., Lactobacillus HPr kinase, hemagglutinin, bovine rotavirus VP6). Here we describe several enhancements to our original spherical polar Fourier docking correlation algorithm. For example, a novel surface sphere smothering algorithm is introduced to generate multiple local coordinate systems around the surface of a large receptor molecule, which may be used to define a small number of initial ligand-docking orientations distributed over the receptor surface. High-resolution spherical polar docking correlations are performed over the resulting receptor surface patches, and candidate docking solutions are refined by using a novel soft molecular mechanics energy minimization procedure. Overall, this approach identified two good solutions at rank 5 or less for two of the seven CAPRI complexes. Subsequent analysis of our results shows that Hex 3.1 is able to place good solutions within a list of

CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site

PubMed Central

Kurcinski, Mateusz; Jamroz, Michal; Blaszczyk, Maciej; Kolinski, Andrzej; Kmiecik, Sebastian

2015-01-01

Protein–peptide interactions play a key role in cell functions. Their structural characterization, though challenging, is important for the discovery of new drugs. The CABS-dock web server provides an interface for modeling protein–peptide interactions using a highly efficient protocol for the flexible docking of peptides to proteins. While other docking algorithms require pre-defined localization of the binding site, CABS-dock does not require such knowledge. Given a protein receptor structure and a peptide sequence (and starting from random conformations and positions of the peptide), CABS-dock performs simulation search for the binding site allowing for full flexibility of the peptide and small fluctuations of the receptor backbone. This protocol was extensively tested over the largest dataset of non-redundant protein–peptide interactions available to date (including bound and unbound docking cases). For over 80% of bound and unbound dataset cases, we obtained models with high or medium accuracy (sufficient for practical applications). Additionally, as optional features, CABS-dock can exclude user-selected binding modes from docking search or to increase the level of flexibility for chosen receptor fragments. CABS-dock is freely available as a web server at http://biocomp.chem.uw.edu.pl/CABSdock. PMID:25943545

A benchmark testing ground for integrating homology modeling and protein docking.

PubMed

Bohnuud, Tanggis; Luo, Lingqi; Wodak, Shoshana J; Bonvin, Alexandre M J J; Weng, Zhiping; Vajda, Sandor; Schueler-Furman, Ora; Kozakov, Dima

2017-01-01

Protein docking procedures carry out the task of predicting the structure of a protein-protein complex starting from the known structures of the individual protein components. More often than not, however, the structure of one or both components is not known, but can be derived by homology modeling on the basis of known structures of related proteins deposited in the Protein Data Bank (PDB). Thus, the problem is to develop methods that optimally integrate homology modeling and docking with the goal of predicting the structure of a complex directly from the amino acid sequences of its component proteins. One possibility is to use the best available homology modeling and docking methods. However, the models built for the individual subunits often differ to a significant degree from the bound conformation in the complex, often much more so than the differences observed between free and bound structures of the same protein, and therefore additional conformational adjustments, both at the backbone and side chain levels need to be modeled to achieve an accurate docking prediction. In particular, even homology models of overall good accuracy frequently include localized errors that unfavorably impact docking results. The predicted reliability of the different regions in the model can also serve as a useful input for the docking calculations. Here we present a benchmark dataset that should help to explore and solve combined modeling and docking problems. This dataset comprises a subset of the experimentally solved 'target' complexes from the widely used Docking Benchmark from the Weng Lab (excluding antibody-antigen complexes). This subset is extended to include the structures from the PDB related to those of the individual components of each complex, and hence represent potential templates for investigating and benchmarking integrated homology modeling and docking approaches. Template sets can be dynamically customized by specifying ranges in sequence similarity and in PDB release dates, or using other filtering options, such as excluding sets of specific structures from the template list. Multiple sequence alignments, as well as structural alignments of the templates to their corresponding subunits in the target are also provided. The resource is accessible online or can be downloaded at http://cluspro.org/benchmark, and is updated on a weekly basis in synchrony with new PDB releases. Proteins 2016; 85:10-16. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Virtual screening studies of Chinese medicine Coptidis Rhizoma as alpha7 nicotinic acetylcholine receptor agonists for treatment of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Xiang, Li; Xu, Youdong; Zhang, Yan; Meng, Xianli; Wang, Ping

2015-04-01

Alzheimer's disease (AD) is an age-related neurodegenerative disease. Extensive in vitro and in vivo experiments have proved that the decreased activity of the cholinergic neuron is responsible for the memory and cognition deterioration. The alpha7 nicotinic acetylcholine receptor (α7-nAChR) is proposed to a drug target of AD, and compounds which acting as α7-nAChR agonists are considered as candidates in AD treatment. Chinese medicine CoptidisRhizoma and its compounds are reported in various anti-AD effects. In this study, virtual screening, docking approaches and hydrogen bond analyses were applied to screen potential α7-nAChR agonists from CoptidisRhizome. The 3D structure of the protein was obtained from PDB database. 87 reported compounds were included in this research and their structures were accessed by NCBI Pubchem. Docking analysis of the compounds was performed using AutoDock 4.2 and AutoDock Vina. The images of the binding modes hydrogen bonds and the hydrophobic interaction were rendered with PyMOL1.5.0.4. and LigPlot+ respectively. Finally, N-tran-feruloyltyramine, isolariciresinol, flavanone, secoisolariciresinol, (+)-lariciresinol and dihydrochalcone, exhibited the lowest docking energy of protein-ligand complex. The results indicate these 6 compounds are potential α7 nAChR agonists, and expected to be effective in AD treatment.

Identifying the binding mode of a molecular scaffold

NASA Astrophysics Data System (ADS)

Chema, Doron; Eren, Doron; Yayon, Avner; Goldblum, Amiram; Zaliani, Andrea

2004-01-01

We describe a method for docking of a scaffold-based series and present its advantages over docking of individual ligands, for determining the binding mode of a molecular scaffold in a binding site. The method has been applied to eight different scaffolds of protein kinase inhibitors (PKI). A single analog of each of these eight scaffolds was previously crystallized with different protein kinases. We have used FlexX to dock a set of molecules that share the same scaffold, rather than docking a single molecule. The main mode of binding is determined by the mode of binding of the largest cluster among the docked molecules that share a scaffold. Clustering is based on our `nearest single neighbor' method [J. Chem. Inf. Comput. Sci., 43 (2003) 208-217]. Additional criteria are applied in those cases in which more than one significant binding mode is found. Using the proposed method, most of the crystallographic binding modes of these scaffolds were reconstructed. Alternative modes, that have not been detected yet by experiments, could also be identified. The method was applied to predict the binding mode of an additional molecular scaffold that was not yet reported and the predicted binding mode has been found to be very similar to experimental results for a closely related scaffold. We suggest that this approach be used as a virtual screening tool for scaffold-based design processes.

Progress in protein-protein docking: atomic resolution predictions in the CAPRI experiment using RosettaDock with an improved treatment of side-chain flexibility.

PubMed

Schueler-Furman, Ora; Wang, Chu; Baker, David

2005-08-01

RosettaDock uses real-space Monte Carlo minimization (MCM) on both rigid-body and side-chain degrees of freedom to identify the lowest free energy docked arrangement of 2 protein structures. An improved version of the method that uses gradient-based minimization for off-rotamer side-chain optimization and includes information from unbound structures was used to create predictions for Rounds 4 and 5 of CAPRI. First, large numbers of independent MCM trajectories were carried out and the lowest free energy docked configurations identified. Second, new trajectories were started from these lowest energy structures to thoroughly sample the surrounding conformation space, and the lowest energy configurations were submitted as predictions. For all cases in which there were no significant backbone conformational changes, a small number of very low-energy configurations were identified in the first, global search and subsequently found to be close to the center of the basin of attraction in the free energy landscape in the second, local search. Following the release of the experimental coordinates, it was found that the centers of these free energy minima were remarkably close to the native structures in not only the rigid-body orientation but also the detailed conformations of the side-chains. Out of 8 targets, the lowest energy models had interface root-mean-square deviations (RMSDs) less than 1.1 A from the correct structures for 6 targets, and interface RMSDs less than 0.4 A for 3 targets. The predictions were top submissions to CAPRI for Targets 11, 12, 14, 15, and 19. The close correspondence of the lowest free energy structures found in our searches to the experimental structures suggests that our free energy function is a reasonable representation of the physical chemistry, and that the real space search with full side-chain flexibility to some extent solves the protein-protein docking problem in the absence of significant backbone conformational changes. On the other hand, the approach fails when there are significant backbone conformational changes as the steric complementarity of the 2 proteins cannot be modeled without incorporating backbone flexibility, and this is the major goal of our current work.

Structure-based design and evaluation of novel N-phenyl-1H-indol-2-amine derivatives for fat mass and obesity-associated (FTO) protein inhibition.

PubMed

Padariya, Monikaben; Kalathiya, Umesh

2016-10-01

Fat mass and obesity-associated (FTO) protein contributes to non-syndromic human obesity which refers to excessive fat accumulation in human body and results in health risk. FTO protein has become a promising target for anti-obesity medicines as there is an immense need for the rational design of potent inhibitors to treat obesity. In our study, a new scaffold N-phenyl-1H-indol-2-amine was selected as a base for FTO protein inhibitors by applying scaffold hopping approach. Using this novel scaffold, different derivatives were designed by extending scaffold structure with potential functional groups. Molecular docking simulations were carried out by using two different docking algorithm implemented in CDOCKER (flexible docking) and AutoDock programs (rigid docking). Analyzing results of rigid and flexible docking, compound MU06 was selected based on different properties and predicted binding affinities for further analysis. Molecular dynamics simulation of FTO/MU06 complex was performed to characterize structure rationale and binding stability. Certainly, Arg96 and His231 residue of FTO protein showed stable interaction with inhibitor MU06 throughout the production dynamics phase. Three residues of FTO protein (Arg96, Asp233, and His231) were found common in making H-bond interactions with MU06 during molecular dynamics simulation and CDOCKER docking. Copyright © 2016 Elsevier Ltd. All rights reserved.

Protein docking by the interface structure similarity: how much structure is needed?

PubMed

Sinha, Rohita; Kundrotas, Petras J; Vakser, Ilya A

2012-01-01

The increasing availability of co-crystallized protein-protein complexes provides an opportunity to use template-based modeling for protein-protein docking. Structure alignment techniques are useful in detection of remote target-template similarities. The size of the structure involved in the alignment is important for the success in modeling. This paper describes a systematic large-scale study to find the optimal definition/size of the interfaces for the structure alignment-based docking applications. The results showed that structural areas corresponding to the cutoff values <12 Å across the interface inadequately represent structural details of the interfaces. With the increase of the cutoff beyond 12 Å, the success rate for the benchmark set of 99 protein complexes, did not increase significantly for higher accuracy models, and decreased for lower-accuracy models. The 12 Å cutoff was optimal in our interface alignment-based docking, and a likely best choice for the large-scale (e.g., on the scale of the entire genome) applications to protein interaction networks. The results provide guidelines for the docking approaches, including high-throughput applications to modeled structures.

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

PubMed

Peterson, Lenna X; Shin, Woong-Hee; Kim, Hyungrae; Kihara, Daisuke

2018-03-01

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase. © 2017 Wiley Periodicals, Inc.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics.

PubMed

Armen, Roger S; Chen, Jianhan; Brooks, Charles L

2009-10-13

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics

PubMed Central

Armen, Roger S.; Chen, Jianhan; Brooks, Charles L.

2009-01-01

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and “noise” that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds. PMID:20160879

Rapid Design of Knowledge-Based Scoring Potentials for Enrichment of Near-Native Geometries in Protein-Protein Docking.

PubMed

Sasse, Alexander; de Vries, Sjoerd J; Schindler, Christina E M; de Beauchêne, Isaure Chauvot; Zacharias, Martin

2017-01-01

Protein-protein docking protocols aim to predict the structures of protein-protein complexes based on the structure of individual partners. Docking protocols usually include several steps of sampling, clustering, refinement and re-scoring. The scoring step is one of the bottlenecks in the performance of many state-of-the-art protocols. The performance of scoring functions depends on the quality of the generated structures and its coupling to the sampling algorithm. A tool kit, GRADSCOPT (GRid Accelerated Directly SCoring OPTimizing), was designed to allow rapid development and optimization of different knowledge-based scoring potentials for specific objectives in protein-protein docking. Different atomistic and coarse-grained potentials can be created by a grid-accelerated directly scoring dependent Monte-Carlo annealing or by a linear regression optimization. We demonstrate that the scoring functions generated by our approach are similar to or even outperform state-of-the-art scoring functions for predicting near-native solutions. Of additional importance, we find that potentials specifically trained to identify the native bound complex perform rather poorly on identifying acceptable or medium quality (near-native) solutions. In contrast, atomistic long-range contact potentials can increase the average fraction of near-native poses by up to a factor 2.5 in the best scored 1% decoys (compared to existing scoring), emphasizing the need of specific docking potentials for different steps in the docking protocol.

Replica Exchange Improves Sampling in Low-Resolution Docking Stage of RosettaDock

PubMed Central

Zhang, Zhe; Lange, Oliver F.

2013-01-01

Many protein-protein docking protocols are based on a shotgun approach, in which thousands of independent random-start trajectories minimize the rigid-body degrees of freedom. Another strategy is enumerative sampling as used in ZDOCK. Here, we introduce an alternative strategy, ReplicaDock, using a small number of long trajectories of temperature replica exchange. We compare replica exchange sampling as low-resolution stage of RosettaDock with RosettaDock's original shotgun sampling as well as with ZDOCK. A benchmark of 30 complexes starting from structures of the unbound binding partners shows improved performance for ReplicaDock and ZDOCK when compared to shotgun sampling at equal or less computational expense. ReplicaDock and ZDOCK consistently reach lower energies and generate significantly more near-native conformations than shotgun sampling. Accordingly, they both improve typical metrics of prediction quality of complex structures after refinement. Additionally, the refined ReplicaDock ensembles reach significantly lower interface energies and many previously hidden features of the docking energy landscape become visible when ReplicaDock is applied. PMID:24009670

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

PubMed

Ashtawy, Hossam M; Mahapatra, Nihar R

2015-01-01

Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins

PubMed Central

2015-01-01

Background Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. Results and conclusion We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex. PMID:25916860

New generation of docking programs: Supercomputer validation of force fields and quantum-chemical methods for docking.

PubMed

Sulimov, Alexey V; Kutov, Danil C; Katkova, Ekaterina V; Ilin, Ivan S; Sulimov, Vladimir B

2017-11-01

Discovery of new inhibitors of the protein associated with a given disease is the initial and most important stage of the whole process of the rational development of new pharmaceutical substances. New inhibitors block the active site of the target protein and the disease is cured. Computer-aided molecular modeling can considerably increase effectiveness of new inhibitors development. Reliable predictions of the target protein inhibition by a small molecule, ligand, is defined by the accuracy of docking programs. Such programs position a ligand in the target protein and estimate the protein-ligand binding energy. Positioning accuracy of modern docking programs is satisfactory. However, the accuracy of binding energy calculations is too low to predict good inhibitors. For effective application of docking programs to new inhibitors development the accuracy of binding energy calculations should be higher than 1kcal/mol. Reasons of limited accuracy of modern docking programs are discussed. One of the most important aspects limiting this accuracy is imperfection of protein-ligand energy calculations. Results of supercomputer validation of several force fields and quantum-chemical methods for docking are presented. The validation was performed by quasi-docking as follows. First, the low energy minima spectra of 16 protein-ligand complexes were found by exhaustive minima search in the MMFF94 force field. Second, energies of the lowest 8192 minima are recalculated with CHARMM force field and PM6-D3H4X and PM7 quantum-chemical methods for each complex. The analysis of minima energies reveals the docking positioning accuracies of the PM7 and PM6-D3H4X quantum-chemical methods and the CHARMM force field are close to one another and they are better than the positioning accuracy of the MMFF94 force field. Copyright © 2017 Elsevier Inc. All rights reserved.

Protein-Protein Docking with F2Dock 2.0 and GB-Rerank

PubMed Central

Chowdhury, Rezaul; Rasheed, Muhibur; Keidel, Donald; Moussalem, Maysam; Olson, Arthur; Sanner, Michel; Bajaj, Chandrajit

2013-01-01

Motivation Computational simulation of protein-protein docking can expedite the process of molecular modeling and drug discovery. This paper reports on our new F2 Dock protocol which improves the state of the art in initial stage rigid body exhaustive docking search, scoring and ranking by introducing improvements in the shape-complementarity and electrostatics affinity functions, a new knowledge-based interface propensity term with FFT formulation, a set of novel knowledge-based filters and finally a solvation energy (GBSA) based reranking technique. Our algorithms are based on highly efficient data structures including the dynamic packing grids and octrees which significantly speed up the computations and also provide guaranteed bounds on approximation error. Results The improved affinity functions show superior performance compared to their traditional counterparts in finding correct docking poses at higher ranks. We found that the new filters and the GBSA based reranking individually and in combination significantly improve the accuracy of docking predictions with only minor increase in computation time. We compared F2 Dock 2.0 with ZDock 3.0.2 and found improvements over it, specifically among 176 complexes in ZLab Benchmark 4.0, F2 Dock 2.0 finds a near-native solution as the top prediction for 22 complexes; where ZDock 3.0.2 does so for 13 complexes. F2 Dock 2.0 finds a near-native solution within the top 1000 predictions for 106 complexes as opposed to 104 complexes for ZDock 3.0.2. However, there are 17 and 15 complexes where F2 Dock 2.0 finds a solution but ZDock 3.0.2 does not and vice versa; which indicates that the two docking protocols can also complement each other. Availability The docking protocol has been implemented as a server with a graphical client (TexMol) which allows the user to manage multiple docking jobs, and visualize the docked poses and interfaces. Both the server and client are available for download. Server: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dock.shtml. Client: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dockclient.shtml. PMID:23483883

A cross docking pipeline for improving pose prediction and virtual screening performance

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Zhang, Kam Y. J.

2018-01-01

Pose prediction and virtual screening performance of a molecular docking method depend on the choice of protein structures used for docking. Multiple structures for a target protein are often used to take into account the receptor flexibility and problems associated with a single receptor structure. However, the use of multiple receptor structures is computationally expensive when docking a large library of small molecules. Here, we propose a new cross-docking pipeline suitable to dock a large library of molecules while taking advantage of multiple target protein structures. Our method involves the selection of a suitable receptor for each ligand in a screening library utilizing ligand 3D shape similarity with crystallographic ligands. We have prospectively evaluated our method in D3R Grand Challenge 2 and demonstrated that our cross-docking pipeline can achieve similar or better performance than using either single or multiple-receptor structures. Moreover, our method displayed not only decent pose prediction performance but also better virtual screening performance over several other methods.

Ligand-protein docking using a quantum stochastic tunneling optimization method.

PubMed

Mancera, Ricardo L; Källblad, Per; Todorov, Nikolay P

2004-04-30

A novel hybrid optimization method called quantum stochastic tunneling has been recently introduced. Here, we report its implementation within a new docking program called EasyDock and a validation with the CCDC/Astex data set of ligand-protein complexes using the PLP score to represent the ligand-protein potential energy surface and ScreenScore to score the ligand-protein binding energies. When taking the top energy-ranked ligand binding mode pose, we were able to predict the correct crystallographic ligand binding mode in up to 75% of the cases. By using this novel optimization method run times for typical docking simulations are significantly shortened. Copyright 2004 Wiley Periodicals, Inc. J Comput Chem 25: 858-864, 2004

Efficient Relaxation of Protein-Protein Interfaces by Discrete Molecular Dynamics Simulations.

PubMed

Emperador, Agusti; Solernou, Albert; Sfriso, Pedro; Pons, Carles; Gelpi, Josep Lluis; Fernandez-Recio, Juan; Orozco, Modesto

2013-02-12

Protein-protein interactions are responsible for the transfer of information inside the cell and represent one of the most interesting research fields in structural biology. Unfortunately, after decades of intense research, experimental approaches still have difficulties in providing 3D structures for the hundreds of thousands of interactions formed between the different proteins in a living organism. The use of theoretical approaches like docking aims to complement experimental efforts to represent the structure of the protein interactome. However, we cannot ignore that current methods have limitations due to problems of sampling of the protein-protein conformational space and the lack of accuracy of available force fields. Cases that are especially difficult for prediction are those in which complex formation implies a non-negligible change in the conformation of the interacting proteins, i.e., those cases where protein flexibility plays a key role in protein-protein docking. In this work, we present a new approach to treat flexibility in docking by global structural relaxation based on ultrafast discrete molecular dynamics. On a standard benchmark of protein complexes, the method provides a general improvement over the results obtained by rigid docking. The method is especially efficient in cases with large conformational changes upon binding, in which structure relaxation with discrete molecular dynamics leads to a predictive success rate double that obtained with state-of-the-art rigid-body docking.

In Silico Screening for Inhibitors of P-Glycoprotein That Target the Nucleotide Binding Domains

PubMed Central

Brewer, Frances K.; Follit, Courtney A.; Vogel, Pia D.

2014-01-01

Multidrug resistances and the failure of chemotherapies are often caused by the expression or overexpression of ATP-binding cassette transporter proteins such as the multidrug resistance protein, P-glycoprotein (P-gp). P-gp is expressed in the plasma membrane of many cell types and protects cells from accumulation of toxins. P-gp uses ATP hydrolysis to catalyze the transport of a broad range of mostly hydrophobic compounds across the plasma membrane and out of the cell. During cancer chemotherapy, the administration of therapeutics often selects for cells which overexpress P-gp, thereby creating populations of cancer cells resistant to a variety of chemically unrelated chemotherapeutics. The present study describes extremely high-throughput, massively parallel in silico ligand docking studies aimed at identifying reversible inhibitors of ATP hydrolysis that target the nucleotide-binding domains of P-gp. We used a structural model of human P-gp that we obtained from molecular dynamics experiments as the protein target for ligand docking. We employed a novel approach of subtractive docking experiments that identified ligands that bound predominantly to the nucleotide-binding domains but not the drug-binding domains of P-gp. Four compounds were found that inhibit ATP hydrolysis by P-gp. Using electron spin resonance spectroscopy, we showed that at least three of these compounds affected nucleotide binding to the transporter. These studies represent a successful proof of principle demonstrating the potential of targeted approaches for identifying specific inhibitors of P-gp. PMID:25270578

Fusion competent synaptic vesicles persist upon active zone disruption and loss of vesicle docking

PubMed Central

Wang, Shan Shan H.; Held, Richard G.; Wong, Man Yan; Liu, Changliang; Karakhanyan, Aziz; Kaeser, Pascal S.

2016-01-01

In a nerve terminal, synaptic vesicle docking and release are restricted to an active zone. The active zone is a protein scaffold that is attached to the presynaptic plasma membrane and opposed to postsynaptic receptors. Here, we generated conditional knockout mice removing the active zone proteins RIM and ELKS, which additionally led to loss of Munc13, Bassoon, Piccolo, and RIM-BP, indicating disassembly of the active zone. We observed a near complete lack of synaptic vesicle docking and a strong reduction in vesicular release probability and the speed of exocytosis, but total vesicle numbers, SNARE protein levels, and postsynaptic densities remained unaffected. Despite loss of the priming proteins Munc13 and RIM and of docked vesicles, a pool of releasable vesicles remained. Thus, the active zone is necessary for synaptic vesicle docking and to enhance release probability, but releasable vesicles can be localized distant from the presynaptic plasma membrane. PMID:27537483

A High Performance Cloud-Based Protein-Ligand Docking Prediction Algorithm

PubMed Central

Chen, Jui-Le; Yang, Chu-Sing

2013-01-01

The potential of predicting druggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the structure-based protein-ligand docking prediction is still unsatisfied until now. Hence, in this paper, a novel docking prediction algorithm, named fast cloud-based protein-ligand docking prediction algorithm (FCPLDPA), is presented to accelerate the docking prediction algorithm. The proposed algorithm works by leveraging two high-performance operators: (1) the novel migration (information exchange) operator is designed specially for cloud-based environments to reduce the computation time; (2) the efficient operator is aimed at filtering out the worst search directions. Our simulation results illustrate that the proposed method outperforms the other docking algorithms compared in this paper in terms of both the computation time and the quality of the end result. PMID:23762864

PTools: an opensource molecular docking library

PubMed Central

Saladin, Adrien; Fiorucci, Sébastien; Poulain, Pierre; Prévost, Chantal; Zacharias, Martin

2009-01-01

Background Macromolecular docking is a challenging field of bioinformatics. Developing new algorithms is a slow process generally involving routine tasks that should be found in a robust library and not programmed from scratch for every new software application. Results We present an object-oriented Python/C++ library to help the development of new docking methods. This library contains low-level routines like PDB-format manipulation functions as well as high-level tools for docking and analyzing results. We also illustrate the ease of use of this library with the detailed implementation of a 3-body docking procedure. Conclusion The PTools library can handle molecules at coarse-grained or atomic resolution and allows users to rapidly develop new software. The library is already in use for protein-protein and protein-DNA docking with the ATTRACT program and for simulation analysis. This library is freely available under the GNU GPL license, together with detailed documentation. PMID:19409097

PTools: an opensource molecular docking library.

PubMed

Saladin, Adrien; Fiorucci, Sébastien; Poulain, Pierre; Prévost, Chantal; Zacharias, Martin

2009-05-01

Macromolecular docking is a challenging field of bioinformatics. Developing new algorithms is a slow process generally involving routine tasks that should be found in a robust library and not programmed from scratch for every new software application. We present an object-oriented Python/C++ library to help the development of new docking methods. This library contains low-level routines like PDB-format manipulation functions as well as high-level tools for docking and analyzing results. We also illustrate the ease of use of this library with the detailed implementation of a 3-body docking procedure. The PTools library can handle molecules at coarse-grained or atomic resolution and allows users to rapidly develop new software. The library is already in use for protein-protein and protein-DNA docking with the ATTRACT program and for simulation analysis. This library is freely available under the GNU GPL license, together with detailed documentation.

The simulation study of protein-protein interfaces based on the 4-helix bundle structure

NASA Astrophysics Data System (ADS)

Fukuda, Masaki; Komatsu, Yu; Morikawa, Ryota; Miyakawa, Takeshi; Takasu, Masako; Akanuma, Satoshi; Yamagishi, Akihiko

2013-02-01

Docking of two protein molecules is induced by intermolecular interactions. Our purposes in this study are: designing binding interfaces on the two proteins, which specifically interact to each other; and inducing intermolecular interactions between the two proteins by mixing them. A 4-helix bundle structure was chosen as a scaffold on which binding interfaces were created. Based on this scaffold, we designed binding interfaces involving charged and nonpolar amino acid residues. We performed molecular dynamics (MD) simulation to identify suitable amino acid residues for the interfaces. We chose YciF protein as the scaffold for the protein-protein docking simulation. We observed the structure of two YciF protein molecules (I and II), and we calculated the distance between centroids (center of gravity) of the interfaces' surface planes of the molecules I and II. We found that the docking of the two protein molecules can be controlled by the number of hydrophobic and charged amino acid residues involved in the interfaces. Existence of six hydrophobic and five charged amino acid residues within an interface were most suitable for the protein-protein docking.

Import of honeybee prepromelittin into the endoplasmic reticulum: structural basis for independence of SRP and docking protein.

PubMed Central

Müller, G; Zimmermann, R

1987-01-01

Honeybee prepromelittin is correctly processed and imported by dog pancreas microsomes. Insertion of prepromelittin into microsomal membranes, as assayed by signal sequence removal, does not depend on signal recognition particle (SRP) and docking protein. We addressed the question as to how prepromelittin bypasses the SRP/docking protein system. Hybrid proteins between prepromelittin, or carboxy-terminally truncated derivatives, and the cytoplasmic protein dihydrofolate reductase from mouse were constructed. These hybrid proteins were analysed for membrane insertion and sequestration into microsomes. The results suggest the following: (i) The signal sequence of prepromelittin is capable of interacting with the SRP/docking protein system, but this interaction is not mandatory for membrane insertion; this is related to the small size of prepromelittin. (ii) In prepromelittin a cluster of negatively charged amino acids must be balanced by a cluster of positively charged amino acids in order to allow membrane insertion. (iii) In general, a signal sequence can be sufficient to mediate membrane insertion independently of SRP and docking protein in the case of short precursor proteins; however, the presence and distribution of charged amino acids within the mature part of these precursors can play distinct roles. Images Fig. 3. Fig. 4. Fig. 5. Fig. 6. Fig. 7. Fig. 8. Fig. 9. PMID:2820722

Structural Insight Into the Role of Mutual Polymorphism and Conservatism in the Contact Zone of the NFR5-K1 Heterodimer With the Nod Factor.

PubMed

Igolkina, A A; Porozov, Yu B; Chizhevskaya, E P; Andronov, E E

2018-01-01

Sandwich-like docking configurations of the heterodimeric complex of NFR5 and K1 Vicia sativa receptor-like kinases together with the putative ligand, Nod factor (NF) of Rhizobium leguminosarum bv. viciae , were modeled and two of the most probable configurations were assessed through the analysis of the mutual polymorphisms and conservatism. We carried out this analysis based on the hypothesis that in a contact zone of two docked components (proteins or ligands) the population polymorphism or conservatism is mutual, i.e., the variation in one component has a reflected variation in the other component. The population material of 30 wild-growing V. sativa (leaf pieces) was collected from a large field (uncultivated for the past 25-years) and pooled; form this pool, 100 randomly selected cloned fragments of NFR5 gene and 100 of K1 gene were sequenced by the Sanger method. Congruence between population trees of NFR5 and K1 haplotypes allowed us to select two respective haplotypes, build their 3D structures, and perform protein-protein docking. In a separate simulation, the protein-ligand docking between NFR5 and NF was carried out. We merged the results of the two docking experiments and extracted NFR5-NF-K1 complexes, in which NF was located within the cavity between two receptors. Molecular dynamics simulations indicated two out of six complexes as stable. Regions of mutual polymorphism in the contact zone of one complex overlapped with known NF structural variations produced by R. leguminosarum bv. viciae . A total of 74% of the contact zone of another complex contained mutually polymorphic and conservative areas. Common traits of the obtained two stable structures allowed us to hypothesize the functional role of three-domain structure of plant LysM-RLKs in their heteromers.

DockTrina: docking triangular protein trimers.

PubMed

Popov, Petr; Ritchie, David W; Grudinin, Sergei

2014-01-01

In spite of the abundance of oligomeric proteins within a cell, the structural characterization of protein-protein interactions is still a challenging task. In particular, many of these interactions involve heteromeric complexes, which are relatively difficult to determine experimentally. Hence there is growing interest in using computational techniques to model such complexes. However, assembling large heteromeric complexes computationally is a highly combinatorial problem. Nonetheless the problem can be simplified greatly by considering interactions between protein trimers. After dimers and monomers, triangular trimers (i.e. trimers with pair-wise contacts between all three pairs of proteins) are the most frequently observed quaternary structural motifs according to the three-dimensional (3D) complex database. This article presents DockTrina, a novel protein docking method for modeling the 3D structures of nonsymmetrical triangular trimers. The method takes as input pair-wise contact predictions from a rigid body docking program. It then scans and scores all possible combinations of pairs of monomers using a very fast root mean square deviation test. Finally, it ranks the predictions using a scoring function which combines triples of pair-wise contact terms and a geometric clash penalty term. The overall approach takes less than 2 min per complex on a modern desktop computer. The method is tested and validated using a benchmark set of 220 bound and seven unbound protein trimer structures. DockTrina will be made available at http://nano-d.inrialpes.fr/software/docktrina. Copyright © 2013 Wiley Periodicals, Inc.

Drosophila photoreceptor axon guidance and targeting requires the dreadlocks SH2/SH3 adapter protein.

PubMed

Garrity, P A; Rao, Y; Salecker, I; McGlade, J; Pawson, T; Zipursky, S L

1996-05-31

Mutations in the Drosophila gene dreadlocks (dock) disrupt photoreceptor cell (R cell) axon guidance and targeting. Genetic mosaic analysis and cell-type-specific expression of dock transgenes demonstrate dock is required in R cells for proper innervation. Dock protein contains one SH2 and three SH3 domains, implicating it in tyrosine kinase signaling, and is highly related to the human proto-oncogene Nck. Dock expression is detected in R cell growth cones in the target region. We propose Dock transmits signals in the growth cone in response to guidance and targeting cues. These findings provide an important step for dissection of signaling pathways regulating growth cone motility.

Protein-ligand docking with multiple flexible side chains

NASA Astrophysics Data System (ADS)

Zhao, Yong; Sanner, Michel F.

2008-09-01

In this work, we validate and analyze the results of previously published cross docking experiments and classify failed dockings based on the conformational changes observed in the receptors. We show that a majority of failed experiments (i.e. 25 out of 33, involving four different receptors: cAPK, CDK2, Ricin and HIVp) are due to conformational changes in side chains near the active site. For these cases, we identify the side chains to be made flexible during docking calculation by superimposing receptors and analyzing steric overlap between various ligands and receptor side chains. We demonstrate that allowing these side chains to assume rotameric conformations enables the successful cross docking of 19 complexes (ligand all atom RMSD < 2.0 Å) using our docking software FLIPDock. The number of side receptor side chains interacting with a ligand can vary according to the ligand's size and shape. Hence, when starting from a complex with a particular ligand one might have to extend the region of potential interacting side chains beyond the ones interacting with the known ligand. We discuss distance-based methods for selecting additional side chains in the neighborhood of the known active site. We show that while using the molecular surface to grow the neighborhood is more efficient than Euclidian-distance selection, the number of side chains selected by these methods often remains too large and additional methods for reducing their count are needed. Despite these difficulties, using geometric constraints obtained from the network of bonded and non-bonded interactions to rank residues and allowing the top ranked side chains to be flexible during docking makes 22 out of 25 complexes successful.

Computational Exploration of a Protein Receptor Binding Space with Student Proposed Peptide Ligands

PubMed Central

King, Matthew D.; Phillips, Paul; Turner, Matthew W.; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; Mcdougal, Owen M.

2017-01-01

Computational molecular docking is a fast and effective in silico method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The DockoMatic tutorial described herein provides a framework by which instructors can guide students through a drug screening exercise. Using receptor models derived from readily available protein crystal structures, docking programs have the ability to predict ligand binding properties, such as preferential binding orientations and binding affinities. The use of computational studies can significantly enhance complimentary wet chemical experimentation by providing insight into the important molecular interactions within the system of interest, as well as guide the design of new candidate ligands based on observed binding motifs and energetics. In this laboratory tutorial, the graphical user interface, DockoMatic, facilitates docking job submissions to the docking engine, AutoDock 4.2. The purpose of this exercise is to successfully dock a 17-amino acid peptide, α-conotoxin TxIA, to the acetylcholine binding protein from Aplysia californica-AChBP to determine the most stable binding configuration. Each student will then propose two specific amino acid substitutions of α-conotoxin TxIA to enhance peptide binding affinity, create the mutant in DockoMatic, and perform docking calculations to compare their results with the class. Students will also compare intermolecular forces, binding energy, and geometric orientation of their prepared analog to their initial α-conotoxin TxIA docking results. PMID:26537635

Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge

PubMed Central

Gallicchio, Emilio; Deng, Nanjie; He, Peng; Wickstrom, Lauren; Perryman, Alexander L.; Santiago, Daniel N.; Forli, Stefano; Olson, Arthur J.; Levy, Ronald M.

2014-01-01

As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization. PMID:24504704

The RCAN carboxyl end mediates calcineurin docking-dependent inhibition via a site that dictates binding to substrates and regulators

PubMed Central

Martínez-Martínez, Sara; Genescà, Lali; Rodríguez, Antonio; Raya, Alicia; Salichs, Eulàlia; Were, Felipe; López-Maderuelo, María Dolores; Redondo, Juan Miguel; de la Luna, Susana

2009-01-01

Specificity of signaling kinases and phosphatases toward their targets is usually mediated by docking interactions with substrates and regulatory proteins. Here, we characterize the motifs involved in the physical and functional interaction of the phosphatase calcineurin with a group of modulators, the RCAN protein family. Mutation of key residues within the hydrophobic docking-cleft of the calcineurin catalytic domain impairs binding to all human RCAN proteins and to the calcineurin interacting proteins Cabin1 and AKAP79. A valine-rich region within the RCAN carboxyl region is essential for binding to the docking site in calcineurin. Although a peptide containing this sequence compromises NFAT signaling in living cells, it does not inhibit calcineurin catalytic activity directly. Instead, calcineurin catalytic activity is inhibited by a motif at the extreme C-terminal region of RCAN, which acts in cis with the docking motif. Our results therefore indicate that the inhibitory action of RCAN on calcineurin-NFAT signaling results not only from the inhibition of phosphatase activity but also from competition between NFAT and RCAN for binding to the same docking site in calcineurin. Thus, competition by substrates and modulators for a common docking site appears to be an essential mechanism in the regulation of Ca2+-calcineurin signaling. PMID:19332797

HPEPDOCK: a web server for blind peptide-protein docking based on a hierarchical algorithm.

PubMed

Zhou, Pei; Jin, Bowen; Li, Hao; Huang, Sheng-You

2018-05-09

Protein-peptide interactions are crucial in many cellular functions. Therefore, determining the structure of protein-peptide complexes is important for understanding the molecular mechanism of related biological processes and developing peptide drugs. HPEPDOCK is a novel web server for blind protein-peptide docking through a hierarchical algorithm. Instead of running lengthy simulations to refine peptide conformations, HPEPDOCK considers the peptide flexibility through an ensemble of peptide conformations generated by our MODPEP program. For blind global peptide docking, HPEPDOCK obtained a success rate of 33.3% in binding mode prediction on a benchmark of 57 unbound cases when the top 10 models were considered, compared to 21.1% for pepATTRACT server. HPEPDOCK also performed well in docking against homology models and obtained a success rate of 29.8% within top 10 predictions. For local peptide docking, HPEPDOCK achieved a high success rate of 72.6% on a benchmark of 62 unbound cases within top 10 predictions, compared to 45.2% for HADDOCK peptide protocol. Our HPEPDOCK server is computationally efficient and consumed an average of 29.8 mins for a global peptide docking job and 14.2 mins for a local peptide docking job. The HPEPDOCK web server is available at http://huanglab.phys.hust.edu.cn/hpepdock/.

AnchorDock: Blind and Flexible Anchor-Driven Peptide Docking.

PubMed

Ben-Shimon, Avraham; Niv, Masha Y

2015-05-05

The huge conformational space stemming from the inherent flexibility of peptides is among the main obstacles to successful and efficient computational modeling of protein-peptide interactions. Current peptide docking methods typically overcome this challenge using prior knowledge from the structure of the complex. Here we introduce AnchorDock, a peptide docking approach, which automatically targets the docking search to the most relevant parts of the conformational space. This is done by precomputing the free peptide's structure and by computationally identifying anchoring spots on the protein surface. Next, a free peptide conformation undergoes anchor-driven simulated annealing molecular dynamics simulations around the predicted anchoring spots. In the challenging task of a completely blind docking test, AnchorDock produced exceptionally good results (backbone root-mean-square deviation ≤ 2.2Å, rank ≤15) for 10 of 13 unbound cases tested. The impressive performance of AnchorDock supports a molecular recognition pathway that is driven via pre-existing local structural elements. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem.

PubMed

Ban, Tomohiro; Ohue, Masahito; Akiyama, Yutaka

2018-04-01

The identification of comprehensive drug-target interactions is important in drug discovery. Although numerous computational methods have been developed over the years, a gold standard technique has not been established. Computational ligand docking and structure-based drug design allow researchers to predict the binding affinity between a compound and a target protein, and thus, they are often used to virtually screen compound libraries. In addition, docking techniques have also been applied to the virtual screening of target proteins (inverse docking) to predict target proteins of a drug candidate. Nevertheless, a more accurate docking method is currently required. In this study, we proposed a method in which a predicted ligand-binding site is covered by multiple grids, termed multiple grid arrangement. Notably, multiple grid arrangement facilitates the conformational search for a grid-based ligand docking software and can be applied to the state-of-the-art commercial docking software Glide (Schrödinger, LLC). We validated the proposed method by re-docking with the Astex diverse benchmark dataset and blind binding site situations, which improved the correct prediction rate of the top scoring docking pose from 27.1% to 34.1%; however, only a slight improvement in target prediction accuracy was observed with inverse docking scenarios. These findings highlight the limitations and challenges of current scoring functions and the need for more accurate docking methods. The proposed multiple grid arrangement method was implemented in Glide by modifying a cross-docking script for Glide, xglide.py. The script of our method is freely available online at http://www.bi.cs.titech.ac.jp/mga_glide/. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

The ClusPro web server for protein-protein docking

PubMed Central

Kozakov, Dima; Hall, David R.; Xia, Bing; Porter, Kathryn A.; Padhorny, Dzmitry; Yueh, Christine; Beglov, Dmitri; Vajda, Sandor

2017-01-01

The ClusPro server (https://cluspro.org) is a widely used tool for protein-protein docking. The server provides a simple home page for basic use, requiring only two files in Protein Data Bank format. However, ClusPro also offers a number of advanced options to modify the search that include the removal of unstructured protein regions, applying attraction or repulsion, accounting for pairwise distance restraints, constructing homo-multimers, considering small angle X-ray scattering (SAXS) data, and finding heparin binding sites. Six different energy functions can be used depending on the type of proteins. Docking with each energy parameter set results in ten models defined by centers of highly populated clusters of low energy docked structures. This protocol describes the use of the various options, the construction of auxiliary restraints files, the selection of the energy parameters, and the analysis of the results. Although the server is heavily used, runs are generally completed in < 4 hours. PMID:28079879

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

NASA Astrophysics Data System (ADS)

Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

2017-08-01

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

Drosophila Ack targets its substrate, the sorting nexin DSH3PX1, to a protein complex involved in axonal guidance.

PubMed

Worby, Carolyn A; Simonson-Leff, Nancy; Clemens, James C; Huddler, Donald; Muda, Marco; Dixon, Jack E

2002-03-15

Dock, the Drosophila orthologue of Nck, is an adaptor protein that is known to function in axonal guidance paradigms in the fly including proper development of neuronal connections in photoreceptor cells and axonal tracking in Bolwig's organ. To develop a better understanding of axonal guidance at the molecular level, we purified proteins in a complex with the SH2 domain of Dock from fly Schneider 2 cells. A protein designated p145 was identified and shown to be a tyrosine kinase with sequence similarity to mammalian Cdc-42-associated tyrosine kinases. We demonstrate that Drosophila Ack (DAck) can be co-immunoprecipitated with Dock and DSH3PX1 from fly cell extracts. The domains responsible for the in vitro interaction between Drosophila Ack and Dock were identified, and direct protein-protein interactions between complex members were established. We conclude that DSH3PX1 is a substrate for DAck in vivo and in vitro and define one of the major in vitro sites of DSH3PX1 phosphorylation to be Tyr-56. Tyr-56 is located within the SH3 domain of DSH3PX1, placing it in an important position for regulating the binding of proline-rich targets. We demonstrate that Tyr-56 phosphorylation by DAck diminishes the DSH3PX1 SH3 domain interaction with the Wiskott-Aldrich Syndrome protein while enabling DSH3PX1 to associate with Dock. Furthermore, when Tyr-56 is mutated to aspartate or glutamate, the binding to Wiskott-Aldrich Syndrome protein is abrogated. These results suggest that the phosphorylation of DSH3PX1 by DAck targets this sorting nexin to a protein complex that includes Dock, an adaptor protein important for axonal guidance.

IRaPPA: Information retrieval based integration of biophysical models for protein assembly selection

PubMed Central

Moal, Iain H.; Barradas-Bautista, Didier; Jiménez-García, Brian; Torchala, Mieczyslaw; van der Velde, Arjan; Vreven, Thom; Weng, Zhiping; Bates, Paul A.; Fernández-Recio, Juan

2018-01-01

Motivation In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction. Results Atomic modeling of protein-protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100. Availability IRaPPA has been implemented in the SwarmDock server (http://bmm.crick.ac.uk/~SwarmDock/), pyDock server (http://life.bsc.es/pid/pydockrescoring/) and ZDOCK server (http://zdock.umassmed.edu/), with code available on request. PMID:28200016

Binding analysis for interaction of diacetylcurcumin with β-casein nanoparticles by using fluorescence spectroscopy and molecular docking calculations

NASA Astrophysics Data System (ADS)

Mehranfar, Fahimeh; Bordbar, Abdol-Khalegh; Fani, Najme; Keyhanfar, Mehrnaz

2013-11-01

The interaction of diacetylcurcumin (DAC), as a novel synthetic derivative of curcumin, with bovine β-casein (an abundant milk protein that is highly amphiphilic and self assembles into stable micellar nanoparticles in aqueous solution) was investigated using fluorescence quenching experiments, Forster energy transfer measurements and molecular docking calculations. The fluorescence quenching measurements revealed the presence of a single binding site on β-casein for DAC with the binding constant value equals to (4.40 ± 0.03) × 104 M-1. Forster energy transfer measurements suggested that the distance between bound DAC and Trp143 residue is higher than the respective critical distance, hence, the static quenching is more likely responsible for fluorescence quenching other than the mechanism of non-radiative energy transfer. Our results from molecular docking calculations indicated that binding of DAC to β-casein predominantly occurred through hydrophobic contacts in the hydrophobic core of protein. Additionally, in vitro investigation of the cytotoxicity of free DAC and DAC-β-casein complex in human breast cancer cell line MCF7 revealed the higher cytotoxic effect of DAC-β-casein complex.

AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility

PubMed Central

Ravindranath, Pradeep Anand; Forli, Stefano; Goodsell, David S.; Olson, Arthur J.; Sanner, Michel F.

2015-01-01

Automated docking of drug-like molecules into receptors is an essential tool in structure-based drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: 1) exponential growth of the search space, demanding more efficient search methods; and 2) increased number of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR–AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking experiments are based on two datasets: 1) SEQ17 –a receptor diversity set containing 17 pairs of apo-holo structures; and 2) CDK2 –a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solutions found for 70.6% vs. 35.3% systems on SEQ17, and 76.9% vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in number of top ranking solutions on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on average 79.8% of all pairwise atomic interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we show that down-weighting the receptor internal energy improves the ranking of correctly docked poses and that runtime for AutoDockFR scales linearly when side-chain flexibility is added. PMID:26629955

An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings

NASA Astrophysics Data System (ADS)

Maffucci, Irene; Hu, Xiao; Fumagalli, Valentina; Contini, Alessandro

2018-03-01

Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a number of explicit water molecules that are the closest to the ligand in each frame of a molecular dynamics trajectory. This method demonstrated improved correlations between calculated and experimental binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the standard MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calculations were performed in triplicates on both classic HPC environments and on standard workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to experiments were also observed when performing Nwat-MMGBSA calculations on 4 ns or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or standard MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC β-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20% and 30%, compared to docking scoring or to standard MM-GBSA rescoring.

Homology modeling, molecular dynamics, and docking studies of pattern-recognition transmembrane protein-lipopolysaccharide and β-1,3 glucan-binding protein from Fenneropenaeus indicus.

PubMed

Sivakamavalli, Jeyachandran; Tripathi, Sunil Kumar; Singh, Sanjeev Kumar; Vaseeharan, Baskaralingam

2015-01-01

Lipopolysaccharide and β-1,3 glucan-binding protein (LGBP) is a family of pattern-recognition transmembrane proteins (PRPs) which plays a vital role in the immune mechanism of crustaceans in adverse conditions. Fenneropenaeus indicus LGBP-deduced amino acid has conserved potential recognition motif for β-1,3 linkages of polysaccharides and putative RGD (Arg-Gly-Asp) cell adhesion sites for the activation of innate defense mechanism. In order to understand the stimulating activity of β-1,3 glucan (β-glucan) and its interaction with LGBP, a 3D model of LGBP is generated. Molecular docking is performed with this model, and the results indicate Arg71 with strong hydrogen bond from RGD domain of LGBP. Moreover, from the docking studies, we also suggest that Arg34, Lys68, Val135, and Ala146 in LGBP are important amino acid residues in binding as they have strong bonding interaction in the active site of LGBP. In our in vitro studies, yeast agglutination results suggest that shrimp F. indicus LGBP possesses sugar binding and recognition sites in its structure, which is responsible for agglutination reaction. Our results were synchronized with the already reported evidence both in vivo and in vitro experiments. This investigation may be valuable for further experimental investigation in the synthesis of novel immunomodulator.

A combinatorial approach to protein docking with flexible side chains.

PubMed

Althaus, Ernst; Kohlbacher, Oliver; Lenhof, Hans-Peter; Müller, Peter

2002-01-01

Rigid-body docking approaches are not sufficient to predict the structure of a protein complex from the unbound (native) structures of the two proteins. Accounting for side chain flexibility is an important step towards fully flexible protein docking. This work describes an approach that allows conformational flexibility for the side chains while keeping the protein backbone rigid. Starting from candidates created by a rigid-docking algorithm, we demangle the side chains of the docking site, thus creating reasonable approximations of the true complex structure. These structures are ranked with respect to the binding free energy. We present two new techniques for side chain demangling. Both approaches are based on a discrete representation of the side chain conformational space by the use of a rotamer library. This leads to a combinatorial optimization problem. For the solution of this problem, we propose a fast heuristic approach and an exact, albeit slower, method that uses branch-and-cut techniques. As a test set, we use the unbound structures of three proteases and the corresponding protein inhibitors. For each of the examples, the highest-ranking conformation produced was a good approximation of the true complex structure.

Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information

PubMed Central

Lopes, Anne; Sacquin-Mora, Sophie; Dimitrova, Viktoriya; Laine, Elodie; Ponty, Yann; Carbone, Alessandra

2013-01-01

Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/ PMID:24339765

Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction.

PubMed

Brylinski, Michal

2013-11-25

A common strategy for virtual screening considers a systematic docking of a large library of organic compounds into the target sites in protein receptors with promising leads selected based on favorable intermolecular interactions. Despite a continuous progress in the modeling of protein-ligand interactions for pharmaceutical design, important challenges still remain, thus the development of novel techniques is required. In this communication, we describe eSimDock, a new approach to ligand docking and binding affinity prediction. eSimDock employs nonlinear machine learning-based scoring functions to improve the accuracy of ligand ranking and similarity-based binding pose prediction, and to increase the tolerance to structural imperfections in the target structures. In large-scale benchmarking using the Astex/CCDC data set, we show that 53.9% (67.9%) of the predicted ligand poses have RMSD of <2 Å (<3 Å). Moreover, using binding sites predicted by recently developed eFindSite, eSimDock models ligand binding poses with an RMSD of 4 Å for 50.0-39.7% of the complexes at the protein homology level limited to 80-40%. Simulations against non-native receptor structures, whose mean backbone rearrangements vary from 0.5 to 5.0 Å Cα-RMSD, show that the ratio of docking accuracy and the estimated upper bound is at a constant level of ∼0.65. Pearson correlation coefficient between experimental and predicted by eSimDock Ki values for a large data set of the crystal structures of protein-ligand complexes from BindingDB is 0.58, which decreases only to 0.46 when target structures distorted to 3.0 Å Cα-RMSD are used. Finally, two case studies demonstrate that eSimDock can be customized to specific applications as well. These encouraging results show that the performance of eSimDock is largely unaffected by the deformations of ligand binding regions, thus it represents a practical strategy for across-proteome virtual screening using protein models. eSimDock is freely available to the academic community as a Web server at http://www.brylinski.org/esimdock .

A Message Passing Approach to Side Chain Positioning with Applications in Protein Docking Refinement *

PubMed Central

Moghadasi, Mohammad; Kozakov, Dima; Mamonov, Artem B.; Vakili, Pirooz; Vajda, Sandor; Paschalidis, Ioannis Ch.

2013-01-01

We introduce a message-passing algorithm to solve the Side Chain Positioning (SCP) problem. SCP is a crucial component of protein docking refinement, which is a key step of an important class of problems in computational structural biology called protein docking. We model SCP as a combinatorial optimization problem and formulate it as a Maximum Weighted Independent Set (MWIS) problem. We then employ a modified and convergent belief-propagation algorithm to solve a relaxation of MWIS and develop randomized estimation heuristics that use the relaxed solution to obtain an effective MWIS feasible solution. Using a benchmark set of protein complexes we demonstrate that our approach leads to more accurate docking predictions compared to a baseline algorithm that does not solve the SCP. PMID:23515575

Protein social behavior makes a stronger signal for partner identification than surface geometry.

PubMed

Laine, Elodie; Carbone, Alessandra

2017-01-01

Cells are interactive living systems where proteins movements, interactions and regulation are substantially free from centralized management. How protein physico-chemical and geometrical properties determine who interact with whom remains far from fully understood. We show that characterizing how a protein behaves with many potential interactors in a complete cross-docking study leads to a sharp identification of its cellular/true/native partner(s). We define a sociability index, or S-index, reflecting whether a protein likes or not to pair with other proteins. Formally, we propose a suitable normalization function that accounts for protein sociability and we combine it with a simple interface-based (ranking) score to discriminate partners from non-interactors. We show that sociability is an important factor and that the normalization permits to reach a much higher discriminative power than shape complementarity docking scores. The social effect is also observed with more sophisticated docking algorithms. Docking conformations are evaluated using experimental binding sites. These latter approximate in the best possible way binding sites predictions, which have reached high accuracy in recent years. This makes our analysis helpful for a global understanding of partner identification and for suggesting discriminating strategies. These results contradict previous findings claiming the partner identification problem being solvable solely with geometrical docking. Proteins 2016; 85:137-154. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

PPI4DOCK: large scale assessment of the use of homology models in free docking over more than 1000 realistic targets.

PubMed

Yu, Jinchao; Guerois, Raphaël

2016-12-15

Protein-protein docking methods are of great importance for understanding interactomes at the structural level. It has become increasingly appealing to use not only experimental structures but also homology models of unbound subunits as input for docking simulations. So far we are missing a large scale assessment of the success of rigid-body free docking methods on homology models. We explored how we could benefit from comparative modelling of unbound subunits to expand docking benchmark datasets. Starting from a collection of 3157 non-redundant, high X-ray resolution heterodimers, we developed the PPI4DOCK benchmark containing 1417 docking targets based on unbound homology models. Rigid-body docking by Zdock showed that for 1208 cases (85.2%), at least one correct decoy was generated, emphasizing the efficiency of rigid-body docking in generating correct assemblies. Overall, the PPI4DOCK benchmark contains a large set of realistic cases and provides new ground for assessing docking and scoring methodologies. Benchmark sets can be downloaded from http://biodev.cea.fr/interevol/ppi4dock/ CONTACT: guerois@cea.frSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

istar: a web platform for large-scale protein-ligand docking.

PubMed

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

2014-01-01

Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar is freely available at http://istar.cse.cuhk.edu.hk/idock.

Blind predictions of protein interfaces by docking calculations in CAPRI.

PubMed

Lensink, Marc F; Wodak, Shoshana J

2010-11-15

Reliable prediction of the amino acid residues involved in protein-protein interfaces can provide valuable insight into protein function, and inform mutagenesis studies, and drug design applications. A fast-growing number of methods are being proposed for predicting protein interfaces, using structural information, energetic criteria, or sequence conservation or by integrating multiple criteria and approaches. Overall however, their performance remains limited, especially when applied to nonobligate protein complexes, where the individual components are also stable on their own. Here, we evaluate interface predictions derived from protein-protein docking calculations. To this end we measure the overlap between the interfaces in models of protein complexes submitted by 76 participants in CAPRI (Critical Assessment of Predicted Interactions) and those of 46 observed interfaces in 20 CAPRI targets corresponding to nonobligate complexes. Our evaluation considers multiple models for each target interface, submitted by different participants, using a variety of docking methods. Although this results in a substantial variability in the prediction performance across participants and targets, clear trends emerge. Docking methods that perform best in our evaluation predict interfaces with average recall and precision levels of about 60%, for a small majority (60%) of the analyzed interfaces. These levels are significantly higher than those obtained for nonobligate complexes by most extant interface prediction methods. We find furthermore that a sizable fraction (24%) of the interfaces in models ranked as incorrect in the CAPRI assessment are actually correctly predicted (recall and precision ≥50%), and that these models contribute to 70% of the correct docking-based interface predictions overall. Our analysis proves that docking methods are much more successful in identifying interfaces than in predicting complexes, and suggests that these methods have an excellent potential of addressing the interface prediction challenge. © 2010 Wiley-Liss, Inc.

Extending RosettaDock with water, sugar, and pH for prediction of complex structures and affinities for CAPRI rounds 20-27.

PubMed

Kilambi, Krishna Praneeth; Pacella, Michael S; Xu, Jianqing; Labonte, Jason W; Porter, Justin R; Muthu, Pravin; Drew, Kevin; Kuroda, Daisuke; Schueler-Furman, Ora; Bonneau, Richard; Gray, Jeffrey J

2013-12-01

Rounds 20-27 of the Critical Assessment of PRotein Interactions (CAPRI) provided a testing platform for computational methods designed to address a wide range of challenges. The diverse targets drove the creation of and new combinations of computational tools. In this study, RosettaDock and other novel Rosetta protocols were used to successfully predict four of the 10 blind targets. For example, for DNase domain of Colicin E2-Im2 immunity protein, RosettaDock and RosettaLigand were used to predict the positions of water molecules at the interface, recovering 46% of the native water-mediated contacts. For α-repeat Rep4-Rep2 and g-type lysozyme-PliG inhibitor complexes, homology models were built and standard and pH-sensitive docking algorithms were used to generate structures with interface RMSD values of 3.3 Å and 2.0 Å, respectively. A novel flexible sugar-protein docking protocol was also developed and used for structure prediction of the BT4661-heparin-like saccharide complex, recovering 71% of the native contacts. Challenges remain in the generation of accurate homology models for protein mutants and sampling during global docking. On proteins designed to bind influenza hemagglutinin, only about half of the mutations were identified that affect binding (T55: 54%; T56: 48%). The prediction of the structure of the xylanase complex involving homology modeling and multidomain docking pushed the limits of global conformational sampling and did not result in any successful prediction. The diversity of problems at hand requires computational algorithms to be versatile; the recent additions to the Rosetta suite expand the capabilities to encompass more biologically realistic docking problems. Copyright © 2013 Wiley Periodicals, Inc.

Identification of new 2,5-diketopiperazine derivatives as simultaneous effective inhibitors of αβ-tubulin and BCRP proteins: Molecular docking, Structure-Activity Relationships and virtual consensus docking studies

NASA Astrophysics Data System (ADS)

Fani, Najmeh; Sattarinezhad, Elham; Bordbar, Abdol-Khalegh

2017-06-01

In the first part of this paper, docking method was employed in order to study the binding mechanism of breast cancer resistance protein (BCRP) with a group of previously synthesized TPS-A derivatives which known as potent inhibitors of this protein to get insight into drug binding site of BCRP and to explore structure-activity relationship of these compounds. Molecular docking results showed that most of these compounds bind in the binding site of BCRP at the interface between the membrane and outer environment. In the second part, a group of designed TPS-A derivatives which showed good binding energies in the binding site of αβ-tubulin in the previous study were chosen to study their binding energies in the binding site of BCRP to investigate their simultaneous inhibitory effect on both αβ-tubulin and BCRP. The results showed that all of these compounds bind to the binding site of BCRP with relatively suitable binding energies and therefore could be potential inhibitors of both αβ-tubulin and BCRP proteins. Finally, virtual consensus docking method was utilized with the aim of design of new 2,5-diketopiperazine derivatives with significant inhibitory effect on both αβ-tubulin and BCRP proteins. For this purpose binding energies of a library of 2,5-diketopiperazine derivatives in the binding sites of αβ-tubulin and BCRP was investigated by using AutoDock and AutoDock vina tools. Molecular docking results revealed that a group of 36 compounds among them exhibit strong anti-tubulin and anti-BCRP activity.

Computational exploration of a protein receptor binding space with student proposed peptide ligands.

PubMed

King, Matthew D; Phillips, Paul; Turner, Matthew W; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; McDougal, Owen M

2016-01-01

Computational molecular docking is a fast and effective in silico method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The DockoMatic tutorial described herein provides a framework by which instructors can guide students through a drug screening exercise. Using receptor models derived from readily available protein crystal structures, docking programs have the ability to predict ligand binding properties, such as preferential binding orientations and binding affinities. The use of computational studies can significantly enhance complimentary wet chemical experimentation by providing insight into the important molecular interactions within the system of interest, as well as guide the design of new candidate ligands based on observed binding motifs and energetics. In this laboratory tutorial, the graphical user interface, DockoMatic, facilitates docking job submissions to the docking engine, AutoDock 4.2. The purpose of this exercise is to successfully dock a 17-amino acid peptide, α-conotoxin TxIA, to the acetylcholine binding protein from Aplysia californica-AChBP to determine the most stable binding configuration. Each student will then propose two specific amino acid substitutions of α-conotoxin TxIA to enhance peptide binding affinity, create the mutant in DockoMatic, and perform docking calculations to compare their results with the class. Students will also compare intermolecular forces, binding energy, and geometric orientation of their prepared analog to their initial α-conotoxin TxIA docking results. © 2015 The International Union of Biochemistry and Molecular Biology.

Exploring the Stability of Ligand Binding Modes to Proteins by Molecular Dynamics Simulations: A Cross-docking Study.

PubMed

Liu, Kai; Kokubo, Hironori

2017-10-23

Docking has become an indispensable approach in drug discovery research to predict the binding mode of a ligand. One great challenge in docking is to efficiently refine the correct pose from various putative docking poses through scoring functions. We recently examined the stability of self-docking poses under molecular dynamics (MD) simulations and showed that equilibrium MD simulations have some capability to discriminate between correct and decoy poses. Here, we have extended our previous work to cross-docking studies for practical applications. Three target proteins (thrombin, heat shock protein 90-alpha, and cyclin-dependent kinase 2) of pharmaceutical interest were selected. Three comparable poses (one correct pose and two decoys) for each ligand were then selected from the docking poses. To obtain the docking poses for the three target proteins, we used three different protocols, namely: normal docking, induced fit docking (IFD), and IFD against the homology model. Finally, five parallel MD equilibrium runs were performed on each pose for the statistical analysis. The results showed that the correct poses were generally more stable than the decoy poses under MD. The discrimination capability of MD depends on the strategy. The safest way was to judge a pose as being stable if any one run among five parallel runs was stable under MD. In this case, 95% of the correct poses were retained under MD, and about 25-44% of the decoys could be excluded by the simulations for all cases. On the other hand, if we judge a pose as being stable when any two or three runs were stable, with the risk of incorrectly excluding some correct poses, approximately 31-53% or 39-56% of the two decoys could be excluded by MD, respectively. Our results suggest that simple equilibrium simulations can serve as an effective filter to exclude decoy poses that cannot be distinguished by docking scores from the computationally expensive free-energy calculations.

Accelerating and focusing protein-protein docking correlations using multi-dimensional rotational FFT generating functions.

PubMed

Ritchie, David W; Kozakov, Dima; Vajda, Sandor

2008-09-01

Predicting how proteins interact at the molecular level is a computationally intensive task. Many protein docking algorithms begin by using fast Fourier transform (FFT) correlation techniques to find putative rigid body docking orientations. Most such approaches use 3D Cartesian grids and are therefore limited to computing three dimensional (3D) translational correlations. However, translational FFTs can speed up the calculation in only three of the six rigid body degrees of freedom, and they cannot easily incorporate prior knowledge about a complex to focus and hence further accelerate the calculation. Furthemore, several groups have developed multi-term interaction potentials and others use multi-copy approaches to simulate protein flexibility, which both add to the computational cost of FFT-based docking algorithms. Hence there is a need to develop more powerful and more versatile FFT docking techniques. This article presents a closed-form 6D spherical polar Fourier correlation expression from which arbitrary multi-dimensional multi-property multi-resolution FFT correlations may be generated. The approach is demonstrated by calculating 1D, 3D and 5D rotational correlations of 3D shape and electrostatic expansions up to polynomial order L=30 on a 2 GB personal computer. As expected, 3D correlations are found to be considerably faster than 1D correlations but, surprisingly, 5D correlations are often slower than 3D correlations. Nonetheless, we show that 5D correlations will be advantageous when calculating multi-term knowledge-based interaction potentials. When docking the 84 complexes of the Protein Docking Benchmark, blind 3D shape plus electrostatic correlations take around 30 minutes on a contemporary personal computer and find acceptable solutions within the top 20 in 16 cases. Applying a simple angular constraint to focus the calculation around the receptor binding site produces acceptable solutions within the top 20 in 28 cases. Further constraining the search to the ligand binding site gives up to 48 solutions within the top 20, with calculation times of just a few minutes per complex. Hence the approach described provides a practical and fast tool for rigid body protein-protein docking, especially when prior knowledge about one or both binding sites is available.

In silico screening for inhibitors of p-glycoprotein that target the nucleotide binding domains.

PubMed

Brewer, Frances K; Follit, Courtney A; Vogel, Pia D; Wise, John G

2014-12-01

Multidrug resistances and the failure of chemotherapies are often caused by the expression or overexpression of ATP-binding cassette transporter proteins such as the multidrug resistance protein, P-glycoprotein (P-gp). P-gp is expressed in the plasma membrane of many cell types and protects cells from accumulation of toxins. P-gp uses ATP hydrolysis to catalyze the transport of a broad range of mostly hydrophobic compounds across the plasma membrane and out of the cell. During cancer chemotherapy, the administration of therapeutics often selects for cells which overexpress P-gp, thereby creating populations of cancer cells resistant to a variety of chemically unrelated chemotherapeutics. The present study describes extremely high-throughput, massively parallel in silico ligand docking studies aimed at identifying reversible inhibitors of ATP hydrolysis that target the nucleotide-binding domains of P-gp. We used a structural model of human P-gp that we obtained from molecular dynamics experiments as the protein target for ligand docking. We employed a novel approach of subtractive docking experiments that identified ligands that bound predominantly to the nucleotide-binding domains but not the drug-binding domains of P-gp. Four compounds were found that inhibit ATP hydrolysis by P-gp. Using electron spin resonance spectroscopy, we showed that at least three of these compounds affected nucleotide binding to the transporter. These studies represent a successful proof of principle demonstrating the potential of targeted approaches for identifying specific inhibitors of P-gp. Copyright © 2014 by The American Society for Pharmacology and Experimental Therapeutics.

Exploring the mechanistic insights of Cas scaffolding protein family member 4 with protein tyrosine kinase 2 in Alzheimer's disease by evaluating protein interactions through molecular docking and dynamic simulations.

PubMed

Hassan, Mubashir; Shahzadi, Saba; Alashwal, Hany; Zaki, Nazar; Seo, Sung-Yum; Moustafa, Ahmed A

2018-05-22

Cas scaffolding protein family member 4 and protein tyrosine kinase 2 are signaling proteins, which are involved in neuritic plaques burden, neurofibrillary tangles, and disruption of synaptic connections in Alzheimer's disease. In the current study, a computational approach was employed to explore the active binding sites of Cas scaffolding protein family member 4 and protein tyrosine kinase 2 proteins and their significant role in the activation of downstream signaling pathways. Sequential and structural analyses were performed on Cas scaffolding protein family member 4 and protein tyrosine kinase 2 to identify their core active binding sites. Molecular docking servers were used to predict the common interacting residues in both Cas scaffolding protein family member 4 and protein tyrosine kinase 2 and their involvement in Alzheimer's disease-mediated pathways. Furthermore, the results from molecular dynamic simulation experiment show the stability of targeted proteins. In addition, the generated root mean square deviations and fluctuations, solvent-accessible surface area, and gyration graphs also depict their backbone stability and compactness, respectively. A better understanding of CAS and their interconnected protein signaling cascade may help provide a treatment for Alzheimer's disease. Further, Cas scaffolding protein family member 4 could be used as a novel target for the treatment of Alzheimer's disease by inhibiting the protein tyrosine kinase 2 pathway.

SAMS Acceleration Measurements on Mir (NASA Increment 4)

NASA Technical Reports Server (NTRS)

DeLombard, Richard

1998-01-01

During NASA Increment 4 (January to May 1997), about 5 gigabytes of acceleration data were collected by the Space Acceleration Measurements System (SAMS) onboard the Russian Space Station, Mir. The data were recorded on 28 optical disks which were returned to Earth on STS-84. During this increment, SAMS data were collected in the Priroda module to support the Mir Structural Dynamics Experiment (MiSDE), the Binary Colloidal Alloy Tests (BCAT), Angular Liquid Bridge (ALB), Candle Flames in Microgravity (CFM), Diffusion Controlled Apparatus Module (DCAM), Enhanced Dynamic Load Sensors (EDLS), Forced Flow Flame Spreading Test (FFFr), Liquid Metal Diffusion (LMD), Protein Crystal Growth in Dewar (PCG/Dewar), Queen's University Experiments in Liquid Diffusion (QUELD), and Technical Evaluation of MIM (TEM). This report points out some of the salient features of the microgravity environment to which these experiments were exposed. Also documented are mission events of interest such as the docked phase of STS-84 operations, a Progress engine bum, Soyuz vehicle docking and undocking, and Progress vehicle docking. This report presents an overview of the SAMS acceleration measurements recorded by 10 Hz and 100 Hz sensor heads. The analyses included herein complement those presented in previous summary reports prepared by the Principal Investigator Microgravity Services (PIMS) group.

Validation studies of the site-directed docking program LibDock.

PubMed

Rao, Shashidhar N; Head, Martha S; Kulkarni, Amit; LaLonde, Judith M

2007-01-01

The performance of the site-features docking algorithm LibDock has been evaluated across eight GlaxoSmithKline targets as a follow-up to a broad validation study of docking and scoring software (Warren, G. L.; Andrews, W. C.; Capelli, A.; Clarke, B.; Lalonde, J.; Lambert, M. H.; Lindvall, M.; Nevins, N.; Semus, S. F.; Senger, S.; Tedesco, G.; Walls, I. D.; Woolven, J. M.; Peishoff, C. E.; Head, M. S. J. Med. Chem. 2006, 49, 5912-5931). Docking experiments were performed to assess both the accuracy in reproducing the binding mode of the ligand and the retrieval of active compounds in a virtual screening protocol using both the DJD (Diller, D. J.; Merz, K. M., Jr. Proteins 2001, 43, 113-124) and LigScore2 (Krammer, A. K.; Kirchoff, P. D.; Jiang, X.; Venkatachalam, C. M.; Waldman, M. J. Mol. Graphics Modell. 2005, 23, 395-407) scoring functions. This study was conducted using DJD scoring, and poses were rescored using all available scoring functions in the Accelrys LigandFit module, including LigScore2. For six out of eight targets at least 30% of the ligands were docked within a root-mean-square difference (RMSD) of 2.0 A for the crystallographic poses when the LigScore2 scoring function was used. LibDock retrieved at least 20% of active compounds in the top 10% of screened ligands for four of the eight targets in the virtual screening protocol. In both studies the LigScore2 scoring function enhanced the retrieval of crystallographic poses or active compounds in comparison with the results obtained using the DJD scoring function. The results for LibDock accuracy and ligand retrieval in virtual screening are compared to 10 other docking and scoring programs. These studies demonstrate the utility of the LigScore2 scoring function and that LibDock as a feature directed docking method performs as well as docking programs that use genetic/growing and Monte Carlo driven algorithms.

Pak functions downstream of Dock to regulate photoreceptor axon guidance in Drosophila.

PubMed

Hing, H; Xiao, J; Harden, N; Lim, L; Zipursky, S L

1999-06-25

The SH2/SH3 adaptor protein Dock has been proposed to transduce signals from guidance receptors to the actin cytoskeleton in Drosophila photoreceptor (R cell) growth cones. Here, we demonstrate that Drosophila p21-activated kinase (Pak) is required in a Dock pathway regulating R cell axon guidance and targeting. Dock and Pak colocalize to R cell axons and growth cones, physically interact, and their loss-of-function phenotypes are indistinguishable. Normal patterns of R cell connectivity require Pak's kinase activity and binding sites for both Dock and Cdc42/Rac. A membrane-tethered form of Pak (Pak(myr) acts as a dominant gain-of-function protein. Retinal expression of Pak(myr) rescues the R cell connectivity phenotype in dock mutants. These data establish Pak as a critical regulator of axon guidance and a downstream effector of Dock in vivo.

Predicting protein complex geometries with a neural network.

PubMed

Chae, Myong-Ho; Krull, Florian; Lorenzen, Stephan; Knapp, Ernst-Walter

2010-03-01

A major challenge of the protein docking problem is to define scoring functions that can distinguish near-native protein complex geometries from a large number of non-native geometries (decoys) generated with noncomplexed protein structures (unbound docking). In this study, we have constructed a neural network that employs the information from atom-pair distance distributions of a large number of decoys to predict protein complex geometries. We found that docking prediction can be significantly improved using two different types of polar hydrogen atoms. To train the neural network, 2000 near-native decoys of even distance distribution were used for each of the 185 considered protein complexes. The neural network normalizes the information from different protein complexes using an additional protein complex identity input neuron for each complex. The parameters of the neural network were determined such that they mimic a scoring funnel in the neighborhood of the native complex structure. The neural network approach avoids the reference state problem, which occurs in deriving knowledge-based energy functions for scoring. We show that a distance-dependent atom pair potential performs much better than a simple atom-pair contact potential. We have compared the performance of our scoring function with other empirical and knowledge-based scoring functions such as ZDOCK 3.0, ZRANK, ITScore-PP, EMPIRE, and RosettaDock. In spite of the simplicity of the method and its functional form, our neural network-based scoring function achieves a reasonable performance in rigid-body unbound docking of proteins. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Transient Ligand Docking Sites in Cerebratulus lacteus Mini-Hemoglobin

PubMed Central

Deng, Pengchi; Nienhaus, Karin; Palladino, Pasquale; Olson, John S.; Blouin, George; Moens, Luc; Dewilde, Sylvia; Geuens, Eva; Nienhaus, G. Ulrich

2007-01-01

The monomeric hemoglobin of the nemertean worm Cerebratulus lacteus functions as an oxygen storage protein to maintain neural activity under hypoxic conditions. It shares a large, apolar matrix tunnel with other small hemoglobins, which has been implicated as a potential ligand migration pathway. Here we explore ligand migration and binding within the distal heme pocket, to which the tunnel provides access to ligands from the outside. FTIR/TDS experiments performed at cryogenic temperatures reveal the presence of three transient ligand docking sites within the distal pocket, the primary docking site B on top of pyrrole C and secondary sites C and D. Site C is assigned to a cavity adjacent to the distal portion of the heme pocket, surrounded by the B and E helices. It has an opening to the apolar tunnel and is expected to be on the pathway for ligand entry and exit, whereas site D, circumscribed by TyrB10, GlnE7, and the CD corner, most likely is located on a side pathway of ligand migration. Flash photolysis experiments at ambient temperatures indicate that the rate-limiting step for ligand binding to CerHb is migration through the apolar channel to site C. Movement from C to B and iron-ligand bond formation involve low energy barriers and thus are very rapid processes in the wt protein. PMID:17531406

Protein social behavior makes a stronger signal for partner identification than surface geometry

PubMed Central

Laine, Elodie

2016-01-01

ABSTRACT Cells are interactive living systems where proteins movements, interactions and regulation are substantially free from centralized management. How protein physico‐chemical and geometrical properties determine who interact with whom remains far from fully understood. We show that characterizing how a protein behaves with many potential interactors in a complete cross‐docking study leads to a sharp identification of its cellular/true/native partner(s). We define a sociability index, or S‐index, reflecting whether a protein likes or not to pair with other proteins. Formally, we propose a suitable normalization function that accounts for protein sociability and we combine it with a simple interface‐based (ranking) score to discriminate partners from non‐interactors. We show that sociability is an important factor and that the normalization permits to reach a much higher discriminative power than shape complementarity docking scores. The social effect is also observed with more sophisticated docking algorithms. Docking conformations are evaluated using experimental binding sites. These latter approximate in the best possible way binding sites predictions, which have reached high accuracy in recent years. This makes our analysis helpful for a global understanding of partner identification and for suggesting discriminating strategies. These results contradict previous findings claiming the partner identification problem being solvable solely with geometrical docking. Proteins 2016; 85:137–154. © 2016 Wiley Periodicals, Inc. PMID:27802579

OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery

PubMed Central

Perryman, Alexander L.; Horta Andrade, Carolina

2016-01-01

The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses. PMID:27764115

OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery.

PubMed

Ekins, Sean; Perryman, Alexander L; Horta Andrade, Carolina

2016-10-01

The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses.

Modeling side-chains using molecular dynamics improve recognition of binding region in CAPRI targets.

PubMed

Camacho, Carlos J

2005-08-01

The CAPRI-II experiment added an extra level of complexity to the problem of predicting protein-protein interactions by including 5 targets for which participants had to build or complete the 3-dimensional (3D) structure of either the receptor or ligand based on the structure of a close homolog. In this article, we describe how modeling key side-chains using molecular dynamics (MD) in explicit solvent improved the recognition of the binding region of a free energy- based computational docking method. In particular, we show that MD is able to predict with relatively high accuracy the rotamer conformation of the anchor side-chains important for molecular recognition as suggested by Rajamani et al. (Proc Natl Acad Sci USA 2004;101:11287-11292). As expected, the conformations are some of the most common rotamers for the given residue, while latch side-chains that undergo induced fit upon binding are forced into less common conformations. Using these models as starting conformations in conjunction with the rigid-body docking server ClusPro and the flexible docking algorithm SmoothDock, we produced valuable predictions for 6 of the 9 targets in CAPRI-II, missing only the 3 targets that underwent significant structural rearrangements upon binding. We also show that our free energy- based scoring function, consisting of the sum of van der Waals, Coulombic electrostatic with a distance-dependent dielectric, and desolvation free energy successfully discriminates the nativelike conformation of our submitted predictions. The latter emphasizes the critical role that thermodynamics plays on our methodology, and validates the generality of the algorithm to predict protein interactions.

Docking analysis of verteporfin with YAP WW domain.

PubMed

Kandoussi, Ilham; Lakhlili, Wiame; Taoufik, Jamal; Ibrahimi, Azeddine

2017-01-01

The YAP oncogene is a known cancer target. Therefore, it is of interest to understand the molecular docking interaction of verteporfin (a derivative of benzo-porphyrin) with the WW domain of YAP (clinically used for photo-dynamic therapy in macular degeneration) as a potential WW domain-ligand modulator by inhibition. A homology protein SWISS MODEL of the human YAP protein was constructed to dock (using AutoDock vina) with the PubChem verteporfin structure for interaction analysis. The docking result shows the possibilities of verteporfin interaction with the oncogenic transcription cofactor YAP having WW1 and WW2 domains. Thus, the ability of verteporfin to bind with the YAP WW domain having modulator activity is implied in this analysis.

Microgravity experiments of nano-satellite docking mechanism for final rendezvous approach and docking phase

NASA Astrophysics Data System (ADS)

Ui, Kyoichi; Matunaga, Saburo; Satori, Shin; Ishikawa, Tomohiro

2005-09-01

Laboratory for Space Systems (LSS), Tokyo Institute of Technology (Tokyo Tech) conducted three-dimensional microgravity environment experiments about a docking mechanism for mothership-daughtership (MS-DS) nano-satellite using the facility of Japan Micro Gravity Center (JAMIC) with Hokkaido Institute of Technology (HIT). LSS has studied and developed a docking mechanism for MS-DS nano-satellite system in final rendezvous approach and docking phase since 2000. Consideration of the docking mechanism is to mate a nano-satellite stably while remaining control error of relative velocity and attitude because it is difficult for nano-satellite to have complicated attitude control and mating systems. Objective of the experiments is to verify fundamental grasping function based on our proposed docking methodology. The proposed docking sequence is divided between approach/grasping phase and guiding phase. In the approach/grasping phase, the docking mechanism grasps the nano-satellite even though the nano-satellite has relative position and attitude control errors as well as relative velocity in a docking space. In the guiding function, the docking mechanism guides the nano-satellite to a docking port while adjusting its attitude in order to transfer electrical power and fuel to the nano-satellite. In the paper, we describe the experimental system including the docking mechanism, control system, the daughtership system and the release mechanism, and describe results of microgravity experiments in JAMIC.

InterPred: A pipeline to identify and model protein-protein interactions.

PubMed

Mirabello, Claudio; Wallner, Björn

2017-06-01

Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Magnetic field effect corroborated with docking study to explore photoinduced electron transfer in drug-protein interaction.

PubMed

Chakraborty, Brotati; Roy, Atanu Singha; Dasgupta, Swagata; Basu, Samita

2010-12-30

Conventional spectroscopic tools such as absorption, fluorescence, and circular dichroism spectroscopy used in the study of photoinduced drug-protein interactions can yield useful information about ground-state and excited-state phenomena. However, photoinduced electron transfer (PET) may be a possible phenomenon in the drug-protein interaction, which may go unnoticed if only conventional spectroscopic observations are taken into account. Laser flash photolysis coupled with an external magnetic field can be utilized to confirm the occurrence of PET and authenticate the spin states of the radicals/radical ions formed. In the study of interaction of the model protein human serum albumin (HSA) with acridine derivatives, acridine yellow (AY) and proflavin (PF(+)), conventional spectroscopic tools along with docking study have been used to decipher the binding mechanism, and laser flash photolysis technique with an associated magnetic field (MF) has been used to explore PET. The results of fluorescence study indicate that fluorescence resonance energy transfer takes place from the protein to the acridine-based drugs. Docking study unveils the crucial role of Ser 232 residue of HSA in explaining the differential behavior of the two drugs towards the model protein. Laser flash photolysis experiments help to identify the radicals/radical ions formed in the due course of PET (PF(•), AY(•-), TrpH(•+), Trp(•)), and the application of an external MF has been used to characterize their initial spin-state. Owing to its distance dependence, MF effect gives an idea about the proximity of the radicals/radical ions during interaction in the system and also helps to elucidate the reaction mechanisms. A prominent MF effect is observed in homogeneous buffer medium owing to the pseudoconfinement of the radicals/radical ions provided by the complex structure of the protein.

Knowledge-Guided Docking of WW Domain Proteins and Flexible Ligands

NASA Astrophysics Data System (ADS)

Lu, Haiyun; Li, Hao; Banu Bte Sm Rashid, Shamima; Leow, Wee Kheng; Liou, Yih-Cherng

Studies of interactions between protein domains and ligands are important in many aspects such as cellular signaling. We present a knowledge-guided approach for docking protein domains and flexible ligands. The approach is applied to the WW domain, a small protein module mediating signaling complexes which have been implicated in diseases such as muscular dystrophy and Liddle’s syndrome. The first stage of the approach employs a substring search for two binding grooves of WW domains and possible binding motifs of peptide ligands based on known features. The second stage aligns the ligand’s peptide backbone to the two binding grooves using a quasi-Newton constrained optimization algorithm. The backbone-aligned ligands produced serve as good starting points to the third stage which uses any flexible docking algorithm to perform the docking. The experimental results demonstrate that the backbone alignment method in the second stage performs better than conventional rigid superposition given two binding constraints. It is also shown that using the backbone-aligned ligands as initial configurations improves the flexible docking in the third stage. The presented approach can also be applied to other protein domains that involve binding of flexible ligand to two or more binding sites.

Web-accessible molecular modeling with Rosetta: The Rosetta Online Server that Includes Everyone (ROSIE).

PubMed

Moretti, Rocco; Lyskov, Sergey; Das, Rhiju; Meiler, Jens; Gray, Jeffrey J

2018-01-01

The Rosetta molecular modeling software package provides a large number of experimentally validated tools for modeling and designing proteins, nucleic acids, and other biopolymers, with new protocols being added continually. While freely available to academic users, external usage is limited by the need for expertise in the Unix command line environment. To make Rosetta protocols available to a wider audience, we previously created a web server called Rosetta Online Server that Includes Everyone (ROSIE), which provides a common environment for hosting web-accessible Rosetta protocols. Here we describe a simplification of the ROSIE protocol specification format, one that permits easier implementation of Rosetta protocols. Whereas the previous format required creating multiple separate files in different locations, the new format allows specification of the protocol in a single file. This new, simplified protocol specification has more than doubled the number of Rosetta protocols available under ROSIE. These new applications include pK a determination, lipid accessibility calculation, ribonucleic acid redesign, protein-protein docking, protein-small molecule docking, symmetric docking, antibody docking, cyclic toxin docking, critical binding peptide determination, and mapping small molecule binding sites. ROSIE is freely available to academic users at http://rosie.rosettacommons.org. © 2017 The Protein Society.

From small sweeteners to sweet proteins: anatomy of the binding sites of the human T1R2_T1R3 receptor.

PubMed

Morini, Gabriella; Bassoli, Angela; Temussi, Piero A

2005-08-25

The sweet taste receptor, a heterodimeric G protein coupled receptor (GPCR) protein, formed by the T1R2 and T1R3 subunits, recognizes several sweet compounds including carbohydrates, amino acids, peptides, proteins, and synthetic sweeteners. Its similarity with the metabotropic glutamate mGluR1 receptor allowed us to build homology models. All possible dimers formed by combinations of the human T1R2 and T1R3 subunits, modeled on the A (closed) or B (open) chains of the extracellular ligand binding domain of the mGluR1 template, yield four ligand binding sites for low-molecular-weight sweeteners. These sites were probed by docking a set of molecules representative of all classes of sweet compounds and calculating the free energy of ligand binding. These sites are not easily accessible to sweet proteins, but docking experiments in silico showed that sweet proteins can bind to a secondary site without entering the deep cleft. Our models account for many experimental observations on the tastes of sweeteners, including sweetness synergy, and can help to design new sweeteners.

Exploring the Therapeutic Mechanism of Desmodium styracifolium on Oxalate Crystal-Induced Kidney Injuries Using Comprehensive Approaches Based on Proteomics and Network Pharmacology.

PubMed

Hou, Jiebin; Chen, Wei; Lu, Hongtao; Zhao, Hongxia; Gao, Songyan; Liu, Wenrui; Dong, Xin; Guo, Zhiyong

2018-01-01

Purpose: As a Chinese medicinal herb, Desmodium styracifolium (Osb.) Merr (DS) has been applied clinically to alleviate crystal-induced kidney injuries, but its effective components and their specific mechanisms still need further exploration. This research first combined the methods of network pharmacology and proteomics to explore the therapeutic protein targets of DS on oxalate crystal-induced kidney injuries to provide a reference for relevant clinical use. Methods: Oxalate-induced kidney injury mouse, rat, and HK-2 cell models were established. Proteins differentially expressed between the oxalate and control groups were respectively screened using iTRAQ combined with MALDI-TOF-MS. The common differential proteins of the three models were further analyzed by molecular docking with DS compounds to acquire differential targets. The inverse docking targets of DS were predicted through the platform of PharmMapper. The protein-protein interaction (PPI) relationship between the inverse docking targets and the differential proteins was established by STRING. Potential targets were further validated by western blot based on a mouse model with DS treatment. The effects of constituent compounds, including luteolin, apigenin, and genistein, were investigated based on an oxalate-stimulated HK-2 cell model. Results: Thirty-six common differentially expressed proteins were identified by proteomic analysis. According to previous research, the 3D structures of 15 major constituents of DS were acquired. Nineteen differential targets, including cathepsin D (CTSD), were found using molecular docking, and the component-differential target network was established. Inverse-docking targets including p38 MAPK and CDK-2 were found, and the network of component-reverse docking target was established. Through PPI analysis, 17 inverse-docking targets were linked to differential proteins. The combined network of component-inverse docking target-differential proteins was then constructed. The expressions of CTSD, p-p38 MAPK, and p-CDK-2 were shown to be increased in the oxalate group and decreased in kidney tissue by the DS treatment. Luteolin, apigenin, and genistein could protect oxalate-stimulated tubular cells as active components of DS. Conclusion: The potential targets including the CTSD, p38 MAPK, and CDK2 of DS in oxalate-induced kidney injuries and the active components (luteolin, apigenin, and genistein) of DS were successfully identified in this study by combining proteomics analysis, network pharmacology prediction, and experimental validation.

Application of the docking program SOL for CSAR benchmark.

PubMed

Sulimov, Alexey V; Kutov, Danil C; Oferkin, Igor V; Katkova, Ekaterina V; Sulimov, Vladimir B

2013-08-26

This paper is devoted to results obtained by the docking program SOL and the post-processing program DISCORE at the CSAR benchmark. SOL and DISCORE programs are described. SOL is the original docking program developed on the basis of the genetic algorithm, MMFF94 force field, rigid protein, precalculated energy grid including desolvation in the frame of simplified GB model, vdW, and electrostatic interactions and taking into account the ligand internal strain energy. An important SOL feature is the single- or multi-processor performance for up to hundreds of CPUs. DISCORE improves the binding energy scoring by the local energy optimization of the ligand docked pose and a simple linear regression on the base of available experimental data. The docking program SOL has demonstrated a good ability for correct ligand positioning in the active sites of the tested proteins in most cases of CSAR exercises. SOL and DISCORE have not demonstrated very exciting results on the protein-ligand binding free energy estimation. Nevertheless, for some target proteins, SOL and DISCORE were among the first in prediction of inhibition activity. Ways to improve SOL and DISCORE are discussed.

Elucidating Mechanisms of Molecular Recognition Between Human Argonaute and miRNA Using Computational Approaches.

PubMed

Jiang, Hanlun; Zhu, Lizhe; Héliou, Amélie; Gao, Xin; Bernauer, Julie; Huang, Xuhui

2017-01-01

MicroRNA (miRNA) and Argonaute (AGO) protein together form the RNA-induced silencing complex (RISC) that plays an essential role in the regulation of gene expression. Elucidating the underlying mechanism of AGO-miRNA recognition is thus of great importance not only for the in-depth understanding of miRNA function but also for inspiring new drugs targeting miRNAs. In this chapter we introduce a combined computational approach of molecular dynamics (MD) simulations, Markov state models (MSMs), and protein-RNA docking to investigate AGO-miRNA recognition. Constructed from MD simulations, MSMs can elucidate the conformational dynamics of AGO at biologically relevant timescales. Protein-RNA docking can then efficiently identify the AGO conformations that are geometrically accessible to miRNA. Using our recent work on human AGO2 as an example, we explain the rationale and the workflow of our method in details. This combined approach holds great promise to complement experiments in unraveling the mechanisms of molecular recognition between large, flexible, and complex biomolecules.

WScore: A Flexible and Accurate Treatment of Explicit Water Molecules in Ligand-Receptor Docking.

PubMed

Murphy, Robert B; Repasky, Matthew P; Greenwood, Jeremy R; Tubert-Brohman, Ivan; Jerome, Steven; Annabhimoju, Ramakrishna; Boyles, Nicholas A; Schmitz, Christopher D; Abel, Robert; Farid, Ramy; Friesner, Richard A

2016-05-12

We have developed a new methodology for protein-ligand docking and scoring, WScore, incorporating a flexible description of explicit water molecules. The locations and thermodynamics of the waters are derived from a WaterMap molecular dynamics simulation. The water structure is employed to provide an atomic level description of ligand and protein desolvation. WScore also contains a detailed model for localized ligand and protein strain energy and integrates an MM-GBSA scoring component with these terms to assess delocalized strain of the complex. Ensemble docking is used to take into account induced fit effects on the receptor conformation, and protein reorganization free energies are assigned via fitting to experimental data. The performance of the method is evaluated for pose prediction, rank ordering of self-docked complexes, and enrichment in virtual screening, using a large data set of PDB complexes and compared with the Glide SP and Glide XP models; significant improvements are obtained.

3dRPC: a web server for 3D RNA-protein structure prediction.

PubMed

Huang, Yangyu; Li, Haotian; Xiao, Yi

2018-04-01

RNA-protein interactions occur in many biological processes. To understand the mechanism of these interactions one needs to know three-dimensional (3D) structures of RNA-protein complexes. 3dRPC is an algorithm for prediction of 3D RNA-protein complex structures and consists of a docking algorithm RPDOCK and a scoring function 3dRPC-Score. RPDOCK is used to sample possible complex conformations of an RNA and a protein by calculating the geometric and electrostatic complementarities and stacking interactions at the RNA-protein interface according to the features of atom packing of the interface. 3dRPC-Score is a knowledge-based potential that uses the conformations of nucleotide-amino-acid pairs as statistical variables and that is used to choose the near-native complex-conformations obtained from the docking method above. Recently, we built a web server for 3dRPC. The users can easily use 3dRPC without installing it locally. RNA and protein structures in PDB (Protein Data Bank) format are the only needed input files. It can also incorporate the information of interface residues or residue-pairs obtained from experiments or theoretical predictions to improve the prediction. The address of 3dRPC web server is http://biophy.hust.edu.cn/3dRPC. yxiao@hust.edu.cn.

GREEN: A program package for docking studies in rational drug design

NASA Astrophysics Data System (ADS)

Tomioka, Nobuo; Itai, Akiko

1994-08-01

A program package, GREEN, has been developed that enables docking studies between ligand molecules and a protein molecule. Based on the structure of the protein molecule, the physical and chemical environment of the ligand-binding site is expressed as three-dimensional grid-point data. The grid-point data are used for the real-time evaluation of the protein-ligand interaction energy, as well as for the graphical representation of the binding-site environment. The interactive docking operation is facilitated by various built-in functions, such as energy minimization, energy contribution analysis and logging of the manipulation trajectory. Interactive modeling functions are incorporated for designing new ligand molecules while considering the binding-site environment and the protein-ligand interaction. As an example of the application of GREEN, a docking study is presented on the complex between trypsin and a synthetic trypsin inhibitor. The program package will be useful for rational drug design, based on the 3D structure of the target protein.

Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets.

PubMed

Feinstein, Wei P; Brylinski, Michal

2015-01-01

Computational approaches have emerged as an instrumental methodology in modern research. For example, virtual screening by molecular docking is routinely used in computer-aided drug discovery. One of the critical parameters for ligand docking is the size of a search space used to identify low-energy binding poses of drug candidates. Currently available docking packages often come with a default protocol for calculating the box size, however, many of these procedures have not been systematically evaluated. In this study, we investigate how the docking accuracy of AutoDock Vina is affected by the selection of a search space. We propose a new procedure for calculating the optimal docking box size that maximizes the accuracy of binding pose prediction against a non-redundant and representative dataset of 3,659 protein-ligand complexes selected from the Protein Data Bank. Subsequently, we use the Directory of Useful Decoys, Enhanced to demonstrate that the optimized docking box size also yields an improved ranking in virtual screening. Binding pockets in both datasets are derived from the experimental complex structures and, additionally, predicted by eFindSite. A systematic analysis of ligand binding poses generated by AutoDock Vina shows that the highest accuracy is achieved when the dimensions of the search space are 2.9 times larger than the radius of gyration of a docking compound. Subsequent virtual screening benchmarks demonstrate that this optimized docking box size also improves compound ranking. For instance, using predicted ligand binding sites, the average enrichment factor calculated for the top 1 % (10 %) of the screening library is 8.20 (3.28) for the optimized protocol, compared to 7.67 (3.19) for the default procedure. Depending on the evaluation metric, the optimal docking box size gives better ranking in virtual screening for about two-thirds of target proteins. This fully automated procedure can be used to optimize docking protocols in order to improve the ranking accuracy in production virtual screening simulations. Importantly, the optimized search space systematically yields better results than the default method not only for experimental pockets, but also for those predicted from protein structures. A script for calculating the optimal docking box size is freely available at www.brylinski.org/content/docking-box-size. Graphical AbstractWe developed a procedure to optimize the box size in molecular docking calculations. Left panel shows the predicted binding pose of NADP (green sticks) compared to the experimental complex structure of human aldose reductase (blue sticks) using a default protocol. Right panel shows the docking accuracy using an optimized box size.

Docking analysis of verteporfin with YAP WW domain

PubMed Central

Kandoussi, Ilham; Lakhlili, Wiame; Taoufik, Jamal; Ibrahimi, Azeddine

2017-01-01

The YAP oncogene is a known cancer target. Therefore, it is of interest to understand the molecular docking interaction of verteporfin (a derivative of benzo-porphyrin) with the WW domain of YAP (clinically used for photo-dynamic therapy in macular degeneration) as a potential WW domain-ligand modulator by inhibition. A homology protein SWISS MODEL of the human YAP protein was constructed to dock (using AutoDock vina) with the PubChem verteporfin structure for interaction analysis. The docking result shows the possibilities of verteporfin interaction with the oncogenic transcription cofactor YAP having WW1 and WW2 domains. Thus, the ability of verteporfin to bind with the YAP WW domain having modulator activity is implied in this analysis. PMID:28943729

Docking screens: right for the right reasons?

PubMed

Kolb, Peter; Irwin, John J

2009-01-01

Whereas docking screens have emerged as the most practical way to use protein structure for ligand discovery, an inconsistent track record raises questions about how well docking actually works. In its favor, a growing number of publications report the successful discovery of new ligands, often supported by experimental affinity data and controls for artifacts. Few reports, however, actually test the underlying structural hypotheses that docking makes. To be successful and not just lucky, prospective docking must not only rank a true ligand among the top scoring compounds, it must also correctly orient the ligand so the score it receives is biophysically sound. If the correct binding pose is not predicted, a skeptic might well infer that the discovery was serendipitous. Surveying over 15 years of the docking literature, we were surprised to discover how rarely sufficient evidence is presented to establish whether docking actually worked for the right reasons. The paucity of experimental tests of theoretically predicted poses undermines confidence in a technique that has otherwise become widely accepted. Of course, solving a crystal structure is not always possible, and even when it is, it can be a lot of work, and is not readily accessible to all groups. Even when a structure can be determined, investigators may prefer to gloss over an erroneous structural prediction to better focus on their discovery. Still, the absence of a direct test of theory by experiment is a loss for method developers seeking to understand and improve docking methods. We hope this review will motivate investigators to solve structures and compare them with their predictions whenever possible, to advance the field.

Ensemble pharmacophore meets ensemble docking: a novel screening strategy for the identification of RIPK1 inhibitors

NASA Astrophysics Data System (ADS)

Fayaz, S. M.; Rajanikant, G. K.

2014-07-01

Programmed cell death has been a fascinating area of research since it throws new challenges and questions in spite of the tremendous ongoing research in this field. Recently, necroptosis, a programmed form of necrotic cell death, has been implicated in many diseases including neurological disorders. Receptor interacting serine/threonine protein kinase 1 (RIPK1) is an important regulatory protein involved in the necroptosis and inhibition of this protein is essential to stop necroptotic process and eventually cell death. Current structure-based virtual screening methods involve a wide range of strategies and recently, considering the multiple protein structures for pharmacophore extraction has been emphasized as a way to improve the outcome. However, using the pharmacophoric information completely during docking is very important. Further, in such methods, using the appropriate protein structures for docking is desirable. If not, potential compound hits, obtained through pharmacophore-based screening, may not have correct ranks and scores after docking. Therefore, a comprehensive integration of different ensemble methods is essential, which may provide better virtual screening results. In this study, dual ensemble screening, a novel computational strategy was used to identify diverse and potent inhibitors against RIPK1. All the pharmacophore features present in the binding site were captured using both the apo and holo protein structures and an ensemble pharmacophore was built by combining these features. This ensemble pharmacophore was employed in pharmacophore-based screening of ZINC database. The compound hits, thus obtained, were subjected to ensemble docking. The leads acquired through docking were further validated through feature evaluation and molecular dynamics simulation.

An Effective Approach for Clustering InhA Molecular Dynamics Trajectory Using Substrate-Binding Cavity Features

PubMed Central

Ruiz, Duncan D. A.; Norberto de Souza, Osmar

2015-01-01

Protein receptor conformations, obtained from molecular dynamics (MD) simulations, have become a promising treatment of its explicit flexibility in molecular docking experiments applied to drug discovery and development. However, incorporating the entire ensemble of MD conformations in docking experiments to screen large candidate compound libraries is currently an unfeasible task. Clustering algorithms have been widely used as a means to reduce such ensembles to a manageable size. Most studies investigate different algorithms using pairwise Root-Mean Square Deviation (RMSD) values for all, or part of the MD conformations. Nevertheless, the RMSD only may not be the most appropriate gauge to cluster conformations when the target receptor has a plastic active site, since they are influenced by changes that occur on other parts of the structure. Hence, we have applied two partitioning methods (k-means and k-medoids) and four agglomerative hierarchical methods (Complete linkage, Ward’s, Unweighted Pair Group Method and Weighted Pair Group Method) to analyze and compare the quality of partitions between a data set composed of properties from an enzyme receptor substrate-binding cavity and two data sets created using different RMSD approaches. Ensembles of representative MD conformations were generated by selecting a medoid of each group from all partitions analyzed. We investigated the performance of our new method for evaluating binding conformation of drug candidates to the InhA enzyme, which were performed by cross-docking experiments between a 20 ns MD trajectory and 20 different ligands. Statistical analyses showed that the novel ensemble, which is represented by only 0.48% of the MD conformations, was able to reproduce 75% of all dynamic behaviors within the binding cavity for the docking experiments performed. Moreover, this new approach not only outperforms the other two RMSD-clustering solutions, but it also shows to be a promising strategy to distill biologically relevant information from MD trajectories, especially for docking purposes. PMID:26218832

An Effective Approach for Clustering InhA Molecular Dynamics Trajectory Using Substrate-Binding Cavity Features.

PubMed

De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D A; Norberto de Souza, Osmar

2015-01-01

Protein receptor conformations, obtained from molecular dynamics (MD) simulations, have become a promising treatment of its explicit flexibility in molecular docking experiments applied to drug discovery and development. However, incorporating the entire ensemble of MD conformations in docking experiments to screen large candidate compound libraries is currently an unfeasible task. Clustering algorithms have been widely used as a means to reduce such ensembles to a manageable size. Most studies investigate different algorithms using pairwise Root-Mean Square Deviation (RMSD) values for all, or part of the MD conformations. Nevertheless, the RMSD only may not be the most appropriate gauge to cluster conformations when the target receptor has a plastic active site, since they are influenced by changes that occur on other parts of the structure. Hence, we have applied two partitioning methods (k-means and k-medoids) and four agglomerative hierarchical methods (Complete linkage, Ward's, Unweighted Pair Group Method and Weighted Pair Group Method) to analyze and compare the quality of partitions between a data set composed of properties from an enzyme receptor substrate-binding cavity and two data sets created using different RMSD approaches. Ensembles of representative MD conformations were generated by selecting a medoid of each group from all partitions analyzed. We investigated the performance of our new method for evaluating binding conformation of drug candidates to the InhA enzyme, which were performed by cross-docking experiments between a 20 ns MD trajectory and 20 different ligands. Statistical analyses showed that the novel ensemble, which is represented by only 0.48% of the MD conformations, was able to reproduce 75% of all dynamic behaviors within the binding cavity for the docking experiments performed. Moreover, this new approach not only outperforms the other two RMSD-clustering solutions, but it also shows to be a promising strategy to distill biologically relevant information from MD trajectories, especially for docking purposes.

Comparative study of the interactions between bisphenol-A and its endocrine disrupting analogues with bovine serum albumin using multi-spectroscopic and molecular docking studies.

PubMed

Ikhlas, Shoeb; Usman, Afia; Ahmad, Masood

2018-04-24

Interaction studies of bisphenol analogues; biphenol-A (BPA), bisphenol-B (BPB), and bisphenol-F (BPF) with bovine serum albumin (BSA) were performed using multi-spectroscopic and molecular docking studies at the protein level. The mechanism of binding of bisphenols with BSA was dynamic in nature. SDS refolding experiments demonstrated no stabilization of BSA structure denatured by BPB, however, BSA denatured by BPA and BPF was found to get stabilized. Also, CD spectra and molecular docking studies revealed that BPB bound more strongly and induced more conformational changes in BSA in comparison to BPA. Hence, this study throws light on the replacement of BPA by its analogues and whether the replacement is associated with a possible risk, raising a doubt that perhaps BPB is not a good substitute of BPA.

DOCK2 regulates cell proliferation through Rac and ERK activation in B cell lymphoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Lei; Nishihara, Hiroshi, E-mail: nisihara@patho2.med.hokudai.ac.jp; Kimura, Taichi

2010-04-23

DOCK2; a member of the CDM protein family, regulates cell motility and cytokine production through the activation of Rac in mammalian hematopoietic cells and plays a pivotal role in the modulation of the immune system. Here we demonstrated the alternative function of DOCK2 in hematopoietic tumor cells, especially in terms of its association with the tumor progression. Immunostaining for DOCK2 in 20 cases of human B cell lymphoma tissue specimens including diffuse large B cell lymphoma and follicular lymphoma revealed the prominent expression of DOCK2 in all of the lymphoma cells. DOCK2-knockdown (KD) of the B cell lymphoma cell lines,more » Ramos and Raji, using the lentiviral shRNA system presented decreased cell proliferation compared to the control cells. Furthermore, the tumor formation of DOCK2-KD Ramos cell in nude mice was significantly abrogated. Western blotting analysis and pull-down assay using GST-PAK-RBD kimeric protein suggested the presence of DOCK2-Rac-ERK pathway regulating the cell proliferation of these lymphoma cells. This is the first report to clarify the prominent role of DOCK2 in hematopoietic malignancy.« less

Postprocessing of docked protein-ligand complexes using implicit solvation models.

PubMed

Lindström, Anton; Edvinsson, Lotta; Johansson, Andreas; Andersson, C David; Andersson, Ida E; Raubacher, Florian; Linusson, Anna

2011-02-28

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.

Peptide docking of HIV-1 p24 with single chain fragment variable (scFv) by CDOCKER algorithm

NASA Astrophysics Data System (ADS)

Karim, Hana Atiqah Abdul; Tayapiwatana, Chatchai; Nimmanpipug, Piyarat; Zain, Sharifuddin M.; Rahman, Noorsaadah Abdul; Lee, Vannajan Sanghiran

2014-10-01

In search for the important residues that might have involve in the binding interaction between the p24 caspid protein of HIV-1 fragment (MET68 - PRO90) with the single chain fragment variable (scFv) of FAB23.5, modern computational chemistry approach has been conducted and applied. The p24 fragment was initially taken out from the 1AFV protein molecule consisting of both light (VL) and heavy (VH) chains of FAB23.5 as well as the HIV-1 caspid protein. From there, the p24 (antigen) fragment was made to dock back into the protein pocket receptor (antibody) by using the CDOCKER algorithm to conduct the molecular docking process. The score calculated from the CDOCKER gave 15 possible docked poses with various docked ligand's positions, the interaction energy as well as the binding energy. The best docked pose that imitates the original antigen's position was determined and further processed to the In Situ minimization to obtain the residues interaction energy as well as to observe the hydrogen bonds interaction in the protein-peptide complex. Based on the results demonstrated, the specific residues in the complex that have shown immense lower interaction energies in the 5Å vicinity region from the peptide are from the heavy chain (VH:TYR105) and light chain (VL: ASN31, TYR32, and GLU97). Those residues play vital roles in the binding mechanism of Antibody-Antigen (Ab-Ag) complex of p24 with FAB23.5.

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

PubMed

Strecker, Claas; Meyer, Bernd

2018-05-29

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

Comparing sixteen scoring functions for predicting biological activities of ligands for protein targets.

PubMed

Xu, Weijun; Lucke, Andrew J; Fairlie, David P

2015-04-01

Accurately predicting relative binding affinities and biological potencies for ligands that interact with proteins remains a significant challenge for computational chemists. Most evaluations of docking and scoring algorithms have focused on enhancing ligand affinity for a protein by optimizing docking poses and enrichment factors during virtual screening. However, there is still relatively limited information on the accuracy of commercially available docking and scoring software programs for correctly predicting binding affinities and biological activities of structurally related inhibitors of different enzyme classes. Presented here is a comparative evaluation of eight molecular docking programs (Autodock Vina, Fitted, FlexX, Fred, Glide, GOLD, LibDock, MolDock) using sixteen docking and scoring functions to predict the rank-order activity of different ligand series for six pharmacologically important protein and enzyme targets (Factor Xa, Cdk2 kinase, Aurora A kinase, COX-2, pla2g2a, β Estrogen receptor). Use of Fitted gave an excellent correlation (Pearson 0.86, Spearman 0.91) between predicted and experimental binding only for Cdk2 kinase inhibitors. FlexX and GOLDScore produced good correlations (Pearson>0.6) for hydrophilic targets such as Factor Xa, Cdk2 kinase and Aurora A kinase. By contrast, pla2g2a and COX-2 emerged as difficult targets for scoring functions to predict ligand activities. Although possessing a high hydrophobicity in its binding site, β Estrogen receptor produced reasonable correlations using LibDock (Pearson 0.75, Spearman 0.68). These findings can assist medicinal chemists to better match scoring functions with ligand-target systems for hit-to-lead optimization using computer-aided drug design approaches. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling protein complexes with BiGGER.

PubMed

Krippahl, Ludwig; Moura, José J; Palma, P Nuno

2003-07-01

This article describes the method and results of our participation in the Critical Assessment of PRediction of Interactions (CAPRI) experiment, using the protein docking program BiGGER (Bimolecular complex Generation with Global Evaluation and Ranking) (Palma et al., Proteins 2000;39:372-384). Of five target complexes (CAPRI targets 2, 4, 5, 6, and 7), only one was successfully predicted (target 6), but BiGGER generated reasonable models for targets 4, 5, and 7, which could have been identified if additional biochemical information had been available. Copyright 2003 Wiley-Liss, Inc.

Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.

PubMed

Makeneni, Spandana; Thieker, David F; Woods, Robert J

2018-03-26

In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody-carbohydrate complexes. The protocol was applied to 10 antibody-carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody-carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.

Rescore protein-protein docked ensembles with an interface contact statistics.

PubMed

Mezei, Mihaly

2017-02-01

The recently developed statistical measure for the type of residue-residue contact at protein complex interfaces, based on a parameter-free definition of contact, has been used to define a contact score that is correlated with the likelihood of correctness of a proposed complex structure. Comparing the proposed contact scores on the native structure and on a set of model structures the proposed measure was shown to generally favor the native structure but in itself was not able to reliably score the native structure to be the best. Adjusting the scores of redocking experiments with the contact score showed that the adjusted score was able to move up the ranking of the native-like structure among the proposed complexes when the native-like was not ranked the best by the respective program. Tests on docking of unbound proteins compared the contact scores of the complexes with the contact score of the crystal structure again showing the tendency of the contact score to favor native-like conformations. The possibility of using the contact score to improve the determination of biological dimers in a crystal structure was also explored. Proteins 2017; 85:235-241. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Comparison of ligand migration and binding in heme proteins of the globin family

NASA Astrophysics Data System (ADS)

Karin, Nienhaus; Ulrich Nienhaus, G.

2015-12-01

The binding of small diatomic ligands such as carbon monoxide or dioxygen to heme proteins is among the simplest biological processes known. Still, it has taken many decades to understand the mechanistic aspects of this process in full detail. Here, we compare ligand binding in three heme proteins of the globin family, myoglobin, a dimeric hemoglobin, and neuroglobin. The combination of structural, spectroscopic, and kinetic experiments over many years by many laboratories has revealed common properties of globins and a clear mechanistic picture of ligand binding at the molecular level. In addition to the ligand binding site at the heme iron, a primary ligand docking site exists that ensures efficient ligand binding to and release from the heme iron. Additional, secondary docking sites can greatly facilitate ligand escape after its dissociation from the heme. Although there is only indirect evidence at present, a preformed histidine gate appears to exist that allows ligand entry to and exit from the active site. The importance of these features can be assessed by studies involving modified proteins (via site-directed mutagenesis) and comparison with heme proteins not belonging to the globin family.

Cross-Link Guided Molecular Modeling with ROSETTA

PubMed Central

Leitner, Alexander; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2013-01-01

Chemical cross-links identified by mass spectrometry generate distance restraints that reveal low-resolution structural information on proteins and protein complexes. The technology to reliably generate such data has become mature and robust enough to shift the focus to the question of how these distance restraints can be best integrated into molecular modeling calculations. Here, we introduce three workflows for incorporating distance restraints generated by chemical cross-linking and mass spectrometry into ROSETTA protocols for comparative and de novo modeling and protein-protein docking. We demonstrate that the cross-link validation and visualization software Xwalk facilitates successful cross-link data integration. Besides the protocols we introduce XLdb, a database of chemical cross-links from 14 different publications with 506 intra-protein and 62 inter-protein cross-links, where each cross-link can be mapped on an experimental structure from the Protein Data Bank. Finally, we demonstrate on a protein-protein docking reference data set the impact of virtual cross-links on protein docking calculations and show that an inter-protein cross-link can reduce on average the RMSD of a docking prediction by 5.0 Å. The methods and results presented here provide guidelines for the effective integration of chemical cross-link data in molecular modeling calculations and should advance the structural analysis of particularly large and transient protein complexes via hybrid structural biology methods. PMID:24069194

IRaPPA: information retrieval based integration of biophysical models for protein assembly selection.

PubMed

Moal, Iain H; Barradas-Bautista, Didier; Jiménez-García, Brian; Torchala, Mieczyslaw; van der Velde, Arjan; Vreven, Thom; Weng, Zhiping; Bates, Paul A; Fernández-Recio, Juan

2017-06-15

In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction. Atomic modeling of protein-protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100. IRaPPA has been implemented in the SwarmDock server ( http://bmm.crick.ac.uk/∼SwarmDock/ ), pyDock server ( http://life.bsc.es/pid/pydockrescoring/ ) and ZDOCK server ( http://zdock.umassmed.edu/ ), with code available on request. moal@ebi.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Role of Crk Adaptor Proteins in Cellular Migration and Invasion in Human Breast Cancer

DTIC Science & Technology

2007-03-01

nucleus. To confirm the staining is indeed specific, another antibody specific for CrkII is being tested. Furthermore, cytoplasmic and nuclear...the endogenous CrkL binding partner, Gab1 , which is enhanced upon HGF stimulation (Appendix 16). One final experiment, showing that the CrkLV5 tag...receptor tyrosine kinases, and a docking protein Gab1 , involved in epithelial dispersal and morphogenesis (5, 11, 12). The NH2-terminal SH3 domain of

MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers.

PubMed

Ohue, Masahito; Shimoda, Takehiro; Suzuki, Shuji; Matsuzaki, Yuri; Ishida, Takashi; Akiyama, Yutaka

2014-11-15

The application of protein-protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of >97% strong scaling. MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: http://www.bi.cs.titech.ac.jp/megadock. akiyama@cs.titech.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Ligand Docking to Intermediate and Close-To-Bound Conformers Generated by an Elastic Network Model Based Algorithm for Highly Flexible Proteins

PubMed Central

Kurkcuoglu, Zeynep; Doruker, Pemra

2016-01-01

Incorporating receptor flexibility in small ligand-protein docking still poses a challenge for proteins undergoing large conformational changes. In the absence of bound structures, sampling conformers that are accessible by apo state may facilitate docking and drug design studies. For this aim, we developed an unbiased conformational search algorithm, by integrating global modes from elastic network model, clustering and energy minimization with implicit solvation. Our dataset consists of five diverse proteins with apo to complex RMSDs 4.7–15 Å. Applying this iterative algorithm on apo structures, conformers close to the bound-state (RMSD 1.4–3.8 Å), as well as the intermediate states were generated. Dockings to a sequence of conformers consisting of a closed structure and its “parents” up to the apo were performed to compare binding poses on different states of the receptor. For two periplasmic binding proteins and biotin carboxylase that exhibit hinge-type closure of two dynamics domains, the best pose was obtained for the conformer closest to the bound structure (ligand RMSDs 1.5–2 Å). In contrast, the best pose for adenylate kinase corresponded to an intermediate state with partially closed LID domain and open NMP domain, in line with recent studies (ligand RMSD 2.9 Å). The docking of a helical peptide to calmodulin was the most challenging case due to the complexity of its 15 Å transition, for which a two-stage procedure was necessary. The technique was first applied on the extended calmodulin to generate intermediate conformers; then peptide docking and a second generation stage on the complex were performed, which in turn yielded a final peptide RMSD of 2.9 Å. Our algorithm is effective in producing conformational states based on the apo state. This study underlines the importance of such intermediate states for ligand docking to proteins undergoing large transitions. PMID:27348230

SAMS Acceleration Measurements on Mir From January to May 1997 (NASA Increment 4)

NASA Technical Reports Server (NTRS)

DeLombard, Richard

1998-01-01

During NASA Increment 4 (January to May 1997), about 5 gigabytes of acceleration data were collected by the Space Acceleration Measurements System (SAMS) onboard the Russian Space Station, Mir. The data were recorded on 28 optical disks which were returned to Earth on STS-84. During this increment, SAMS data were collected in the Priroda module to support the Mir Structural Dynamics Experiment (MiSDE), the Binary Colloidal Alloy Tests (BCAT), Angular Liquid Bridge (ALB), Candle Flames in Microgravity (CFM), Diffusion Controlled Apparatus Module (DCAM), Enhanced Dynamic Load Sensors (EDLS), Forced Flow Flame Spreading Test (FFFT), Liquid Metal Diffusion (LMD), Protein Crystal Growth in Dewar (PCG/Dewar), Queen's University Experiments in Liquid Diffusion (QUELD), and Technical Evaluation of MIM (TEM). This report points out some of the salient features of the microgravity environment to which these experiments were exposed. Also documented are mission events of interest such as the docked phase of STS-84 operations, a Progress engine burn, Soyuz vehicle docking and undocking, and Progress vehicle docking. This report presents an overview of the SAMS acceleration measurements recorded by 10 Hz and 100 Hz sensor heads. The analyses included herein complement those presented in previous summary reports prepared by the Principal Investigator Microgravity Services (PIMS) group.

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins.

PubMed

Akbal-Delibas, Bahar; Haspel, Nurit

2013-01-01

We introduce a protein docking refinement method that accepts complexes consisting of any number of monomeric units. The method uses a scoring function based on a tight coupling between evolutionary conservation, geometry and physico-chemical interactions. Understanding the role of protein complexes in the basic biology of organisms heavily relies on the detection of protein complexes and their structures. Different computational docking methods are developed for this purpose, however, these methods are often not accurate and their results need to be further refined to improve the geometry and the energy of the resulting complexes. Also, despite the fact that complexes in nature often have more than two monomers, most docking methods focus on dimers since the computational complexity increases exponentially due to the addition of monomeric units. Our results show that the refinement scheme can efficiently handle complexes with more than two monomers by biasing the results towards complexes with native interactions, filtering out false positive results. Our refined complexes have better IRMSDs with respect to the known complexes and lower energies than those initial docked structures. Evolutionary conservation information allows us to bias our results towards possible functional interfaces, and the probabilistic selection scheme helps us to escape local energy minima. We aim to incorporate our refinement method in a larger framework which also enables docking of multimeric complexes given only monomeric structures.

Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

PubMed Central

Whisenant, Thomas C.; Ho, David T.; Benz, Ryan W.; Rogers, Jeffrey S.; Kaake, Robyn M.; Gordon, Elizabeth A.; Huang, Lan; Baldi, Pierre; Bardwell, Lee

2010-01-01

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new ‘D-site’ class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates. PMID:20865152

Molecular docking of superantigens with class II major histocompatibility complex proteins.

PubMed

Olson, M A; Cuff, L

1997-01-01

The molecular recognition of two superantigens with class II major histocompatibility complex molecules was simulated by using protein-protein docking. Superantigens studied were staphylococcal enterotoxin B (SEB) and toxic shock syndrome toxin-1 (TSST-1) in their crystallographic assemblies with HLA-DR1. Rigid-body docking was performed sampling configurational space of the interfacial surfaces by employing a strategy of partitioning the contact regions on HLA-DR1 into separate molecular recognition units. Scoring of docked conformations was based on an electrostatic continuum model evaluated with the finite-difference Poisson-Boltzmann method. Estimates of nonpolar contributions were derived from the buried molecular surface areas. We found for both superantigens that docking the HLA-DR1 surface complementary with the SEB and TSST-1 contact regions containing a homologous hydrophobic surface loop provided sufficient recognition for the reconstitution of native-like conformers exhibiting the highest-scoring free energies. For the SEB complex, the calculations were successful in reproducing the total association free energy. A comparison of the free-energy determinants of the conserved hydrophobic contact residue indicates functional similarity between the two proteins for this interface. Though both superantigens share a common global association mode, differences in binding topology distinguish the conformational specificities underlying recognition.

BiGGER: a new (soft) docking algorithm for predicting protein interactions.

PubMed

Palma, P N; Krippahl, L; Wampler, J E; Moura, J J

2000-06-01

A new computationally efficient and automated "soft docking" algorithm is described to assist the prediction of the mode of binding between two proteins, using the three-dimensional structures of the unbound molecules. The method is implemented in a software package called BiGGER (Bimolecular Complex Generation with Global Evaluation and Ranking) and works in two sequential steps: first, the complete 6-dimensional binding spaces of both molecules is systematically searched. A population of candidate protein-protein docked geometries is thus generated and selected on the basis of the geometric complementarity and amino acid pairwise affinities between the two molecular surfaces. Most of the conformational changes observed during protein association are treated in an implicit way and test results are equally satisfactory, regardless of starting from the bound or the unbound forms of known structures of the interacting proteins. In contrast to other methods, the entire molecular surfaces are searched during the simulation, using absolutely no additional information regarding the binding sites. In a second step, an interaction scoring function is used to rank the putative docked structures. The function incorporates interaction terms that are thought to be relevant to the stabilization of protein complexes. These include: geometric complementarity of the surfaces, explicit electrostatic interactions, desolvation energy, and pairwise propensities of the amino acid side chains to contact across the molecular interface. The relative functional contribution of each of these interaction terms to the global scoring function has been empirically adjusted through a neural network optimizer using a learning set of 25 protein-protein complexes of known crystallographic structures. In 22 out of 25 protein-protein complexes tested, near-native docked geometries were found with C(alpha) RMS deviations < or =4.0 A from the experimental structures, of which 14 were found within the 20 top ranking solutions. The program works on widely available personal computers and takes 2 to 8 hours of CPU time to run any of the docking tests herein presented. Finally, the value and limitations of the method for the study of macromolecular interactions, not yet revealed by experimental techniques, are discussed.

Exportin Crm1 is repurposed as a docking protein to generate microtubule organizing centers at the nuclear pore.

PubMed

Bao, Xun X; Spanos, Christos; Kojidani, Tomoko; Lynch, Eric M; Rappsilber, Juri; Hiraoka, Yasushi; Haraguchi, Tokuko; Sawin, Kenneth E

2018-05-29

Non-centrosomal microtubule organizing centers (MTOCs) are important for microtubule organization in many cell types. In fission yeast Schizosaccharomyces pombe , the protein Mto1, together with partner protein Mto2 (Mto1/2 complex), recruits the g-tubulin complex to multiple non-centrosomal MTOCs, including the nuclear envelope (NE). Here, we develop a comparative-interactome mass spectrometry approach to determine how Mto1 localizes to the NE. Surprisingly, we find that Mto1, a constitutively cytoplasmic protein, docks at nuclear pore complexes (NPCs), via interaction with exportin Crm1 and cytoplasmic FG-nucleoporin Nup146. Although Mto1 is not a nuclear export cargo, it binds Crm1 via a nuclear export signal-like sequence, and docking requires both Ran in the GTP-bound state and Nup146 FG repeats. In addition to determining the mechanism of MTOC formation at the NE, our results reveal a novel role for Crm1 and the nuclear export machinery in the stable docking of a cytoplasmic protein complex at NPCs. © 2018, Bao et al.

Exportin Crm1 is repurposed as a docking protein to generate microtubule organizing centers at the nuclear pore

PubMed Central

Bao, Xun X; Spanos, Christos; Kojidani, Tomoko; Lynch, Eric M; Rappsilber, Juri; Hiraoka, Yasushi; Haraguchi, Tokuko

2018-01-01

Non-centrosomal microtubule organizing centers (MTOCs) are important for microtubule organization in many cell types. In fission yeast Schizosaccharomyces pombe, the protein Mto1, together with partner protein Mto2 (Mto1/2 complex), recruits the γ-tubulin complex to multiple non-centrosomal MTOCs, including the nuclear envelope (NE). Here, we develop a comparative-interactome mass spectrometry approach to determine how Mto1 localizes to the NE. Surprisingly, we find that Mto1, a constitutively cytoplasmic protein, docks at nuclear pore complexes (NPCs), via interaction with exportin Crm1 and cytoplasmic FG-nucleoporin Nup146. Although Mto1 is not a nuclear export cargo, it binds Crm1 via a nuclear export signal-like sequence, and docking requires both Ran in the GTP-bound state and Nup146 FG repeats. In addition to determining the mechanism of MTOC formation at the NE, our results reveal a novel role for Crm1 and the nuclear export machinery in the stable docking of a cytoplasmic protein complex at NPCs. PMID:29809148

Assessing the applicability of template-based protein docking in the twilight zone.

PubMed

Negroni, Jacopo; Mosca, Roberto; Aloy, Patrick

2014-09-02

The structural modeling of protein interactions in the absence of close homologous templates is a challenging task. Recently, template-based docking methods have emerged to exploit local structural similarities to help ab-initio protocols provide reliable 3D models for protein interactions. In this work, we critically assess the performance of template-based docking in the twilight zone. Our results show that, while it is possible to find templates for nearly all known interactions, the quality of the obtained models is rather limited. We can increase the precision of the models at expenses of coverage, but it drastically reduces the potential applicability of the method, as illustrated by the whole-interactome modeling of nine organisms. Template-based docking is likely to play an important role in the structural characterization of the interaction space, but we still need to improve the repertoire of structural templates onto which we can reliably model protein complexes. Copyright © 2014 Elsevier Ltd. All rights reserved.

in silico identification of cross affinity towards Cry1Ac pesticidal protein with receptor enzyme in Bos taurus and sequence, structure analysis of crystal proteins for stability.

PubMed

Ebenezer, King Solomon; Nachimuthu, Ramesh; Thiagarajan, Prabha; Velu, Rajesh Kannan

2013-01-01

Any novel protein introduced into the GM crops need to be evaluated for cross affinity on living organisms. Many researchers are currently focusing on the impact of Bacillus thuringiensis cotton on soil and microbial diversity by field experiments. In spite of this, in silico approach might be helpful to elucidate the impact of cry genes. The crystal a protein which was produced by Bt at the time of sporulation has been used as a biological pesticide to target the insectivorous pests like Cry1Ac for Helicoverpa armigera and Cry2Ab for Spodoptera sp. and Heliothis sp. Here, we present the comprehensive in silico analysis of Cry1Ac and Cry2Ab proteins with available in silico tools, databases and docking servers. Molecular docking of Cry1Ac with procarboxypeptidase from Helicoverpa armigera and Cry1Ac with Leucine aminopeptidase from Bos taurus has showed the 125(th) amino acid position to be the preference site of Cry1Ac protein. The structures were compared with each other and it showed 5% of similarity. The cross affinity of this toxin that have confirmed the earlier reports of ill effects of Bt cotton consumed by cattle.

Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins

PubMed Central

de Beauchene, Isaure Chauvot; de Vries, Sjoerd J.; Zacharias, Martin

2016-01-01

Abstract Protein-RNA complexes are important for many biological processes. However, structural modeling of such complexes is hampered by the high flexibility of RNA. Particularly challenging is the docking of single-stranded RNA (ssRNA). We have developed a fragment-based approach to model the structure of ssRNA bound to a protein, based on only the protein structure, the RNA sequence and conserved contacts. The conformational diversity of each RNA fragment is sampled by an exhaustive library of trinucleotides extracted from all known experimental protein–RNA complexes. The method was applied to ssRNA with up to 12 nucleotides which bind to dimers of the RNA recognition motifs (RRMs), a highly abundant eukaryotic RNA-binding domain. The fragment based docking allows a precise de novo atomic modeling of protein-bound ssRNA chains. On a benchmark of seven experimental ssRNA–RRM complexes, near-native models (with a mean heavy-atom deviation of <3 Å from experiment) were generated for six out of seven bound RNA chains, and even more precise models (deviation < 2 Å) were obtained for five out of seven cases, a significant improvement compared to the state of the art. The method is not restricted to RRMs but was also successfully applied to Pumilio RNA binding proteins. PMID:27131381

GalaxyHomomer: a web server for protein homo-oligomer structure prediction from a monomer sequence or structure.

PubMed

Baek, Minkyung; Park, Taeyong; Heo, Lim; Park, Chiwook; Seok, Chaok

2017-07-03

Homo-oligomerization of proteins is abundant in nature, and is often intimately related with the physiological functions of proteins, such as in metabolism, signal transduction or immunity. Information on the homo-oligomer structure is therefore important to obtain a molecular-level understanding of protein functions and their regulation. Currently available web servers predict protein homo-oligomer structures either by template-based modeling using homo-oligomer templates selected from the protein structure database or by ab initio docking of monomer structures resolved by experiment or predicted by computation. The GalaxyHomomer server, freely accessible at http://galaxy.seoklab.org/homomer, carries out template-based modeling, ab initio docking or both depending on the availability of proper oligomer templates. It also incorporates recently developed model refinement methods that can consistently improve model quality. Moreover, the server provides additional options that can be chosen by the user depending on the availability of information on the monomer structure, oligomeric state and locations of unreliable/flexible loops or termini. The performance of the server was better than or comparable to that of other available methods when tested on benchmark sets and in a recent CASP performed in a blind fashion. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Dimerization of a flocculent protein from Moringa oleifera: experimental evidence and in silico interpretation.

PubMed

Pavankumar, Asalapuram R; Kayathri, Rajarathinam; Murugan, Natarajan A; Zhang, Qiong; Srivastava, Vaibhav; Okoli, Chuka; Bulone, Vincent; Rajarao, Gunaratna K; Ågren, Hans

2014-01-01

Many proteins exist in dimeric and other oligomeric forms to gain stability and functional advantages. In this study, the dimerization property of a coagulant protein (MO2.1) from Moringa oleifera seeds was addressed through laboratory experiments, protein-protein docking studies and binding free energy calculations. The structure of MO2.1 was predicted by homology modelling, while binding free energy and residues-distance profile analyses provided insight into the energetics and structural factors for dimer formation. Since the coagulation activities of the monomeric and dimeric forms of MO2.1 were comparable, it was concluded that oligomerization does not affect the biological activity of the protein.

Dock mediates Scar- and WASp-dependent actin polymerization through interaction with cell adhesion molecules in founder cells and fusion-competent myoblasts.

PubMed

Kaipa, Balasankara Reddy; Shao, Huanjie; Schäfer, Gritt; Trinkewitz, Tatjana; Groth, Verena; Liu, Jianqi; Beck, Lothar; Bogdan, Sven; Abmayr, Susan M; Önel, Susanne-Filiz

2013-01-01

The formation of the larval body wall musculature of Drosophila depends on the asymmetric fusion of two myoblast types, founder cells (FCs) and fusion-competent myoblasts (FCMs). Recent studies have established an essential function of Arp2/3-based actin polymerization during myoblast fusion, formation of a dense actin focus at the site of fusion in FCMs, and a thin sheath of actin in FCs and/or growing muscles. The formation of these actin structures depends on recognition and adhesion of myoblasts that is mediated by cell surface receptors of the immunoglobulin superfamily. However, the connection of the cell surface receptors with Arp2/3-based actin polymerization is poorly understood. To date only the SH2-SH3 adaptor protein Crk has been suggested to link cell adhesion with Arp2/3-based actin polymerization in FCMs. Here, we propose that the SH2-SH3 adaptor protein Dock, like Crk, links cell adhesion with actin polymerization. We show that Dock is expressed in FCs and FCMs and colocalizes with the cell adhesion proteins Sns and Duf at cell-cell contact points. Biochemical data in this study indicate that different domains of Dock are involved in binding the cell adhesion molecules Duf, Rst, Sns and Hbs. We emphasize the importance of these interactions by quantifying the enhanced myoblast fusion defects in duf dock, sns dock and hbs dock double mutants. Additionally, we show that Dock interacts biochemically and genetically with Drosophila Scar, Vrp1 and WASp. Based on these data, we propose that Dock links cell adhesion in FCs and FCMs with either Scar- or Vrp1-WASp-dependent Arp2/3 activation.

The Drosophila SH2-SH3 adapter protein Dock is expressed in embryonic axons and facilitates synapse formation by the RP3 motoneuron.

PubMed

Desai, C J; Garrity, P A; Keshishian, H; Zipursky, S L; Zinn, K

1999-04-01

The Dock SH2-SH3 domain adapter protein, a homolog of the mammalian Nck oncoprotein, is required for axon guidance and target recognition by photoreceptor axons in Drosophila larvae. Here we show that Dock is widely expressed in neurons and at muscle attachment sites in the embryo, and that this expression pattern has both maternal and zygotic components. In motoneurons, Dock is concentrated in growth cones. Loss of zygotic dock function causes a selective delay in synapse formation by the RP3 motoneuron at the cleft between muscles 7 and 6. These muscles often completely lack innervation in late stage 16 dock mutant embryos. RP3 does form a synapse later in development, however, because muscles 7 and 6 are normally innervated in third-instar mutant larvae. The absence of zygotically expressed Dock also results in subtle defects in a longitudinal axon pathway in the embryonic central nervous system. Concomitant loss of both maternally and zygotically derived Dock dramatically enhances these central nervous system defects, but does not increase the delay in RP3 synaptogenesis. These results indicate that Dock facilitates synapse formation by the RP3 motoneuron and is also required for guidance of some interneuronal axons The involvement of Dock in the conversion of the RP3 growth cone into a presynaptic terminal may reflect a role for Dock-mediated signaling in remodeling of the growth cone's cytoskeleton.

Molecular Docking Studies of Flavonoids Derivatives on the Flavonoid 3- O-Glucosyltransferase.

PubMed

Harsa, Alexandra M; Harsa, Teodora E; Diudea, Mircea V; Janezic, Dusanka

2015-01-01

A study of 30 flavonoid derivatives, taken from PubChem database and docked on flavonoid 3-O-glucosyltransferase 3HBF, next submitted to a QSAR study, performed within a hypermolecule frame, to model their LD50 values, is reported. The initial set of molecules was split into a training set and the test set (taken from the best scored molecules in the docking test); the predicted LD50 values, computed on similarity clusters, built up for each of the molecules of the test set, surpassed in accuracy the best model. The binding energies to 3HBF protein, provided by the docking step, are not related to the LD50 of these flavonoids, more protein targets are to be investigated in this respect. However, the docking step was useful in choosing the test set of molecules.

Knowing when to give up: early-rejection stratagems in ligand docking

NASA Astrophysics Data System (ADS)

Skone, Gwyn; Voiculescu, Irina; Cameron, Stephen

2009-10-01

Virtual screening is an important resource in the drug discovery community, of which protein-ligand docking is a significant part. Much software has been developed for this purpose, largely by biochemists and those in related disciplines, who pursue ever more accurate representations of molecular interactions. The resulting tools, however, are very processor-intensive. This paper describes some initial results from a project to review computational chemistry techniques for docking from a non-chemistry standpoint. An abstract blueprint for protein-ligand docking using empirical scoring functions is suggested, and this is used to discuss potential improvements. By introducing computer science tactics such as lazy function evaluation, dramatic increases to throughput can and have been realized using a real-world docking program. Naturally, they can be extended to any system that approximately corresponds to the architecture outlined.

[Supercomputer investigation of the protein-ligand system low-energy minima].

PubMed

Oferkin, I V; Sulimov, A V; Katkova, E V; Kutov, D K; Grigoriev, F V; Kondakova, O A; Sulimov, V B

2015-01-01

The accuracy of the protein-ligand binding energy calculations and ligand positioning is strongly influenced by the choice of the docking target function. This work demonstrates the evaluation of the five different target functions used in docking: functions based on MMFF94 force field and functions based on PM7 quantum-chemical method accounting or without accounting the implicit solvent model (PCM, COSMO or SGB). For these purposes the ligand positions corresponding to the minima of the target function and the experimentally known ligand positions in the protein active site (crystal ligand positions) were compared. Each function was examined on the same test-set of 16 protein-ligand complexes. The new parallelized docking program FLM based on Monte Carlo search algorithm was developed to perform the comprehensive low-energy minima search and to calculate the protein-ligand binding energy. This study demonstrates that the docking target function based on the MMFF94 force field can be used to detect the crystal or near crystal positions of the ligand by the finding the low-energy local minima spectrum of the target function. The importance of solvent accounting in the docking process for the accurate ligand positioning is also shown. The accuracy of the ligand positioning as well as the correlation between the calculated and experimentally determined protein-ligand binding energies are improved when the MMFF94 force field is substituted by the new PM7 method with implicit solvent accounting.

The binding domain of the HMGB1 inhibitor carbenoxolone: Theory and experiment

NASA Astrophysics Data System (ADS)

Mollica, Luca; Curioni, Alessandro; Andreoni, Wanda; Bianchi, Marco E.; Musco, Giovanna

2008-05-01

We present a combined computational and experimental study of the interaction of the Box A of the HMGB1 protein and carbenoxolone, an inhibitor of its pro-inflammatory activity. The computational approach consists of classical molecular dynamics (MD) simulations based on the GROMOS force field with quantum-refined (QRFF) atomic charges for the ligand. Experimental data consist of fluorescence intensities, chemical shift displacements, saturation transfer differences and intermolecular Nuclear Overhauser Enhancement signals. Good agreement is found between observations and the conformation of the ligand-protein complex resulting from QRFF-MD. In contrast, simple docking procedures and MD based on the unrefined force field provide models inconsistent with experiment. The ligand-protein binding is dominated by non-directional interactions.

Isolation of anticancer drug TAXOL from Pestalotiopsis breviseta with apoptosis and B-Cell lymphoma protein docking studies.

PubMed

Kathiravan, G; Sureban, Sripathi M; Sree, Harsha N; Bhuvaneshwari, V; Kramony, Evelin

2012-12-01

Extraction and investigation of TAXOL from Pestalotiopsis breviseta (Sacc.) using protein docking, which is a computational technique that samples conformations of small molecules in protein-binding sites. Scoring functions are used to assess which of these conformations best complements the protein binding site and active site prediction. Coelomycetous fungi P. breviseta (Sacc.) Steyaert was screened for the production of TAXOL, an anticancer drug. TAXOL PRODUCTION WAS CONFIRMED BY THE FOLLOWING METHODS: Ultraviolet (UV) spectroscopic analysis, Infrared analysis, High performance liquid chromatography analysis (HPLC), and Liquid chromatography mass spectrum (LC-MASS). TAXOL produced by the fungi was compared with authentic TAXOL, and protein docking studies were performed. The BCL2 protein of human origin showed a higher affinity toward the compound paclitaxel. It has the binding energy value of -13.0061 (KJ/Mol) with four hydrogen bonds.

Isolation of anticancer drug TAXOL from Pestalotiopsis breviseta with apoptosis and B-Cell lymphoma protein docking studies

PubMed Central

Kathiravan, G.; Sureban, Sripathi M.; Sree, Harsha N.; Bhuvaneshwari, V.; Kramony, Evelin

2012-01-01

Background: Extraction and investigation of TAXOL from Pestalotiopsis breviseta (Sacc.) using protein docking, which is a computational technique that samples conformations of small molecules in protein-binding sites. Scoring functions are used to assess which of these conformations best complements the protein binding site and active site prediction. Materials and Methods: Coelomycetous fungi P. breviseta (Sacc.) Steyaert was screened for the production of TAXOL, an anticancer drug. Results: TAXOL production was confirmed by the following methods: Ultraviolet (UV) spectroscopic analysis, Infrared analysis, High performance liquid chromatography analysis (HPLC), and Liquid chromatography mass spectrum (LC-MASS). TAXOL produced by the fungi was compared with authentic TAXOL, and protein docking studies were performed. Conclusion: The BCL2 protein of human origin showed a higher affinity toward the compound paclitaxel. It has the binding energy value of −13.0061 (KJ/Mol) with four hydrogen bonds. PMID:24808664

Domain requirements for the Dock adapter protein in growth- cone signaling.

PubMed

Rao, Y; Zipursky, S L

1998-03-03

Tyrosine phosphorylation has been implicated in growth-cone guidance through genetic, biochemical, and pharmacological studies. Adapter proteins containing src homology 2 (SH2) domains and src homology 3 (SH3) domains provide a means of linking guidance signaling through phosphotyrosine to downstream effectors regulating growth-cone motility. The Drosophila adapter, Dreadlocks (Dock), the homolog of mammalian Nck containing three N-terminal SH3 domains and a single SH2 domain, is highly specialized for growth-cone guidance. In this paper, we demonstrate that Dock can couple signals in either an SH2-dependent or an SH2-independent fashion in photoreceptor (R cell) growth cones, and that Dock displays different domain requirements in different neurons.

Simulation of carbohydrates, from molecular docking to dynamics in water.

PubMed

Sapay, Nicolas; Nurisso, Alessandra; Imberty, Anne

2013-01-01

Modeling of carbohydrates is particularly challenging because of the variety of structures resulting for the high number of monosaccharides and possible linkages and also because of their intrinsic flexibility. The development of carbohydrate parameters for molecular modeling is still an active field. Nowadays, main carbohydrates force fields are GLYCAM06, CHARMM36, and GROMOS 45A4. GLYCAM06 includes the largest choice of compounds and is compatible with the AMBER force fields and associated. Furthermore, AMBER includes tools for the implementation of new parameters. When looking at protein-carbohydrate interaction, the choice of the starting structure is of importance. Such complex can be sometimes obtained from the Protein Data Bank-although the stereochemistry of sugars may require some corrections. When no experimental data is available, molecular docking simulation is generally used to the obtain protein-carbohydrate complex coordinates. As molecular docking parameters are not specifically dedicated to carbohydrates, inaccuracies should be expected, especially for the docking of polysaccharides. This issue can be addressed at least partially by combining molecular docking with molecular dynamics simulation in water.

Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy.

PubMed

Therrien, Eric; Weill, Nathanael; Tomberg, Anna; Corbeil, Christopher R; Lee, Devin; Moitessier, Nicolas

2014-11-24

The use of predictive computational methods in the drug discovery process is in a state of continual growth. Over the last two decades, an increasingly large number of docking tools have been developed to identify hits or optimize lead molecules through in-silico screening of chemical libraries to proteins. In recent years, the focus has been on implementing protein flexibility and water molecules. Our efforts led to the development of Fitted first reported in 2007 and further developed since then. In this study, we wished to evaluate the impact of protein flexibility and occurrence of water molecules on the accuracy of the Fitted docking program to discriminate active compounds from inactive compounds in virtual screening (VS) campaigns. For this purpose, a total of 171 proteins cocrystallized with small molecules representing 40 unique enzymes and receptors as well as sets of known ligands and decoys were selected from the Protein Data Bank (PDB) and the Directory of Useful Decoys (DUD), respectively. This study revealed that implementing displaceable crystallographic or computationally placed particle water molecules and protein flexibility can improve the enrichment in active compounds. In addition, an informed decision based on library diversity or research objectives (hit discovery vs lead optimization) on which implementation to use may lead to significant improvements.

A Critical Assessment of the Performance of Protein-ligand Scoring Functions Based on NMR Chemical Shift Perturbations

PubMed Central

Wang, Bing; Westerhoff, Lance M.; Merz, Kenneth M.

2008-01-01

We have generated docking poses for the FKBP-GPI complex using eight docking programs, and compared their scoring functions with scoring based on NMR chemical shift perturbations (NMRScore). Because the chemical shift perturbation (CSP) is exquisitely sensitive on the orientation of ligand inside the binding pocket, NMRScore offers an accurate and straightforward approach to score different poses. All scoring functions were inspected by their abilities to highly rank the native-like structures and separate them from decoy poses generated for a protein-ligand complex. The overall performance of NMRScore is much better than that of energy-based scoring functions associated with docking programs in both aspects. In summary, we find that the combination of docking programs with NMRScore results in an approach that can robustly determine the binding site structure for a protein-ligand complex, thereby, providing a new tool facilitating the structure-based drug discovery process. PMID:17867664

The Drosophila DOCK family protein Sponge is required for development of the air sac primordium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morishita, Kazushge; Anh Suong, Dang Ngoc; Yoshida, Hideki

Dedicator of cytokinesis (DOCK) family genes are known as DOCK1-DOCK11 in mammals. DOCK family proteins mainly regulate actin filament polymerization and/or depolymerization and are GEF proteins, which contribute to cellular signaling events by activating small G proteins. Sponge (Spg) is a Drosophila counterpart to mammalian DOCK3/DOCK4, and plays a role in embryonic central nervous system development, R7 photoreceptor cell differentiation, and adult thorax development. In order to conduct further functional analyses on Spg in vivo, we examined its localization in third instar larval wing imaginal discs. Immunostaining with purified anti-Spg IgG revealed that Spg mainly localized in the air sacmore » primordium (ASP) in wing imaginal discs. Spg is therefore predicted to play an important role in the ASP. The specific knockdown of Spg by the breathless-GAL4 driver in tracheal cells induced lethality accompanied with a defect in ASP development and the induction of apoptosis. The monitoring of ERK signaling activity in wing imaginal discs by immunostaining with anti-diphospho-ERK IgG revealed reductions in the ERK signal cascade in Spg knockdown clones. Furthermore, the overexpression of D-raf suppressed defects in survival and the proliferation of cells in the ASP induced by the knockdown of Spg. Collectively, these results indicate that Spg plays a critical role in ASP development and tracheal cell viability that is mediated by the ERK signaling pathway. - Highlights: • Spg mainly localizes in the air sac primordium in wing imaginal discs. • Spg plays a critical role in air sac primordium development. • Spg positively regulates the ERK signal cascade.« less

Molecular Docking and Drug Discovery in β-Adrenergic Receptors.

PubMed

Vilar, Santiago; Sobarzo-Sanchez, Eduardo; Santana, Lourdes; Uriarte, Eugenio

2017-01-01

Evolution in computer engineering, availability of increasing amounts of data and the development of new and fast docking algorithms and software have led to improved molecular simulations with crucial applications in virtual high-throughput screening and drug discovery. Moreover, analysis of protein-ligand recognition through molecular docking has become a valuable tool in drug design. In this review, we focus on the applicability of molecular docking on a particular class of G protein-coupled receptors: the β-adrenergic receptors, which are relevant targets in clinic for the treatment of asthma and cardiovascular diseases. We describe the binding site in β-adrenergic receptors to understand key factors in ligand recognition along with the proteins activation process. Moreover, we focus on the discovery of new lead compounds that bind the receptors, on the evaluation of virtual screening using the active/ inactive binding site states, and on the structural optimization of known families of binders to improve β-adrenergic affinity. We also discussed strengths and challenges related to the applicability of molecular docking in β-adrenergic receptors. Molecular docking is a valuable technique in computational chemistry to deeply analyze ligand recognition and has led to important breakthroughs in drug discovery and design in the field of β-adrenergic receptors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Dock/Nck facilitates PTP61F/PTP1B regulation of insulin signalling.

PubMed

Wu, Chia-Lun; Buszard, Bree; Teng, Chun-Hung; Chen, Wei-Lin; Warr, Coral G; Tiganis, Tony; Meng, Tzu-Ching

2011-10-01

PTP1B (protein tyrosine phosphatase 1B) is a negative regulator of IR (insulin receptor) activation and glucose homoeostasis, but the precise molecular mechanisms governing PTP1B substrate selectivity and the regulation of insulin signalling remain unclear. In the present study we have taken advantage of Drosophila as a model organism to establish the role of the SH3 (Src homology 3)/SH2 adaptor protein Dock (Dreadlocks) and its mammalian counterpart Nck in IR regulation by PTPs. We demonstrate that the PTP1B orthologue PTP61F dephosphorylates the Drosophila IR in S2 cells in vitro and attenuates IR-induced eye overgrowth in vivo. Our studies indicate that Dock forms a stable complex with PTP61F and that Dock/PTP61F associate with the IR in response to insulin. We report that Dock is required for effective IR dephosphorylation and inactivation by PTP61F in vitro and in vivo. Furthermore, we demonstrate that Nck interacts with PTP1B and that the Nck/PTP1B complex inducibly associates with the IR for the attenuation of IR activation in mammalian cells. Our studies reveal for the first time that the adaptor protein Dock/Nck attenuates insulin signalling by recruiting PTP61F/PTP1B to its substrate, the IR.

Scoring ligand similarity in structure-based virtual screening.

PubMed

Zavodszky, Maria I; Rohatgi, Anjali; Van Voorst, Jeffrey R; Yan, Honggao; Kuhn, Leslie A

2009-01-01

Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein-ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein-ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein-ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein-ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein-ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds. (c) 2009 John Wiley & Sons, Ltd.

In-silico Investigation of Antitrypanosomal Phytochemicals from Nigerian Medicinal Plants

PubMed Central

Setzer, William N.; Ogungbe, Ifedayo V.

2012-01-01

Background Human African trypanosomiasis (HAT), a parasitic protozoal disease, is caused primarily by two subspecies of Trypanosoma brucei. HAT is a re-emerging disease and currently threatens millions of people in sub-Saharan Africa. Many affected people live in remote areas with limited access to health services and, therefore, rely on traditional herbal medicines for treatment. Methods A molecular docking study has been carried out on phytochemical agents that have been previously isolated and characterized from Nigerian medicinal plants, either known to be used ethnopharmacologically to treat parasitic infections or known to have in-vitro antitrypanosomal activity. A total of 386 compounds from 19 species of medicinal plants were investigated using in-silico molecular docking with validated Trypanosoma brucei protein targets that were available from the Protein Data Bank (PDB): Adenosine kinase (TbAK), pteridine reductase 1 (TbPTR1), dihydrofolate reductase (TbDHFR), trypanothione reductase (TbTR), cathepsin B (TbCatB), heat shock protein 90 (TbHSP90), sterol 14α-demethylase (TbCYP51), nucleoside hydrolase (TbNH), triose phosphate isomerase (TbTIM), nucleoside 2-deoxyribosyltransferase (TbNDRT), UDP-galactose 4′ epimerase (TbUDPGE), and ornithine decarboxylase (TbODC). Results This study revealed that triterpenoid and steroid ligands were largely selective for sterol 14α-demethylase; anthraquinones, xanthones, and berberine alkaloids docked strongly to pteridine reductase 1 (TbPTR1); chromenes, pyrazole and pyridine alkaloids preferred docking to triose phosphate isomerase (TbTIM); and numerous indole alkaloids showed notable docking energies with UDP-galactose 4′ epimerase (TbUDPGE). Polyphenolic compounds such as flavonoid gallates or flavonoid glycosides tended to be promiscuous docking agents, giving strong docking energies with most proteins. Conclusions This in-silico molecular docking study has identified potential biomolecular targets of phytochemical components of antitrypanosomal plants and has determined which phytochemical classes and structural manifolds likely target trypanosomal enzymes. The results could provide the framework for synthetic modification of bioactive phytochemicals, de novo synthesis of structural motifs, and lead to further phytochemical investigations. PMID:22848767

In Silico and In Vitro Investigation of the Piperine's Male Contraceptive Effect: Docking and Molecular Dynamics Simulation Studies in Androgen-Binding Protein and Androgen Receptor.

PubMed

Chinta, Gopichand; Ramya Chandar Charles, Mariasoosai; Klopčič, Ivana; Sollner Dolenc, Marija; Periyasamy, Latha; Selvaraj Coumar, Mohane

2015-07-01

Understanding the molecular mechanism of action of traditional medicines is an important step towards developing marketable drugs from them. Piperine, an active constituent present in the Piper species, is used extensively in Ayurvedic medicines (practiced on the Indian subcontinent). Among others, piperine is known to possess a male contraceptive effect; however, the molecular mechanism of action for this effect is not very clear. In this regard, detailed docking and molecular dynamics simulation studies of piperine with the androgen-binding protein and androgen receptors were carried out. Androgen receptors control male sexual behavior and fertility, while the androgen-binding protein binds testosterone and maintains its concentration at optimal levels to stimulate spermatogenesis in the testis. It was found that piperine docks to the androgen-binding protein, similar to dihydrotestosterone, and to androgen receptors, similar to cyproterone acetate (antagonist). Also, the piperine-androgen-binding protein and piperine-androgen receptors interactions were found to be stable throughout 30 ns of molecular dynamics simulation. Further, two independent simulations for 10 ns each also confirmed the stability of these interactions. Detailed analysis of the piperine-androgen-binding protein interactions shows that piperine interacts with Ser42 of the androgen-binding protein and could block the binding with its natural ligands dihydrotestosterone/testosterone. Moreover, piperine interacts with Thr577 of the androgen receptors in a manner similar to the antagonist cyproterone acetate. Based on the in silico results, piperine was tested in the MDA-kb2 cell line using the luciferase reporter gene assay and was found to antagonize the effect of dihydrotestosterone at nanomolar concentrations. Further detailed biochemical experiments could help to develop piperine as an effective male contraceptive agent in the future. Georg Thieme Verlag KG Stuttgart · New York.

On Docking, Scoring and Assessing Protein-DNA Complexes in a Rigid-Body Framework

PubMed Central

Parisien, Marc; Freed, Karl F.; Sosnick, Tobin R.

2012-01-01

We consider the identification of interacting protein-nucleic acid partners using the rigid body docking method FTdock, which is systematic and exhaustive in the exploration of docking conformations. The accuracy of rigid body docking methods is tested using known protein-DNA complexes for which the docked and undocked structures are both available. Additional tests with large decoy sets probe the efficacy of two published statistically derived scoring functions that contain a huge number of parameters. In contrast, we demonstrate that state-of-the-art machine learning techniques can enormously reduce the number of parameters required, thereby identifying the relevant docking features using a miniscule fraction of the number of parameters in the prior works. The present machine learning study considers a 300 dimensional vector (dependent on only 15 parameters), termed the Chemical Context Profile (CCP), where each dimension reflects a specific type of protein amino acid-nucleic acid base interaction. The CCP is designed to capture the chemical complementarities of the interface and is well suited for machine learning techniques. Our objective function is the Chemical Context Discrepancy (CCD), which is defined as the angle between the native system's CCP vector and the decoy's vector and which serves as a substitute for the more commonly used root mean squared deviation (RMSD). We demonstrate that the CCP provides a useful scoring function when certain dimensions are properly weighted. Finally, we explore how the amino acids on a protein's surface can help guide DNA binding, first through long-range interactions, followed by direct contacts, according to specific preferences for either the major or minor grooves of the DNA. PMID:22393431

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

PubMed

Bai, Fang; Morcos, Faruck; Cheng, Ryan R; Jiang, Hualiang; Onuchic, José N

2016-12-13

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

The Importance of Ligand Conformational Energies in Carbohydrate Docking: Sorting the Wheat from the Chaff

PubMed Central

Nivedha, Anita K.; Makeneni, Spandana; Foley, B. Lachele; Tessier, Matthew B.; Woods, Robert J.

2014-01-01

Docking algorithms that aim to be applicable to a broad range of ligands suffer reduced accuracy because they are unable to incorporate ligand-specific conformational energies. Here, we develop internal energy functions, Carbohydrate Intrinsic (CHI), to account for the rotational preferences of the glycosidic torsion angles in carbohydrates. The relative energies predicted by the CHI energy functions mirror the conformational distributions of glycosidic linkages determined from a survey of oligosaccharide-protein complexes in the Protein Data Bank. Addition of CHI energies to the standard docking scores in Autodock 3, 4.2, and Vina consistently improves pose ranking of oligosaccharides docked to a set of anti-carbohydrate antibodies. The CHI energy functions are also independent of docking algorithm, and with minor modifications, may be incorporated into both theoretical modeling methods, and experimental NMR or X-ray structure refinement programs. PMID:24375430

Prediction of protein-peptide interactions: application of the XPairIt API to anthrax lethal factor and substrates

NASA Astrophysics Data System (ADS)

Hurley, Margaret M.; Sellers, Michael S.

2013-05-01

As software and methodology develop, key aspects of molecular interactions such as detailed energetics and flexibility are continuously better represented in docking simulations. In the latest iteration of the XPairIt API and Docking Protocol, we perform a blind dock of a peptide into the cleavage site of the Anthrax lethal factor (LF) metalloprotein. Molecular structures are prepared from RCSB:1JKY and we demonstrate a reasonably accurate docked peptide through analysis of protein motion and, using NCI Plot, visualize and characterize the forces leading to binding. We compare our docked structure to the 1JKY crystal structure and the more recent 1PWV structure, and discuss both captured and overlooked interactions. Our results offer a more detailed look at secondary contact and show that both van der Waals and electrostatic interactions from peptide residues further from the enzyme's catalytic site are significant.

Optimization of pyDock for the new CAPRI challenges: Docking of homology-based models, domain-domain assembly and protein-RNA binding.

PubMed

Pons, Carles; Solernou, Albert; Perez-Cano, Laura; Grosdidier, Solène; Fernandez-Recio, Juan

2010-11-15

We describe here our results in the last CAPRI edition. We have participated in all targets, both as predictors and as scorers, using our pyDock docking methodology. The new challenges (homology-based modeling of the interacting subunits, domain-domain assembling, and protein-RNA interactions) have pushed our computer tools to the limits and have encouraged us to devise new docking approaches. Overall, the results have been quite successful, in line with previous editions, especially considering the high difficulty of some of the targets. Our docking approaches succeeded in five targets as predictors or as scorers (T29, T34, T35, T41, and T42). Moreover, with the inclusion of available information on the residues expected to be involved in the interaction, our protocol would have also succeeded in two additional cases (T32 and T40). In the remaining targets (except T37), results were equally poor for most of the groups. We submitted the best model (in ligand RMSD) among scorers for the unbound-bound target T29, the second best model among scorers for the protein-RNA target T34, and the only correct model among predictors for the domain assembly target T35. In summary, our excellent results for the new proposed challenges in this CAPRI edition showed the limitations and applicability of our approaches and encouraged us to continue developing methodologies for automated biomolecular docking. © 2010 Wiley-Liss, Inc.

Investigation on the interaction of Rutin with serum albumins: Insights from spectroscopic and molecular docking techniques.

PubMed

Sengupta, Priti; Sardar, Pinki Saha; Roy, Pritam; Dasgupta, Swagata; Bose, Adity

2018-06-01

The binding interaction of Rutin, a flavonoid, with model transport proteins, bovine serum albumin (BSA) and human serum albumin (HSA), were investigated using different spectroscopic techniques, such as fluorescence, time-resolved single photon counting (TCSPC) and circular dichroism (CD) spectroscopy as well as molecular docking method. The emission studies revealed that the fluorescence quenching of BSA/HSA by Rutin occurred through a simultaneous static and dynamic quenching process, and we have evaluated both the quenching constants individually. The binding constants of Rutin-BSA and Rutin-HSA system were found to be 2.14 × 10 6  M -1 and 2.36 × 10 6  M -1 at 298 K respectively, which were quite high. Further, influence of some biologically significant metal ions (Ca 2+ , Zn 2+ and Mg 2+ ) on binding of Rutin to BSA and HSA were also investigated. Thermodynamic parameters justified the involvement of hydrogen bonding and weak van der Waals forces in the interaction of Rutin with both BSA and HSA. Further a site-marker competitive experiment was performed to evaluate Rutin binding site in the albumins. Additionally, the CD spectra of BSA and HSA revealed that the secondary structure of the proteins was perturbed in the presence of Rutin. Finally protein-ligand docking studies have also been performed to determine the probable location of the ligand molecule. Copyright © 2018 Elsevier B.V. All rights reserved.

Molecular docking performance evaluated on the D3R Grand Challenge 2015 drug-like ligand datasets

NASA Astrophysics Data System (ADS)

Selwa, Edithe; Martiny, Virginie Y.; Iorga, Bogdan I.

2016-09-01

The D3R Grand Challenge 2015 was focused on two protein targets: Heat Shock Protein 90 (HSP90) and Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4). We used a protocol involving a preliminary analysis of the available data in PDB and PubChem BioAssay, and then a docking/scoring step using more computationally demanding parameters that were required to provide more reliable predictions. We could evidence that different docking software and scoring functions can behave differently on individual ligand datasets, and that the flexibility of specific binding site residues is a crucial element to provide good predictions.

Design-Based Peptidomimetic Ligand Discovery to Target HIV TAR RNA Using Comparative Analysis of Different Docking Methods.

PubMed

Fu, Junjie; Xia, Amy; Dai, Yao; Qi, Xin

2016-01-01

Discovering molecules capable of binding to HIV trans-activation responsive region (TAR) RNA thereby disrupting its interaction with Tat protein is an attractive strategy for developing novel antiviral drugs. Computational docking is considered as a useful tool for predicting binding affinity and conducting virtual screening. Although great progress in predicting protein-ligand interactions has been achieved in the past few decades, modeling RNA-ligand interactions is still largely unexplored due to the highly flexible nature of RNA. In this work, we performed molecular docking study with HIV TAR RNA using previously identified cyclic peptide L22 and its analogues with varying affinities toward HIV-1 TAR RNA. Furthermore, sarcosine scan was conducted to generate derivatives of CGP64222, a peptide-peptoid hybrid with inhibitory activity on Tat/TAR RNA interaction. Each compound was docked using CDOCKER, Surflex-Dock and FlexiDock to compare the effectiveness of each method. It was found that FlexiDock energy values correlated well with the experimental Kd values and could be used to predict the affinity of the ligands toward HIV-1 TAR RNA with a superior accuracy. Our results based on comparative analysis of different docking methods in RNA-ligand modeling will facilitate the structure-based discovery of HIV TAR RNA ligands for antiviral therapy.

Use of double-stranded RNA-mediated interference to determine the substrates of protein tyrosine kinases and phosphatases.

PubMed

Muda, Marco; Worby, Carolyn A; Simonson-Leff, Nancy; Clemens, James C; Dixon, Jack E

2002-08-15

Despite the wealth of information generated by genome-sequencing projects, the identification of in vivo substrates of specific protein kinases and phosphatases is hampered by the large number of candidate enzymes, overlapping enzyme specificity and sequence similarity. In the present study, we demonstrate the power of RNA interference (RNAi) to dissect signal transduction cascades involving specific kinases and phosphatases. RNAi is used to identify the cellular tyrosine kinases upstream of the phosphorylation of Down-Syndrome cell-adhesion molecule (Dscam), a novel cell-surface molecule of the immunoglobulin-fibronectin super family, which has been shown to be important for axonal path-finding in Drosophila. Tyrosine phosphorylation of Dscam recruits the Src homology 2 domain of the adaptor protein Dock to the receptor. Dock, the ortho- logue of mammalian Nck, is also essential for correct axonal path-finding in Drosophila. We further determined that Dock is tyrosine-phosphorylated in vivo and identified DPTP61F as the protein tyrosine phosphatase responsible for maintaining Dock in its non-phosphorylated state. The present study illustrates the versatility of RNAi in the identification of the physiological substrates for protein kinases and phosphatases.

CDOCKER and lambda λ -dynamics for prospective prediction in D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Ding, Xinqiang; Hayes, Ryan L.; Vilseck, Jonah Z.; Charles, Murchtricia K.; Brooks, Charles L.

2018-01-01

The opportunity to prospectively predict ligand bound poses and free energies of binding to the Farnesoid X Receptor in the D3R Grand Challenge 2 provided a useful exercise to evaluate CHARMM based docking (CDOCKER) and λ-dynamics methodologies for use in "real-world" applications in computer aided drug design. In addition to measuring their current performance, several recent methodological developments have been analyzed retrospectively to highlight best procedural practices in future applications. For pose prediction with CDOCKER, when the protein structure used for rigid receptor docking was close to the crystallographic holo structure, reliable poses were obtained. Benzimidazoles, with a known holo receptor structure, were successfully docked with an average RMSD of 0.97 Å. Other non-benzimidazole ligands displayed less accuracy largely because the receptor structures we chose for docking were too different from the experimental holo structures. However, retrospective analysis has shown that when these ligands were re-docked into their holo structures, the average RMSD dropped to 1.18 Å for all ligands. When sulfonamides and spiros were docked with the apo structure, which agrees more with their holo structure than the structures we chose, five out of six ligands were correctly docked. These docking results emphasize the need for flexible receptor docking approaches. For λ-dynamics techniques, including multisite λ-dynamics (MSλD), reasonable agreement with experiment was observed for the 33 ligands investigated; root mean square errors of 2.08 and 1.67 kcal/mol were obtained for free energy sets 1 and 2, respectively. Retrospectively, soft-core potentials, adaptive landscape flattening, and biasing potential replica exchange (BP-REX) algorithms were critical to model large substituent perturbations with sufficient precision and within restrictive timeframes, such as was required with participation in Grand Challenge 2. These developments, their associated benefits, and proposed procedures for their use in future applications are discussed.

CDOCKER and λ-dynamics for prospective prediction in D₃R Grand Challenge 2.

PubMed

Ding, Xinqiang; Hayes, Ryan L; Vilseck, Jonah Z; Charles, Murchtricia K; Brooks, Charles L

2018-01-01

The opportunity to prospectively predict ligand bound poses and free energies of binding to the Farnesoid X Receptor in the D3R Grand Challenge 2 provided a useful exercise to evaluate CHARMM based docking (CDOCKER) and [Formula: see text]-dynamics methodologies for use in "real-world" applications in computer aided drug design. In addition to measuring their current performance, several recent methodological developments have been analyzed retrospectively to highlight best procedural practices in future applications. For pose prediction with CDOCKER, when the protein structure used for rigid receptor docking was close to the crystallographic holo structure, reliable poses were obtained. Benzimidazoles, with a known holo receptor structure, were successfully docked with an average RMSD of 0.97 [Formula: see text]. Other non-benzimidazole ligands displayed less accuracy largely because the receptor structures we chose for docking were too different from the experimental holo structures. However, retrospective analysis has shown that when these ligands were re-docked into their holo structures, the average RMSD dropped to 1.18 [Formula: see text] for all ligands. When sulfonamides and spiros were docked with the apo structure, which agrees more with their holo structure than the structures we chose, five out of six ligands were correctly docked. These docking results emphasize the need for flexible receptor docking approaches. For [Formula: see text]-dynamics techniques, including multisite [Formula: see text]-dynamics (MS[Formula: see text]D), reasonable agreement with experiment was observed for the 33 ligands investigated; root mean square errors of 2.08 and 1.67 kcal/mol were obtained for free energy sets 1 and 2, respectively. Retrospectively, soft-core potentials, adaptive landscape flattening, and biasing potential replica exchange (BP-REX) algorithms were critical to model large substituent perturbations with sufficient precision and within restrictive timeframes, such as was required with participation in Grand Challenge 2. These developments, their associated benefits, and proposed procedures for their use in future applications are discussed.

Domain requirements for the Dock adapter protein in growth- cone signaling

PubMed Central

Rao, Yong; Zipursky, S. Lawrence

1998-01-01

Tyrosine phosphorylation has been implicated in growth-cone guidance through genetic, biochemical, and pharmacological studies. Adapter proteins containing src homology 2 (SH2) domains and src homology 3 (SH3) domains provide a means of linking guidance signaling through phosphotyrosine to downstream effectors regulating growth-cone motility. The Drosophila adapter, Dreadlocks (Dock), the homolog of mammalian Nck containing three N-terminal SH3 domains and a single SH2 domain, is highly specialized for growth-cone guidance. In this paper, we demonstrate that Dock can couple signals in either an SH2-dependent or an SH2-independent fashion in photoreceptor (R cell) growth cones, and that Dock displays different domain requirements in different neurons. PMID:9482841

Characterizing SHP2 as a Novel Therapeutic Target in Breast Cancer

DTIC Science & Technology

2013-02-01

attempted to elucidate interactions with molecular docking (5). The peptide was docked into the SH2 active site of 2SHP.pdb (with SH2 domains...activated protein kinase (MAPK) pathway, which is read as a drop in phosphorylated ERK protein(3). 5 First, the problem of cell permeability

In silico investigation of potential mTOR inhibitors from traditional Chinese medicine for treatment of Leigh syndrome.

PubMed

Chen, Kuan-Chung; Lee, Wen-Yuan; Chen, Hsin-Yi; Chen, Calvin Yu-Chian

2014-01-01

A recent research demonstrates that the inhibition of mammalian target of rapamycin (mTOR) improves survival and health for patients with Leigh syndrome. mTOR proteins can be treated as drug target proteins against Leigh syndrome and other mitochondrial disorders. In this study, we aim to identify potent TCM compounds from the TCM Database@Taiwan as lead compounds of mTOR inhibitors. PONDR-Fit protocol was employed to predict the disordered disposition in mTOR protein before virtual screening. After virtual screening, the MD simulation was employed to validate the stability of interactions between each ligand and mTOR protein in the docking poses from docking simulation. The top TCM compounds, picrasidine M and acerosin, have higher binding affinities with target protein in docking simulation than control. There have H-bonds with residues Val2240 and π interactions with common residue Trp2239. After MD simulation, the top TCM compounds maintain similar docking poses under dynamic conditions. The top two TCM compounds, picrasidine M and acerosin, were extracted from Picrasma quassioides (D. Don) Benn. and Vitex negundo L. Hence, we propose the TCM compounds, picrasidine M and acerosin, as potential candidates as lead compounds for further study in drug development process with the mTOR protein against Leigh syndrome and other mitochondrial disorders.

S4MPLE--Sampler for Multiple Protein-Ligand Entities: Methodology and Rigid-Site Docking Benchmarking.

PubMed

Hoffer, Laurent; Chira, Camelia; Marcou, Gilles; Varnek, Alexandre; Horvath, Dragos

2015-05-19

This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed for folding or docking, S4MPLE transcends this artificial specialization. It supports folding, docking of a flexible ligand into a flexible site and simultaneous docking of several ligands. The trick behind it is the formal assimilation of inter-molecular to intra-molecular DoF associated to putative inter-molecular contact axes. This is implemented within the genetic operators powering a Lamarckian Genetic Algorithm (GA). Further novelty includes differentiable interaction fingerprints to control population diversity, and fitting a simple continuum solvent model and favorable contact bonus terms to the AMBER/GAFF force field. Novel applications-docking of fragment-like compounds, simultaneous docking of multiple ligands, including free crystallographic waters-were published elsewhere. This paper discusses: (a) methodology, (b) set-up of the force field energy functions and (c) their validation in classical redocking tests. More than 80% success in redocking was achieved (RMSD of top-ranked pose < 2.0 Å).

Differential regulation of protein tyrosine kinase signalling by Dock and the PTP61F variants.

PubMed

Willoughby, Lee F; Manent, Jan; Allan, Kirsten; Lee, Han; Portela, Marta; Wiede, Florian; Warr, Coral; Meng, Tzu-Ching; Tiganis, Tony; Richardson, Helena E

2017-07-01

Tyrosine phosphorylation-dependent signalling is coordinated by the opposing actions of protein tyrosine kinases (PTKs) and protein tyrosine phosphatases (PTPs). There is a growing list of adaptor proteins that interact with PTPs and facilitate the dephosphorylation of substrates. The extent to which any given adaptor confers selectivity for any given substrate in vivo remains unclear. Here we have taken advantage of Drosophila melanogaster as a model organism to explore the influence of the SH3/SH2 adaptor protein Dock on the abilities of the membrane (PTP61Fm)- and nuclear (PTP61Fn)-targeted variants of PTP61F (the Drosophila othologue of the mammalian enzymes PTP1B and TCPTP respectively) to repress PTK signalling pathways in vivo. PTP61Fn effectively repressed the eye overgrowth associated with activation of the epidermal growth factor receptor (EGFR), PTK, or the expression of the platelet-derived growth factor/vascular endothelial growth factor receptor (PVR) or insulin receptor (InR) PTKs. PTP61Fn repressed EGFR and PVR-induced mitogen-activated protein kinase signalling and attenuated PVR-induced STAT92E signalling. By contrast, PTP61Fm effectively repressed EGFR- and PVR-, but not InR-induced tissue overgrowth. Importantly, coexpression of Dock with PTP61F allowed for the efficient repression of the InR-induced eye overgrowth, but did not enhance the PTP61Fm-mediated inhibition of EGFR and PVR-induced signalling. Instead, Dock expression increased, and PTP61Fm coexpression further exacerbated the PVR-induced eye overgrowth. These results demonstrate that Dock selectively enhances the PTP61Fm-mediated attenuation of InR signalling and underscores the specificity of PTPs and the importance of adaptor proteins in regulating PTP function in vivo. © 2017 Federation of European Biochemical Societies.

Role of binding entropy in the refinement of protein-ligand docking predictions: analysis based on the use of 11 scoring functions.

PubMed

Ruvinsky, Anatoly M

2007-06-01

We present results of testing the ability of eleven popular scoring functions to predict native docked positions using a recently developed method (Ruvinsky and Kozintsev, J Comput Chem 2005, 26, 1089) for estimation the entropy contributions of relative motions to protein-ligand binding affinity. The method is based on the integration of the configurational integral over clusters obtained from multiple docked positions. We use a test set of 100 PDB protein-ligand complexes and ensembles of 101 docked positions generated by (Wang et al. J Med Chem 2003, 46, 2287) for each ligand in the test set. To test the suggested method we compared the averaged root-mean square deviations (RMSD) of the top-scored ligand docked positions, accounting and not accounting for entropy contributions, relative to the experimentally determined positions. We demonstrate that the method increases docking accuracy by 10-21% when used in conjunction with the AutoDock scoring function, by 2-25% with G-Score, by 7-41% with D-Score, by 0-8% with LigScore, by 1-6% with PLP, by 0-12% with LUDI, by 2-8% with F-Score, by 7-29% with ChemScore, by 0-9% with X-Score, by 2-19% with PMF, and by 1-7% with DrugScore. We also compared the performance of the suggested method with the method based on ranking by cluster occupancy only. We analyze how the choice of a clustering-RMSD and a low bound of dense clusters impacts on docking accuracy of the scoring methods. We derive optimal intervals of the clustering-RMSD for 11 scoring functions.

Pharmacophore-Based Similarity Scoring for DOCK

PubMed Central

2015-01-01

Pharmacophore modeling incorporates geometric and chemical features of known inhibitors and/or targeted binding sites to rationally identify and design new drug leads. In this study, we have encoded a three-dimensional pharmacophore matching similarity (FMS) scoring function into the structure-based design program DOCK. Validation and characterization of the method are presented through pose reproduction, crossdocking, and enrichment studies. When used alone, FMS scoring dramatically improves pose reproduction success to 93.5% (∼20% increase) and reduces sampling failures to 3.7% (∼6% drop) compared to the standard energy score (SGE) across 1043 protein–ligand complexes. The combined FMS+SGE function further improves success to 98.3%. Crossdocking experiments using FMS and FMS+SGE scoring, for six diverse protein families, similarly showed improvements in success, provided proper pharmacophore references are employed. For enrichment, incorporating pharmacophores during sampling and scoring, in most cases, also yield improved outcomes when docking and rank-ordering libraries of known actives and decoys to 15 systems. Retrospective analyses of virtual screenings to three clinical drug targets (EGFR, IGF-1R, and HIVgp41) using X-ray structures of known inhibitors as pharmacophore references are also reported, including a customized FMS scoring protocol to bias on selected regions in the reference. Overall, the results and fundamental insights gained from this study should benefit the docking community in general, particularly researchers using the new FMS method to guide computational drug discovery with DOCK. PMID:25229837

Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2

NASA Astrophysics Data System (ADS)

Baumgartner, Matthew P.; Evans, David A.

2018-01-01

Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds. We tested a number of pose prediction methods as part of the challenge; we found that docking methods that incorporate protein flexibility (Induced Fit Docking) outperformed methods that treated the protein as rigid. We also found that using binding pose metadynamics, a molecular dynamics based method, to score docked poses provided the best predictions of our methods with an average RMSD of 2.01 Å. We tested both structure-based (e.g. docking) and ligand-based methods (e.g. QSAR) in the affinity prediction portion of the competition. We found that our structure-based methods based on docking with Smina (Spearman ρ = 0.614), performed slightly better than our ligand-based methods (ρ = 0.543), and had equivalent performance with the other top methods in the competition. Despite the overall good performance of our methods in comparison to other participants in the challenge, there exists significant room for improvement especially in cases such as these where protein flexibility plays such a large role.

Identification of Novel Aldose Reductase Inhibitors from Spices: A Molecular Docking and Simulation Study.

PubMed

Antony, Priya; Vijayan, Ranjit

2015-01-01

Hyperglycemia in diabetic patients results in a diverse range of complications such as diabetic retinopathy, neuropathy, nephropathy and cardiovascular diseases. The role of aldose reductase (AR), the key enzyme in the polyol pathway, in these complications is well established. Due to notable side-effects of several drugs, phytochemicals as an alternative has gained considerable importance for the treatment of several ailments. In order to evaluate the inhibitory effects of dietary spices on AR, a collection of phytochemicals were identified from Zingiber officinale (ginger), Curcuma longa (turmeric) Allium sativum (garlic) and Trigonella foenum graecum (fenugreek). Molecular docking was performed for lead identification and molecular dynamics simulations were performed to study the dynamic behaviour of these protein-ligand interactions. Gingerenones A, B and C, lariciresinol, quercetin and calebin A from these spices exhibited high docking score, binding affinity and sustained protein-ligand interactions. Rescoring of protein ligand interactions at the end of MD simulations produced binding scores that were better than the initially docked conformations. Docking results, ligand interactions and ADMET properties of these molecules were significantly better than commercially available AR inhibitors like epalrestat, sorbinil and ranirestat. Thus, these natural molecules could be potent AR inhibitors.

Identification of Novel Aldose Reductase Inhibitors from Spices: A Molecular Docking and Simulation Study

PubMed Central

Antony, Priya; Vijayan, Ranjit

2015-01-01

Hyperglycemia in diabetic patients results in a diverse range of complications such as diabetic retinopathy, neuropathy, nephropathy and cardiovascular diseases. The role of aldose reductase (AR), the key enzyme in the polyol pathway, in these complications is well established. Due to notable side-effects of several drugs, phytochemicals as an alternative has gained considerable importance for the treatment of several ailments. In order to evaluate the inhibitory effects of dietary spices on AR, a collection of phytochemicals were identified from Zingiber officinale (ginger), Curcuma longa (turmeric) Allium sativum (garlic) and Trigonella foenum graecum (fenugreek). Molecular docking was performed for lead identification and molecular dynamics simulations were performed to study the dynamic behaviour of these protein-ligand interactions. Gingerenones A, B and C, lariciresinol, quercetin and calebin A from these spices exhibited high docking score, binding affinity and sustained protein-ligand interactions. Rescoring of protein ligand interactions at the end of MD simulations produced binding scores that were better than the initially docked conformations. Docking results, ligand interactions and ADMET properties of these molecules were significantly better than commercially available AR inhibitors like epalrestat, sorbinil and ranirestat. Thus, these natural molecules could be potent AR inhibitors. PMID:26384019

Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand

PubMed Central

DeLuca, Samuel; Khar, Karen; Meiler, Jens

2015-01-01

RosettaLigand has been successfully used to predict binding poses in protein-small molecule complexes. However, the RosettaLigand docking protocol is comparatively slow in identifying an initial starting pose for the small molecule (ligand) making it unfeasible for use in virtual High Throughput Screening (vHTS). To overcome this limitation, we developed a new sampling approach for placing the ligand in the protein binding site during the initial ‘low-resolution’ docking step. It combines the translational and rotational adjustments to the ligand pose in a single transformation step. The new algorithm is both more accurate and more time-efficient. The docking success rate is improved by 10–15% in a benchmark set of 43 protein/ligand complexes, reducing the number of models that typically need to be generated from 1000 to 150. The average time to generate a model is reduced from 50 seconds to 10 seconds. As a result we observe an effective 30-fold speed increase, making RosettaLigand appropriate for docking medium sized ligand libraries. We demonstrate that this improved initial placement of the ligand is critical for successful prediction of an accurate binding position in the ‘high-resolution’ full atom refinement step. PMID:26207742

The role of protein plasticity in computational rationalization studies on regioselectivity in testosterone hydroxylation by cytochrome P450 BM3 mutants.

PubMed

de Beer, Stephanie B A; van Bergen, Laura A H; Keijzer, Karlijn; Rea, Vanina; Venkataraman, Harini; Guerra, Celia Fonseca; Bickelhaupt, F Matthias; Vermeulen, Nico P E; Commandeur, Jan N M; Geerke, Daan P

2012-02-01

Recently, it was found that mutations in the binding cavity of drug-metabolizing Cytochrome P450 BM3 mutants can result in major changes in regioselectivity in testosterone (TES) hydroxylation. In the current work, we report the intrinsic reactivity of TES' C-H bonds and our attempts to rationalize experimentally observed changes in TES hydroxylation using a protein structure-based in silico approach, by setting up and employing a combined Molecular Dynamics (MD) and ligand docking approach to account for the flexibility and plasticity of BM3 mutants. Using this approach, about 100,000 TES binding poses were obtained per mutant. The predicted regioselectivity in TES hydroxylation by the mutants was found to be in disagreement with experiment. As revealed in a detailed structural analysis of the obtained docking poses, this disagreement is due to limitations in correctly scoring hydrogen-bonding and steric interactions with specific active-site residues, which could explain the experimentally observed trends in regioselectivity in TES hydroxylation.

Hot-spot analysis for drug discovery targeting protein-protein interactions.

PubMed

Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

New additions to the ClusPro server motivated by CAPRI.

PubMed

Vajda, Sandor; Yueh, Christine; Beglov, Dmitri; Bohnuud, Tanggis; Mottarella, Scott E; Xia, Bing; Hall, David R; Kozakov, Dima

2017-03-01

The heavily used protein-protein docking server ClusPro performs three computational steps as follows: (1) rigid body docking, (2) RMSD based clustering of the 1000 lowest energy structures, and (3) the removal of steric clashes by energy minimization. In response to challenges encountered in recent CAPRI targets, we added three new options to ClusPro. These are (1) accounting for small angle X-ray scattering data in docking; (2) considering pairwise interaction data as restraints; and (3) enabling discrimination between biological and crystallographic dimers. In addition, we have developed an extremely fast docking algorithm based on 5D rotational manifold FFT, and an algorithm for docking flexible peptides that include known sequence motifs. We feel that these developments will further improve the utility of ClusPro. However, CAPRI emphasized several shortcomings of the current server, including the problem of selecting the right energy parameters among the five options provided, and the problem of selecting the best models among the 10 generated for each parameter set. In addition, results convinced us that further development is needed for docking homology models. Finally, we discuss the difficulties we have encountered when attempting to develop a refinement algorithm that would be computationally efficient enough for inclusion in a heavily used server. Proteins 2017; 85:435-444. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Biophysical characterization of the interaction between M2-1 protein of hRSV and quercetin.

PubMed

Teixeira, Thiago Salem Pançonato; Caruso, Ícaro Putinhon; Lopes, Bruno Rafael Pereira; Regasini, Luis Octávio; Toledo, Karina Alves de; Fossey, Marcelo Andrés; Souza, Fátima Pereira de

2017-02-01

hRSV is the major causative agent of acute respiratory infections. Among its eleven proteins, M2-1 is a transcription antiterminator, making it an interesting target for antivirals. Quercetin is a flavonol which inhibits some virus infectivity and replication. In the present work, the M2-1 gene was cloned, expressed and the protein was purified. Thermal stability and secondary structure were analyzed by circular dichroism and the interaction with Quercetin was evaluated by fluorescence spectroscopy. Molecular docking experiments were performed to understand this mechanism of interaction. The purified protein is mainly composed of α-helix, with a melting temperature of 328.6K (≈55°C). M2-1 titration with Quercetin showed it interacts with two sites, one with a strong constant association K1 (site 1≈1.5×10 6 M -1 ) by electrostatic interactions, and another with a weak constant association K2 (site 2≈1.1×10 5 M -1 ) by a hydrophobic interaction. Ligand's docking shows it interacts with the N-terminus face in a more polar pocket and, between the domains of oligomerization and RNA and P protein interaction, in a more hydrophobic pocket, as predicted by experimental data. Therefore, we postulated this ligand could be interacting with important domains of the protein, avoiding viral replication and budding. Copyright © 2016 Elsevier B.V. All rights reserved.

On the computation of molecular surface correlations for protein docking using fourier techniques.

PubMed

Sakk, Eric

2007-08-01

The computation of surface correlations using a variety of molecular models has been applied to the unbound protein docking problem. Because of the computational complexity involved in examining all possible molecular orientations, the fast Fourier transform (FFT) (a fast numerical implementation of the discrete Fourier transform (DFT)) is generally applied to minimize the number of calculations. This approach is rooted in the convolution theorem which allows one to inverse transform the product of two DFTs in order to perform the correlation calculation. However, such a DFT calculation results in a cyclic or "circular" correlation which, in general, does not lead to the same result as the linear correlation desired for the docking problem. In this work, we provide computational bounds for constructing molecular models used in the molecular surface correlation problem. The derived bounds are then shown to be consistent with various intuitive guidelines previously reported in the protein docking literature. Finally, these bounds are applied to different molecular models in order to investigate their effect on the correlation calculation.

Blind Pose Prediction, Scoring, and Affinity Ranking of the CSAR 2014 Dataset.

PubMed

Martiny, Virginie Y; Martz, François; Selwa, Edithe; Iorga, Bogdan I

2016-06-27

The 2014 CSAR Benchmark Exercise was focused on three protein targets: coagulation factor Xa, spleen tyrosine kinase, and bacterial tRNA methyltransferase. Our protocol involved a preliminary analysis of the structural information available in the Protein Data Bank for the protein targets, which allowed the identification of the most appropriate docking software and scoring functions to be used for the rescoring of several docking conformations datasets, as well as for pose prediction and affinity ranking. The two key points of this study were (i) the prior evaluation of molecular modeling tools that are most adapted for each target and (ii) the increased search efficiency during the docking process to better explore the conformational space of big and flexible ligands.

Integrated machine learning, molecular docking and 3D-QSAR based approach for identification of potential inhibitors of trypanosomal N-myristoyltransferase.

PubMed

Singh, Nidhi; Shah, Priyanka; Dwivedi, Hemlata; Mishra, Shikha; Tripathi, Renu; Sahasrabuddhe, Amogh A; Siddiqi, Mohammad Imran

2016-11-15

N-Myristoyltransferase (NMT) catalyzes the transfer of myristate to the amino-terminal glycine of a subset of proteins, a co-translational modification involved in trafficking substrate proteins to membrane locations, stabilization and protein-protein interactions. It is a studied and validated pre-clinical drug target for fungal and parasitic infections. In the present study, a machine learning approach, docking studies and CoMFA analysis have been integrated with the objective of translation of knowledge into a pipelined workflow towards the identification of putative hits through the screening of large compound libraries. In the proposed pipeline, the reported parasitic NMT inhibitors have been used to develop predictive machine learning classification models. Simultaneously, a TbNMT complex model was generated to establish the relationship between the binding mode of the inhibitors for LmNMT and TbNMT through molecular dynamics simulation studies. A 3D-QSAR model was developed and used to predict the activity of the proposed hits in the subsequent step. The hits classified as active based on the machine learning model were assessed as the potential anti-trypanosomal NMT inhibitors through molecular docking studies, predicted activity using a QSAR model and visual inspection. In the final step, the proposed pipeline was validated through in vitro experiments. A total of seven hits have been proposed and tested in vitro for evaluation of dual inhibitory activity against Leishmania donovani and Trypanosoma brucei. Out of these five compounds showed significant inhibition against both of the organisms. The common topmost active compound SEW04173 belongs to a pyrazole carboxylate scaffold and is anticipated to enrich the chemical space with enhanced potency through optimization.

Mapping multiple potential ATP binding sites on the matrix side of the bovine ADP/ATP carrier by the combined use of MD simulation and docking.

PubMed

Di Marino, Daniele; Oteri, Francesco; della Rocca, Blasco Morozzo; D'Annessa, Ilda; Falconi, Mattia

2012-06-01

The mitochondrial adenosine diphosphate/adenosine triphosphate (ADP/ATP) carrier-AAC-was crystallized in complex with its specific inhibitor carboxyatractyloside (CATR). The protein consists of a six-transmembrane helix bundle that defines the nucleotide translocation pathway, which is closed towards the matrix side due to sharp kinks in the odd-numbered helices. In this paper, we describe the interaction between the matrix side of the AAC transporter and the ATP(4-) molecule using carrier structures obtained through classical molecular dynamics simulation (MD) and a protein-ligand docking procedure. Fifteen structures were extracted from a previously published MD trajectory through clustering analysis, and 50 docking runs were carried out for each carrier conformation, for a total of 750 runs ("MD docking"). The results were compared to those from 750 docking runs performed on the X-ray structure ("X docking"). The docking procedure indicated the presence of a single interaction site in the X-ray structure that was conserved in the structures extracted from the MD trajectory. MD docking showed the presence of a second binding site that was not found in the X docking. The interaction strategy between the AAC transporter and the ATP(4-) molecule was analyzed by investigating the composition and 3D arrangement of the interaction pockets, together with the orientations of the substrate inside them. A relationship between sequence repeats and the ATP(4-) binding sites in the AAC carrier structure is proposed.

Potential interaction of natural dietary bioactive compounds with COX-2.

PubMed

Maldonado-Rojas, Wilson; Olivero-Verbel, Jesus

2011-09-01

Bioactive natural products present in the diet play an important role in several biological processes, and many have been involved in the alleviation and control of inflammation-related diseases. These actions have been linked to both gene expression modulation of pro-inflammatory enzymes, such as cyclooxygenase 2 (COX-2), and to an action involving a direct inhibitory binding on this protein. In this study, several food-related compounds with known gene regulatory action on inflammation have been examined in silico as COX-2 ligands, utilizing AutoDock Vina, GOLD and Surflex-Dock (SYBYL) as docking protocols. Curcumin and all-trans retinoic acid presented the maximum absolute AutoDock Vina-derived binding affinities (9.3 kcal/mol), but genistein, apigenin, cyanidin, kaempferol, and docosahexaenoic acid, were close to this value. AutoDock Vina affinities and GOLD scores for several known COX-2 inhibitors significatively correlated with reported median inhibitory concentrations (R² = 0.462, P < 0.001 and R² = 0.238, P = 0.029, respectively), supporting the computational reliability of the predictions made by our docking simulations. Moreover, docking analysis insinuate the synergistic action of curcumin on celecoxib-induced inhibition of COX-2 may occur allosterically, as this natural compound docks to a place different from the inhibitor binding site. These results suggest that the anti-inflammatory properties of some food-derived molecules could be the result of their direct binding capabilities to COX-2, and this process can be modeled using protein-ligand docking methodologies. Copyright © 2011 Elsevier Inc. All rights reserved.

Fast Approximations of the Rotational Diffusion Tensor and their Application to Structural Assembly of Molecular Complexes

PubMed Central

Berlin, Konstantin; O’Leary, Dianne P.; Fushman, David

2011-01-01

We present and evaluate a rigid-body, deterministic, molecular docking method, called ELMDOCK, that relies solely on the three-dimensional structure of the individual components and the overall rotational diffusion tensor of the complex, obtained from nuclear spin-relaxation measurements. We also introduce a docking method, called ELMPATIDOCK, derived from ELMDOCK and based on the new concept of combining the shape-related restraints from rotational diffusion with those from residual dipolar couplings, along with ambiguous contact/interface-related restraints obtained from chemical shift perturbations. ELMDOCK and ELMPATIDOCK use two novel approximations of the molecular rotational diffusion tensor that allow computationally efficient docking. We show that these approximations are accurate enough to properly dock the two components of a complex without the need to recompute the diffusion tensor at each iteration step. We analyze the accuracy, robustness, and efficiency of these methods using synthetic relaxation data for a large variety of protein-protein complexes. We also test our method on three protein systems for which the structure of the complex and experimental relaxation data are available, and analyze the effect of flexible unstructured tails on the outcome of docking. Additionally, we describe a method for integrating the new approximation methods into the existing docking approaches that use the rotational diffusion tensor as a restraint. The results show that the proposed docking method is robust against experimental errors in the relaxation data or structural rearrangements upon complex formation and is computationally more efficient than current methods. The developed approximations are accurate enough to be used in structure refinement protocols. PMID:21604302

Fast approximations of the rotational diffusion tensor and their application to structural assembly of molecular complexes.

PubMed

Berlin, Konstantin; O'Leary, Dianne P; Fushman, David

2011-07-01

We present and evaluate a rigid-body, deterministic, molecular docking method, called ELMDOCK, that relies solely on the three-dimensional structure of the individual components and the overall rotational diffusion tensor of the complex, obtained from nuclear spin-relaxation measurements. We also introduce a docking method, called ELMPATIDOCK, derived from ELMDOCK and based on the new concept of combining the shape-related restraints from rotational diffusion with those from residual dipolar couplings, along with ambiguous contact/interface-related restraints obtained from chemical shift perturbations. ELMDOCK and ELMPATIDOCK use two novel approximations of the molecular rotational diffusion tensor that allow computationally efficient docking. We show that these approximations are accurate enough to properly dock the two components of a complex without the need to recompute the diffusion tensor at each iteration step. We analyze the accuracy, robustness, and efficiency of these methods using synthetic relaxation data for a large variety of protein-protein complexes. We also test our method on three protein systems for which the structure of the complex and experimental relaxation data are available, and analyze the effect of flexible unstructured tails on the outcome of docking. Additionally, we describe a method for integrating the new approximation methods into the existing docking approaches that use the rotational diffusion tensor as a restraint. The results show that the proposed docking method is robust against experimental errors in the relaxation data or structural rearrangements upon complex formation and is computationally more efficient than current methods. The developed approximations are accurate enough to be used in structure refinement protocols. Copyright © 2011 Wiley-Liss, Inc.

Automated Docking with Protein Flexibility in the Design of Femtomolar “Click Chemistry” Inhibitors of Acetylcholinesterase

PubMed Central

Morris, Garrett M.; Green, Luke G.; Radić, Zoran; Taylor, Palmer; Sharpless, K. Barry; Olson, Arthur J.; Grynszpan, Flavio

2013-01-01

The use of computer-aided structure-based drug design prior to synthesis has proven to be generally valuable in suggesting improved binding analogues of existing ligands.1 Here we describe the application of the program AutoDock2 to the design of a focused library that was used in the “click chemistry in-situ” generation of the most potent non-covalent inhibitor of the enzyme acetylcholinesterase (AChE) yet developed (Kd = ~100 fM).3 AutoDock version 3.0.5 has been widely distributed and successfully used to predict bound conformations of flexible ligands. Here, we also used a version of AutoDock which permits additional conformational flexibility in selected amino acid sidechains of the target protein. PMID:23451944

Template-Based Modeling of Protein-RNA Interactions.

PubMed

Zheng, Jinfang; Kundrotas, Petras J; Vakser, Ilya A; Liu, Shiyong

2016-09-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes.

A python-based docking program utilizing a receptor bound ligand shape: PythDock.

PubMed

Chung, Jae Yoon; Cho, Seung Joo; Hah, Jung-Mi

2011-09-01

PythDock is a heuristic docking program that uses Python programming language with a simple scoring function and a population based search engine. The scoring function considers electrostatic and dispersion/repulsion terms. The search engine utilizes a particle swarm optimization algorithm. A grid potential map is generated using the shape information of a bound ligand within the active site. Therefore, the searching area is more relevant to the ligand binding. To evaluate the docking performance of PythDock, two well-known docking programs (AutoDock and DOCK) were also used with the same data. The accuracy of docked results were measured by the difference of the ligand structure between x-ray structure, and docked pose, i.e., average root mean squared deviation values of the bound ligand were compared for fourteen protein-ligand complexes. Since the number of ligands' rotational flexibility is an important factor affecting the accuracy of a docking, the data set was chosen to have various degrees of flexibility. Although PythDock has a scoring function simpler than those of other programs (AutoDock and DOCK), our results showed that PythDock predicted more accurate poses than both AutoDock4.2 and DOCK6.2. This indicates that PythDock could be a useful tool to study ligand-receptor interactions and could also be beneficial in structure based drug design.

Investigation of the inhibitors of histone-lysine N-methyltransferase SETD2 for acute lymphoblastic leukaemia from traditional Chinese medicine.

PubMed

Chang, Y-L; Chen, H-Y; Chen, K-B; Chen, K-C; Chang, K-L; Chang, P-C; Chang, T-T; Chen, Y-C

2016-07-01

Leukaemia is the leading cause of childhood malignancies. Recent research indicates that the SETD2 gene is associated with acute lymphoblastic leukaemia. This study aims to identify potential lead compounds from traditional Chinese medicine (TCM) using virtual screening for SET domain containing 2 (SETD2) protein against acute lymphoblastic leukaemia. Docking simulation was performed to determine potential candidates which obtain suitable docking poses in the binding domain of the SETD2 protein. We also performed molecular dynamics (MD) simulation to investigate the stability of docking poses of SETD2 protein complexes with the top three TCM candidates and a control. According to the results of docking and MD simulation, coniselin and coniferyl ferulate have high binding affinity and stable interactions with the SETD2 protein. Coniselin is isolated from the alcoholic extract of Comiselinum vaginatum Thell. Coniferyl ferulate can be isolated from Angelica sinensis, Poria cocos (Schw.) Wolf, and Notopterygium forbesii. Although S-adenosyl-L-homocysteine has more stable interactions with key residues in the binding domain than coniselin and coniferyl ferulate during MD simulation, the TCM compounds coniselin and coniferyl ferulate are still potential candidates as lead compounds for further study in the drug development process with the SETD2 protein against acute lymphoblastic leukaemia.

Ranking targets in structure-based virtual screening of three-dimensional protein libraries: methods and problems.

PubMed

Kellenberger, Esther; Foata, Nicolas; Rognan, Didier

2008-05-01

Structure-based virtual screening is a promising tool to identify putative targets for a specific ligand. Instead of docking multiple ligands into a single protein cavity, a single ligand is docked in a collection of binding sites. In inverse screening, hits are in fact targets which have been prioritized within the pool of best ranked proteins. The target rate depends on specificity and promiscuity in protein-ligand interactions and, to a considerable extent, on the effectiveness of the scoring function, which still is the Achilles' heel of molecular docking. In the present retrospective study, virtual screening of the sc-PDB target library by GOLD docking was carried out for four compounds (biotin, 4-hydroxy-tamoxifen, 6-hydroxy-1,6-dihydropurine ribonucleoside, and methotrexate) of known sc-PDB targets and, several ranking protocols based on GOLD fitness score and topological molecular interaction fingerprint (IFP) comparison were evaluated. For the four investigated ligands, the fusion of GOLD fitness and two IFP scores allowed the recovery of most targets, including the rare proteins which are not readily suitable for statistical analysis, while significantly filtering out most false positive entries. The current survey suggests that selecting a small number of targets (<20) for experimental evaluation is achievable with a pure structure-based approach.

Evaluation of protein adsorption and preferred binding regions in multimodal chromatography using NMR

PubMed Central

Chung, Wai Keen; Freed, Alexander S.; Holstein, Melissa A.; McCallum, Scott A.; Cramer, Steven M.

2010-01-01

NMR titration experiments with labeled human ubiquitin were employed in concert with chromatographic data obtained with a library of ubiquitin mutants to study the nature of protein adsorption in multimodal (MM) chromatography. The elution order of the mutants on the MM resin was significantly different from that obtained by ion-exchange chromatography. Further, the chromatographic results with the protein library indicated that mutations in a defined region induced greater changes in protein affinity to the solid support. Chemical shift mapping and determination of dissociation constants from NMR titration experiments with the MM ligand and isotopically enriched ubiquitin were used to determine and rank the relative binding affinities of interaction sites on the protein surface. The results with NMR confirmed that the protein possessed a distinct preferred binding region for the MM ligand in agreement with the chromatographic results. Finally, coarse-grained ligand docking simulations were employed to study the modes of interaction between the MM ligand and ubiquitin. The use of NMR titration experiments in concert with chromatographic data obtained with protein libraries represents a previously undescribed approach for elucidating the structural basis of protein binding affinity in MM chromatographic systems. PMID:20837551

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling

NASA Astrophysics Data System (ADS)

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling.

PubMed

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Ensemble-based docking: From hit discovery to metabolism and toxicity predictions.

PubMed

Evangelista, Wilfredo; Weir, Rebecca L; Ellingson, Sally R; Harris, Jason B; Kapoor, Karan; Smith, Jeremy C; Baudry, Jerome

2016-10-15

This paper describes and illustrates the use of ensemble-based docking, i.e., using a collection of protein structures in docking calculations for hit discovery, the exploration of biochemical pathways and toxicity prediction of drug candidates. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rapid computational identification of the targets of protein kinase inhibitors.

PubMed

Rockey, William M; Elcock, Adrian H

2005-06-16

We describe a method for rapidly computing the relative affinities of an inhibitor for all individual members of a family of homologous receptors. The approach, implemented in a new program, SCR, models inhibitor-receptor interactions in full atomic detail with an empirical energy function and includes an explicit account of flexibility in homology-modeled receptors through sampling of libraries of side chain rotamers. SCR's general utility was demonstrated by application to seven different protein kinase inhibitors: for each inhibitor, relative binding affinities with panels of approximately 20 protein kinases were computed and compared with experimental data. For five of the inhibitors (SB203580, purvalanol B, imatinib, H89, and hymenialdisine), SCR provided excellent reproduction of the experimental trends and, importantly, was capable of identifying the targets of inhibitors even when they belonged to different kinase families. The method's performance in a predictive setting was demonstrated by performing separate training and testing applications, and its key assumptions were tested by comparison with a number of alternative approaches employing the ligand-docking program AutoDock (Morris et al. J. Comput. Chem. 1998, 19, 1639-1662). These comparison tests included using AutoDock in nondocking and docking modes and performing energy minimizations of inhibitor-kinase complexes with the molecular mechanics code GROMACS (Berendsen et al. Comput. Phys. Commun. 1995, 91, 43-56). It was found that a surprisingly important aspect of SCR's approach is its assumption that the inhibitor be modeled in the same orientation for each kinase: although this assumption is in some respects unrealistic, calculations that used apparently more realistic approaches produced clearly inferior results. Finally, as a large-scale application of the method, SB203580, purvalanol B, and imatinib were screened against an almost full complement of 493 human protein kinases using SCR in order to identify potential new targets; the predicted targets of SB203580 were compared with those identified in recent proteomics-based experiments. These kinome-wide screens, performed within a day on a small cluster of PCs, indicate that explicit computation of inhibitor-receptor binding affinities has the potential to promote rapid discovery of new therapeutic targets for existing inhibitors.

In silico characterization and analysis of RTBP1 and NgTRF1 protein through MD simulation and molecular docking - A comparative study.

PubMed

Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran

2015-02-06

Gaining access to sequence and structure information of telomere binding proteins helps in understanding the essential biological processes involve in conserved sequence specific interaction between DNA and the proteins. Rice telomere binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix turn helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain but till now there is very less communication on the in silico studies of these complete proteins.Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK web server.Digging up all the facts about the proteins it was reveled that around 120 amino acids in the tail part was showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicates the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and Energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

In Silico Characterization and Analysis of RTBP1 and NgTRF1 Protein Through MD Simulation and Molecular Docking: A Comparative Study.

PubMed

Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran

2015-09-01

Gaining access to sequence and structure information of telomere-binding proteins helps in understanding the essential biological processes involve in conserved sequence-specific interaction between DNA and the proteins. Rice telomere-binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix-turn-helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain, but till now there is very less communication on the in silico studies of these complete proteins. Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK Web server. By digging up all the facts about the proteins, it was revealed that around 120 amino acids in the tail part were showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicate the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA-binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

Ultrafast protein structure-based virtual screening with Panther

NASA Astrophysics Data System (ADS)

Niinivehmas, Sanna P.; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T.

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Ultrafast protein structure-based virtual screening with Panther.

PubMed

Niinivehmas, Sanna P; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

An In-Silico Investigation of Phytochemicals as Antiviral Agents Against Dengue Fever.

PubMed

Powers, Chelsea N; Setzer, William N

2016-01-01

A virtual screening analysis of our library of phytochemical structures with dengue virus protein targets has been carried out using a molecular docking approach. A total of 2194 plant-derived secondary metabolites have been docked. This molecule set comprised of 290 alkaloids (68 indole alkaloids, 153 isoquinoline alkaloids, 5 quinoline alkaloids, 13 piperidine alkaloids, 14 steroidal alkaloids, and 37 miscellaneous alkaloids), 678 terpenoids (47 monoterpenoids, 169 sesquiterpenoids, 265 diterpenoids, 81 steroids, and 96 triterpenoids), 20 aurones, 81 chalcones, 349 flavonoids, 120 isoflavonoids, 74 lignans, 58 stilbenoids, 169 miscellaneous polyphenolic compounds, 100 coumarins, 28 xanthones, 67 quinones, and 160 miscellaneous phytochemicals. Dengue virus protein targets examined included dengue virus protease (NS2B-NS3pro), helicase (NS3 helicase), methyltransferase (MTase), RNA-dependent RNA polymerase (RdRp), and the dengue virus envelope protein. Polyphenolic compounds, flavonoids, chalcones, and other phenolics were the most numerous of the strongly docking ligands for dengue virus protein targets.

Tail Docking of Canine Puppies: Reassessment of the Tail's Role in Communication, the Acute Pain Caused by Docking and Interpretation of Behavioural Responses.

PubMed

Mellor, David J

2018-05-31

Laws, regulations and professional standards increasingly aim to ban or restrict non-therapeutic tail docking in canine puppies. These constraints have usually been justified by reference to loss of tail participation in communication between dogs, the acute pain presumed to be caused during docking itself, subsequent experiences of chronic pain and heightened pain sensitivity, and the occurrence of other complications. These areas are reconsidered here. First, a scientifically robust examination of the dynamic functional foundations, sensory components and key features of body language that are integral to canine communication shows that the role of the tail has been greatly underestimated. More specifically, it shows that tail behaviour is so embedded in canine communication that docking can markedly impede unambiguous interactions between different dogs and between dogs and people. These interactions include the expression of wide ranges of both negative and positive emotions, moods and intentions that are of daily significance for dog welfare. Moreover, all docked dogs may experience these impediments throughout their lives, which challenges assertions by opponents to such bans or restrictions that the tail is a dispensable appendage. Second, and in contrast, a re-examination of the sensory capacities of canine puppies reveals that they cannot consciously experience acute or chronic pain during at least the first week after birth, which is when they are usually docked. The contrary view is based on questionable between-species extrapolation of information about pain from neurologically mature newborns such as calves, lambs, piglets and human infants, which certainly can consciously experience pain in response to injury, to neurologically immature puppies which remain unconscious and therefore unable to experience pain until about two weeks after birth. Third, underpinned by the incorrect conclusion that puppies are conscious at the usual docking age, it is argued here that the well-validated human emotional drive or desire to care for and protect vulnerable young, leads observers to misread striking docking-induced behaviour as indicating that the puppies consciously experience significant acute pain and distress. Fourth, updated information reaffirms the conclusion that a significant proportion of dogs docked as puppies will subsequently experience persistent and significant chronic pain and heightened pain sensitivity. And fifth, other reported negative consequences of docking should also be considered because, although their prevalence is unclear, when they do occur they would have significant negative welfare impacts. It is argued that the present analysis strengthens the rationale for such bans or restrictions on docking of puppies by clarifying which of several justifications previously used are and are not scientifically supportable. In particular, it highlights the major roles the tail plays in canine communication, as well as the lifetime handicaps to communication caused by docking. Thus, it is concluded that non-therapeutic tail docking of puppies represents an unnecessary removal of a necessary appendage and should therefore be banned or restricted.

Principal component analysis on molecular descriptors as an alternative point of view in the search of new Hsp90 inhibitors.

PubMed

Lauria, Antonino; Ippolito, Mario; Almerico, Anna Maria

2009-10-01

Inhibiting a protein that regulates multiple signal transduction pathways in cancer cells is an attractive goal for cancer therapy. Heat shock protein 90 (Hsp90) is one of the most promising molecular targets for such an approach. In fact, Hsp90 is a ubiquitous molecular chaperone protein that is involved in folding, activating and assembling of many key mediators of signal transduction, cellular growth, differentiation, stress-response and apoptothic pathways. With the aim to analyze which molecular descriptors have the higher importance in the binding interactions of these classes, we first performed molecular docking experiments on the 187 Hsp90 inhibitors included in the BindingDB, a public database of measured binding affinities. Further, for each frozen conformation obtained from the docking, a set of 250 molecular descriptors was calculated, and the resulting Structure/Descriptors matrix was submitted to Principal Component Analysis. From the factor scores it emerged a good clusterization among similar compounds both in terms of structural class and activity spectrum, while examination of the loadings of the first two factors also allowed to study the classes of descriptors which mainly contribute to each one.

FlexAID: Revisiting Docking on Non-Native-Complex Structures.

PubMed

Gaudreault, Francis; Najmanovich, Rafael J

2015-07-27

Small-molecule protein docking is an essential tool in drug design and to understand molecular recognition. In the present work we introduce FlexAID, a small-molecule docking algorithm that accounts for target side-chain flexibility and utilizes a soft scoring function, i.e. one that is not highly dependent on specific geometric criteria, based on surface complementarity. The pairwise energy parameters were derived from a large dataset of true positive poses and negative decoys from the PDBbind database through an iterative process using Monte Carlo simulations. The prediction of binding poses is tested using the widely used Astex dataset as well as the HAP2 dataset, while performance in virtual screening is evaluated using a subset of the DUD dataset. We compare FlexAID to AutoDock Vina, FlexX, and rDock in an extensive number of scenarios to understand the strengths and limitations of the different programs as well as to reported results for Glide, GOLD, and DOCK6 where applicable. The most relevant among these scenarios is that of docking on flexible non-native-complex structures where as is the case in reality, the target conformation in the bound form is not known a priori. We demonstrate that FlexAID, unlike other programs, is robust against increasing structural variability. FlexAID obtains equivalent sampling success as GOLD and performs better than AutoDock Vina or FlexX in all scenarios against non-native-complex structures. FlexAID is better than rDock when there is at least one critical side-chain movement required upon ligand binding. In virtual screening, FlexAID results are lower on average than those of AutoDock Vina and rDock. The higher accuracy in flexible targets where critical movements are required, intuitive PyMOL-integrated graphical user interface and free source code as well as precompiled executables for Windows, Linux, and Mac OS make FlexAID a welcome addition to the arsenal of existing small-molecule protein docking methods.

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

PubMed Central

Fang, Ye; Ding, Yun; Feinstein, Wei P.; Koppelman, David M.; Moreno, Juana; Jarrell, Mark; Ramanujam, J.; Brylinski, Michal

2016-01-01

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249. PMID:27420300

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

PubMed

Fang, Ye; Ding, Yun; Feinstein, Wei P; Koppelman, David M; Moreno, Juana; Jarrell, Mark; Ramanujam, J; Brylinski, Michal

2016-01-01

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.

Domain-specific interactions between MLN8237 and human serum albumin estimated by STD and WaterLOGSY NMR, ITC, spectroscopic, and docking techniques.

PubMed

Yang, Hongqin; Liu, Jiuyang; Huang, Yanmei; Gao, Rui; Tang, Bin; Li, Shanshan; He, Jiawei; Li, Hui

2017-03-30

Alisertib (MLN8237) is an orally administered inhibitor of Aurora A kinase. This small-molecule inhibitor is under clinical or pre-clinical phase for the treatment of advanced malignancies. The present study provides a detailed characterization of the interaction of MLN8237 with a drug transport protein called human serum albumin (HSA). STD and WaterLOGSY nuclear magnetic resonance (NMR)-binding studies were conducted first to confirm the binding of MLN8237 to HSA. In the ligand orientation assay, the binding sites of MLN8237 were validated through two site-specific spy molecules (warfarin sodium and ibuprofen, which are two known site-selective probes) by using STD and WaterLOGSY NMR competition techniques. These competition experiments demonstrate that both spy molecules do not compete with MLN8237 for the specific binding site. The AutoDock-based blind docking study recognizes the hydrophobic subdomain IB of the protein as the probable binding site for MLN8237. Thermodynamic investigations by isothermal titration calorimetry (ITC) reveal that the non-covalent interaction between MLN8237 and HSA (binding constant was approximately 10 5  M -1 ) is driven mainly by favorable entropy and unfavorable enthalpy. In addition, synchronous fluorescence, circular dichroism (CD), and 3D fluorescence spectroscopy suggest that MLN8237 may induce conformational changes in HSA.

Domain-specific interactions between MLN8237 and human serum albumin estimated by STD and WaterLOGSY NMR, ITC, spectroscopic, and docking techniques

PubMed Central

Yang, Hongqin; Liu, Jiuyang; Huang, Yanmei; Gao, Rui; Tang, Bin; Li, Shanshan; He, Jiawei; Li, Hui

2017-01-01

Alisertib (MLN8237) is an orally administered inhibitor of Aurora A kinase. This small-molecule inhibitor is under clinical or pre-clinical phase for the treatment of advanced malignancies. The present study provides a detailed characterization of the interaction of MLN8237 with a drug transport protein called human serum albumin (HSA). STD and WaterLOGSY nuclear magnetic resonance (NMR)-binding studies were conducted first to confirm the binding of MLN8237 to HSA. In the ligand orientation assay, the binding sites of MLN8237 were validated through two site-specific spy molecules (warfarin sodium and ibuprofen, which are two known site-selective probes) by using STD and WaterLOGSY NMR competition techniques. These competition experiments demonstrate that both spy molecules do not compete with MLN8237 for the specific binding site. The AutoDock-based blind docking study recognizes the hydrophobic subdomain IB of the protein as the probable binding site for MLN8237. Thermodynamic investigations by isothermal titration calorimetry (ITC) reveal that the non-covalent interaction between MLN8237 and HSA (binding constant was approximately 105 M−1) is driven mainly by favorable entropy and unfavorable enthalpy. In addition, synchronous fluorescence, circular dichroism (CD), and 3D fluorescence spectroscopy suggest that MLN8237 may induce conformational changes in HSA. PMID:28358124

Clostridium perfringens Iota-Toxin: Mapping of Receptor Binding and Ia Docking Domains on Ib

PubMed Central

Marvaud, Jean-Christophe; Smith, Theresa; Hale, Martha L.; Popoff, Michel R.; Smith, Leonard A.; Stiles, Bradley G.

2001-01-01

Clostridium perfringens iota-toxin is a binary toxin consisting of iota a (Ia), an ADP-ribosyltransferase that modifies actin, and iota b (Ib), which binds to a cell surface protein and translocates Ia into a target cell. Fusion proteins of recombinant Ib and truncated variants were tested for binding to Vero cells and docking with Ia via fluorescence-activated cytometry and cytotoxicity experiments. C-terminal residues (656 to 665) of Ib were critical for cell surface binding, and truncated Ib variants containing ≥200 amino acids of the C terminus were effective Ib competitors and prevented iota cytotoxicity. The N-terminal domain (residues 1 to 106) of Ib was important for Ia docking, yet this region was not an effective competitor of iota cytotoxicity. Further studies showed that Ib lacking just the N-terminal 27 residues did not facilitate Ia entry into a target cell and subsequent cytotoxicity. Five monoclonal antibodies against Ib were also tested with each truncated Ib variant for epitope and structural mapping by surface plasmon resonance and an enzyme-linked immunosorbent assay. Each antibody bound to a linear epitope within the N terminus (residues 28 to 66) or the C terminus (residues 632 to 655). Antibodies that target the C terminus neutralized in vitro cytotoxicity and delayed the lethal effects of iota-toxin in mice. PMID:11254604

Domain-specific interactions between MLN8237 and human serum albumin estimated by STD and WaterLOGSY NMR, ITC, spectroscopic, and docking techniques

NASA Astrophysics Data System (ADS)

Yang, Hongqin; Liu, Jiuyang; Huang, Yanmei; Gao, Rui; Tang, Bin; Li, Shanshan; He, Jiawei; Li, Hui

2017-03-01

Alisertib (MLN8237) is an orally administered inhibitor of Aurora A kinase. This small-molecule inhibitor is under clinical or pre-clinical phase for the treatment of advanced malignancies. The present study provides a detailed characterization of the interaction of MLN8237 with a drug transport protein called human serum albumin (HSA). STD and WaterLOGSY nuclear magnetic resonance (NMR)-binding studies were conducted first to confirm the binding of MLN8237 to HSA. In the ligand orientation assay, the binding sites of MLN8237 were validated through two site-specific spy molecules (warfarin sodium and ibuprofen, which are two known site-selective probes) by using STD and WaterLOGSY NMR competition techniques. These competition experiments demonstrate that both spy molecules do not compete with MLN8237 for the specific binding site. The AutoDock-based blind docking study recognizes the hydrophobic subdomain IB of the protein as the probable binding site for MLN8237. Thermodynamic investigations by isothermal titration calorimetry (ITC) reveal that the non-covalent interaction between MLN8237 and HSA (binding constant was approximately 105 M-1) is driven mainly by favorable entropy and unfavorable enthalpy. In addition, synchronous fluorescence, circular dichroism (CD), and 3D fluorescence spectroscopy suggest that MLN8237 may induce conformational changes in HSA.

Coordinating structural and functional synapse development: postsynaptic p21-activated kinase independently specifies glutamate receptor abundance and postsynaptic morphology.

PubMed

Albin, Stephanie D; Davis, Graeme W

2004-08-04

Here, we show that postsynaptic p21-activated kinase (Pak) signaling diverges into two genetically separable pathways at the Drosophila neuromuscular junction. One pathway controls glutamate receptor abundance. Pak signaling within this pathway is specified by a required interaction with the adaptor protein Dreadlocks (Dock). We demonstrate that Dock is localized to the synapse via an Src homology 2-mediated protein interaction. Dock is not necessary for Pak localization but is necessary to restrict Pak signaling to control glutamate receptor abundance. A second genetically separable function of Pak kinase signaling controls muscle membrane specialization through the regulation of synaptic Discs-large. In this pathway, Dock is dispensable. We present a model in which divergent Pak signaling is able to coordinate two different features of postsynaptic maturation, receptor abundance, and muscle membrane specialization.

The SH2/SH3 adaptor protein dock interacts with the Ste20-like kinase misshapen in controlling growth cone motility.

PubMed

Ruan, W; Pang, P; Rao, Y

1999-11-01

Recent studies suggest that the SH2/SH3 adaptor Dock/Nck transduces tyrosine phosphorylation signals to the actin cytoskeleton in regulating growth cone motility. The signaling cascade linking the action of Dock/Nck to the reorganization of cytoskeleton is poorly understood. We now demonstrate that Dock interacts with the Ste20-like kinase Misshapen (Msn) in the Drosophila photoreceptor (R cell) growth cones. Loss of msn causes a failure of growth cones to stop at the target, a phenotype similar to loss of dock, whereas overexpression of msn induces pretarget growth cone termination. Physical and genetic interactions between Msn and Dock indicate a role for Msn in the Dock signaling pathway. We propose that Msn functions as a key controller of growth cone cytoskeleton in response to Dock-mediated signals.

CovalentDock Cloud: a web server for automated covalent docking.

PubMed

Ouyang, Xuchang; Zhou, Shuo; Ge, Zemei; Li, Runtao; Kwoh, Chee Keong

2013-07-01

Covalent binding is an important mechanism for many drugs to gain its function. We developed a computational algorithm to model this chemical event and extended it to a web server, the CovalentDock Cloud, to make it accessible directly online without any local installation and configuration. It provides a simple yet user-friendly web interface to perform covalent docking experiments and analysis online. The web server accepts the structures of both the ligand and the receptor uploaded by the user or retrieved from online databases with valid access id. It identifies the potential covalent binding patterns, carries out the covalent docking experiments and provides visualization of the result for user analysis. This web server is free and open to all users at http://docking.sce.ntu.edu.sg/.

CovalentDock Cloud: a web server for automated covalent docking

PubMed Central

Ouyang, Xuchang; Zhou, Shuo; Ge, Zemei; Li, Runtao; Kwoh, Chee Keong

2013-01-01

Covalent binding is an important mechanism for many drugs to gain its function. We developed a computational algorithm to model this chemical event and extended it to a web server, the CovalentDock Cloud, to make it accessible directly online without any local installation and configuration. It provides a simple yet user-friendly web interface to perform covalent docking experiments and analysis online. The web server accepts the structures of both the ligand and the receptor uploaded by the user or retrieved from online databases with valid access id. It identifies the potential covalent binding patterns, carries out the covalent docking experiments and provides visualization of the result for user analysis. This web server is free and open to all users at http://docking.sce.ntu.edu.sg/. PMID:23677616

Conserved electrostatic fields at the Ras-effector interface measured through vibrational Stark effect spectroscopy explain the difference in tilt angle in the Ras binding domains of Raf and RalGDS.

PubMed

Walker, David M; Wang, Ruifei; Webb, Lauren J

2014-10-07

Vibrational Stark effect (VSE) spectroscopy was used to measure the electrostatic fields present at the interface of the human guanosine triphosphatase (GTPase) Ras docked with the Ras binding domain (RBD) of the protein kinase Raf. Nine amino acids located on the surface of Raf were selected for labeling with a nitrile vibrational probe. Eight of the probe locations were situated along the interface of Ras and Raf, and one probe was 2 nm away on the opposite side of Raf. Vibrational frequencies of the nine Raf nitrile probes were compared both in the monomeric, solvated protein and when docked with wild-type (WT) Ras to construct a comprehensive VSE map of the Ras-Raf interface. Molecular dynamics (MD) simulations employing an umbrella sampling strategy were used to generate a Boltzmann-weighted ensemble of nitrile positions in both the monomeric and docked complexes to determine the effect that docking has on probe location and orientation and to aid in the interpretation of VSE results. These results were compared to an identical study that was previously conducted on nine nitrile probes on the RBD of Ral guanidine dissociation stimulator (RalGDS) to make comparisons between the docked complexes formed when either of the two effectors bind to WT Ras. This comparison finds that there are three regions of conserved electrostatic fields that are formed upon docking of WT Ras with both downstream effectors. Conservation of this pattern in the docked complex then results in different binding orientations observed in otherwise structurally similar proteins. This work supports an electrostatic cause of the known binding tilt angle between the Ras-Raf and Ras-RalGDS complexes.

Computational evaluation of new homologous down regulators of Translationally Controlled Tumor Protein (TCTP) targeted for tumor reversion.

PubMed

Nayarisseri, Anuraj; Yadav, Mukesh; Wishard, Rohan

2013-12-01

The Translationally Controlled Tumor Protein (TCTP) has been investigated for tumor reversion and is a target of cancer therapy. Down regulators which suppress the expression of TCTP can trigger the process of tumor reversion leading to the transformation of tumor cells into revertant cells. The present investigation is a novel protein-protein docking approach to target TCTP by a set of proteins similar to the protein: sorting nexin 6 (SNX6) which is an established down regulator of TCTP. The established down regulator along with its set of most similar proteins were modeled using the PYTHON based software - MODELLER v9.9, followed by structure validation using the Procheck Package. Further TCTP was docked with its established and prospective down regulators using the flexible docking protocol suite HADDOCK. The results were evaluated and ranked according to the RMSD values of the complex and the HADDOCK score, which is a weighted sum of van der Waal's energy, electrostatic energy, restraints violation energy and desolvation energy. Results concluded the protein sorting nexin 6 of Mus musculus to be a better down regulator of TCTP, as compared to the suggested down regulator (Homo sapiens snx6).

Task-parallel message passing interface implementation of Autodock4 for docking of very large databases of compounds using high-performance super-computers.

PubMed

Collignon, Barbara; Schulz, Roland; Smith, Jeremy C; Baudry, Jerome

2011-04-30

A message passing interface (MPI)-based implementation (Autodock4.lga.MPI) of the grid-based docking program Autodock4 has been developed to allow simultaneous and independent docking of multiple compounds on up to thousands of central processing units (CPUs) using the Lamarkian genetic algorithm. The MPI version reads a single binary file containing precalculated grids that represent the protein-ligand interactions, i.e., van der Waals, electrostatic, and desolvation potentials, and needs only two input parameter files for the entire docking run. In comparison, the serial version of Autodock4 reads ASCII grid files and requires one parameter file per compound. The modifications performed result in significantly reduced input/output activity compared with the serial version. Autodock4.lga.MPI scales up to 8192 CPUs with a maximal overhead of 16.3%, of which two thirds is due to input/output operations and one third originates from MPI operations. The optimal docking strategy, which minimizes docking CPU time without lowering the quality of the database enrichments, comprises the docking of ligands preordered from the most to the least flexible and the assignment of the number of energy evaluations as a function of the number of rotatable bounds. In 24 h, on 8192 high-performance computing CPUs, the present MPI version would allow docking to a rigid protein of about 300K small flexible compounds or 11 million rigid compounds.

Epitope-based immunoinformatics and molecular docking studies of nucleocapsid protein and ovarian tumor domain of crimean-congo hemorrhagic Fever virus.

PubMed

Srinivasan, Pappu; Kumar, Sivakumar Prasanth; Karthikeyan, Muthusamy; Jeyakanthan, Jeyaram; Jasrai, Yogesh T; Pandya, Himanshu A; Rawal, Rakesh M; Patel, Saumya K

2011-01-01

Crimean-Congo hemorrhagic fever virus (CCHFV), the fatal human pathogen is transmitted to humans by tick bite, or exposure to infected blood or tissues of infected livestock. The CCHFV genome consists of three RNA segments namely, S, M, and L. The unusual large viral L protein has an ovarian tumor (OTU) protease domain located in the N terminus. It is likely that the protein may be autoproteolytically cleaved to generate the active virus L polymerase with additional functions. Identification of the epitope regions of the virus is important for the diagnosis, phylogeny studies, and drug discovery. Early diagnosis and treatment of CCHF infection is critical to the survival of patients and the control of the disease. In this study, we undertook different in silico approaches using molecular docking and immunoinformatics tools to predict epitopes which can be helpful for vaccine designing. Small molecule ligands against OTU domain and protein-protein interaction between a viral and a host protein have been studied using docking tools.

Binding of mitomycin C to blood proteins: A spectroscopic analysis and molecular docking

NASA Astrophysics Data System (ADS)

Jang, Jongchol; Liu, Hui; Chen, Wei; Zou, Guolin

2009-06-01

Mitomycin C (MMC) was the first recognized bioreductive alkylating agent, and has been widely used clinically for antitumor therapy. The binding of MMC to two human blood proteins, human serum albumin (HSA) and human hemoglobin (HHb), have been investigated by fluorescence quenching, synchronous fluorescence, circular dichroism (CD) spectroscopy and molecular docking methods. The fluorescence data showed that binding of MMC to proteins caused strong fluorescence quenching of proteins through a static quenching way, and each protein had only one binding site for the drug. The binding constants of MMC to HSA and HHb at 298 K were 2.71 × 10 4 and 2.56 × 10 4 L mol -1, respectively. Thermodynamic analysis suggested that both hydrophobic interaction and hydrogen bonding played major roles in the binding of MMC to HSA or HHb. The CD spectroscopy indicated that the secondary structures of the two proteins were not changed in the presence of MMC. The study of molecular docking showed that MMC was located in the entrance of site I of HSA, and in the central cavity of HHb.

A Systems Biology-Based Approach to Uncovering Molecular Mechanisms Underlying Effects of Traditional Chinese Medicine Qingdai in Chronic Myelogenous Leukemia, Involving Integration of Network Pharmacology and Molecular Docking Technology.

PubMed

Zhou, Chao; Liu, LiJuan; Zhuang, Jing; Wei, JunYu; Zhang, TingTing; Gao, ChunDi; Liu, Cun; Li, HuaYao; Si, HongZong; Sun, ChangGang

2018-06-23

BACKGROUND The method of multiple targets overall control is increasingly used to predict the main active ingredient and potential target group of Chinese traditional medicines and to determine the mechanisms involved in their curative effects. Qingdai is the main traditional Chinese medicine used in the treatment of chronic myelogenous leukemia (CML), but the complex active ingredients and antitumor targets in treatment of CML have not been clearly defined in previous studies. MATERIAL AND METHODS We constructed a protein-protein interaction network diagram of CML with 638 nodes (proteins) and 1830 edges, based on the biological function of chronic myelocytic leukemia by use of Cytoscape, and we determined 19 key gene nodes in the CML molecule by network topological properties analysis in a data bank. Then, we used the Surflex-dock plugin in SYBYL7.3 docking and acquired the protein crystal structures of key genes involved in CML from the chemical composition of the traditional Chinese medicine Qingdai with key proteins in CML networks. RESULTS According to the score and the spatial structure, the pharmacodynamically active ingredients of Qingdai are Isdirubin, Isoindigo, N-phenyl-2-naphthylamine, and Isatin, among which Isdirubin is the most important. We further screened the most effective activity key protein structures of CML to find the best pharmacodynamically active ingredients of Qingdai, according to the binding interactions of the inhibitors at the catalytic site performed in best docking combinations. CONCLUSIONS The results suggest that Isdirubin plays a role in resistance to CML by altering the expressions of PIK3CA, MYC, JAK2, and TP53 target proteins. Network pharmacology and molecular docking technology can be used to search for possible reactive molecules in traditional chinese medicines (TCM) and to elucidate their molecular mechanisms.

Template-Based Modeling of Protein-RNA Interactions

PubMed Central

Zheng, Jinfang; Kundrotas, Petras J.; Vakser, Ilya A.

2016-01-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes. PMID:27662342

Comparing the binding interaction between β-lactoglobulin and flavonoids with different structure by multi-spectroscopy analysis and molecular docking.

PubMed

Li, Ti; Hu, Peng; Dai, Taotao; Li, Panying; Ye, Xiaoqin; Chen, Jun; Liu, Chengmei

2018-05-04

Four kinds of flavonoids (apigenin, naringenin, kaempferol, genistein) were skillfully selected to investigate the interaction between flavonoids and β-lactoglobulin (β-LG) by multi-spectroscopy analysis and molecular docking. Hydrogenation on C2C3 double bond weakened the affinity of apigenin for β-LG and it's most obvious, followed by hydroxylation of C3 and position isomerism of phenyl ring B. The main interaction force for apigenin and naringenin binding to β-LG (van der Waals forces and hydrogen bonds) was different from that of genistein and kaempferol (hydrophobic interactions). Circular dichroism and fluorescence experiments indicated that conformation of β-LG became loose and surface hydrophobicity of β-LG was reduced in the presence of flavonoids. Molecular docking indicated that flavonoids interacted with specific amino acid residues located on the outer surface of β-LG. These findings can provide a deep understanding about the interaction mechanism between flavonoids and protein, and it may be valuable in dairy incorporation with flavonoids. Copyright © 2018. Published by Elsevier B.V.

Charged and Hydrophobic Surfaces on the A Chain of Shiga-Like Toxin 1 Recognize the C-Terminal Domain of Ribosomal Stalk Proteins

PubMed Central

McCluskey, Andrew J.; Bolewska-Pedyczak, Eleonora; Jarvik, Nick; Chen, Gang; Sidhu, Sachdev S.; Gariépy, Jean

2012-01-01

Shiga-like toxins are ribosome-inactivating proteins (RIP) produced by pathogenic E. coli strains that are responsible for hemorrhagic colitis and hemolytic uremic syndrome. The catalytic A1 chain of Shiga-like toxin 1 (SLT-1), a representative RIP, first docks onto a conserved peptide SD[D/E]DMGFGLFD located at the C-terminus of all three eukaryotic ribosomal stalk proteins and halts protein synthesis through the depurination of an adenine base in the sarcin-ricin loop of 28S rRNA. Here, we report that the A1 chain of SLT-1 rapidly binds to and dissociates from the C-terminal peptide with a monomeric dissociation constant of 13 µM. An alanine scan performed on the conserved peptide revealed that the SLT-1 A1 chain interacts with the anionic tripeptide DDD and the hydrophobic tetrapeptide motif FGLF within its sequence. Based on these 2 peptide motifs, SLT-1 A1 variants were generated that displayed decreased affinities for the stalk protein C-terminus and also correlated with reduced ribosome-inactivating activities in relation to the wild-type A1 chain. The toxin-peptide interaction and subsequent toxicity were shown to be mediated by cationic and hydrophobic docking surfaces on the SLT-1 catalytic domain. These docking surfaces are located on the opposite face of the catalytic cleft and suggest that the docking of the A1 chain to SDDDMGFGLFD may reorient its catalytic domain to face its RNA substrate. More importantly, both the delineated A1 chain ribosomal docking surfaces and the ribosomal peptide itself represent a target and a scaffold, respectively, for the design of generic inhibitors to block the action of RIPs. PMID:22355345

High-throughput docking for the identification of new influenza A virus polymerase inhibitors targeting the PA-PB1 protein-protein interaction.

PubMed

Tintori, Cristina; Laurenzana, Ilaria; Fallacara, Anna Lucia; Kessler, Ulrich; Pilger, Beatrice; Stergiou, Lilli; Botta, Maurizio

2014-01-01

A high-throughput molecular docking approach was successfully applied for the selection of potential inhibitors of the Influenza RNA-polymerase which act by targeting the PA-PB1 protein-protein interaction. Commercially available compounds were purchased and biologically evaluated in vitro using an ELISA-based assay. As a result, some compounds possessing a 3-cyano-4,6-diphenyl-pyridine nucleus emerged as effective inhibitors with the best ones showing IC50 values in the micromolar range. Copyright © 2013 Elsevier Ltd. All rights reserved.

Unraveling the molecular mechanisms of nitrogenase conformational protection against oxygen in diazotrophic bacteria.

PubMed

Lery, Letícia M S; Bitar, Mainá; Costa, Mauricio G S; Rössle, Shaila C S; Bisch, Paulo M

2010-12-22

G. diazotrophicus and A. vinelandii are aerobic nitrogen-fixing bacteria. Although oxygen is essential for the survival of these organisms, it irreversibly inhibits nitrogenase, the complex responsible for nitrogen fixation. Both microorganisms deal with this paradox through compensatory mechanisms. In A. vinelandii a conformational protection mechanism occurs through the interaction between the nitrogenase complex and the FeSII protein. Previous studies suggested the existence of a similar system in G. diazotrophicus, but the putative protein involved was not yet described. This study intends to identify the protein coding gene in the recently sequenced genome of G. diazotrophicus and also provide detailed structural information of nitrogenase conformational protection in both organisms. Genomic analysis of G. diazotrophicus sequences revealed a protein coding ORF (Gdia0615) enclosing a conserved "fer2" domain, typical of the ferredoxin family and found in A. vinelandii FeSII. Comparative models of both FeSII and Gdia0615 disclosed a conserved beta-grasp fold. Cysteine residues that coordinate the 2[Fe-S] cluster are in conserved positions towards the metallocluster. Analysis of solvent accessible residues and electrostatic surfaces unveiled an hydrophobic dimerization interface. Dimers assembled by molecular docking presented a stable behaviour and a proper accommodation of regions possibly involved in binding of FeSII to nitrogenase throughout molecular dynamics simulations in aqueous solution. Molecular modeling of the nitrogenase complex of G. diazotrophicus was performed and models were compared to the crystal structure of A. vinelandii nitrogenase. Docking experiments of FeSII and Gdia0615 with its corresponding nitrogenase complex pointed out in both systems a putative binding site presenting shape and charge complementarities at the Fe-protein/MoFe-protein complex interface. The identification of the putative FeSII coding gene in G. diazotrophicus genome represents a large step towards the understanding of the conformational protection mechanism of nitrogenase against oxygen. In addition, this is the first study regarding the structural complementarities of FeSII-nitrogenase interactions in diazotrophic bacteria. The combination of bioinformatic tools for genome analysis, comparative protein modeling, docking calculations and molecular dynamics provided a powerful strategy for the elucidation of molecular mechanisms and structural features of FeSII-nitrogenase interaction.

Bone Morphogenetic Protein 4 Promotes Vascular Smooth Muscle Contractility by Activating MicroRNA-21 (miR-21), which Down-regulates Expression of Family of Dedicator of Cytokinesis (DOCK) Proteins*

PubMed Central

Kang, Hara; Davis-Dusenbery, Brandi N.; Nguyen, Peter H.; Lal, Ashish; Lieberman, Judy; Van Aelst, Linda; Lagna, Giorgio; Hata, Akiko

2012-01-01

The bone morphogenetic protein 4 (BMP4) signaling pathway plays a critical role in the promotion and maintenance of the contractile phenotype in vascular smooth muscle cell (vSMC). Misexpression or inactivating mutations of the BMP receptor gene can lead to dedifferentiation of vSMC characterized by increased migration and proliferation that is linked to vascular proliferative disorders. Previously we demonstrated that vSMCs increase microRNA-21 (miR-21) biogenesis upon BMP4 treatment, which induces contractile gene expression by targeting programmed cell death 4 (PDCD4). To identify novel targets of miR-21 that are critical for induction of the contractile phenotype by BMP4, biotinylated miR-21 was expressed in vSMCs followed by an affinity purification of mRNAs associated with miR-21. Nearly all members of the dedicator of cytokinesis (DOCK) 180-related protein superfamily were identified as targets of miR-21. Down-regulation of DOCK4, -5, and -7 by miR-21 inhibited cell migration and promoted cytoskeletal organization by modulating an activity of small GTPase. Thus, this study uncovers a regulatory mechanism of the vSMC phenotype by the BMP4-miR-21 axis through DOCK family proteins. PMID:22158624

Virtual Screening of Novel Glucosamine-6-Phosphate Synthase Inhibitors.

PubMed

Lather, Amit; Sharma, Sunil; Khatkar, Anurag

2018-01-01

Infections caused by microorganisms are the major cause of death today. The tremendous and improper use of antimicrobial agents leads to antimicrobial resistance. Various currently available antimicrobial drugs are inadequate to control the infections and lead to various adverse drug reactions. Efforts based on computer-aided drug design (CADD) can excavate a large number of databases to generate new, potent hits and minimize the requirement of time as well as money for the discovery of newer antimicrobials. Pharmaceutical sciences also have made development with advances in drug designing concepts. The current research article focuses on the study of various G-6-P synthase inhibitors from literature cited molecular database. Docking analysis was conducted and ADMET data of various molecules was evaluated by Schrodinger Glide and PreADMET software, respectively. Here, the results presented efficacy of various inhibitors towards enzyme G-6-P synthase. Docking scores, binding energy and ADMET data of various molecules showed good inhibitory potential toward G-6-P synthase as compared to standard antibiotics. This novel antimicrobial drug target G-6-P synthase has not so extensively been explored for its application in antimicrobial therapy, so the work done so far proved highly essential. This article has helped the drug researchers and scientists to intensively explore about this wonderful antimicrobial drug target. The Schrodinger, Inc. (New York, USA) software was utilized to carry out the computational calculations and docking studies. The hardware configuration was Intel® core (TM) i5-4210U CPU @ 2.40GHz, RAM memory 4.0 GB under 64-bit window operating system. The ADMET data was calculated by using the PreADMET tool (PreADMET ver. 2.0). All the computational work was completed in the Laboratory for Enzyme Inhibition Studies, Department of Pharmaceutical Sciences, M.D. University, Rohtak, INDIA. Molecular docking studies were carried out to identify the binding affinities and interaction between the inhibitors and the target proteins (G-6-P synthase) by using Glide software (Schrodinger Inc. U.S.A.-Maestro version 10.2). Grid-based Ligand Docking with Energetic (Glide) is one of the most accurate docking softwares available for ligand-protein, protein-protein binding studies. A library of hundreds of available ligands was docked against targeted proteins G-6-P synthase having PDB ID 1moq. Results of docking are shown in Table 1 and Table 2. Results of G-6-P synthase docking showed that some compounds were found to have comparable docking score and binding energy (kj/mol) as compared to standard antibiotics. Many of the ligands showed hydrogen bond interaction, hydrophobic interactions, electrostatic interactions, ionic interactions and π- π stacking with the various amino acid residues in the binding pockets of G-6-P synthase. The docking study estimated free energy of binding, binding pose andglide score and all these parameters provide a promising tool for the discovery of new potent natural inhibitors of G-6-P synthase. These G-6-P synthase inhibitors could further be used as antimicrobials. Here, a detailed binding analysis and new insights of inhibitors from various classes of molecules were docked in binding cavity of G-6-P synthase. ADME and toxicity prediction of these compounds will further accentuate us to study these compounds in vivo. This information will possibly present further expansion of effective antimicrobials against several microbial infections. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Conformational analysis, X-ray crystallographic, FT-IR, FT-Raman, DFT, MEP and molecular docking studies on 1-(1-(3-methoxyphenyl) ethylidene) thiosemicarbazide

NASA Astrophysics Data System (ADS)

Saravanan, R. R.; Seshadri, S.; Gunasekaran, S.; Mendoza-Meroño, R.; Garcia-Granda, S.

2015-03-01

Conformational analysis, X-ray crystallographic, FT-IR, FT-Raman, DFT, MEP and molecular docking studies on 1-(1-(3-methoxyphenyl) ethylidene) thiosemicarbazide (MPET) are investigated. From conformational analysis the examination of the positions of a molecule taken and the energy changes is observed. The docking studies of the ligand MPET with target protein showed that this is a good molecule which docks well with target related to HMG-CoA. Hence MPET can be considered for developing into a potent anti-cholesterol drug. MEP assists in optimization of electrostatic interactions between the protein and the ligand. The MEP surface displays the molecular shape, size and electrostatic potential values. The optimized geometry of the compound was calculated from the DFT-B3LYP gradient calculations employing 6-31G (d, p) basis set and calculated vibrational frequencies are evaluated via comparison with experimental values.

Coding and quantification of a facial expression for pain in lambs.

PubMed

Guesgen, M J; Beausoleil, N J; Leach, M; Minot, E O; Stewart, M; Stafford, K J

2016-11-01

Facial expressions are routinely used to assess pain in humans, particularly those who are non-verbal. Recently, there has been an interest in developing coding systems for facial grimacing in non-human animals, such as rodents, rabbits, horses and sheep. The aims of this preliminary study were to: 1. Qualitatively identify facial feature changes in lambs experiencing pain as a result of tail-docking and compile these changes to create a Lamb Grimace Scale (LGS); 2. Determine whether human observers can use the LGS to differentiate tail-docked lambs from control lambs and differentiate lambs before and after docking; 3. Determine whether changes in facial action units of the LGS can be objectively quantified in lambs before and after docking; 4. Evaluate effects of restraint of lambs on observers' perceptions of pain using the LGS and on quantitative measures of facial action units. By comparing images of lambs before (no pain) and after (pain) tail-docking, the LGS was devised in consultation with scientists experienced in assessing facial expression in other species. The LGS consists of five facial action units: Orbital Tightening, Mouth Features, Nose Features, Cheek Flattening and Ear Posture. The aims of the study were addressed in two experiments. In Experiment I, still images of the faces of restrained lambs were taken from video footage before and after tail-docking (n=4) or sham tail-docking (n=3). These images were scored by a group of five naïve human observers using the LGS. Because lambs were restrained for the duration of the experiment, Ear Posture was not scored. The scores for the images were averaged to provide one value per feature per period and then scores for the four LGS action units were averaged to give one LGS score per lamb per period. In Experiment II, still images of the faces nine lambs were taken before and after tail-docking. Stills were taken when lambs were restrained and unrestrained in each period. A different group of five human observers scored the images from Experiment II. Changes in facial action units were also quantified objectively by a researcher using image measurement software. In both experiments LGS scores were analyzed using a linear MIXED model to evaluate the effects of tail docking on observers' perception of facial expression changes. Kendall's Index of Concordance was used to measure reliability among observers. In Experiment I, human observers were able to use the LGS to differentiate docked lambs from control lambs. LGS scores significantly increased from before to after treatment in docked lambs but not control lambs. In Experiment II there was a significant increase in LGS scores after docking. This was coupled with changes in other validated indicators of pain after docking in the form of pain-related behaviour. Only two components, Mouth Features and Orbital Tightening, showed significant quantitative changes after docking. The direction of these changes agree with the description of these facial action units in the LGS. Restraint affected people's perceptions of pain as well as quantitative measures of LGS components. Freely moving lambs were scored lower using the LGS over both periods and had a significantly smaller eye aperture and smaller nose and ear angles than when they were held. Agreement among observers for LGS scores were fair overall (Experiment I: W=0.60; Experiment II: W=0.66). This preliminary study demonstrates changes in lamb facial expression associated with pain. The results of these experiments should be interpreted with caution due to low lamb numbers. Copyright © 2016 Elsevier B.V. All rights reserved.

[Anti-tumor target prediction and activity verification of Ganoderma lucidum triterpenoids].

PubMed

Du, Guo-Hua; Wang, Hong-Xu; Yan, Zheng; Liu, Li-Ying; Chen, Ruo-Yun

2017-02-01

It has reported that Ganoderma lucidum triterpenoids had anti-tumor activity. However, the anti-tumor target is still unclear. The present study was designed to investigate the anti-tumor activity of G. lucidum triterpenoids on different tumor cells, and predict their potential targets by virtual screening. In this experiment, molecular docking was used to simulate the interactions of 26 triterpenoids isolated from G. lucidum and 11 target proteins by LibDock module of Discovery Studio2016 software, then the anti-tumor targets of triterpenoids were predicted. In addition, the in vitro anti-tumor effects of triterpenoids were evaluated by MTT assay by determining the inhibition of proliferation in 5 tumor cell lines. The docking results showed that the poses were greater than five, and Libdock Scores higher than 100, which can be used to determine whether compounds were activity. Eight triterpenoids might have anti-tumor activity as a result of good docking, five of which had multiple targets. MTT experiments demonstrated that the ganoderic acid Y had a certain inhibitory activity on lung cancer cell H460, with IC₅₀ of 22.4 μmol•L ⁻¹, followed by 7-oxo-ganoderic acid Z2, with IC₅₀ of 43.1 μmol•L ⁻¹. However, the other triterpenoids had no anti-tumor activity in the detected tumor cell lines. Taking together, molecular docking approach established here can be used for preliminary screening of anti-tumor activity of G.lucidum ingredients. Through this screening method, combined with the MTT assay, we can conclude that ganoderic acid Y had antitumor activity, especially anti-lung cancer, and 7-oxo-ganoderic acid Z2 as well as ganoderon B, to a certain extent, had anti-tumor activity. These findings can provide basis for the development of anti-tumor drugs. However, the anti-tumor mechanisms need to be further studied. Copyright© by the Chinese Pharmaceutical Association.

Homology modeling and docking studies of human Bcl-2L10 protein.

PubMed

Bhargavi, K; Kalyan Chaitanya, P; Ramasree, D; Vasavi, M; Murthy, D K; Uma, V

2010-12-01

Cancer, an unrestrained proliferation of cells, is one of the lead cause of death. Nearly 12.5 million people are diagnosed with cancer worldwide, 7.5 million people die of which 2.5 million cases are from India. Major cause for cancer is restriction of programmed cell death (apoptosis). Multiple signaling pathways regulate apoptosis. Bcl-2 (B - Cell Lymphomas-2) family proteins play a vital role as central regulators of apoptosis. Bcl-2L10, a novel anti-apoptotic protein, blocks apoptosis by mitochondrial dependent mechanism. The present study evaluates the 3D structure of Bcl-2L10 protein using homology modeling and aims to understand plausible functional and binding interactions between Bcl-2L10 with BH3 domain of BAX using protein - protein docking. The docking studies show binding of BH3 domain at Lys 110, Trp-111, Pro-115, Glu-119 and Asp-127 in the groove of BH 1, 2 and 3 domains of Bcl-2L10. Heterodimerization of anti-apoptotic Bcl-2 and BH3 domain of pro-apoptotic Bcl-2 proteins instigates apoptosis. Profound understanding of Bcl-2 pathway may prove useful in identification of future therapeutic targets for cancer.

A novel intermembrane space–targeting signal docks cysteines onto Mia40 during mitochondrial oxidative folding

PubMed Central

Sideris, Dionisia P.; Petrakis, Nikos; Katrakili, Nitsa; Mikropoulou, Despina; Gallo, Angelo; Ciofi-Baffoni, Simone; Banci, Lucia; Bertini, Ivano

2009-01-01

Mia40 imports Cys-containing proteins into the mitochondrial intermembrane space (IMS) by ensuring their Cys-dependent oxidative folding. In this study, we show that the specific Cys of the substrate involved in docking with Mia40 is substrate dependent, the process being guided by an IMS-targeting signal (ITS) present in Mia40 substrates. The ITS is a 9-aa internal peptide that (a) is upstream or downstream of the docking Cys, (b) is sufficient for crossing the outer membrane and for targeting nonmitochondrial proteins, (c) forms an amphipathic helix with crucial hydrophobic residues on the side of the docking Cys and dispensable charged residues on the other side, and (d) fits complementary to the substrate cleft of Mia40 via hydrophobic interactions of micromolar affinity. We rationalize the dual function of Mia40 as a receptor and an oxidase in a two step–specific mechanism: an ITS-guided sliding step orients the substrate noncovalently, followed by docking of the substrate Cys now juxtaposed to pair with the Mia40 active Cys. PMID:20026652

Interaction of a potential chloride channel blocker with a model transport protein: a spectroscopic and molecular docking investigation.

PubMed

Ganguly, Aniruddha; Paul, Bijan Kumar; Ghosh, Soumen; Dalapati, Sasanka; Guchhait, Nikhil

2014-05-14

The present work demonstrates a detailed characterization of the interaction of a potential chloride channel blocker, 9-methyl anthroate (9-MA), with a model transport protein, Bovine Serum Albumin (BSA). The modulated photophysical properties of the emissive drug molecule within the microheterogeneous bio-environment of the protein have been exploited spectroscopically to monitor the probe-protein binding interaction. Apart from evaluating the binding constant, the probable location of the neutral molecule within the protein cavity (subdomain IB) is explored by an AutoDock-based blind docking simulation. The absence of the Red-Edge Effect has been corroborated by the enhanced lifetime of the probe, being substantially greater than the solvent reorientation time. A dip-and-rise characteristic of the rotational relaxation profile of the drug within the protein has been argued to originate from a significant difference in the lifetime as well as amplitude of the free and protein-bound drug molecule. Unfolding of the protein in the presence of the drug molecule has been probed by the decrease of the α-helical content, obtained via circular dichroism (CD) spectroscopy, which is also supported by the gradual loss of the esterase activity of the protein in the presence of the drug molecule.

Cell biology. ER-to-Golgi traffic--this bud's for you.

PubMed

Brittle, E E; Waters, M G

2000-07-21

How do protein-transporting vesicles, which bud from the endoplasmic reticulum (ER), specifically dock to, and fuse with, the Golgi apparatus? In their Perspective, Brittle and Waters discuss new work (Allan et al.) suggesting that some vesicle-associated docking and fusion proteins are "programmed" during vesicle budding from the ER and direct downstream events that occur during fusion of these transport vesicles with the membranes of the Golgi.

PyPLIF: Python-based Protein-Ligand Interaction Fingerprinting.

PubMed

Radifar, Muhammad; Yuniarti, Nunung; Istyastono, Enade Perdana

2013-01-01

Structure-based virtual screening (SBVS) methods often rely on docking score. The docking score is an over-simplification of the actual ligand-target binding. Its capability to model and predict the actual binding reality is limited. Recently, interaction fingerprinting (IFP) has come and offered us an alternative way to model reality. IFP provides us an alternate way to examine protein-ligand interactions. The docking score indicates the approximate affinity and IFP shows the interaction specificity. IFP is a method to convert three dimensional (3D) protein-ligand interactions into one dimensional (1D) bitstrings. The bitstrings are subsequently employed to compare the protein-ligand interaction predicted by the docking tool against the reference ligand. These comparisons produce scores that can be used to enhance the quality of SBVS campaigns. However, some IFP tools are either proprietary or using a proprietary library, which limits the access to the tools and the development of customized IFP algorithm. Therefore, we have developed PyPLIF, a Python-based open source tool to analyze IFP. In this article, we describe PyPLIF and its application to enhance the quality of SBVS in order to identify antagonists for estrogen α receptor (ERα). PyPLIF is freely available at http://code.google.com/p/pyplif.

[Regression analysis to select native-like structures from decoys of antigen-antibody docking].

PubMed

Chen, Zhengshan; Chi, Xiangyang; Fan, Pengfei; Zhang, Guanying; Wang, Meirong; Yu, Changming; Chen, Wei

2018-06-25

Given the increasing exploitation of antibodies in different contexts such as molecular diagnostics and therapeutics, it would be beneficial to unravel properties of antigen-antibody interaction with modeling of computational protein-protein docking, especially, in the absence of a cocrystal structure. However, obtaining a native-like antigen-antibody structure remains challenging due in part to failing to reliably discriminate accurate from inaccurate structures among tens of thousands of decoys after computational docking with existing scoring function. We hypothesized that some important physicochemical and energetic features could be used to describe antigen-antibody interfaces and identify native-like antigen-antibody structure. We prepared a dataset, a subset of Protein-Protein Docking Benchmark Version 4.0, comprising 37 nonredundant 3D structures of antigen-antibody complexes, and used it to train and test multivariate logistic regression equation which took several important physicochemical and energetic features of decoys as dependent variables. Our results indicate that the ability to identify native-like structures of our method is superior to ZRANK and ZDOCK score for the subset of antigen-antibody complexes. And then, we use our method in workflow of predicting epitope of anti-Ebola glycoprotein monoclonal antibody-4G7 and identify three accurate residues in its epitope.

Is It Reliable to Take the Molecular Docking Top Scoring Position as the Best Solution without Considering Available Structural Data?

PubMed

Ramírez, David; Caballero, Julio

2018-04-28

Molecular docking is the most frequently used computational method for studying the interactions between organic molecules and biological macromolecules. In this context, docking allows predicting the preferred pose of a ligand inside a receptor binding site. However, the selection of the “best” solution is not a trivial task, despite the widely accepted selection criterion that the best pose corresponds to the best energy score. Here, several rigid-target docking methods were evaluated on the same dataset with respect to their ability to reproduce crystallographic binding orientations, to test if the best energy score is a reliable criterion for selecting the best solution. For this, two experiments were performed: (A) to reconstruct the ligand-receptor complex by performing docking of the ligand in its own crystal structure receptor (defined as self-docking), and (B) to reconstruct the ligand-receptor complex by performing docking of the ligand in a crystal structure receptor that contains other ligand (defined as cross-docking). Root-mean square deviation (RMSD) was used to evaluate how different the obtained docking orientation is from the corresponding co-crystallized pose of the same ligand molecule. We found that docking score function is capable of predicting crystallographic binding orientations, but the best ranked solution according to the docking energy is not always the pose that reproduces the experimental binding orientation. This happened when self-docking was achieved, but it was critical in cross-docking. Taking into account that docking is typically used with predictive purposes, during cross-docking experiments, our results indicate that the best energy score is not a reliable criterion to select the best solution in common docking applications. It is strongly recommended to choose the best docking solution according to the scoring function along with additional structural criteria described for analogue ligands to assure the selection of a correct docking solution.

Molecular Docking, Molecular Dynamics Simulations, Computational Screening to Design Quorum Sensing Inhibitors Targeting LuxP of Vibrio harveyi and Its Biological Evaluation.

PubMed

Rajamanikandan, Sundaraj; Jeyakanthan, Jeyaraman; Srinivasan, Pappu

2017-01-01

Quorum sensing (QS) plays an important role in the biofilm formation, production of virulence factors and stress responses in Vibrio harveyi. Therefore, interrupting QS is a possible approach to modulate bacterial behavior. In the present study, three docking protocols, such as Rigid Receptor Docking (RRD), Induced Fit Docking (IFD), and Quantum Polarized Ligand Docking (QPLD) were used to elucidate the binding mode of boronic acid derivatives into the binding pocket of LuxP protein in V. harveyi. Among the three docking protocols, IFD accurately predicted the correct binding mode of the studied inhibitors. Molecular dynamics (MD) simulations of the protein-ligand complexes indicates that the inter-molecular hydrogen bonds formed between the protein and ligand complex remains stable during the simulation time. Pharmacophore and shape-based virtual screening were performed to find selective and potent compounds from ChemBridge database. Five hit compounds were selected and subjected to IFD and MD simulations to validate the binding mode. In addition, enrichment calculation was performed to discriminate and separate active compounds from the inactive compounds. Based on the computational studies, the potent Bicyclo [2.2.1] hept-5-ene-2,3-dicarboxylic acid-2,6-dimethylpyridine 1-oxide (ChemBridge_5144368) was selected for in vitro assays. The compound exhibited dose dependent inhibition in bioluminescence and also inhibits biofilm formation in V. harveyi to the level of 64.25 %. The result from the study suggests that ChemBridge_5144368 could serve as an anti-quorum sensing molecule for V. harveyi.

A flexible docking scheme to explore the binding selectivity of PDZ domains.

PubMed

Gerek, Z Nevin; Ozkan, S Banu

2010-05-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

A flexible docking scheme to explore the binding selectivity of PDZ domains

PubMed Central

Gerek, Z Nevin; Ozkan, S Banu

2010-01-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using RosettaLigand, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately. PMID:20196074

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

PubMed

Klett, Javier; Núñez-Salgado, Alfonso; Dos Santos, Helena G; Cortés-Cabrera, Álvaro; Perona, Almudena; Gil-Redondo, Rubén; Abia, David; Gago, Federico; Morreale, Antonio

2012-09-11

An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.

Vibrational Stark effect spectroscopy reveals complementary electrostatic fields created by protein-protein binding at the interface of Ras and Ral.

PubMed

Walker, David M; Hayes, Ellen C; Webb, Lauren J

2013-08-07

Electrostatic fields at the interface of the GTPase H-Ras (Ras) docked with the Ras binding domain of the protein Ral guanine nucleoside dissociation stimulator (Ral) were measured with vibrational Stark effect (VSE) spectroscopy. Nine residues on the surface of Ras that participate in the protein-protein interface were systematically mutated to cysteine and subsequently converted to cyanocysteine in order to introduce a nitrile VSE probe into the protein-protein interface. The absorption energy of the nitrile was measured both on the surface of Ras in its monomeric state, then after incubation with the Ras binding domain of Ral to form the docked complex. Boltzmann-weighted structural snapshots of the nitrile-labeled Ras protein were generated both in monomeric and docked configurations from molecular dynamics simulations using enhanced sampling of the cyanocysteine side chain's χ2 dihedral angle. These snapshots were used to determine that on average, most of the nitrile probes were aligned along the Ras surface, parallel to the Ras-Ral interface. The average solvent-accessible surface areas (SASA) of the cyanocysteine side chain were found to be <60 Å(2) for all measured residues, and was not significantly different whether the nitrile was on the surface of the Ras monomer or immersed in the docked complex. Changes in the absorption energy of the nitrile probe at nine positions along the Ras-Ral interface were compared to results of a previous study examining this interface with Ral-based probes, and found a pattern of low electrostatic field in the core of the interface surrounded by a ring of high electrostatic field around the perimeter of the interface. These data are used to rationalize several puzzling features of the Ras-Ral interface.

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods.

PubMed

Moitessier, Nicolas; Pottel, Joshua; Therrien, Eric; Englebienne, Pablo; Liu, Zhaomin; Tomberg, Anna; Corbeil, Christopher R

2016-09-20

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

da Silva Figueiredo Celestino Gomes, Priscila; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2018-01-01

A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein-ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM-HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.

Shape Complementarity of Protein-Protein Complexes at Multiple Resolutions

PubMed Central

Zhang, Qing; Sanner, Michel; Olson, Arthur J.

2010-01-01

Biological complexes typically exhibit intermolecular interfaces of high shape complementarity. Many computational docking approaches use this surface complementarity as a guide in the search for predicting the structures of protein-protein complexes. Proteins often undergo conformational changes in order to create a highly complementary interface when associating. These conformational changes are a major cause of failure for automated docking procedures when predicting binding modes between proteins using their unbound conformations. Low resolution surfaces in which high frequency geometric details are omitted have been used to address this problem. These smoothed, or blurred, surfaces are expected to minimize the differences between free and bound structures, especially those that are due to side chain conformations or small backbone deviations. In spite of the fact that this approach has been used in many docking protocols, there has yet to be a systematic study of the effects of such surface smoothing on the shape complementarity of the resulting interfaces. Here we investigate this question by computing shape complementarity of a set of 66 protein-protein complexes represented by multi-resolution blurred surfaces. Complexed and unbound structures are available for these protein-protein complexes. They are a subset of complexes from a non-redundant docking benchmark selected for rigidity (i.e. the proteins undergo limited conformational changes between their bound and unbound states). In this work we construct the surfaces by isocontouring a density map obtained by accumulating the densities of Gaussian functions placed at all atom centers of the molecule. The smoothness or resolution is specified by a Gaussian fall-off coefficient, termed “blobbyness”. Shape complementarity is quantified using a histogram of the shortest distances between two proteins' surface mesh vertices for both the crystallographic complexes and the complexes built using the protein structures in their unbound conformation. The histograms calculated for the bound complex structures demonstrate that medium resolution smoothing (blobbyness=−0.9) can reproduce about 88% of the shape complementarity of atomic resolution surfaces. Complexes formed from the free component structures show a partial loss of shape complementarity (more overlaps and gaps) with the atomic resolution surfaces. For surfaces smoothed to low resolution (blobbyness=−0.3), we find more consistency of shape complementarity between the complexed and free cases. To further reduce bad contacts without significantly impacting the good contacts we introduce another blurred surface, in which the Gaussian densities of flexible atoms are reduced. From these results we discuss the use of shape complementarity in protein-protein docking. PMID:18837463

An In-Silico Investigation of Phytochemicals as Antiviral Agents Against Dengue Fever

PubMed Central

Powers, Chelsea N.; Setzer, William N.

2016-01-01

Abstract: A virtual screening analysis of our library of phytochemical structures with dengue virus protein targets has been carried out using a molecular docking approach. A total of 2194 plant-derived secondary metabolites have been docked. This molecule set comprised of 290 alkaloids (68 indole alkaloids, 153 isoquinoline alkaloids, 5 quinoline alkaloids, 13 piperidine alkaloids, 14 steroidal alkaloids, and 37 miscellaneous alkaloids), 678 terpenoids (47 monoterpenoids, 169 sesquiterpenoids, 265 diterpenoids, 81 steroids, and 96 triterpenoids), 20 aurones, 81 chalcones, 349 flavonoids, 120 isoflavonoids, 74 lignans, 58 stilbenoids, 169 miscellaneous polyphenolic compounds, 100 coumarins, 28 xanthones, 67 quinones, and 160 miscellaneous phytochemicals. Dengue virus protein targets examined included dengue virus protease (NS2B-NS3pro), helicase (NS3 helicase), methyltransferase (MTase), RNA-dependent RNA polymerase (RdRp), and the dengue virus envelope protein. Polyphenolic compounds, flavonoids, chalcones, and other phenolics were the most numerous of the strongly docking ligands for dengue virus protein targets. PMID:27151482

In Silico Analyses of Substrate Interactions with Human Serum Paraoxonase 1

DTIC Science & Technology

2008-01-01

substrate interactions of HuPON1 remains elusive. In this study, we apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the...mod- eling; docking; molecular dynamics simulations ; binding free energy decomposition. 486 PROTEINS Published 2008 WILEY-LISS, INC. yThis article is a...apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the binding interactions of HuPON1 with representative substrates. The

Fast and accurate grid representations for atom-based docking with partner flexibility.

PubMed

de Vries, Sjoerd J; Zacharias, Martin

2017-06-30

Macromolecular docking methods can broadly be divided into geometric and atom-based methods. Geometric methods use fast algorithms that operate on simplified, grid-like molecular representations, while atom-based methods are more realistic and flexible, but far less efficient. Here, a hybrid approach of grid-based and atom-based docking is presented, combining precalculated grid potentials with neighbor lists for fast and accurate calculation of atom-based intermolecular energies and forces. The grid representation is compatible with simultaneous multibody docking and can tolerate considerable protein flexibility. When implemented in our docking method ATTRACT, grid-based docking was found to be ∼35x faster. With the OPLSX forcefield instead of the ATTRACT coarse-grained forcefield, the average speed improvement was >100x. Grid-based representations may allow atom-based docking methods to explore large conformational spaces with many degrees of freedom, such as multiple macromolecules including flexibility. This increases the domain of biological problems to which docking methods can be applied. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

New Additions to the ClusPro Server Motivated by CAPRI

PubMed Central

Vajda, Sandor; Yueh, Christine; Beglov, Dmitri; Bohnuud, Tanggis; Mottarella, Scott E.; Xia, Bing; Hall, David R.; Kozakov, Dima

2016-01-01

The heavily used protein-protein docking server ClusPro performs three computational steps as follows: (1) rigid body docking, (2) RMSD based clustering of the 1000 lowest energy structures, and (3) the removal of steric clashes by energy minimization. In response to challenges encountered in recent CAPRI targets, we added three new options to ClusPro. These are (1) accounting for Small Angle X-ray Scattering (SAXS) data in docking; (2) considering pairwise interaction data as restraints; and (3) enabling discrimination between biological and crystallographic dimers. In addition, we have developed an extremely fast docking algorithm based on 5D rotational manifold FFT, and an algorithm for docking flexible peptides that include known sequence motifs. We feel that these developments will further improve the utility of ClusPro. However, CAPRI emphasized several shortcomings of the current server, including the problem of selecting the right energy parameters among the five options provided, and the problem of selecting the best models among the 10 generated for each parameter set. In addition, results convinced us that further development is needed for docking homology models. Finally we discuss the difficulties we have encountered when attempting to develop a refinement algorithm that would be computationally efficient enough for inclusion in a heavily used server. PMID:27936493

Computer-aided identification of novel protein targets of bisphenol A.

PubMed

Montes-Grajales, Diana; Olivero-Verbel, Jesus

2013-10-09

The xenoestrogen bisphenol A (2,2-bis-(p-hydroxyphenyl)-2-propane, BPA) is a known endocrine-disrupting chemical used in the fabrication of plastics, resins and flame retardants, that can be found throughout the environment and in numerous every day products. Human exposure to this chemical is extensive and generally occurs via oral route because it leaches from the food and beverage containers that contain it. Although most of the effects related to BPA exposure have been linked to the activation of the estrogen receptor (ER), the mechanisms of the interaction of BPA with protein targets different from ER are still unknown. Therefore, the objective of this work was to use a bioinformatics approach to identify possible new targets for BPA. Docking studies were performed between the optimized structure of BPA and 271 proteins related to different biochemical processes, as selected by text-mining. Refinement docking experiments and conformational analyses were carried out using LigandScout 3.0 for the proteins selected through the affinity ranking (lower than -8.0kcal/mol). Several proteins including ERR gamma (-9.9kcal/mol), and dual specificity protein kinases CLK-4 (-9.5kcal/mol), CLK-1 (-9.1kcal/mol) and CLK-2 (-9.0kcal/mol) presented great in silico binding affinities for BPA. The interactions between those proteins and BPA were mostly hydrophobic with the presence of some hydrogen bonds formed by leucine and asparagine residues. Therefore, this study suggests that this endocrine disruptor may have other targets different from the ER. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

BiPPred: Combined sequence- and structure-based prediction of peptide binding to the Hsp70 chaperone BiP.

PubMed

Schneider, Markus; Rosam, Mathias; Glaser, Manuel; Patronov, Atanas; Shah, Harpreet; Back, Katrin Christiane; Daake, Marina Angelika; Buchner, Johannes; Antes, Iris

2016-10-01

Substrate binding to Hsp70 chaperones is involved in many biological processes, and the identification of potential substrates is important for a comprehensive understanding of these events. We present a multi-scale pipeline for an accurate, yet efficient prediction of peptides binding to the Hsp70 chaperone BiP by combining sequence-based prediction with molecular docking and MMPBSA calculations. First, we measured the binding of 15mer peptides from known substrate proteins of BiP by peptide array (PA) experiments and performed an accuracy assessment of the PA data by fluorescence anisotropy studies. Several sequence-based prediction models were fitted using this and other peptide binding data. A structure-based position-specific scoring matrix (SB-PSSM) derived solely from structural modeling data forms the core of all models. The matrix elements are based on a combination of binding energy estimations, molecular dynamics simulations, and analysis of the BiP binding site, which led to new insights into the peptide binding specificities of the chaperone. Using this SB-PSSM, peptide binders could be predicted with high selectivity even without training of the model on experimental data. Additional training further increased the prediction accuracies. Subsequent molecular docking (DynaDock) and MMGBSA/MMPBSA-based binding affinity estimations for predicted binders allowed the identification of the correct binding mode of the peptides as well as the calculation of nearly quantitative binding affinities. The general concept behind the developed multi-scale pipeline can readily be applied to other protein-peptide complexes with linearly bound peptides, for which sufficient experimental binding data for the training of classical sequence-based prediction models is not available. Proteins 2016; 84:1390-1407. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Investigating the importance of Delaunay-based definition of atomic interactions in scoring of protein-protein docking results.

PubMed

Jafari, Rahim; Sadeghi, Mehdi; Mirzaie, Mehdi

2016-05-01

The approaches taken to represent and describe structural features of the macromolecules are of major importance when developing computational methods for studying and predicting their structures and interactions. This study attempts to explore the significance of Delaunay tessellation for the definition of atomic interactions by evaluating its impact on the performance of scoring protein-protein docking prediction. Two sets of knowledge-based scoring potentials are extracted from a training dataset of native protein-protein complexes. The potential of the first set is derived using atomic interactions extracted from Delaunay tessellated structures. The potential of the second set is calculated conventionally, that is, using atom pairs whose interactions were determined by their separation distances. The scoring potentials were tested against two different docking decoy sets and their performances were compared. The results show that, if properly optimized, the Delaunay-based scoring potentials can achieve higher success rate than the usual scoring potentials. These results and the results of a previous study on the use of Delaunay-based potentials in protein fold recognition, all point to the fact that Delaunay tessellation of protein structure can provide a more realistic definition of atomic interaction, and therefore, if appropriately utilized, may be able to improve the accuracy of pair potentials. Copyright © 2016 Elsevier Inc. All rights reserved.

Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2018-01-01

Molecular docking is a powerful tool in the field of computer-aided molecular design. In particular, it is the technique of choice for the prediction of a ligand pose within its target binding site. A multitude of docking methods is available nowadays, whose performance may vary depending on the data set. Therefore, some non-trivial choices should be made before starting a docking simulation. In the same framework, the selection of the target structure to use could be challenging, since the number of available experimental structures is increasing. Both issues have been explored within this work. The pose prediction of a pool of 36 compounds provided by D3R Grand Challenge 2 organizers was preceded by a pipeline to choose the best protein/docking-method couple for each blind ligand. An integrated benchmark approach including ligand shape comparison and cross-docking evaluations was implemented inside our DockBench software. The results are encouraging and show that bringing attention to the choice of the docking simulation fundamental components improves the results of the binding mode predictions.

jMetalCpp: optimizing molecular docking problems with a C++ metaheuristic framework.

PubMed

López-Camacho, Esteban; García Godoy, María Jesús; Nebro, Antonio J; Aldana-Montes, José F

2014-02-01

Molecular docking is a method for structure-based drug design and structural molecular biology, which attempts to predict the position and orientation of a small molecule (ligand) in relation to a protein (receptor) to produce a stable complex with a minimum binding energy. One of the most widely used software packages for this purpose is AutoDock, which incorporates three metaheuristic techniques. We propose the integration of AutoDock with jMetalCpp, an optimization framework, thereby providing both single- and multi-objective algorithms that can be used to effectively solve docking problems. The resulting combination of AutoDock + jMetalCpp allows users of the former to easily use the metaheuristics provided by the latter. In this way, biologists have at their disposal a richer set of optimization techniques than those already provided in AutoDock. Moreover, designers of metaheuristic techniques can use molecular docking for case studies, which can lead to more efficient algorithms oriented to solving the target problems.  jMetalCpp software adapted to AutoDock is freely available as a C++ source code at http://khaos.uma.es/AutodockjMetal/.

Investigation of potent lead for acquired immunodeficiency syndrome from traditional Chinese medicine.

PubMed

Hung, Tzu-Chieh; Lee, Wen-Yuan; Chen, Kuen-Bao; Chan, Yueh-Chiu; Chen, Calvin Yu-Chian

2014-01-01

Acquired immunodeficiency syndrome (AIDS), caused by human immunodeficiency virus (HIV), has become, because of the rapid spread of the disease, a serious global problem and cannot be treated. Recent studies indicate that VIF is a protein of HIV to prevent all of human immunity to attack HIV. Molecular compounds of traditional Chinese medicine (TCM) database filtered through molecular docking and molecular dynamics simulations to inhibit VIF can protect against HIV. Glutamic acid, plantagoguanidinic acid, and Aurantiamide acetate based docking score higher with other TCM compounds selected. Molecular dynamics are useful for analysis and detection ligand interactions. According to the docking position, hydrophobic interactions, hydrogen bonding changes, and structure variation, the study try to select the efficacy of traditional Chinese medicine compound Aurantiamide acetate is better than the other for protein-ligand interactions to maintain the protein composition, based on changes in the structure.

Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015

NASA Astrophysics Data System (ADS)

Slynko, Inna; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2016-09-01

High affinity ligands for a given target tend to share key molecular interactions with important anchoring amino acids and therefore often present quite conserved interaction patterns. This simple concept was formalized in a topological knowledge-based scoring function (GRIM) for selecting the most appropriate docking poses from previously X-rayed interaction patterns. GRIM first converts protein-ligand atomic coordinates (docking poses) into a simple 3D graph describing the corresponding interaction pattern. In a second step, proposed graphs are compared to that found from template structures in the Protein Data Bank. Last, all docking poses are rescored according to an empirical score (GRIMscore) accounting for overlap of maximum common subgraphs. Taking the opportunity of the public D3R Grand Challenge 2015, GRIM was used to rescore docking poses for 36 ligands (6 HSP90α inhibitors, 30 MAP4K4 inhibitors) prior to the release of the corresponding protein-ligand X-ray structures. When applied to the HSP90α dataset, for which many protein-ligand X-ray structures are already available, GRIM provided very high quality solutions (mean rmsd = 1.06 Å, n = 6) as top-ranked poses, and significantly outperformed a state-of-the-art scoring function. In the case of MAP4K4 inhibitors, for which preexisting 3D knowledge is scarce and chemical diversity is much larger, the accuracy of GRIM poses decays (mean rmsd = 3.18 Å, n = 30) although GRIM still outperforms an energy-based scoring function. GRIM rescoring appears to be quite robust with comparison to the other approaches competing for the same challenge (42 submissions for the HSP90 dataset, 27 for the MAP4K4 dataset) as it ranked 3rd and 2nd respectively, for the two investigated datasets. The rescoring method is quite simple to implement, independent on a docking engine, and applicable to any target for which at least one holo X-ray structure is available.

Molecular docking and simulation studies of gustatory receptor of Aedes aegypti: A potent drug target to distract host-seeking behaviour in mosquitoes.

PubMed

Gupta, Krishna Kant; Sethi, Guneswar; Jayaraman, Manikandan

2016-01-01

It is well reported that exhaled CO 2 and skin odour from human being assist female mosquitoes to locate human host. Basically, the receptors for this activity are expressed in cpA neurons. In both Aedes aegypti and Anopheles gambiae, this CO 2-sensitive olfactory neuron detects myriad number of chemicals present in human skin. Therefore, manipulation of gustatory receptors housing these neurons may serve as important targets for behavioural intervention. The study was aimed towards virtual screening of small molecules in the analyzed conserved active site residues of gustatory receptor and molecular dynamics simulation study of optimum protein-ligand complex to identify a suitable lead molecule for distracting host-seeking behaviour of mosquitoes. The conserved residue analysis of gustatory receptor (GR) of Ae. aegypti and An. gambiae was performed. The structure of GR protein from Ae. aegypti was modeled and validated, and then molecular docking was performed to screen 2903 small molecules against the predicted active residues of GR. Further, simulation studies were also carried out to prove protein-ligand stability. The glutamine 154 residue of GR was found to be highly conserved in Ae. aegypti and An. gambiae. Docking results indicated that the dodecanoic acid, 1,2,3-propanetriyl ester (dynasan 112) was interacting with this residue, as it showed better LibDock score than previously reported ethyl acetate used as mosquito repellant. Simulation studies indicated the structural instability of GR protein in docked form with dynasan 112 suggesting its involvement in structural changes. Based on the interaction energies and stability, this compound has been proposed to be used in mosquitoes' repellant. A novel effective odorant acting as inhibitor of GR is proposed based on its stability, docking score, interactions and RMSD, considering ethyl pyruvate as a standard inhibitor. Host preference and host-seeking ability of mosquito vectors play key roles in disease transmission, a clear understanding of these aspects is essential for preventing the spread of the disease.

Geraniin extracted from the rind of Nephelium lappaceum binds to dengue virus type-2 envelope protein and inhibits early stage of virus replication.

PubMed

Abdul Ahmad, Siti Aisyah; Palanisamy, Uma D; Tejo, Bimo A; Chew, Miaw Fang; Tham, Hong Wai; Syed Hassan, Sharifah

2017-11-21

The rapid rise and spread in dengue cases, together with the unavailability of safe vaccines and effective antiviral drugs, warrant the need to discover and develop novel anti-dengue treatments. In this study the antiviral activity of geraniin, extracted from the rind of Nephelium lappaceum, against dengue virus type-2 (DENV-2) was investigated. Geraniin was prepared from Nephelium lappaceum rind by reverse phase C-18 column chromatography. Cytotoxicity of geraniin towards Vero cells was evaluated using MTT assay while IC 50 value was determined by plaque reduction assay. The mode-of-action of geraniin was characterized using the virucidal, attachment, penetration and the time-of-addition assays'. Docking experiments with geraniin molecule and the DENV envelope (E) protein was also performed. Finally, recombinant E Domain III (rE-DIII) protein was produced to physiologically test the binding of geraniin to DENV-2 E-DIII protein, through ELISA competitive binding assay. Cytotoxicity assay confirmed that geraniin was not toxic to Vero cells, even at the highest concentration tested. The compound exhibited DENV-2 plaque formation inhibition, with an IC 50 of 1.75 μM. We further revealed that geraniin reduced viral infectivity and inhibited DENV-2 from attaching to the cells but had little effect on its penetration. Geraniin was observed to be most effective when added at the early stage of DENV-2 infection. Docking experiments showed that geraniin binds to DENV E protein, specifically at the DIII region, while the ELISA competitive binding assay confirmed geraniin's interaction with rE-DIII with high affinity. Geraniin from the rind of Nephelium lappaceum has antiviral activity against DENV-2. It is postulated that the compound inhibits viral attachment by binding to the E-DIII protein and interferes with the initial cell-virus interaction. Our results demonstrate that geraniin has the potential to be developed into an effective antiviral treatment, particularly for early phase dengue viral infection.

Multiple ligand simultaneous docking: orchestrated dancing of ligands in binding sites of protein.

PubMed

Li, Huameng; Li, Chenglong

2010-07-30

Present docking methodologies simulate only one single ligand at a time during docking process. In reality, the molecular recognition process always involves multiple molecular species. Typical protein-ligand interactions are, for example, substrate and cofactor in catalytic cycle; metal ion coordination together with ligand(s); and ligand binding with water molecules. To simulate the real molecular binding processes, we propose a novel multiple ligand simultaneous docking (MLSD) strategy, which can deal with all the above processes, vastly improving docking sampling and binding free energy scoring. The work also compares two search strategies: Lamarckian genetic algorithm and particle swarm optimization, which have respective advantages depending on the specific systems. The methodology proves robust through systematic testing against several diverse model systems: E. coli purine nucleoside phosphorylase (PNP) complex with two substrates, SHP2NSH2 complex with two peptides and Bcl-xL complex with ABT-737 fragments. In all cases, the final correct docking poses and relative binding free energies were obtained. In PNP case, the simulations also capture the binding intermediates and reveal the binding dynamics during the recognition processes, which are consistent with the proposed enzymatic mechanism. In the other two cases, conventional single-ligand docking fails due to energetic and dynamic coupling among ligands, whereas MLSD results in the correct binding modes. These three cases also represent potential applications in the areas of exploring enzymatic mechanism, interpreting noisy X-ray crystallographic maps, and aiding fragment-based drug design, respectively. 2010 Wiley Periodicals, Inc.

A spectroscopic and molecular docking approach on the binding of tinzaparin sodium with human serum albumin

NASA Astrophysics Data System (ADS)

Abdullah, Saleh M. S.; Fatma, Sana; Rabbani, Gulam; Ashraf, Jalaluddin M.

2017-01-01

Protein bound toxins are poorly removed by conventional extracorporeal therapies. Venous thromboembolism (VTE) is a major cause of morbidity and mortality in patients with cancer. The interaction between tinzaparin, an inhibitor of angiotensin converting enzyme and human serum albumin, a principal plasma protein in the liver has been investigated in vitro under a simulated physiological condition by UV-vis spectrophotometry and fluorescence spectrometry. The intrinsic fluorescence intensity of human serum albumin was strongly quenched by tinzaparin (TP). The binding constants and binding stoichiometry can be calculated from the data obtained from fluorescence quenching experiments. The negative value of ΔG° reveals that the binding process is a spontaneous process. Thermodynamic analysis shows that the HSA-TP complex formation occurs via hydrogen bonds, hydrophobic interactions and undergoes slight structural changes as evident by far-UV CD. It indicated that the hydrophobic interactions play a main role in the binding of TP to human serum albumin. In addition, the distance between TP (acceptor) and tryptophan residues of human serum albumin (donor) was estimated to be 2.21 nm according to the Förster's resonance energy transfer theory. For the deeper understanding of the interaction, thermodynamic, and molecular docking studies were performed as well. Our docking results suggest that TP forms stable complex with HSA (Kb ∼ 104) and its primary binding site is located in subdomain IIA (Sudlow Site I). The results obtained herein will be of biological significance in pharmacology and clinical medicine.

Consensus Induced Fit Docking (cIFD): methodology, validation, and application to the discovery of novel Crm1 inhibitors

NASA Astrophysics Data System (ADS)

Kalid, Ori; Toledo Warshaviak, Dora; Shechter, Sharon; Sherman, Woody; Shacham, Sharon

2012-11-01

We present the Consensus Induced Fit Docking (cIFD) approach for adapting a protein binding site to accommodate multiple diverse ligands for virtual screening. This novel approach results in a single binding site structure that can bind diverse chemotypes and is thus highly useful for efficient structure-based virtual screening. We first describe the cIFD method and its validation on three targets that were previously shown to be challenging for docking programs (COX-2, estrogen receptor, and HIV reverse transcriptase). We then demonstrate the application of cIFD to the challenging discovery of irreversible Crm1 inhibitors. We report the identification of 33 novel Crm1 inhibitors, which resulted from the testing of 402 purchased compounds selected from a screening set containing 261,680 compounds. This corresponds to a hit rate of 8.2 %. The novel Crm1 inhibitors reveal diverse chemical structures, validating the utility of the cIFD method in a real-world drug discovery project. This approach offers a pragmatic way to implicitly account for protein flexibility without the additional computational costs of ensemble docking or including full protein flexibility during virtual screening.

Characterization and comparison of perezone with some analogues. Experimental and theoretical study

NASA Astrophysics Data System (ADS)

Escobedo-González, Rene Gerardo; Bahena, Luis; Arias Tellez, José Luis; Hinojosa Torres, Jaime; Ruvalcaba, Rene Miranda; Aceves-Hernández, Juan Manuel

2015-10-01

Perezone had been used for centuries in the traditional Mexican medicine, it is useful and a handful of illness. Perezone and other derivatives also present activity against certain lines of cancer, such as the myeloblastoid leukemia cell line K-562 and carcinoma cell lines (PC-3 and SKLU-1) with IC50 <10 μM. Perezone and isoperezone have shown the major cytotoxic potency. Characterization of perezone was carried out by UV-Visible, IR, DSC, TGA and powder X-ray diffraction, as well as docking studies using caspase-3 structures as receptors. Theoretical studies for optimizing the geometry of perezone were carried out and the results compared with values of single crystal X-ray diffraction. The experimental values of atomic distances, angles and dihedral angles are in good agreement with the theoretical values. Interaction of perezone with the cysteine catalytic site with the caspase-3 was found in the docking studies. A docking study of perezone, with horminone, thymoquinone and isoperezone as ligands and the protein apoptein, caspase-3 as receptor, was carried to demonstrate that the hindrance steric factor, chemical structure and the functional groups are important in the biological activity of these natural products. The docking score energetic values are in good agreement with the experimental cytotoxic results obtained from the experiments when perezone and analogues were studied in different types of cancer.

In Silico and Wet Lab Studies Reveal the Cholesterol Lowering Efficacy of Lauric Acid, a Medium Chain Fat of Coconut Oil.

PubMed

Lekshmi Sheela, Devi; Nazeem, Puthiyaveetil Abdulla; Narayanankutty, Arunaksharan; Manalil, Jeksy Jos; Raghavamenon, Achuthan C

2016-12-01

The coconut oil (CO) contains 91 % of saturated fatty acids in which 72 % are medium chain fatty acids (MCFAs) like lauric, capric and caprylic acids. In contrast to animal fat, coconut oil has no cholesterol. Despite this fact, CO is sidelined among other vegetable oils due to the health hazards attributed to the saturated fatty acids. Though various medicinal effects of CO have been reported including the hypolipidemic activity, people are still confused in the consumption of this natural oil. In silico analyses and wet lab experiments have been carried out to identify the hypolipidemic properties of MCFAs and phenolic acids in CO by using different protein targets involved in cholesterol synthesis. The molecular docking studies were carried out using CDOCKER protocol in Accelery's Discovery Studio, by taking different proteins like HMG- CoA reductase and cholesterol esterase as targets and the different phytocompounds in coconut as ligands. Molecular docking highlighted the potential of lauric acid in inhibiting the protein targets involved in hyperlipidemics. Further, validation of in silico results was carried out through in vivo studies. The activity of key enzymes HMG- CoA reductase and lipoprotein lipase were found reduced in animals fed with lauric acid and CO.

An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design.

PubMed

Ballante, Flavio; Marshall, Garland R

2016-01-25

Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e., by determining the docking accuracy (DA)) in order to select the most appropriate docking procedure and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different root-mean-square deviation (RMSD) formulas, scoring functions, and format results, it is both difficult and time-consuming to consistently determine and compare their predictive capabilities in order to identify the best protocol to use for the target of interest and to extrapolate the binding poses (i.e., best-docked (BD), best-cluster (BC), and best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures called Clusterizer and DockAccessor have been developed and implemented for use with some common and "free-for-academics" programs such as AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC, and BF poses as well as to perform consistent cluster and DA analyses. Clusterizer and DockAccessor (code available over the Internet) represent two novel tools to collect computationally determined poses and detect the most predictive docking approach. Herein an application to human lysine deacetylase (hKDAC) inhibitors is illustrated.

Independent signaling by Drosophila insulin receptor for axon guidance and growth.

PubMed

Li, Caroline R; Guo, Dongyu; Pick, Leslie

2013-01-01

The Drosophila insulin receptor (DInR) regulates a diverse array of biological processes including growth, axon guidance, and sugar homeostasis. Growth regulation by DInR is mediated by Chico, the Drosophila homolog of vertebrate insulin receptor substrate proteins IRS1-4. In contrast, DInR regulation of photoreceptor axon guidance in the developing visual system is mediated by the SH2-SH3 domain adaptor protein Dreadlocks (Dock). In vitro studies by others identified five NPXY motifs, one in the juxtamembrane region and four in the signaling C-terminal tail (C-tail), important for interaction with Chico. Here we used yeast two-hybrid assays to identify regions in the DInR C-tail that interact with Dock. These Dock binding sites were in separate portions of the C-tail from the previously identified Chico binding sites. To test whether these sites are required for growth or axon guidance in whole animals, a panel of DInR proteins, in which the putative Chico and Dock interaction sites had been mutated individually or in combination, were tested for their ability to rescue viability, growth and axon guidance defects of dinr mutant flies. Sites required for viability were identified. Unexpectedly, mutation of both putative Dock binding sites, either individually or in combination, did not lead to defects in photoreceptor axon guidance. Thus, either sites also required for viability are necessary for DInR function in axon guidance and/or there is redundancy built into the DInR/Dock interaction such that Dock is able to interact with multiple regions of DInR. We also found that simultaneous mutation of all five NPXY motifs implicated in Chico interaction drastically decreased growth in both male and female adult flies. These animals resembled chico mutants, supporting the notion that DInR interacts directly with Chico in vivo to control body size. Mutation of these five NPXY motifs did not affect photoreceptor axon guidance, segregating the roles of DInR in the processes of growth and axon guidance.

"Soft docking": matching of molecular surface cubes.

PubMed

Jiang, F; Kim, S H

1991-05-05

Molecular recognition is achieved through the complementarity of molecular surface structures and energetics with, most commonly, associated minor conformational changes. This complementarity can take many forms: charge-charge interaction, hydrogen bonding, van der Waals' interaction, and the size and shape of surfaces. We describe a method that exploits these features to predict the sites of interactions between two cognate molecules given their three-dimensional structures. We have developed a "cube representation" of molecular surface and volume which enables us not only to design a simple algorithm for a six-dimensional search but also to allow implicitly the effects of the conformational changes caused by complex formation. The present molecular docking procedure may be divided into two stages. The first is the selection of a population of complexes by geometric "soft docking", in which surface structures of two interacting molecules are matched with each other, allowing minor conformational changes implicitly, on the basis of complementarity in size and shape, close packing, and the absence of steric hindrance. The second is a screening process to identify a subpopulation with many favorable energetic interactions between the buried surface areas. Once the size of the subpopulation is small, one may further screen to find the correct complex based on other criteria or constraints obtained from biochemical, genetic, and theoretical studies, including visual inspection. We have tested the present method in two ways. First is a control test in which we docked the components of a molecular complex of known crystal structure available in the Protein Data Bank (PDB). Two molecular complexes were used: (1) a ternary complex of dihydrofolate reductase, NADPH and methotrexate (3DFR in PDB) and (2) a binary complex of trypsin and trypsin inhibitor (2PTC in PDB). The components of each complex were taken apart at an arbitrary relative orientation and then docked together again. The results show that the geometric docking alone is sufficient to determine the correct docking solutions in these ideal cases, and that the cube representation of the molecules does not degrade the docking process in the search for the correct solution. The second is the more realistic experiment in which we docked the crystal structures of uncomplexed molecules and then compared the structures of docked complexes with the crystal structures of the corresponding complexes. This is to test the capability of our method in accommodating the effects of the conformational changes in the binding sites of the molecules in docking.(ABSTRACT TRUNCATED AT 400 WORDS)

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

PubMed

LaBute, Montiago X; Zhang, Xiaohua; Lenderman, Jason; Bennion, Brian J; Wong, Sergio E; Lightstone, Felice C

2014-01-01

Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC) to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409) of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs) during 10-fold cross-validation (0.60-0.69 and 0.61-0.74, respectively). Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with increasing number of CPUs to tens of thousands of protein targets and millions of potential drug candidates.

FRODOCK 2.0: fast protein-protein docking server.

PubMed

Ramírez-Aportela, Erney; López-Blanco, José Ramón; Chacón, Pablo

2016-08-01

The prediction of protein-protein complexes from the structures of unbound components is a challenging and powerful strategy to decipher the mechanism of many essential biological processes. We present a user-friendly protein-protein docking server based on an improved version of FRODOCK that includes a complementary knowledge-based potential. The web interface provides a very effective tool to explore and select protein-protein models and interactively screen them against experimental distance constraints. The competitive success rates and efficiency achieved allow the retrieval of reliable potential protein-protein binding conformations that can be further refined with more computationally demanding strategies. The server is free and open to all users with no login requirement at http://frodock.chaconlab.org pablo@chaconlab.org Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Apollo Soyuz, mission evaluation report

NASA Technical Reports Server (NTRS)

1975-01-01

The Apollo Soyuz mission was the first manned space flight to be conducted jointly by two nations - the United States and the Union of Soviet Socialist Republics. The primary purpose of the mission was to test systems for rendezvous and docking of manned spacecraft that would be suitable for use as a standard international system, and to demonstrate crew transfer between spacecraft. The secondary purpose was to conduct a program of scientific and applications experimentation. With minor modifications, the Apollo and Soyuz spacecraft were like those flown on previous missions. However, a new module was built specifically for this mission - the docking module. It served as an airlock for crew transfer and as a structural base for the docking mechanism that interfaced with a similar mechanism on the Soyuz orbital module. The postflight evaluation of the performance of the docking system and docking module, as well as the overall performance of the Apollo spacecraft and experiments is presented. In addition, the mission is evaluated from the viewpoints of the flight crew, ground support operations, and biomedical operations. Descriptions of the docking mechanism, docking module, crew equipment and experiment hardware are given.

U.S. Army Research Laboratory (ARL) XPairIt Simulator for Peptide Docking and Analysis

DTIC Science & Technology

2014-07-01

results from a case study, docking a short peptide to a small protein. For this test we choose the 1RXZ system from the Protein Data Bank, which...estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data ...core of XPairIt, which additionally contains many data management and organization options, analysis tools, and custom simulation methodology. Two

Molecular docking based screening of compounds against VP40 from Ebola virus.

PubMed

M Alam El-Din, Hanaa; A Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process.

Molecular docking based screening of compounds against VP40 from Ebola virus

PubMed Central

M Alam El-Din, Hanaa; A. Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process. PMID:28149054

An investigation of molecular dynamics simulation and molecular docking: interaction of citrus flavonoids and bovine β-lactoglobulin in focus.

PubMed

Sahihi, M; Ghayeb, Y

2014-08-01

Citrus flavonoids are natural compounds with important health benefits. The study of their interaction with a transport protein, such as bovine β-lactoglobulin (BLG), at the atomic level could be a valuable factor to control their transport to biological sites. In the present study, molecular docking and molecular dynamics simulation methods were used to investigate the interaction of hesperetin, naringenin, nobiletin and tangeretin as citrus flavonoids and BLG as transport protein. The molecular docking results revealed that these flavonoids bind in the internal cavity of BLG and the BLG affinity for binding the flavonoids follows naringenin>hesperetin>tangeretin>nobiletin. The docking results also indicated that the BLG-flavonoid complexes are stabilized through hydrophobic interactions, hydrogen bond interactions and π-π stacking interactions. The analysis of molecular dynamics (MD) simulation trajectories showed that the root mean square deviation (RMSD) of various systems reaches equilibrium and fluctuates around the mean value at various times. Time evolution of the radius of gyration, total solvent accessible surface of the protein and the second structure of protein showed as well that BLG and BLG-flavonoid complexes were stable around 2500ps, and there was not any conformational change as for BLG-flavonoid complexes. Further, the profiles of atomic fluctuations indicated the rigidity of the ligand binding site during the simulation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Probing the interaction of anticancer drug temsirolimus with human serum albumin: molecular docking and spectroscopic insight.

PubMed

Shamsi, Anas; Ahmed, Azaj; Bano, Bilqees

2018-05-01

The binding interaction between temsirolimus, an important antirenal cancer drug, and HSA, an important carrier protein was scrutinized making use of UV and fluorescence spectroscopy. Hyper chromaticity observed in UV spectroscopy in the presence of temsirolimus as compared to free HSA suggests the formation of complex between HSA and temsirolimus. Fluorescence quenching experiments clearly showed quenching in the fluorescence of HSA in the presence of temsirolimus confirming the complex formation and also confirmed that static mode of interaction is operative for this binding process. Binding constant values obtained through UV and fluorescence spectroscopy reveal strong interaction; temsirolimus binds to HSA at 298 K with a binding constant of 2.9 × 10 4  M -1 implying the strength of interaction. The negative Gibbs free energy obtained through Isothermal titration calorimetry as well as quenching experiments suggests that binding process is spontaneous. Molecular docking further provides an insight of various residues that are involved in this binding process; showing the binding energy to be -12.9 kcal/mol. CD spectroscopy was retorted to analyze changes in secondary structure of HSA; increased intensity in presence of temsirolimus showing changes in secondary structure of HSA induced by temsirolimus. This study is of importance as it provides an insight into the binding mechanism of an important antirenal cancer drug with an important carrier protein. Once temsirolimus binds to HSA, it changes conformation of HSA which in turn can alter the functionality of this important carrier protein and this altered functionality of HSA can be highlighted in variety of diseases.

Molecular mechanism of membrane binding of the GRP1 PH domain.

PubMed

Lai, Chun-Liang; Srivastava, Anand; Pilling, Carissa; Chase, Anna R; Falke, Joseph J; Voth, Gregory A

2013-09-09

The pleckstrin homology (PH) domain of the general receptor of phosphoinositides 1 (GRP1) protein selectively binds to a rare signaling phospholipid, phosphatidylinositol (3,4,5)-trisphosphate (PIP3), in the membrane. The specific PIP3 lipid docking of GRP1 PH domain is essential to protein cellular function and is believed to occur in a stepwise process, electrostatic-driven membrane association followed by the specific PIP3 binding. By a combination of all-atom molecular dynamics (MD) simulations, coarse-grained analysis, electron paramagnetic resonance (EPR) membrane docking geometry, and fluorescence resonance energy transfer (FRET) kinetic studies, we have investigated the search and bind process in the GRP1 PH domain at the molecular scale. We simulated the two membrane binding states of the GRP1 PH domain in the PIP3 search process, before and after the GRP1 PH domain docks with the PIP3 lipid. Our results suggest that the background anionic phosphatidylserine lipids, which constitute around one-fifth of the membrane by composition, play a critical role in the initial stages of recruiting protein to the membrane surface through non-specific electrostatic interactions. Our data also reveal a previously unseen transient membrane association mechanism that is proposed to enable a two-dimensional "hopping" search of the membrane surface for the rare PIP3 target lipid. We further modeled the PIP3-bound membrane-protein system using the EPR membrane docking structure for the MD simulations, quantitatively validating the EPR membrane docking structure and augmenting our understanding of the binding interface with atomic-level detail. Several observations and hypotheses reached from our MD simulations are also supported by experimental kinetic studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Resident CAPS on dense-core vesicles docks and primes vesicles for fusion

PubMed Central

Kabachinski, Greg; Kielar-Grevstad, D. Michelle; Zhang, Xingmin; James, Declan J.; Martin, Thomas F. J.

2016-01-01

The Ca2+-dependent exocytosis of dense-core vesicles in neuroendocrine cells requires a priming step during which SNARE protein complexes assemble. CAPS (aka CADPS) is one of several factors required for vesicle priming; however, the localization and dynamics of CAPS at sites of exocytosis in live neuroendocrine cells has not been determined. We imaged CAPS before, during, and after single-vesicle fusion events in PC12 cells by TIRF micro­scopy. In addition to being a resident on cytoplasmic dense-core vesicles, CAPS was present in clusters of approximately nine molecules near the plasma membrane that corresponded to docked/tethered vesicles. CAPS accompanied vesicles to the plasma membrane and was present at all vesicle exocytic events. The knockdown of CAPS by shRNA eliminated the VAMP-2–dependent docking and evoked exocytosis of fusion-competent vesicles. A CAPS(ΔC135) protein that does not localize to vesicles failed to rescue vesicle docking and evoked exocytosis in CAPS-depleted cells, showing that CAPS residence on vesicles is essential. Our results indicate that dense-core vesicles carry CAPS to sites of exocytosis, where CAPS promotes vesicle docking and fusion competence, probably by initiating SNARE complex assembly. PMID:26700319

The Mr 140,000 Intermediate Chain of Chlamydomonas Flagellar Inner Arm Dynein Is a WD-Repeat Protein Implicated in Dynein Arm Anchoring

PubMed Central

Yang, Pinfen; Sale, Winfield S.

1998-01-01

Previous structural and biochemical studies have revealed that the inner arm dynein I1 is targeted and anchored to a unique site located proximal to the first radial spoke in each 96-nm axoneme repeat on flagellar doublet microtubules. To determine whether intermediate chains mediate the positioning and docking of dynein complexes, we cloned and characterized the 140-kDa intermediate chain (IC140) of the I1 complex. Sequence and secondary structural analysis, with particular emphasis on β-sheet organization, predicted that IC140 contains seven WD repeats. Reexamination of other members of the dynein intermediate chain family of WD proteins indicated that these polypeptides also bear seven WD/β-sheet repeats arranged in the same pattern along each intermediate chain protein. A polyclonal antibody was raised against a 53-kDa fusion protein derived from the C-terminal third of IC140. The antibody is highly specific for IC140 and does not bind to other dynein intermediate chains or proteins in Chlamydomonas flagella. Immunofluorescent microscopy of Chlamydomonas cells confirmed that IC140 is distributed along the length of both flagellar axonemes. In vitro reconstitution experiments demonstrated that the 53-kDa C-terminal fusion protein binds specifically to axonemes lacking the I1 complex. Chemical cross-linking indicated that IC140 is closely associated with a second intermediate chain in the I1 complex. These data suggest that IC140 contains domains responsible for the assembly and docking of the I1 complex to the doublet microtubule cargo. PMID:9843573

Clustering molecular dynamics trajectories for optimizing docking experiments.

PubMed

De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

Cell Division in genus Corynebacterium: protein-protein interaction and molecular docking of SepF and FtsZ in the understanding of cytokinesis in pathogenic species.

PubMed

Oliveira, Alberto F; Folador, Edson L; Gomide, Anne C P; Goes-Neto, Aristóteles; Azevedo, Vasco A C; Wattam, Alice R

2018-02-15

The genus Corynebacterium includes species of great importance in medical, veterinary and biotechnological fields. The genus-specific families (PLfams) from PATRIC have been used to observe conserved proteins associated to all species. Our results showed a large number of conserved proteins that are associated with the cellular division process. Was not observe in our results other proteins like FtsA and ZapA that interact with FtsZ. Our findings point that SepF overlaps the function of this proteins explored by molecular docking, protein-protein interaction and sequence analysis. Transcriptomic analysis showed that these two (Sepf and FtsZ) proteins can be expressed in different conditions together. The work presents novelties on molecules participating in the cell division event, from the interaction of FtsZ and SepF, as new therapeutic targets.

C2 Domain of Protein Kinase Cα: Elucidation of the Membrane Docking Surface by Site-Directed Fluorescence and Spin Labeling†

PubMed Central

Kohout, Susy C.; Corbalán-García, Senena; Gómez-Fernández, Juan C.; Falke, Joseph J.

2013-01-01

The C2 domain is a conserved signaling motif that triggers membrane docking in a Ca2+-dependent manner, but the membrane docking surfaces of many C2 domains have not yet been identified. Two extreme models can be proposed for the docking of the protein kinase Cα (PKCα) C2 domain to membranes. In the parallel model, the membrane-docking surface includes the Ca2+ binding loops and an anion binding site on β-strands 3–4, such that the β-strands are oriented parallel to the membrane. In the perpendicular model, the docking surface is localized to the Ca2+ binding loops and the β-strands are oriented perpendicular to the membrane surface. The present study utilizes site-directed fluorescence and spin-labeling to map out the membrane docking surface of the PKCα C2 domain. Single cysteine residues were engineered into 18 locations scattered over all regions of the protein surface, and were used as attachment sites for spectroscopic probes. The environmentally sensitive fluorescein probe identified positions where Ca2+ activation or membrane docking trigger measurable fluorescence changes. Ca2+ binding was found to initiate a global conformational change, while membrane docking triggered the largest fluorescein environmental changes at labeling positions on the three Ca2+ binding loops (CBL), thereby localizing these loops to the membrane docking surface. Complementary EPR power saturation measurements were carried out using a nitroxide spin probe to determine a membrane depth parameter, Φ, for each spin-labeled mutant. Positive membrane depth parameters indicative of membrane insertion were found for three positions, all located on the Ca2+ binding loops: N189 on CBL 1, and both R249 and R252 on CBL 3. In addition, EPR power saturation revealed that five positions near the anion binding site are partially protected from collisions with an aqueous paramagnetic probe, indicating that the anion binding site lies at or near the surface of the headgroup layer. Together, the fluorescence and EPR results indicate that the Ca2+ first and third Ca2+ binding loops insert directly into the lipid headgroup region of the membrane, and that the anion binding site on β-strands 3–4 lies near the headgroups. The data support a model in which the β-strands are tilted toward the parallel orientation relative to the membrane surface. PMID:12564928

Single-Point Mutation with a Rotamer Library Toolkit: Toward Protein Engineering.

PubMed

Pottel, Joshua; Moitessier, Nicolas

2015-12-28

Protein engineers have long been hard at work to harness biocatalysts as a natural source of regio-, stereo-, and chemoselectivity in order to carry out chemistry (reactions and/or substrates) not previously achieved with these enzymes. The extreme labor demands and exponential number of mutation combinations have induced computational advances in this domain. The first step in our virtual approach is to predict the correct conformations upon mutation of residues (i.e., rebuilding side chains). For this purpose, we opted for a combination of molecular mechanics and statistical data. In this work, we have developed automated computational tools to extract protein structural information and created conformational libraries for each amino acid dependent on a variable number of parameters (e.g., resolution, flexibility, secondary structure). We have also developed the necessary tool to apply the mutation and optimize the conformation accordingly. For side-chain conformation prediction, we obtained overall average root-mean-square deviations (RMSDs) of 0.91 and 1.01 Å for the 18 flexible natural amino acids within two distinct sets of over 3000 and 1500 side-chain residues, respectively. The commonly used dihedral angle differences were also evaluated and performed worse than the state of the art. These two metrics are also compared. Furthermore, we generated a family-specific library for kinases that produced an average 2% lower RMSD upon side-chain reconstruction and a residue-specific library that yielded a 17% improvement. Ultimately, since our protein engineering outlook involves using our docking software, Fitted/Impacts, we applied our mutation protocol to a benchmarked data set for self- and cross-docking. Our side-chain reconstruction does not hinder our docking software, demonstrating differences in pose prediction accuracy of approximately 2% (RMSD cutoff metric) for a set of over 200 protein/ligand structures. Similarly, when docking to a set of over 100 kinases, side-chain reconstruction (using both general and biased conformation libraries) had minimal detriment to the docking accuracy.

Extracellular domains play different roles in gap junction formation and docking compatibility.

PubMed

Bai, Donglin; Wang, Ao Hong

2014-02-15

GJ (gap junction) channels mediate direct intercellular communication and play an important role in many physiological processes. Six connexins oligomerize to form a hemichannel and two hemichannels dock together end-to-end to form a GJ channel. Connexin extracellular domains (E1 and E2) have been shown to be important for the docking, but the molecular mechanisms behind the docking and formation of GJ channels are not clear. Recent developments in atomic GJ structure and functional studies on a series of connexin mutants revealed that E1 and E2 are likely to play different roles in the docking. Non-covalent interactions at the docking interface, including hydrogen bonds, are predicted to form between interdocked extracellular domains. Protein sequence alignment analysis on the docking compatible/incompatible connexins indicate that the E1 domain is important for the formation of the GJ channel and the E2 domain is important in the docking compatibility in heterotypic channels. Interestingly, the hydrogen-bond forming or equivalent residues in both E1 and E2 domains are mutational hot spots for connexin-linked human diseases. Understanding the molecular mechanisms of GJ docking can assist us to develop novel strategies in rescuing the disease-linked connexin mutants.

Domain wise docking analyses of the modular chitin binding protein CBP50 from Bacillus thuringiensis serovar konkukian S4.

PubMed

Sehar, Ujala; Mehmood, Muhammad Aamer; Hussain, Khadim; Nawaz, Salman; Nadeem, Shahid; Siddique, Muhammad Hussnain; Nadeem, Habibullah; Gull, Munazza; Ahmad, Niaz; Sohail, Iqra; Gill, Saba Shahid; Majeed, Summera

2013-01-01

This paper presents an in silico characterization of the chitin binding protein CBP50 from B. thuringiensis serovar konkukian S4 through homology modeling and molecular docking. The CBP50 has shown a modular structure containing an N-terminal CBM33 domain, two consecutive fibronectin-III (Fn-III) like domains and a C-terminal CBM5 domain. The protein presented a unique modular structure which could not be modeled using ordinary procedures. So, domain wise modeling using MODELLER and docking analyses using Autodock Vina were performed. The best conformation for each domain was selected using standard procedure. It was revealed that four amino acid residues Glu-71, Ser-74, Glu-76 and Gln-90 from N-terminal domain are involved in protein-substrate interaction. Similarly, amino acid residues Trp-20, Asn-21, Ser-23 and Val-30 of Fn-III like domains and Glu-15, Ala-17, Ser-18 and Leu-35 of C-terminal domain were involved in substrate binding. Site-directed mutagenesis of these proposed amino acid residues in future will elucidate the key amino acids involved in chitin binding activity of CBP50 protein.

CyClus: a fast, comprehensive cylindrical interface approximation clustering/reranking method for rigid-body protein-protein docking decoys.

PubMed

Omori, Satoshi; Kitao, Akio

2013-06-01

We propose a fast clustering and reranking method, CyClus, for protein-protein docking decoys. This method enables comprehensive clustering of whole decoys generated by rigid-body docking using cylindrical approximation of the protein-proteininterface and hierarchical clustering procedures. We demonstrate the clustering and reranking of 54,000 decoy structures generated by ZDOCK for each complex within a few minutes. After parameter tuning for the test set in ZDOCK benchmark 2.0 with the ZDOCK and ZRANK scoring functions, blind tests for the incremental data in ZDOCK benchmark 3.0 and 4.0 were conducted. CyClus successfully generated smaller subsets of decoys containing near-native decoys. For example, the number of decoys required to create subsets containing near-native decoys with 80% probability was reduced from 22% to 50% of the number required in the original ZDOCK. Although specific ZDOCK and ZRANK results were demonstrated, the CyClus algorithm was designed to be more general and can be applied to a wide range of decoys and scoring functions by adjusting just two parameters, p and T. CyClus results were also compared to those from ClusPro. Copyright © 2013 Wiley Periodicals, Inc.

Diverse, high-quality test set for the validation of protein-ligand docking performance.

PubMed

Hartshorn, Michael J; Verdonk, Marcel L; Chessari, Gianni; Brewerton, Suzanne C; Mooij, Wijnand T M; Mortenson, Paul N; Murray, Christopher W

2007-02-22

A procedure for analyzing and classifying publicly available crystal structures has been developed. It has been used to identify high-resolution protein-ligand complexes that can be assessed by reconstructing the electron density for the ligand using the deposited structure factors. The complexes have been clustered according to the protein sequences, and clusters have been discarded if they do not represent proteins thought to be of direct interest to the pharmaceutical or agrochemical industry. Rules have been used to exclude complexes containing non-drug-like ligands. One complex from each cluster has been selected where a structure of sufficient quality was available. The final Astex diverse set contains 85 diverse, relevant protein-ligand complexes, which have been prepared in a format suitable for docking and are to be made freely available to the entire research community (http://www.ccdc.cam.ac.uk). The performance of the docking program GOLD against the new set is assessed using a variety of protocols. Relatively unbiased protocols give success rates of approximately 80% for redocking into native structures, but it is possible to get success rates of over 90% with some protocols.

In vitro guanine nucleotide exchange activity of DHR-2/DOCKER/CZH2 domains.

PubMed

Côté, Jean-François; Vuori, Kristiina

2006-01-01

Rho family GTPases regulate a large variety of biological processes, including the reorganization of the actin cytoskeleton. Like other members of the Ras superfamily of small GTP-binding proteins, Rho GTPases cycle between a GDP-bound (inactive) and a GTP-bound (active) state, and, when active, the GTPases relay extracellular signals to a large number of downstream effectors. Guanine nucleotide exchange factors (GEFs) promote the exchange of GDP for GTP on Rho GTPases, thereby activating them. Most Rho-GEFs mediate their effects through their signature domain known as the Dbl Homology-Pleckstrin Homology (DH-PH) module. Recently, we and others identified a family of evolutionarily conserved, DOCK180-related proteins that also display GEF activity toward Rho GTPases. The DOCK180-family of proteins lacks the canonical DH-PH module. Instead, they rely on a novel domain, termed DHR-2, DOCKER, or CZH2, to exchange GDP for GTP on Rho targets. In this chapter, the experimental approach that we used to uncover the exchange activity of the DHR-2 domain of DOCK180-related proteins will be described.

BP-Dock: A Flexible Docking Scheme for Exploring Protein–Ligand Interactions Based on Unbound Structures

PubMed Central

Bolia, Ashini; Gerek, Z. Nevin; Ozkan, S. Banu

2016-01-01

Molecular docking serves as an important tool in modeling protein–ligand interactions. However, it is still challenging to incorporate overall receptor flexibility, especially backbone flexibility, in docking due to the large conformational space that needs to be sampled. To overcome this problem, we developed a novel flexible docking approach, BP-Dock (Backbone Perturbation-Dock) that can integrate both backbone and side chain conformational changes induced by ligand binding through a multi-scale approach. In the BP-Dock method, we mimic the nature of binding-induced events as a first-order approximation by perturbing the residues along the protein chain with a small Brownian kick one at a time. The response fluctuation profile of the chain upon these perturbations is computed using the perturbation response scanning method. These response fluctuation profiles are then used to generate binding-induced multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, we applied our approach on a large and diverse data set using unbound structures as receptors. We also compared the BP-Dock results with bound and unbound docking, where overall receptor flexibility was not taken into account. Our results highlight the importance of modeling backbone flexibility in docking for recapitulating the experimental binding affinities, especially when an unbound structure is used. With BP-Dock, we can generate a wide range of binding site conformations realized in nature even in the absence of a ligand that can help us to improve the accuracy of unbound docking. We expect that our fast and efficient flexible docking approach may further aid in our understanding of protein–ligand interactions as well as virtual screening of novel targets for rational drug design. PMID:24380381

Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein-Protein Interactions

PubMed Central

Johnson, David K.; Karanicolas, John

2016-01-01

Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased “pocket optimization” simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its “exemplar”: a perfect, but non-physical, pseudo-ligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 minutes on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against a “pocket-optimized” ensemble of protein conformations, which in turn facilitates identification of more diverse classes of active compounds for a given protein target. PMID:26726827

FlexPepDock lessons from CAPRI peptide-protein rounds and suggested new criteria for assessment of model quality and utility.

PubMed

Marcu, Orly; Dodson, Emma-Joy; Alam, Nawsad; Sperber, Michal; Kozakov, Dima; Lensink, Marc F; Schueler-Furman, Ora

2017-03-01

CAPRI rounds 28 and 29 included, for the first time, peptide-receptor targets of three different systems, reflecting increased appreciation of the importance of peptide-protein interactions. The CAPRI rounds allowed us to objectively assess the performance of Rosetta FlexPepDock, one of the first protocols to explicitly include peptide flexibility in docking, accounting for peptide conformational changes upon binding. We discuss here successes and challenges in modeling these targets: we obtain top-performing, high-resolution models of the peptide motif for cases with known binding sites but there is a need for better modeling of flanking regions, as well as better selection criteria, in particular for unknown binding sites. These rounds have also provided us the opportunity to reassess the success criteria, to better reflect the quality of a peptide-protein complex model. Using all models submitted to CAPRI, we analyze the correlation between current classification criteria and the ability to retrieve critical interface features, such as hydrogen bonds and hotspots. We find that loosening the backbone (and ligand) RMSD threshold, together with a restriction on the side chain RMSD measure, allows us to improve the selection of high-accuracy models. We also suggest a new measure to assess interface hydrogen bond recovery, which is not assessed by the current CAPRI criteria. Finally, we find that surprisingly much can be learned from rather inaccurate models about binding hotspots, suggesting that the current status of peptide-protein docking methods, as reflected by the submitted CAPRI models, can already have a significant impact on our understanding of protein interactions. Proteins 2017; 85:445-462. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Apollo Soyuz test project, USA-USSR. [mission plan of spacecraft docking

NASA Technical Reports Server (NTRS)

1975-01-01

The mission plan of the docking of a United States Apollo and a Soviet Union Soyuz spacecraft in Earth orbit to test compatible rendezvous and docking equipment and procedures is presented. Space experiments conducted jointly by the astronauts and cosmonauts during the joint phase of the mission as well as experiments performed solely by the U.S. astronauts and spread over the nine day span of the flight are included. Biographies of the astronauts and cosmonauts are given.

Diversity and transcription of proteases involved in the maturation of hydrogenases in Nostoc punctiforme ATCC 29133 and Nostoc sp. strain PCC 7120

PubMed Central

2009-01-01

Background The last step in the maturation process of the large subunit of [NiFe]-hydrogenases is a proteolytic cleavage of the C-terminal by a hydrogenase specific protease. Contrary to other accessory proteins these hydrogenase proteases are believed to be specific whereby one type of hydrogenases specific protease only cleaves one type of hydrogenase. In cyanobacteria this is achieved by the gene product of either hupW or hoxW, specific for the uptake or the bidirectional hydrogenase respectively. The filamentous cyanobacteria Nostoc punctiforme ATCC 29133 and Nostoc sp strain PCC 7120 may contain a single uptake hydrogenase or both an uptake and a bidirectional hydrogenase respectively. Results In order to examine these proteases in cyanobacteria, transcriptional analyses were performed of hupW in Nostoc punctiforme ATCC 29133 and hupW and hoxW in Nostoc sp. strain PCC 7120. These studies revealed numerous transcriptional start points together with putative binding sites for NtcA (hupW) and LexA (hoxW). In order to investigate the diversity and specificity among hydrogeanse specific proteases we constructed a phylogenetic tree which revealed several subgroups that showed a striking resemblance to the subgroups previously described for [NiFe]-hydrogenases. Additionally the proteases specificity was also addressed by amino acid sequence analysis and protein-protein docking experiments with 3D-models derived from bioinformatic studies. These studies revealed a so called "HOXBOX"; an amino acid sequence specific for protease of Hox-type which might be involved in docking with the large subunit of the hydrogenase. Conclusion Our findings suggest that the hydrogenase specific proteases are under similar regulatory control as the hydrogenases they cleave. The result from the phylogenetic study also indicates that the hydrogenase and the protease have co-evolved since ancient time and suggests that at least one major horizontal gene transfer has occurred. This co-evolution could be the result of a close interaction between the protease and the large subunit of the [NiFe]-hydrogenases, a theory supported by protein-protein docking experiments performed with 3D-models. Finally we present data that may explain the specificity seen among hydrogenase specific proteases, the so called "HOXBOX"; an amino acid sequence specific for proteases of Hox-type. This opens the door for more detailed studies of the specificity found among hydrogenase specific proteases and the structural properties behind it. PMID:19284580

Anesthetic Binding in a Pentameric Ligand-Gated Ion Channel: GLIC

PubMed Central

Chen, Qiang; Cheng, Mary Hongying; Xu, Yan; Tang, Pei

2010-01-01

Cys-loop receptors are molecular targets of general anesthetics, but the knowledge of anesthetic binding to these proteins remains limited. Here we investigate anesthetic binding to the bacterial Gloeobacter violaceus pentameric ligand-gated ion channel (GLIC), a structural homolog of cys-loop receptors, using an experimental and computational hybrid approach. Tryptophan fluorescence quenching experiments showed halothane and thiopental binding at three tryptophan-associated sites in the extracellular (EC) domain, transmembrane (TM) domain, and EC-TM interface of GLIC. An additional binding site at the EC-TM interface was predicted by docking analysis and validated by quenching experiments on the N200W GLIC mutant. The binding affinities (KD) of 2.3 ± 0.1 mM and 0.10 ± 0.01 mM were derived from the fluorescence quenching data of halothane and thiopental, respectively. Docking these anesthetics to the original GLIC crystal structure and the structures relaxed by molecular dynamics simulations revealed intrasubunit sites for most halothane binding and intersubunit sites for thiopental binding. Tryptophans were within reach of both intra- and intersubunit binding sites. Multiple molecular dynamics simulations on GLIC in the presence of halothane at different sites suggested that anesthetic binding at the EC-TM interface disrupted the critical interactions for channel gating, altered motion of the TM23 linker, and destabilized the open-channel conformation that can lead to inhibition of GLIC channel current. The study has not only provided insights into anesthetic binding in GLIC, but also demonstrated a successful fusion of experiments and computations for understanding anesthetic actions in complex proteins. PMID:20858424

A Subspace Semi-Definite programming-based Underestimation (SSDU) method for stochastic global optimization in protein docking*

PubMed Central

Nan, Feng; Moghadasi, Mohammad; Vakili, Pirooz; Vajda, Sandor; Kozakov, Dima; Ch. Paschalidis, Ioannis

2015-01-01

We propose a new stochastic global optimization method targeting protein docking problems. The method is based on finding a general convex polynomial underestimator to the binding energy function in a permissive subspace that possesses a funnel-like structure. We use Principal Component Analysis (PCA) to determine such permissive subspaces. The problem of finding the general convex polynomial underestimator is reduced into the problem of ensuring that a certain polynomial is a Sum-of-Squares (SOS), which can be done via semi-definite programming. The underestimator is then used to bias sampling of the energy function in order to recover a deep minimum. We show that the proposed method significantly improves the quality of docked conformations compared to existing methods. PMID:25914440

Skylab

NASA Image and Video Library

1973-01-01

This photograph shows the internal configuration of Skylab's Multiple Docking Adapter (MDA), including callouts for its various internal experiments and facilities. Designed and manufactured by the Marshall Space Flight Center, the MDA housed a number of experiment control and stowage units and provided a docking port for the Apollo Command Module.

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

PubMed

Ross, Gregory A; Morris, Garrett M; Biggin, Philip C

2012-01-01

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

Electrostatics in protein–protein docking

PubMed Central

Heifetz, Alexander; Katchalski-Katzir, Ephraim; Eisenstein, Miriam

2002-01-01

A novel geometric-electrostatic docking algorithm is presented, which tests and quantifies the electrostatic complementarity of the molecular surfaces together with the shape complementarity. We represent each molecule to be docked as a grid of complex numbers, storing information regarding the shape of the molecule in the real part and information regarding the electrostatic character of the molecule in the imaginary part. The electrostatic descriptors are derived from the electrostatic potential of the molecule. Thus, the electrostatic character of the molecule is represented as patches of positive, neutral, or negative values. The potential for each molecule is calculated only once and stored as potential spheres adequate for exhaustive rotation/translation scans. The geometric-electrostatic docking algorithm is applied to 17 systems, starting form the structures of the unbound molecules. The results—in terms of the complementarity scores of the nearly correct solutions, their ranking in the lists of sorted solutions, and their statistical uniqueness—are compared with those of geometric docking, showing that the inclusion of electrostatic complementarity in docking is very important, in particular in docking of unbound structures. Based on our results, we formulate several "good electrostatic docking rules": The geometric-electrostatic docking procedure is more successful than geometric docking when the potential patches are large and when the potential extends away from the molecular surface and protrudes into the solvent. In contrast, geometric docking is recommended when the electrostatic potential around the molecules to be docked appears homogenous, that is, with a similar sign all around the molecule. PMID:11847280

Building protein-protein interaction networks for Leishmania species through protein structural information.

PubMed

Dos Santos Vasconcelos, Crhisllane Rafaele; de Lima Campos, Túlio; Rezende, Antonio Mauro

2018-03-06

Systematic analysis of a parasite interactome is a key approach to understand different biological processes. It makes possible to elucidate disease mechanisms, to predict protein functions and to select promising targets for drug development. Currently, several approaches for protein interaction prediction for non-model species incorporate only small fractions of the entire proteomes and their interactions. Based on this perspective, this study presents an integration of computational methodologies, protein network predictions and comparative analysis of the protozoan species Leishmania braziliensis and Leishmania infantum. These parasites cause Leishmaniasis, a worldwide distributed and neglected disease, with limited treatment options using currently available drugs. The predicted interactions were obtained from a meta-approach, applying rigid body docking tests and template-based docking on protein structures predicted by different comparative modeling techniques. In addition, we trained a machine-learning algorithm (Gradient Boosting) using docking information performed on a curated set of positive and negative protein interaction data. Our final model obtained an AUC = 0.88, with recall = 0.69, specificity = 0.88 and precision = 0.83. Using this approach, it was possible to confidently predict 681 protein structures and 6198 protein interactions for L. braziliensis, and 708 protein structures and 7391 protein interactions for L. infantum. The predicted networks were integrated to protein interaction data already available, analyzed using several topological features and used to classify proteins as essential for network stability. The present study allowed to demonstrate the importance of integrating different methodologies of interaction prediction to increase the coverage of the protein interaction of the studied protocols, besides it made available protein structures and interactions not previously reported.

Covalent Docking of Large Libraries for the Discovery of Chemical Probes

PubMed Central

London, Nir; Miller, Rand M.; Krishnan, Shyam; Uchida, Kenji; Irwin, John J.; Eidam, Oliv; Gibold, Lucie; Cimermančič, Peter; Bonnet, Richard; Shoichet, Brian K.; Taunton, Jack

2014-01-01

Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency, and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1, and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org). PMID:25344815

Covalent docking of large libraries for the discovery of chemical probes.

PubMed

London, Nir; Miller, Rand M; Krishnan, Shyam; Uchida, Kenji; Irwin, John J; Eidam, Oliv; Gibold, Lucie; Cimermančič, Peter; Bonnet, Richard; Shoichet, Brian K; Taunton, Jack

2014-12-01

Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1 and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including what are to our knowledge the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org/).

Probabilistic cross-link analysis and experiment planning for high-throughput elucidation of protein structure.

PubMed

Ye, Xiaoduan; O'Neil, Patrick K; Foster, Adrienne N; Gajda, Michal J; Kosinski, Jan; Kurowski, Michal A; Bujnicki, Janusz M; Friedman, Alan M; Bailey-Kellogg, Chris

2004-12-01

Emerging high-throughput techniques for the characterization of protein and protein-complex structures yield noisy data with sparse information content, placing a significant burden on computation to properly interpret the experimental data. One such technique uses cross-linking (chemical or by cysteine oxidation) to confirm or select among proposed structural models (e.g., from fold recognition, ab initio prediction, or docking) by testing the consistency between cross-linking data and model geometry. This paper develops a probabilistic framework for analyzing the information content in cross-linking experiments, accounting for anticipated experimental error. This framework supports a mechanism for planning experiments to optimize the information gained. We evaluate potential experiment plans using explicit trade-offs among key properties of practical importance: discriminability, coverage, balance, ambiguity, and cost. We devise a greedy algorithm that considers those properties and, from a large number of combinatorial possibilities, rapidly selects sets of experiments expected to discriminate pairs of models efficiently. In an application to residue-specific chemical cross-linking, we demonstrate the ability of our approach to plan experiments effectively involving combinations of cross-linkers and introduced mutations. We also describe an experiment plan for the bacteriophage lambda Tfa chaperone protein in which we plan dicysteine mutants for discriminating threading models by disulfide formation. Preliminary results from a subset of the planned experiments are consistent and demonstrate the practicality of planning. Our methods provide the experimenter with a valuable tool (available from the authors) for understanding and optimizing cross-linking experiments.

The sorting nexin, DSH3PX1, connects the axonal guidance receptor, Dscam, to the actin cytoskeleton.

PubMed

Worby, C A; Simonson-Leff, N; Clemens, J C; Kruger, R P; Muda, M; Dixon, J E

2001-11-09

Dock, an adaptor protein that functions in Drosophila axonal guidance, consists of three tandem Src homology 3 (SH3) domains preceding an SH2 domain. To develop a better understanding of axonal guidance at the molecular level, we used the SH2 domain of Dock to purify a protein complex from fly S2 cells. Five proteins were obtained in pure form from this protein complex. The largest protein in the complex was identified as Dscam (Down syndrome cell adhesion molecule), which was subsequently shown to play a key role in directing neurons of the fly embryo to correct positions within the nervous system (Schmucker, D., Clemens, J. C., Shu, H., Worby, C. A., Xiao, J., Muda, M., Dixon, J. E., and Zipursky, S. L. (2000) Cell 101, 671-684). The smallest protein in this complex (p63) has now been identified. We have named p63 DSH3PX1 because it appears to be the Drosophila orthologue of the human protein known as SH3PX1. DSH3PX1 is comprised of an NH(2)-terminal SH3 domain, an internal PHOX homology (PX) domain, and a carboxyl-terminal coiled-coil region. Because of its PX domain, DSH3PX1 is considered to be a member of a growing family of proteins known collectively as sorting nexins, some of which have been shown to be involved in vesicular trafficking. We demonstrate that DSH3PX1 immunoprecipitates with Dock and Dscam from S2 cell extracts. The domains responsible for the in vitro interaction between DSH3PX1 and Dock were also identified. We further show that DSH3PX1 interacts with the Drosophila orthologue of Wasp, a protein component of actin polymerization machinery, and that DSH3PX1 co-immunoprecipitates with AP-50, the clathrin-coat adapter protein. This evidence places DSH3PX1 in a complex linking cell surface receptors like Dscam to proteins involved in cytoskeletal rearrangements and/or receptor trafficking.

Identification of Biomarkers for Resistance to Fusarium oxysporum f. sp. cubense Infection and in Silico Studies in Musa paradisiaca Cultivar Puttabale through Proteomic Approach.

PubMed

Ramu, Venkatesh; Venkatarangaiah, Krishna; Krishnappa, Pradeepa; Shimoga Rajanna, Santosh Kumar; Deeplanaik, Nagaraja; Chandra Pal, Anup; Kini, Kukkundoor Ramachandra

2016-02-24

Panama wilt caused by Fusarium oxysporum f. sp. cubense (Foc) is one of the major disease constraints of banana production. Previously, we reported the disease resistance Musa paradisiaca cv. puttabale clones developed from Ethylmethanesulfonate and Foc culture filtrate against Foc inoculation. Here, the same resistant clones and susceptible clones were used for the study of protein accumulation against Foc inoculation by two-dimensional gel electrophoresis (2-DE), their expression pattern and an in silico approach. The present investigation revealed mass-spectrometry identified 16 proteins that were over accumulated and 5 proteins that were under accumulated as compared to the control. The polyphosphoinositide binding protein ssh2p (PBPssh2p) and Indoleacetic acid-induced-like (IAA) protein showed significant up-regulation and down-regulation. The docking of the pathogenesis-related protein (PR) with the fungal protein endopolygalacturonase (PG) exemplify the three ionic interactions and seven hydrophobic residues that tends to good interaction at the active site of PG with free energy of assembly dissociation (1.5 kcal/mol). The protein-ligand docking of the Peptide methionine sulfoxide reductase chloroplastic-like protein (PMSRc) with the ligand β-1,3 glucan showed minimum binding energy (-6.48 kcal/mol) and docking energy (-8.2 kcal/mol) with an interaction of nine amino-acid residues. These explorations accelerate the research in designing the host pathogen interaction studies for the better management of diseases.

Identification of Biomarkers for Resistance to Fusarium oxysporum f. sp. cubense Infection and in Silico Studies in Musa paradisiaca Cultivar Puttabale through Proteomic Approach

PubMed Central

Ramu, Venkatesh; Venkatarangaiah, Krishna; Krishnappa, Pradeepa; Shimoga Rajanna, Santosh Kumar; Deeplanaik, Nagaraja; Chandra Pal, Anup; Kini, Kukkundoor Ramachandra

2016-01-01

Panama wilt caused by Fusarium oxysporum f. sp. cubense (Foc) is one of the major disease constraints of banana production. Previously, we reported the disease resistance Musa paradisiaca cv. puttabale clones developed from Ethylmethanesulfonate and Foc culture filtrate against Foc inoculation. Here, the same resistant clones and susceptible clones were used for the study of protein accumulation against Foc inoculation by two-dimensional gel electrophoresis (2-DE), their expression pattern and an in silico approach. The present investigation revealed mass-spectrometry identified 16 proteins that were over accumulated and 5 proteins that were under accumulated as compared to the control. The polyphosphoinositide binding protein ssh2p (PBPssh2p) and Indoleacetic acid-induced-like (IAA) protein showed significant up-regulation and down-regulation. The docking of the pathogenesis-related protein (PR) with the fungal protein endopolygalacturonase (PG) exemplify the three ionic interactions and seven hydrophobic residues that tends to good interaction at the active site of PG with free energy of assembly dissociation (1.5 kcal/mol). The protein-ligand docking of the Peptide methionine sulfoxide reductase chloroplastic-like protein (PMSRc) with the ligand β-1,3 glucan showed minimum binding energy (−6.48 kcal/mol) and docking energy (−8.2 kcal/mol) with an interaction of nine amino-acid residues. These explorations accelerate the research in designing the host pathogen interaction studies for the better management of diseases. PMID:28248219

Studies on interaction of insect repellent compounds with odorant binding receptor proteins by in silico molecular docking approach.

PubMed

Gopal, J Vinay; Kannabiran, K

2013-12-01

The aim of the study was to identify the interactions between insect repellent compounds and target olfactory proteins. Four compounds, camphor (C10H16O), carvacrol (C10H14O), oleic acid (C18H34O2) and firmotox (C22H28O5) were chosen as ligands. Seven olfactory proteins of insects with PDB IDs: 3K1E, 1QWV, 1TUJ, 1OOF, 2ERB, 3R1O and OBP1 were chosen for docking analysis. Patch dock was used and pymol for visualizing the structures. The interactions of these ligands with few odorant binding proteins showed binding energies. The ligand camphor had showed a binding energy of -136 kcal/mol with OBP1 protein. The ligand carvacrol interacted with 1QWV and 1TUJ proteins with a least binding energy of -117.45 kcal/mol and -21.78 kcal/mol respectively. The ligand oleic acid interacted with 1OOF, 2ERB, 3R1O and OBP1 with least binding energies. Ligand firmotox interacted with OBP1 and showed least binding energies. Three ligands (camphor, oleic acid and firmotox) had one, two, three interactions with a single protein OBP1 of Nilaparvatha lugens (Rice pest). From this in silico study we identified the interaction patterns for insect repellent compounds with the target insect odarant proteins. The results of our study revealed that the chosen ligands showed hydrogen bond interactions with the target olfactory receptor proteins.

Solving Kinetic Equations for the Laser Flash Photolysis Experiment on Nitric Oxide Synthases: Effect of Conformational Dynamics on the Interdomain Electron Transfer.

PubMed

Astashkin, Andrei V; Feng, Changjian

2015-11-12

The production of nitric oxide by the nitric oxide synthase (NOS) enzyme depends on the interdomain electron transfer (IET) between the flavin mononucleotide (FMN) and heme domains. Although the rate of this IET has been measured by laser flash photolysis (LFP) for various NOS proteins, no rigorous analysis of the relevant kinetic equations was performed so far. In this work, we provide an analytical solution of the kinetic equations underlying the LFP approach. The derived expressions reveal that the bulk IET rate is significantly affected by the conformational dynamics that determines the formation and dissociation rates of the docking complex between the FMN and heme domains. We show that in order to informatively study the electron transfer across the NOS enzyme, LFP should be used in combination with other spectroscopic methods that could directly probe the docking equilibrium and the conformational change rate constants. The implications of the obtained analytical expressions for the interpretation of the LFP results from various native and modified NOS proteins are discussed. The mathematical formulas derived in this work should also be applicable for interpreting the IET kinetics in other modular redox enzymes.

Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015.

PubMed

Slynko, Inna; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2016-09-01

High affinity ligands for a given target tend to share key molecular interactions with important anchoring amino acids and therefore often present quite conserved interaction patterns. This simple concept was formalized in a topological knowledge-based scoring function (GRIM) for selecting the most appropriate docking poses from previously X-rayed interaction patterns. GRIM first converts protein-ligand atomic coordinates (docking poses) into a simple 3D graph describing the corresponding interaction pattern. In a second step, proposed graphs are compared to that found from template structures in the Protein Data Bank. Last, all docking poses are rescored according to an empirical score (GRIMscore) accounting for overlap of maximum common subgraphs. Taking the opportunity of the public D3R Grand Challenge 2015, GRIM was used to rescore docking poses for 36 ligands (6 HSP90α inhibitors, 30 MAP4K4 inhibitors) prior to the release of the corresponding protein-ligand X-ray structures. When applied to the HSP90α dataset, for which many protein-ligand X-ray structures are already available, GRIM provided very high quality solutions (mean rmsd = 1.06 Å, n = 6) as top-ranked poses, and significantly outperformed a state-of-the-art scoring function. In the case of MAP4K4 inhibitors, for which preexisting 3D knowledge is scarce and chemical diversity is much larger, the accuracy of GRIM poses decays (mean rmsd = 3.18 Å, n = 30) although GRIM still outperforms an energy-based scoring function. GRIM rescoring appears to be quite robust with comparison to the other approaches competing for the same challenge (42 submissions for the HSP90 dataset, 27 for the MAP4K4 dataset) as it ranked 3rd and 2nd respectively, for the two investigated datasets. The rescoring method is quite simple to implement, independent on a docking engine, and applicable to any target for which at least one holo X-ray structure is available.

Epitope-based peptide vaccine design and target site depiction against Ebola viruses: an immunoinformatics study.

PubMed

Khan, M A; Hossain, M U; Rakib-Uz-Zaman, S M; Morshed, M N

2015-07-01

Ebola viruses (EBOVs) have been identified as an emerging threat in recent year as it causes severe haemorrhagic fever in human. Epitope-based vaccine design for EBOVs remains a top priority because a mere progress has been made in this regard. Another reason is the lack of antiviral drug and licensed vaccine although there is a severe outbreak in Central Africa. In this study, we aimed to design an epitope-based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites using various immunoinformatics and docking simulation tools. The capacity to induce both humoral and cell-mediated immunity by T cell and B cell was checked for the selected protein. The peptide region spanning 9 amino acids from 42 to 50 and the sequence TLASIGTAF were found as the most potential B and T cell epitopes, respectively. This peptide could interact with 12 HLAs and showed high population coverage up to 80.99%. Using molecular docking, the epitope was further appraised for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post-therapeutic strategy, docking study of predicted 3D structure identified suitable therapeutic inhibitor against targeted protein. However, this computational epitope-based peptide vaccine designing and target site prediction against EBOVs open up a new horizon which may be the prospective way in Ebola viruses research; the results require validation by in vitro and in vivo experiments. © 2015 John Wiley & Sons Ltd.

Novel Penicillin Analogues as Potential Antimicrobial Agents; Design, Synthesis and Docking Studies.

PubMed

Ashraf, Zaman; Bais, Abdul; Manir, Md Maniruzzaman; Niazi, Umar

2015-01-01

A number of penicillin derivatives (4a-h) were synthesized by the condensation of 6-amino penicillinic acid (6-APA) with non-steroidal anti-inflammatory drugs as antimicrobial agents. In silico docking study of these analogues was performed against Penicillin Binding Protein (PDBID 1CEF) using AutoDock Tools 1.5.6 in order to investigate the antimicrobial data on structural basis. Penicillin binding proteins function as either transpeptidases or carboxypeptidases and in few cases demonstrate transglycosylase activity in bacteria. The excellent antibacterial potential was depicted by compounds 4c and 4e against Escherichia coli, Staphylococcus epidermidus and Staphylococcus aureus compared to the standard amoxicillin. The most potent penicillin derivative 4e exhibited same activity as standard amoxicillin against S. aureus. In the enzyme inhibitory assay the compound 4e inhibited E. coli MurC with an IC50 value of 12.5 μM. The docking scores of these compounds 4c and 4e also verified their greater antibacterial potential. The results verified the importance of side chain functionalities along with the presence of central penam nucleus. The binding affinities calculated from docking results expressed in the form of binding energies ranges from -7.8 to -9.2kcal/mol. The carboxylic group of penam nucleus in all these compounds is responsible for strong binding with receptor protein with the bond length ranges from 3.4 to 4.4 Ǻ. The results of present work ratify that derivatives 4c and 4e may serve as a structural template for the design and development of potent antimicrobial agents.

Novel Penicillin Analogues as Potential Antimicrobial Agents; Design, Synthesis and Docking Studies

PubMed Central

Ashraf, Zaman; Bais, Abdul; Manir, Md. Maniruzzaman; Niazi, Umar

2015-01-01

A number of penicillin derivatives (4a-h) were synthesized by the condensation of 6-amino penicillinic acid (6-APA) with non-steroidal anti-inflammatory drugs as antimicrobial agents. In silico docking study of these analogues was performed against Penicillin Binding Protein (PDBID 1CEF) using AutoDock Tools 1.5.6 in order to investigate the antimicrobial data on structural basis. Penicillin binding proteins function as either transpeptidases or carboxypeptidases and in few cases demonstrate transglycosylase activity in bacteria. The excellent antibacterial potential was depicted by compounds 4c and 4e against Escherichia coli, Staphylococcus epidermidus and Staphylococcus aureus compared to the standard amoxicillin. The most potent penicillin derivative 4e exhibited same activity as standard amoxicillin against S. aureus. In the enzyme inhibitory assay the compound 4e inhibited E. coli MurC with an IC50 value of 12.5 μM. The docking scores of these compounds 4c and 4e also verified their greater antibacterial potential. The results verified the importance of side chain functionalities along with the presence of central penam nucleus. The binding affinities calculated from docking results expressed in the form of binding energies ranges from -7.8 to -9.2kcal/mol. The carboxylic group of penam nucleus in all these compounds is responsible for strong binding with receptor protein with the bond length ranges from 3.4 to 4.4 Ǻ. The results of present work ratify that derivatives 4c and 4e may serve as a structural template for the design and development of potent antimicrobial agents. PMID:26267242

Activated Cdc42 kinase regulates Dock localization in male germ cells during Drosophila spermatogenesis.

PubMed

Abdallah, Abbas M; Zhou, Xin; Kim, Christine; Shah, Kushani K; Hogden, Christopher; Schoenherr, Jessica A; Clemens, James C; Chang, Henry C

2013-06-15

Deregulation of the non-receptor tyrosine kinase ACK1 (Activated Cdc42-associated kinase) correlates with poor prognosis in cancers and has been implicated in promoting metastasis. To further understand its in vivo function, we have characterized the developmental defects of a null mutation in Drosophila Ack, which bears a high degree of sequence similarity to mammalian ACK1 but lacks a CRIB domain. We show that Ack, while not essential for viability, is critical for sperm formation. This function depends on Ack tyrosine kinase activity and is required cell autonomously in differentiating male germ cells at or after the spermatocyte stage. Ack associates predominantly with endocytic clathrin sites in spermatocytes, but disruption of Ack function has no apparent effect on clathrin localization and receptor-mediated internalization of Boss (Bride of sevenless) protein in eye discs. Instead, Ack is required for the subcellular distribution of Dock (dreadlocks), the Drosophila homolog of the SH2- and SH3-containing adaptor protein Nck. Moreover, Dock forms a complex with Ack, and the localization of Dock in male germ cells depends on its SH2 domain. Together, our results suggest that Ack-dependent tyrosine phosphorylation recruits Dock to promote sperm differentiation. Copyright © 2013 Elsevier Inc. All rights reserved.

SpaceDock: A Performance Task Platform for Spaceflight Operations

NASA Technical Reports Server (NTRS)

Marshburn, Thomas H.; Strangman, Gary E.; Strauss, Monica S.; Sutton, Jeffrey P.

2003-01-01

Preliminary evidence during both short- and long-duration spaceflight indicates that perceptual-motor coordination changes occur and persist in-flight. However, there is presently no in-flight method for evaluating astronaut performance on mission-critical tasks such as docking. We present a portable platform we have developed for attempting and evaluating docking, and describe the results of a pilot study wherein flight novices learned the docking task. Methods: A dual-joystick, six degrees of freedom platform-called SpaceDock-was developed to enable portable, adaptable performance testing in a spaceflight operations setting. Upon this platform, a simplified docking task was created, involving a constant rate of approach towards a docking target and requiring the user to correct translation in two dimensions and attitude orientation along one dimension (either pitch or roll). Ten flight naive subjects performed the task over a 45 min period and all joystick inputs and timings were collected, from which we could successfully reconstruct travel paths, input profiles and relative target displacements. Results: Subjects exhibited significant improvements in docking over the course of the experiment. Learning to compensate for roll-alterations was robust, whereas compensation for pitch-alterations was not in evidence in this population and relatively short training period. Conclusion: The SpaceDock platform can provide a novel method for training and testing subjects, on a spaceflight-relevant task, and can be used to examine behavioral learning, strategy use, and has been adapted for use in brain imaging experiments.

ARCADE-R2 experiment on board BEXUS 17 stratospheric balloon

NASA Astrophysics Data System (ADS)

Barbetta, Marco; Boesso, Alessandro; Branz, Francesco; Carron, Andrea; Olivieri, Lorenzo; Prendin, Jacopo; Rodeghiero, Gabriele; Sansone, Francesco; Savioli, Livia; Spinello, Fabio; Francesconi, Alessandro

2015-09-01

This paper provides an overview of the ARCADE-R2 experiment, a technology demonstrator that aimed to prove the feasibility of small-scale satellite and/or aircraft systems with automatic (a) attitude determination, (b) control and (c) docking capabilities. The experiment embodies a simplified scenario in which an unmanned vehicle mock-up performs rendezvous and docking operations with a fixed complementary unit. The experiment is composed by a supporting structure, which holds a small vehicle with one translational and one rotational degree of freedom, and its fixed target. The dual system features three main custom subsystems: a relative infrared navigation sensor, an attitude control system based on a reaction wheel and a small-scale docking mechanism. The experiment bus is equipped with pressure and temperature sensors, and wind probes to monitor the external environmental conditions. The experiment flew on board the BEXUS 17 stratospheric balloon on October 10, 2013, where several navigation-control-docking sequences were executed and data on the external pressure, temperature, wind speed and direction were collected, characterizing the atmospheric loads applied to the vehicle. This paper describes the critical components of ARCADE-R2 as well as the main results obtained from the balloon flight.

Predicting receptor functionality of signaling lymphocyte activation molecule for measles virus hemagglutinin by docking simulation.

PubMed

Suzuki, Yoshiyuki

2017-05-01

Predicting susceptibility of various species to a virus assists assessment of risk of interspecies transmission. Evaluation of receptor functionality may be useful in screening for susceptibility. In this study, docking simulation was conducted for measles virus hemagglutinin (MV-H) and immunoglobulin-like variable domain of signaling lymphocyte activation molecule (SLAM-V). It was observed that the docking scores for MV-H and SLAM-V correlated with the activity of SLAM as an MV receptor. These results suggest that the receptor functionality may be predicted from the docking scores of virion surface proteins and cellular receptor molecules. © 2017 The Societies and John Wiley & Sons Australia, Ltd.

Automated Docking Screens: A Feasibility Study

PubMed Central

2009-01-01

Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 Å rmsd 50−60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 Å rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org. PMID:19719084

Automated docking screens: a feasibility study.

PubMed

Irwin, John J; Shoichet, Brian K; Mysinger, Michael M; Huang, Niu; Colizzi, Francesco; Wassam, Pascal; Cao, Yiqun

2009-09-24

Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 A rmsd 50-60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 A rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org .

An Elmo–Dock complex locally controls Rho GTPases and actin remodeling during cadherin-mediated adhesion

PubMed Central

Collins, Caitlin

2014-01-01

Cell–cell contact formation is a dynamic process requiring the coordination of cadherin-based cell–cell adhesion and integrin-based cell migration. A genome-wide RNA interference screen for proteins required specifically for cadherin-dependent cell–cell adhesion identified an Elmo–Dock complex. This was unexpected as Elmo–Dock complexes act downstream of integrin signaling as Rac guanine-nucleotide exchange factors. In this paper, we show that Elmo2 recruits Dock1 to initial cell–cell contacts in Madin–Darby canine kidney cells. At cell–cell contacts, both Elmo2 and Dock1 are essential for the rapid recruitment and spreading of E-cadherin, actin reorganization, localized Rac and Rho GTPase activities, and the development of strong cell–cell adhesion. Upon completion of cell–cell adhesion, Elmo2 and Dock1 no longer localize to cell–cell contacts and are not required subsequently for the maintenance of cell–cell adhesion. These studies show that Elmo–Dock complexes are involved in both integrin- and cadherin-based adhesions, which may help to coordinate the transition of cells from migration to strong cell–cell adhesion. PMID:25452388

Comparative modeling and docking studies of p16ink4/cyclin D1/Rb pathway genes in lung cancer revealed functionally interactive residue of RB1 and its functional partner E2F1.

PubMed

Naqsh e Zahra, Syeda; Khattak, Naureen Aslam; Mir, Asif

2013-01-01

Lung cancer is the major cause of mortality worldwide. Major signalling pathways that could play significant role in lung cancer therapy include (1) Growth promoting pathways (Epidermal Growth Factor Receptor/Ras/ PhosphatidylInositol 3-Kinase) (2) Growth inhibitory pathways (p53/Rb/P14ARF, STK11) (3) Apoptotic pathways (Bcl-2/Bax/Fas/FasL). Insilico strategy was implemented to solve the mystery behind selected lung cancer pathway by applying comparative modeling and molecular docking studies. YASARA [v 12.4.1] was utilized to predict structural models of P16-INK4 and RB1 genes using template 4ELJ-A and 1MX6-B respectively. WHAT CHECK evaluation tool demonstrated overall quality of predicted P16-INK4 and RB1 with Z-score of -0.132 and -0.007 respectively which showed a strong indication of reliable structure prediction. Protein-protein interactions were explored by utilizing STRING server, illustrated that CDK4 and E2F1 showed strong interaction with P16-INK4 and RB1 based on confidence score of 0.999 and 0.999 respectively. In order to facilitate a comprehensive understanding of the complex interactions between candidate genes with their functional interactors, GRAMM-X server was used. Protein-protein docking investigation of P16-INK4 revealed four ionic bonds illustrating Arg47, Arg80,Cys72 and Met1 residues as actively participating in interactions with CDK4 while docking results of RB1 showed four hydrogen bonds involving Glu864, Ser567, Asp36 and Arg861 residues which interact strongly with its respective functional interactor E2F1. This research may provide a basis for understanding biological insights of P16-INK4 and RB1 proteins which will be helpful in future to design a suitable drug to inhibit the disease pathogenesis as we have determined the interacting amino acids which can be targeted in order to design a ligand in-vitro to propose a drug for clinical trials. Protein -protein docking of candidate genes and their important interacting residues likely to be provide a gateway for developing computer aided drug designing.

Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches

NASA Astrophysics Data System (ADS)

Thangsunan, Patcharapong; Kittiwachana, Sila; Meepowpan, Puttinan; Kungwan, Nawee; Prangkio, Panchika; Hannongbua, Supa; Suree, Nuttee

2016-06-01

Improving performance of scoring functions for drug docking simulations is a challenging task in the modern discovery pipeline. Among various ways to enhance the efficiency of scoring function, tuning of energetic component approach is an attractive option that provides better predictions. Herein we present the first development of rapid and simple tuning models for predicting and scoring inhibitory activity of investigated ligands docked into catalytic core domain structures of HIV-1 integrase (IN) enzyme. We developed the models using all energetic terms obtained from flexible ligand-rigid receptor dockings by AutoDock4, followed by a data analysis using either partial least squares (PLS) or self-organizing maps (SOMs). The models were established using 66 and 64 ligands of mercaptobenzenesulfonamides for the PLS-based and the SOMs-based inhibitory activity predictions, respectively. The models were then evaluated for their predictability quality using closely related test compounds, as well as five different unrelated inhibitor test sets. Weighting constants for each energy term were also optimized, thus customizing the scoring function for this specific target protein. Root-mean-square error (RMSE) values between the predicted and the experimental inhibitory activities were determined to be <1 (i.e. within a magnitude of a single log scale of actual IC50 values). Hence, we propose that, as a pre-functional assay screening step, AutoDock4 docking in combination with these subsequent rapid weighted energy tuning methods via PLS and SOMs analyses is a viable approach to predict the potential inhibitory activity and to discriminate among small drug-like molecules to target a specific protein of interest.

Independent signaling by Drosophila insulin receptor for axon guidance and growth

PubMed Central

Li, Caroline R.; Guo, Dongyu; Pick, Leslie

2014-01-01

The Drosophila insulin receptor (DInR) regulates a diverse array of biological processes including growth, axon guidance, and sugar homeostasis. Growth regulation by DInR is mediated by Chico, the Drosophila homolog of vertebrate insulin receptor substrate proteins IRS1–4. In contrast, DInR regulation of photoreceptor axon guidance in the developing visual system is mediated by the SH2-SH3 domain adaptor protein Dreadlocks (Dock). In vitro studies by others identified five NPXY motifs, one in the juxtamembrane region and four in the signaling C-terminal tail (C-tail), important for interaction with Chico. Here we used yeast two-hybrid assays to identify regions in the DInR C-tail that interact with Dock. These Dock binding sites were in separate portions of the C-tail from the previously identified Chico binding sites. To test whether these sites are required for growth or axon guidance in whole animals, a panel of DInR proteins, in which the putative Chico and Dock interaction sites had been mutated individually or in combination, were tested for their ability to rescue viability, growth and axon guidance defects of dinr mutant flies. Sites required for viability were identified. Unexpectedly, mutation of both putative Dock binding sites, either individually or in combination, did not lead to defects in photoreceptor axon guidance. Thus, either sites also required for viability are necessary for DInR function in axon guidance and/or there is redundancy built into the DInR/Dock interaction such that Dock is able to interact with multiple regions of DInR. We also found that simultaneous mutation of all five NPXY motifs implicated in Chico interaction drastically decreased growth in both male and female adult flies. These animals resembled chico mutants, supporting the notion that DInR interacts directly with Chico in vivo to control body size. Mutation of these five NPXY motifs did not affect photoreceptor axon guidance, segregating the roles of DInR in the processes of growth and axon guidance. PMID:24478707

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.

PubMed

Barradas-Bautista, Didier; Fernández-Recio, Juan

2017-01-01

Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level.

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations

PubMed Central

2017-01-01

Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level. PMID:28841721

Coiled coil interactions for the targeting of liposomes for nucleic acid delivery

NASA Astrophysics Data System (ADS)

Oude Blenke, Erik E.; van den Dikkenberg, Joep; van Kolck, Bartjan; Kros, Alexander; Mastrobattista, Enrico

2016-04-01

Coiled coil interactions are strong protein-protein interactions that are involved in many biological processes, including intracellular trafficking and membrane fusion. A synthetic heterodimeric coiled-coil forming peptide pair, known as E3 (EIAALEK)3 and K3 (KIAALKE)3 was used to functionalize liposomes encapsulating a splice correcting oligonucleotide or siRNA. These peptide-functionalized vesicles are highly stable in solution but start to cluster when vesicles modified with complementary peptides are mixed together, demonstrating that the peptides quickly coil and crosslink the vesicles. When one of the peptides was anchored to the cell membrane using a hydrophobic cholesterol anchor, vesicles functionalized with the complementary peptide could be docked to these cells, whereas non-functionalized cells did not show any vesicle tethering. Although the anchored peptides do not have a downstream signaling pathway, microscopy pictures revealed that after four hours, the majority of the docked vesicles were internalized by endocytosis. Finally, for the first time, it was shown that the coiled coil assembly at the interface between the vesicles and the cell membrane induces active uptake and leads to cytosolic delivery of the nucleic acid cargo. Both the siRNA and the splice correcting oligonucleotide were functionally delivered, resulting respectively in the silencing or recovery of luciferase expression in the appropriate cell lines. These results demonstrate that the docking to the cell by coiled coil interaction can induce active uptake and achieve the successful intracellular delivery of otherwise membrane impermeable nucleic acids in a highly specific manner.Coiled coil interactions are strong protein-protein interactions that are involved in many biological processes, including intracellular trafficking and membrane fusion. A synthetic heterodimeric coiled-coil forming peptide pair, known as E3 (EIAALEK)3 and K3 (KIAALKE)3 was used to functionalize liposomes encapsulating a splice correcting oligonucleotide or siRNA. These peptide-functionalized vesicles are highly stable in solution but start to cluster when vesicles modified with complementary peptides are mixed together, demonstrating that the peptides quickly coil and crosslink the vesicles. When one of the peptides was anchored to the cell membrane using a hydrophobic cholesterol anchor, vesicles functionalized with the complementary peptide could be docked to these cells, whereas non-functionalized cells did not show any vesicle tethering. Although the anchored peptides do not have a downstream signaling pathway, microscopy pictures revealed that after four hours, the majority of the docked vesicles were internalized by endocytosis. Finally, for the first time, it was shown that the coiled coil assembly at the interface between the vesicles and the cell membrane induces active uptake and leads to cytosolic delivery of the nucleic acid cargo. Both the siRNA and the splice correcting oligonucleotide were functionally delivered, resulting respectively in the silencing or recovery of luciferase expression in the appropriate cell lines. These results demonstrate that the docking to the cell by coiled coil interaction can induce active uptake and achieve the successful intracellular delivery of otherwise membrane impermeable nucleic acids in a highly specific manner. Electronic supplementary information (ESI) available: Two videos of the experiment are shown in Fig. 5, demonstrating the distinctive characteristics of the peptide pair in a mixed population of cells are available in online. Video S1 shows the experiment in the bright field channel including the green channel (calcein-AM stained unfunctionalized cells) and orange channel (rhodamine labeled liposomes). Video S2 shows the exact same frames but combining the fluorescent channels only, including the blue channel for Hoechst nuclear staining. Both videos consist of 31 frames at a frame rate of 5 fps. The labeled liposomes are injected after frame 1. The videos span a total timeframe of 15 minutes. See DOI: 10.1039/c6nr00711b

Modeling and docking antibody structures with Rosetta

PubMed Central

Weitzner, Brian D.; Jeliazkov, Jeliazko R.; Lyskov, Sergey; Marze, Nicholas; Kuroda, Daisuke; Frick, Rahel; Adolf-Bryfogle, Jared; Biswas, Naireeta; Dunbrack, Roland L.; Gray, Jeffrey J.

2017-01-01

We describe Rosetta-based computational protocols for predicting the three-dimensional structure of an antibody from sequence (RosettaAntibody) and then docking the antibody to protein antigens (SnugDock). Antibody modeling leverages canonical loop conformations to graft large segments from experimentally-determined structures as well as (1) energetic calculations to minimize loops, (2) docking methodology to refine the VL–VH relative orientation, and (3) de novo prediction of the elusive complementarity determining region (CDR) H3 loop. To alleviate model uncertainty, antibody–antigen docking resamples CDR loop conformations and can use multiple models to represent an ensemble of conformations for the antibody, the antigen or both. These protocols can be run fully-automated via the ROSIE web server (http://rosie.rosettacommons.org/) or manually on a computer with user control of individual steps. For best results, the protocol requires roughly 1,000 CPU-hours for antibody modeling and 250 CPU-hours for antibody–antigen docking. Tasks can be completed in under a day by using public supercomputers. PMID:28125104

Docking studies of antidepressants against single crystal structure of tryptophan 2, 3-dioxygenase using Molegro Virtual Docker software.

PubMed

Dawood, Shazia; Zarina, Shamshad; Bano, Samina

2014-09-01

Tryptophan 2, 3-dioxygenase (TDO) a heme containing enzyme found in mammalian liver is responsible for tryptophan (Trp) catabolism. Trp is an essential amino acid that is degraded in to N-formylkynurenine by the action of TDO. The protein ligand interaction plays a significant role in structural based drug designing. The current study illustrates the binding of established antidepressants (ADs) against TDO enzyme using in-silico docking studies. For this purpose, Fluoxetine, Paroxetine, Sertraline, Fluvoxamine, Seproxetine, Citalopram, Moclobamide, Hyperforin and Amoxepine were selected. In-silico docking studies were carried out using Molegro Virtual Docker (MVD) software. Docking results show that all ADs fit well in the active site of TDO moreover Hyperforin and Paroxetine exhibited high docking scores of -152.484k cal/mol and -139.706k cal/mol, respectively. It is concluded that Hyperforin and Paroxetine are possible lead molecules because of their high docking scores as compared to other ADs examined. Therefore, these two ADs stand as potent inhibitors of TDO enzyme.

Application of molecular docking for the degradation of organic pollutants in the environmental remediation: A review.

PubMed

Liu, Zhifeng; Liu, Yujie; Zeng, Guangming; Shao, Binbin; Chen, Ming; Li, Zhigang; Jiang, Yilin; Liu, Yang; Zhang, Yu; Zhong, Hua

2018-07-01

The molecular docking has been employed successfully to study the mechanism of biodegradation in the environmental remediation in the past few years, although medical science and biology are the main application areas for it. Molecular docking is a very convenient and low cost method to understand the reaction mechanism of proteins or enzymes with ligands with a high accuracy. This paper mainly provides a review for the application of molecular docking between organic pollutants and enzymes. It summarizes the fundamental knowledge of molecular docking, such as its theory, available softwares and main databases. Moreover, five types of pollutants, including phenols, BTEX (benzene, toluene, ethylbenzene, and xylenes), nitrile, polycyclic aromatic hydrocarbons (PAHs), and high polymer (e.g., lignin and cellulose), are discussed from molecular level. Different removal mechanisms are also explained in detail via docking technology. Even though this method shows promising application in the research of biodegradation, further studies are still needed to relate with actual condition. Copyright © 2018 Elsevier Ltd. All rights reserved.

Characterization of domain-specific interaction of synthesized dye with serum proteins by spectroscopic and docking approaches along with determination of in vitro cytotoxicity and antiviral activity.

PubMed

Rudra, Suparna; Dasmandal, Somnath; Patra, Chiranjit; Patel, Biman Kumar; Paul, Suvendu; Mahapatra, Ambikesh

2017-11-20

The interaction between a synthesized dye with proteins, bovine, and human serum albumin (BSA, HSA, respectively) under physiological conditions has been characterized in detail, by means of steady-state and time-resolved fluorescence, UV-vis absorption, and circular dichroism (CD) techniques. An extensive time-resolved fluorescence spectroscopic characterization of the quenching process has been undertaken in conjugation with temperature-dependent fluorescence quenching studies to divulge the actual quenching mechanism. From the thermodynamic observations, it is clear that the binding process is a spontaneous molecular interaction, in which van der Waals and hydrogen bonding interactions play the major roles. The UV-vis absorption and CD results confirm that the dye can induce conformational and micro-environmental changes of both the proteins. In addition, the dye binding provokes the functionality of the native proteins in terms of esterase-like activity. The average binding distance (r) between proteins and dye has been calculated using FRET. Cytotoxicity and antiviral effects of the dye have been found using Vero cell and HSV-1F virus by performing MTT assay. The AutoDock-based docking simulation reveals the probable binding location of dye within the sub-domain IIA of HSA and IB of BSA.

Ensemble docking to difficult targets in early-stage drug discovery: Methodology and application to fibroblast growth factor 23.

PubMed

Velazquez, Hector A; Riccardi, Demian; Xiao, Zhousheng; Quarles, Leigh Darryl; Yates, Charless Ryan; Baudry, Jerome; Smith, Jeremy C

2018-02-01

Ensemble docking is now commonly used in early-stage in silico drug discovery and can be used to attack difficult problems such as finding lead compounds which can disrupt protein-protein interactions. We give an example of this methodology here, as applied to fibroblast growth factor 23 (FGF23), a protein hormone that is responsible for regulating phosphate homeostasis. The first small-molecule antagonists of FGF23 were recently discovered by combining ensemble docking with extensive experimental target validation data (Science Signaling, 9, 2016, ra113). Here, we provide a detailed account of how ensemble-based high-throughput virtual screening was used to identify the antagonist compounds discovered in reference (Science Signaling, 9, 2016, ra113). Moreover, we perform further calculations, redocking those antagonist compounds identified in reference (Science Signaling, 9, 2016, ra113) that performed well on drug-likeness filters, to predict possible binding regions. These predicted binding modes are rescored with the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) approach to calculate the most likely binding site. Our findings suggest that the antagonist compounds antagonize FGF23 through the disruption of protein-protein interactions between FGF23 and fibroblast growth factor receptor (FGFR). © 2017 John Wiley & Sons A/S.

Caffeine and sulfadiazine interact differently with human serum albumin: A combined fluorescence and molecular docking study

NASA Astrophysics Data System (ADS)

Islam, Mullah Muhaiminul; Sonu, Vikash K.; Gashnga, Pynsakhiat Miki; Moyon, N. Shaemningwar; Mitra, Sivaprasad

2016-01-01

The interaction and binding behavior of the well-known drug sulfadiazine (SDZ) and psychoactive stimulant caffeine (CAF) with human serum albumin (HSA) was monitored by in vitro fluorescence titration and molecular docking calculations under physiological condition. The quenching of protein fluorescence on addition of CAF is due to the formation of protein-drug complex in the ground state; whereas in case of SDZ, the experimental results were explained on the basis of sphere of action model. Although both these compounds bind preferentially in Sudlow's site 1 of the protein, the association constant is approximately two fold higher in case of SDZ (∼4.0 × 104 M-1) in comparison with CAF (∼9.3 × 102 M-1) and correlates well with physico-chemical properties like pKa and lipophilicity of the drugs. Temperature dependent fluorescence study reveals that both SDZ and CAF bind spontaneously with HSA. However, the binding of SDZ with the protein is mainly governed by the hydrophobic forces in contrast with that of CAF; where, the interaction is best explained in terms of electrostatic mechanism. Molecular docking calculation predicts the binding of these drugs in different location of sub-domain IIA in the protein structure.

NMR Model of PrgI-SipD Interaction and its Implications in the Needle-Tip Assembly of the Salmonella Type III Secretion System

PubMed Central

Rathinavelan, Thenmalarchelvi; Lara-Tejero, Maria; Lefebre, Matthew; Chatterjee, Srirupa; McShan, Andrew C.; Guo, Da-Chuan; Tang, Chun; Galan, Jorge E.; De Guzman, Roberto N.

2014-01-01

Salmonella and other pathogenic bacteria use the type III secretion system (T3SS) to inject virulence proteins into human cells to initiate infections. The structural component of the T3SS contains a needle and a needle tip. The needle is assembled from PrgI needle protomers and the needle tip is capped with several copies of the SipD tip protein. How a tip protein docks on the needle is unclear. A crystal structure of a PrgI-SipD fusion protein docked on the PrgI needle results in steric clash of SipD at the needle tip when modeled on the recent atomic structure of the needle. Thus, there is currently no good model of how SipD is docked on the PrgI needle tip. Previously, we showed by NMR paramagnetic relaxation enhancement (PRE) methods that a specific region in the SipD coiled-coil is the binding site for PrgI. Others have hypothesized that a domain of the tip protein – the N-terminal α-helical hairpin, has to swing away during the assembly of the needle apparatus. Here, we show by PRE methods that a truncated form of SipD lacking the α-helical hairpin domain binds more tightly to PrgI. Further, PRE-based structure calculations revealed multiple PrgI binding sites on the SipD coiled-coil. Our PRE results together with the recent NMR-derived atomic structure of the Salmonella needle suggest a possible model of how SipD might dock at the PrgI needle tip. SipD and PrgI are conserved in other bacterial T3SSs, thus our results have wider implication in understanding other needle-tip complexes. PMID:24951833

Molecular modeling, dynamics studies and density functional theory approaches to identify potential inhibitors of SIRT4 protein from Homo sapiens : a novel target for the treatment of type 2 diabetes.

PubMed

Choubey, Sanjay K; Prabhu, Dhamodharan; Nachiappan, Mutharasappan; Biswal, Jayshree; Jeyakanthan, Jeyaraman

2017-11-01

Type 2 diabetes is one of the biggest health challenges in the world and WHO projects it to be the 7th leading cause of death in 2030. It is a chronic condition affecting the way our body metabolizes sugar. Insulin resistance is high risk factor marked by expression of Lipoprotein Lipases and Peroxisome Proliferator-Activated Receptor that predisposes to type 2 diabetes. AMP-dependent protein kinase in AMPK signaling pathway is a central sensor of energy status. Deregulation of AMPK signaling leads to inflammation, oxidative stress, and deactivation of autophagy which are implicated in pathogenesis of insulin resistance. SIRT4 protein deactivates AMPK as well as directly inhibits insulin secretion. SIRT4 overexpression leads to dyslipidimeia, decreased fatty acid oxidation, and lipogenesis which are the characteristic features of insulin resistance promoting type 2 diabetes. This makes SIRT4 a novel therapeutic target to control type 2 diabetes. Virtual screening and molecular docking studies were performed to obtain potential ligands. To further optimize the geometry of protein-ligand complexes Quantum Polarized Ligand Docking was performed. Binding Free Energy was calculated for the top three ligand molecules. In view of exploring the stereoelectronic features of the ligand, density functional theory approach was implemented at B3LYP/6-31G* level. 30 ns MD simulation studies of the protein-ligand complexes were done. The present research work proposes ZINC12421989 as potential inhibitor of SIRT4 with docking score (-7.54 kcal/mol), docking energy (-51.34 kcal/mol), binding free energy (-70.21 kcal/mol), and comparatively low energy gap (-0.1786 eV) for HOMO and LUMO indicating reactivity of the lead molecule.

Interaction of the minocycline with extracelluar protein and intracellular protein by multi-spectral techniques and molecular docking

NASA Astrophysics Data System (ADS)

Fang, Qing; Wang, Yirun; Hu, Taoying; Liu, Ying

2017-02-01

The interaction of minocyeline (MNC) with extracelluar protein (lysozyme, LYSO) or intracellular protein (bovine hemoglobin, BHb) was investigated using multi-spectral techniques and molecular docking in vitro. Fluorescence studies suggested that MNC quenched LYSO/BHb fluorescence in a static mode with binding constants of 2.01 and 0.26 × 104 L•mol-1 at 298 K, respectively. The LYZO-MNC system was more easily influenced by temperature (298 and 310 K) than the BHb-MNC system. The thermodynamic parameters demonstrated that hydrogen bonds and van der Waals forces played the major role in the binding process. Based on the Förster theory of nonradiative energy transfer, the binding distances between MNC and the inner tryptophan residues of LYSO and BHb were calculated to be 4.34 and 3.49 nm, respectively. Furthermore, circular dichroism spectra (CD), Fourier transforms infrared (FTIR), UV-vis, and three-dimensional fluorescence spectra results indicated the secondary structures of LYSO and BHb were partially destroyed by MNC with the α-helix percentage of LYZO-MNC increased (17.8-28.6%) while that of BHb-MNC was decreased (41.6-39.6%). UV-vis spectral results showed these binding interactions could cause conformational and some micro-environmental changes of LYSO and BHb. In accordance with the results of molecular docking, In LYZO-MNC system, MNC was mainly bound in the active site hinge region where Trp-62 and Trp-63 are located, and in MNC-BHb system, MNC was close to the subunit α 1 of BHb, molecular docking analysis supported the thermodynamic results well. The work contributes to clarify the mechanism of MNC with two proteins at molecular level.

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

PubMed

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

Single-Molecule Imaging Reveals the Activation Dynamics of Intracellular Protein Smad3 on Cell Membrane

NASA Astrophysics Data System (ADS)

Li, Nan; Yang, Yong; He, Kangmin; Zhang, Fayun; Zhao, Libo; Zhou, Wei; Yuan, Jinghe; Liang, Wei; Fang, Xiaohong

2016-09-01

Smad3 is an intracellular protein that plays a key role in propagating transforming growth factor β (TGF-β) signals from cell membrane to nucleus. However whether the transient process of Smad3 activation occurs on cell membrane and how it is regulated remains elusive. Using advanced live-cell single-molecule fluorescence microscopy to image and track fluorescent protein-labeled Smad3, we observed and quantified, for the first time, the dynamics of individual Smad3 molecules docking to and activation on the cell membrane. It was found that Smad3 docked to cell membrane in both unstimulated and stimulated cells, but with different diffusion rates and dissociation kinetics. The change in its membrane docking dynamics can be used to study the activation of Smad3. Our results reveal that Smad3 binds with type I TGF-β receptor (TRI) even in unstimulated cells. Its activation is regulated by TRI phosphorylation but independent of receptor endocytosis. This study offers new information on TGF-β/Smad signaling, as well as a new approach to investigate the activation of intracellular signaling proteins for a better understanding of their functions in signal transduction.

Protein–Protein Interactions Modulate the Docking-Dependent E3-Ubiquitin Ligase Activity of Carboxy-Terminus of Hsc70-Interacting Protein (CHIP)*

PubMed Central

Narayan, Vikram; Landré, Vivien; Ning, Jia; Hernychova, Lenka; Muller, Petr; Verma, Chandra; Walkinshaw, Malcolm D.; Blackburn, Elizabeth A.; Ball, Kathryn L.

2015-01-01

CHIP is a tetratricopeptide repeat (TPR) domain protein that functions as an E3-ubiquitin ligase. As well as linking the molecular chaperones to the ubiquitin proteasome system, CHIP also has a docking-dependent mode where it ubiquitinates native substrates, thereby regulating their steady state levels and/or function. Here we explore the effect of Hsp70 on the docking-dependent E3-ligase activity of CHIP. The TPR-domain is revealed as a binding site for allosteric modulators involved in determining CHIP's dynamic conformation and activity. Biochemical, biophysical and modeling evidence demonstrate that Hsp70-binding to the TPR, or Hsp70-mimetic mutations, regulate CHIP-mediated ubiquitination of p53 and IRF-1 through effects on U-box activity and substrate binding. HDX-MS was used to establish that conformational-inhibition-signals extended from the TPR-domain to the U-box. This underscores inter-domain allosteric regulation of CHIP by the core molecular chaperones. Defining the chaperone-associated TPR-domain of CHIP as a manager of inter-domain communication highlights the potential for scaffolding modules to regulate, as well as assemble, complexes that are fundamental to protein homeostatic control. PMID:26330542

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

PubMed Central

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components. PMID:29692857

Liprin-α3 controls vesicle docking and exocytosis at the active zone of hippocampal synapses.

PubMed

Wong, Man Yan; Liu, Changliang; Wang, Shan Shan H; Roquas, Aram C F; Fowler, Stephen C; Kaeser, Pascal S

2018-02-27

The presynaptic active zone provides sites for vesicle docking and release at central nervous synapses and is essential for speed and accuracy of synaptic transmission. Liprin-α binds to several active zone proteins, and loss-of-function studies in invertebrates established important roles for Liprin-α in neurodevelopment and active zone assembly. However, Liprin-α localization and functions in vertebrates have remained unclear. We used stimulated emission depletion superresolution microscopy to systematically determine the localization of Liprin-α2 and Liprin-α3, the two predominant Liprin-α proteins in the vertebrate brain, relative to other active-zone proteins. Both proteins were widely distributed in hippocampal nerve terminals, and Liprin-α3, but not Liprin-α2, had a prominent component that colocalized with the active-zone proteins Bassoon, RIM, Munc13, RIM-BP, and ELKS. To assess Liprin-α3 functions, we generated Liprin-α3-KO mice by using CRISPR/Cas9 gene editing. We found reduced synaptic vesicle tethering and docking in hippocampal neurons of Liprin-α3-KO mice, and synaptic vesicle exocytosis was impaired. Liprin-α3 KO also led to mild alterations in active zone structure, accompanied by translocation of Liprin-α2 to active zones. These findings establish important roles for Liprin-α3 in active-zone assembly and function, and suggest that interplay between various Liprin-α proteins controls their active-zone localization.

Elucidating the interaction of clofazimine with bovine liver catalase; a comprehensive spectroscopic and molecular docking approach.

PubMed

Zaman, Masihuz; Nusrat, Saima; Zakariya, Syed Mohammad; Khan, Mohsin Vahid; Ajmal, Mohammad Rehan; Khan, Rizwan Hasan

2017-08-01

Nowadays, understanding of interface between protein and drugs has become an active research area of interest. These types of interactions provide structural guidelines in drug design with greater clinical efficacy. Thus, structural changes in catalase induced by clofazimine were monitored by various biophysical techniques including UV-visible spectrometer, fluorescence spectroscopy, circular dichroism, and dynamic light scattering techniques. Increase in absorption spectra (UV-visible spectrum) confers the complex formation between drug and protein. Fluorescence quenching with a binding constants of 2.47 × 10 4  M -1 revealed that clofazimine binds with protein. Using fluorescence resonance energy transfer, the distance (r) between the protein (donor) and drug (acceptor) was found to be 2.89 nm. Negative Gibbs free energy change (ΔG°) revealed that binding process is spontaneous. In addition, an increase in α-helicity was observed by far-UV circular dichroism spectra by adding clofazimine to protein. Dynamic light scattering results indicate that topology of bovine liver catalase was slightly altered in the presence of clofazimine. Hydrophobic interactions are the main forces between clofazimine and catalase interaction as depicted by molecular docking studies. Apart from hydrophobic interactions, some hydrogen bonding was also observed during docking method. The results obtained from the present study may establish abundant in optimizing the properties of ligand-protein mixtures relevant for numerous formulations. Copyright © 2017 John Wiley & Sons, Ltd.

Impact of S100A8 expression on kidney cancer progression and molecular docking studies for kidney cancer therapeutics.

PubMed

Mirza, Zeenat; Schulten, Hans-Juergen; Farsi, Hasan Ma; Al-Maghrabi, Jaudah A; Gari, Mamdooh A; Chaudhary, Adeel Ga; Abuzenadah, Adel M; Al-Qahtani, Mohammed H; Karim, Sajjad

2014-04-01

The proinflammatory protein S100A8, which is expressed in myeloid cells under physiological conditions, is strongly expressed in human cancer tissues. Its role in tumor cell differentiation and tumor progression is largely unclear and virtually unstudied in kidney cancer. In the present study, we investigated whether S100A8 could be a potential anticancer drug target and therapeutic biomarker for kidney cancer, and the underlying molecular mechanisms by exploiting its interaction profile with drugs. Microarray-based transcriptomics experiments using Affymetrix HuGene 1.0 ST arrays were applied to renal cell carcinoma specimens from Saudi patients for identification of significant genes associated with kidney cancer. In addition, we retrieved selected expression data from the National Center for Biotechnology Information Gene Expression Omnibus database for comparative analysis and confirmation of S100A8 expression. Ingenuity Pathway Analysis (IPA) was used to elucidate significant molecular networks and pathways associated with kidney cancer. The probable polar and non-polar interactions of possible S100A8 inhibitors (aspirin, celecoxib, dexamethasone and diclofenac) were examined by performing molecular docking and binding free energy calculations. Detailed analysis of bound structures and their binding free energies was carried out for S100A8, its known partner (S100A9), and S100A8-S100A9 complex (calprotectin). In our microarray experiments, we identified 1,335 significantly differentially expressed genes, including S100A8, in kidney cancer using a cut-off of p<0.05 and fold-change of 2. Functional analysis of kidney cancer-associated genes showed overexpression of genes involved in cell-cycle progression, DNA repair, cell death, tumor morphology and tissue development. Pathway analysis showed significant disruption of pathways of atherosclerosis signaling, liver X receptor/retinoid X receptor (LXR/RXR) activation, notch signaling, and interleukin-12 (IL-12) signaling. We identified S100A8 as a prospective biomarker for kidney cancer and in silico analysis showed that aspirin, celecoxib, dexamethasone and diclofenac binds to S100A8 and may inhibit downstream signaling in kidney cancer. The present study provides an initial overview of differentially expressed genes in kidney cancer of Saudi Arabian patients using whole-transcript, high-density expression arrays. Our analysis suggests distinct transcriptomic signatures, with significantly high levels of S100A8, and underlying molecular mechanisms contributing to kidney cancer progression. Our docking-based findings shed insight into S100A8 protein as an attractive anticancer target for therapeutic intervention in kidney cancer. To our knowledge, this is the first structure-based docking study for the selected protein targets using the chosen ligands.

Specific interactions between mycobacterial FtsZ protein and curcumin derivatives: Molecular docking and ab initio molecular simulations

NASA Astrophysics Data System (ADS)

Fujimori, Mitsuki; Sogawa, Haruki; Ota, Shintaro; Karpov, Pavel; Shulga, Sergey; Blume, Yaroslav; Kurita, Noriyuki

2018-01-01

Filamentous temperature-sensitive Z (FtsZ) protein plays essential role in bacteria cell division, and its inhibition prevents Mycobacteria reproduction. Here we adopted curcumin derivatives as candidates of novel inhibitors and investigated their specific interactions with FtsZ, using ab initio molecular simulations based on protein-ligand docking, classical molecular mechanics and ab initio fragment molecular orbital (FMO) calculations. Based on FMO calculations, we specified the most preferable site of curcumin binding to FtsZ and highlighted the key amino acid residues for curcumin binding at an electronic level. The result will be useful for proposing novel inhibitors against FtsZ based on curcumin derivatives.

Protein Models Docking Benchmark 2

PubMed Central

Anishchenko, Ivan; Kundrotas, Petras J.; Tuzikov, Alexander V.; Vakser, Ilya A.

2015-01-01

Structural characterization of protein-protein interactions is essential for our ability to understand life processes. However, only a fraction of known proteins have experimentally determined structures. Such structures provide templates for modeling of a large part of the proteome, where individual proteins can be docked by template-free or template-based techniques. Still, the sensitivity of the docking methods to the inherent inaccuracies of protein models, as opposed to the experimentally determined high-resolution structures, remains largely untested, primarily due to the absence of appropriate benchmark set(s). Structures in such a set should have pre-defined inaccuracy levels and, at the same time, resemble actual protein models in terms of structural motifs/packing. The set should also be large enough to ensure statistical reliability of the benchmarking results. We present a major update of the previously developed benchmark set of protein models. For each interactor, six models were generated with the model-to-native Cα RMSD in the 1 to 6 Å range. The models in the set were generated by a new approach, which corresponds to the actual modeling of new protein structures in the “real case scenario,” as opposed to the previous set, where a significant number of structures were model-like only. In addition, the larger number of complexes (165 vs. 63 in the previous set) increases the statistical reliability of the benchmarking. We estimated the highest accuracy of the predicted complexes (according to CAPRI criteria), which can be attained using the benchmark structures. The set is available at http://dockground.bioinformatics.ku.edu. PMID:25712716

Application of binding free energy calculations to prediction of binding modes and affinities of MDM2 and MDMX inhibitors.

PubMed

Lee, Hui Sun; Jo, Sunhwan; Lim, Hyun-Suk; Im, Wonpil

2012-07-23

Molecular docking is widely used to obtain binding modes and binding affinities of a molecule to a given target protein. Despite considerable efforts, however, prediction of both properties by docking remains challenging mainly due to protein's structural flexibility and inaccuracy of scoring functions. Here, an integrated approach has been developed to improve the accuracy of binding mode and affinity prediction and tested for small molecule MDM2 and MDMX antagonists. In this approach, initial candidate models selected from docking are subjected to equilibration MD simulations to further filter the models. Free energy perturbation molecular dynamics (FEP/MD) simulations are then applied to the filtered ligand models to enhance the ability in predicting the near-native ligand conformation. The calculated binding free energies for MDM2 complexes are overestimated compared to experimental measurements mainly due to the difficulties in sampling highly flexible apo-MDM2. Nonetheless, the FEP/MD binding free energy calculations are more promising for discriminating binders from nonbinders than docking scores. In particular, the comparison between the MDM2 and MDMX results suggests that apo-MDMX has lower flexibility than apo-MDM2. In addition, the FEP/MD calculations provide detailed information on the different energetic contributions to ligand binding, leading to a better understanding of the sensitivity and specificity of protein-ligand interactions.

JADOPPT: java based AutoDock preparing and processing tool.

PubMed

García-Pérez, Carlos; Peláez, Rafael; Therón, Roberto; Luis López-Pérez, José

2017-02-15

AutoDock is a very popular software package for docking and virtual screening. However, currently it is hard work to visualize more than one result from the virtual screening at a time. To overcome this limitation we have designed JADOPPT, a tool for automatically preparing and processing multiple ligand-protein docked poses obtained from AutoDock. It allows the simultaneous visual assessment and comparison of multiple poses through clustering methods. Moreover, it permits the representation of reference ligands with known binding modes, binding site residues, highly scoring regions for the ligand, and the calculated binding energy of the best ranked results. JADOPPT, supplementary material (Case Studies 1 and 2) and video tutorials are available at http://visualanalytics.land/cgarcia/JADOPPT.html. carlosgarcia@usal.es or pelaez@usal.es. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

FPGA acceleration of rigid-molecule docking codes

PubMed Central

Sukhwani, B.; Herbordt, M.C.

2011-01-01

Modelling the interactions of biological molecules, or docking, is critical both to understanding basic life processes and to designing new drugs. The field programmable gate array (FPGA) based acceleration of a recently developed, complex, production docking code is described. The authors found that it is necessary to extend their previous three-dimensional (3D) correlation structure in several ways, most significantly to support simultaneous computation of several correlation functions. The result for small-molecule docking is a 100-fold speed-up of a section of the code that represents over 95% of the original run-time. An additional 2% is accelerated through a previously described method, yielding a total acceleration of 36× over a single core and 10× over a quad-core. This approach is found to be an ideal complement to graphics processing unit (GPU) based docking, which excels in the protein–protein domain. PMID:21857870

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

PubMed

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

2017-12-09

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

Dissecting Nck/Dock signaling pathways in Drosophila visual system.

PubMed

Rao, Yong

2005-01-01

The establishment of neuronal connections during embryonic development requires the precise guidance and targeting of the neuronal growth cone, an expanded cellular structure at the leading tip of a growing axon. The growth cone contains sophisticated signaling systems that allow the rapid communication between guidance receptors and the actin cytoskeleton in generating directed motility. Previous studies demonstrated a specific role for the Nck/Dock SH2/SH3 adapter protein in photoreceptor (R cell) axon guidance and target recognition in the Drosophila visual system, suggesting strongly that Nck/Dock is one of the long-sought missing links between cell surface receptors and the actin cytoskeleton. In this review, I discuss the recent progress on dissecting the Nck/Dock signaling pathways in R-cell growth cones. These studies have identified additional key components of the Nck/Dock signaling pathways for linking the receptor signaling to the remodeling of the actin cytoskeleton in controlling growth-cone motility.

Dissecting Nck/Dock Signaling Pathways in Drosophila Visual System

PubMed Central

2005-01-01

The establishment of neuronal connections during embryonic development requires the precise guidance and targeting of the neuronal growth cone, an expanded cellular structure at the leading tip of a growing axon. The growth cone contains sophisticated signaling systems that allow the rapid communication between guidance receptors and the actin cytoskeleton in generating directed motility. Previous studies demonstrated a specific role for the Nck/Dock SH2/SH3 adapter protein in photoreceptor (R cell) axon guidance and target recognition in the Drosophila visual system, suggesting strongly that Nck/Dock is one of the long-sought missing links between cell surface receptors and the actin cytoskeleton. In this review, I discuss the recent progress on dissecting the Nck/Dock signaling pathways in R-cell growth cones. These studies have identified additional key components of the Nck/Dock signaling pathways for linking the receptor signaling to the remodeling of the actin cytoskeleton in controlling growth-cone motility. PMID:15951852

Virtual Screening with AutoDock: Theory and Practice

PubMed Central

Cosconati, Sandro; Forli, Stefano; Perryman, Alex L.; Harris, Rodney; Goodsell, David S.; Olson, Arthur J.

2011-01-01

Importance to the field Virtual screening is a computer-based technique for identifying promising compounds to bind to a target molecule of known structure. Given the rapidly increasing number of protein and nucleic acid structures, virtual screening continues to grow as an effective method for the discovery of new inhibitors and drug molecules. Areas covered in this review We describe virtual screening methods that are available in the AutoDock suite of programs, and several of our successes in using AutoDock virtual screening in pharmaceutical lead discovery. What the reader will gain A general overview of the challenges of virtual screening is presented, along with the tools available in the AutoDock suite of programs for addressing these challenges. Take home message Virtual screening is an effective tool for the discovery of compounds for use as leads in drug discovery, and the free, open source program AutoDock is an effective tool for virtual screening. PMID:21532931

RNA-Seq and molecular docking reveal multi-level pesticide resistance in the bed bug

PubMed Central

2012-01-01

Background Bed bugs (Cimex lectularius) are hematophagous nocturnal parasites of humans that have attained high impact status due to their worldwide resurgence. The sudden and rampant resurgence of C. lectularius has been attributed to numerous factors including frequent international travel, narrower pest management practices, and insecticide resistance. Results We performed a next-generation RNA sequencing (RNA-Seq) experiment to find differentially expressed genes between pesticide-resistant (PR) and pesticide-susceptible (PS) strains of C. lectularius. A reference transcriptome database of 51,492 expressed sequence tags (ESTs) was created by combining the databases derived from de novo assembled mRNA-Seq tags (30,404 ESTs) and our previous 454 pyrosequenced database (21,088 ESTs). The two-way GLMseq analysis revealed ~15,000 highly significant differentially expressed ESTs between the PR and PS strains. Among the top 5,000 differentially expressed ESTs, 109 putative defense genes (cuticular proteins, cytochrome P450s, antioxidant genes, ABC transporters, glutathione S-transferases, carboxylesterases and acetyl cholinesterase) involved in penetration resistance and metabolic resistance were identified. Tissue and development-specific expression of P450 CYP3 clan members showed high mRNA levels in the cuticle, Malpighian tubules, and midgut; and in early instar nymphs, respectively. Lastly, molecular modeling and docking of a candidate cytochrome P450 (CYP397A1V2) revealed the flexibility of the deduced protein to metabolize a broad range of insecticide substrates including DDT, deltamethrin, permethrin, and imidacloprid. Conclusions We developed significant molecular resources for C. lectularius putatively involved in metabolic resistance as well as those participating in other modes of insecticide resistance. RNA-Seq profiles of PR strains combined with tissue-specific profiles and molecular docking revealed multi-level insecticide resistance in C. lectularius. Future research that is targeted towards RNA interference (RNAi) on the identified metabolic targets such as cytochrome P450s and cuticular proteins could lay the foundation for a better understanding of the genetic basis of insecticide resistance in C. lectularius. PMID:22226239

Interaction between phillygenin and human serum albumin based on spectroscopic and molecular docking

NASA Astrophysics Data System (ADS)

Song, W.; Ao, M. Z.; Shi, Y.; Yuan, L. F.; Yuan, X. X.; Yu, L. J.

2012-01-01

In this paper, the interaction of human serum albumin (HSA) with phillygenin was investigated by fluorescence, circular dichroism (CD), UV-vis spectroscopic and molecular docking methods under physiological conditions. The Stern-Volmer analysis indicated that the fluorescence quenching of HSA by phillygenin resulted from static mechanism, and the binding constants were 1.71 × 10 5, 1.61 × 10 5 and 1.47 × 10 4 at 300, 305 and 310 K, respectively. The results of UV-vis spectra show that the secondary structure of the protein has been changed in the presence of phillygenin. The CD spectra showed that HSA conformation was altered by phillygenin with a major reduction of α-helix and an increase in β-sheet and random coil structures, indicating a partial protein unfolding. The distance between donor (HSA) and acceptor (phillygenin) was calculated to be 3.52 nm and the results of synchronous fluorescence spectra showed that binding of phillygenin to HSA can induce conformational changes in HSA. Molecular docking experiments found that phillygenin binds with HSA at IIIA domain of hydrophobic pocket with hydrogen bond interactions. The ionic bonds were formed with the O (4), O (5) and O (6) of phillygenin with nitrogen of ASN109, ARG186 and LEU115, respectively. The hydrogen bonds are formed between O (2) of phillygenin and SER419. In the presence of copper (II), iron (III) and alcohol, the apparent association constant KA and the number of binding sites of phillygenin on HSA were both decreased in the range of 88.84-91.97% and 16.09-18.85%, respectively. In view of the evidence presented, it is expected to enrich our knowledge of the interaction dynamics of phillygenin to the important plasma protein HSA, and it is also expected to provide important information of designs of new inspired drugs.

Watching proteins function with 150-ps time-resolved X-ray crystallography

NASA Astrophysics Data System (ADS)

Anfinrud, Philip

2007-03-01

We have used time-resolved Laue crystallography to characterize ligand migration pathways and dynamics in wild-type and several mutant forms of myoglobin (Mb), a ligand-binding heme protein found in muscle tissue. In these pump-probe experiments, which were conducted on the ID09B time-resolved beamline at the European Synchrotron and Radiation Facility, a laser pulse photodissociates CO from an MbCO crystal and a suitably delayed X-ray pulse probes its structure via Laue diffraction. Single-site mutations in the vicinity of the heme pocket docking site were found to have a dramatic effect on ligand migration. To visualize this process, time-resolved electron density maps were stitched together into movies that unveil with <2-å spatial resolution and 150-ps time-resolution the correlated protein motions that accompany and/or mediate ligand migration. These studies help to illustrate at an atomic level relationships between protein structure, dynamics, and function.

Analysis of Species-Selectivity of Human, Mouse and Rat Cytochrome P450 1A and 2B Subfamily Enzymes using Molecular Modeling, Docking and Dynamics Simulations.

PubMed

Karthikeyan, Bagavathy Shanmugam; Suvaithenamudhan, Suvaiyarasan; Akbarsha, Mohammad Abdulkader; Parthasarathy, Subbiah

2018-06-01

Cytochrome P450 (CYP) 1A and 2B subfamily enzymes are important drug metabolizing enzymes, and are highly conserved across species in terms of sequence homology. However, there are major to minor structural and macromolecular differences which provide for species-selectivity and substrate-selectivity. Therefore, species-selectivity of CYP1A and CYP2B subfamily proteins across human, mouse and rat was analyzed using molecular modeling, docking and dynamics simulations when the chiral molecules quinine and quinidine were used as ligands. The three-dimensional structures of 17 proteins belonging to CYP1A and CYP2B subfamilies of mouse and rat were predicted by adopting homology modeling using the available structures of human CYP1A and CYP2B proteins as templates. Molecular docking and dynamics simulations of quinine and quinidine with CYP1A subfamily proteins revealed the existence of species-selectivity across the three species. On the other hand, in the case of CYP2B subfamily proteins, no role for chirality of quinine and quinidine in forming complexes with CYP2B subfamily proteins of the three species was indicated. Our findings reveal the roles of active site amino acid residues of CYP1A and CYP2B subfamily proteins and provide insights into species-selectivity of these enzymes across human, mouse, and rat.

Assessing the performance of MM/PBSA and MM/GBSA methods. 8. Predicting binding free energies and poses of protein-RNA complexes.

PubMed

Chen, Fu; Sun, Huiyong; Wang, Junmei; Zhu, Feng; Liu, Hui; Wang, Zhe; Lei, Tailong; Li, Youyong; Hou, Tingjun

2018-06-21

Molecular docking provides a computationally efficient way to predict the atomic structural details of protein-RNA interactions (PRI), but accurate prediction of the three-dimensional structures and binding affinities for PRI is still notoriously difficult, partly due to the unreliability of the existing scoring functions for PRI. MM/PBSA and MM/GBSA are more theoretically rigorous than most scoring functions for protein-RNA docking, but their prediction performance for protein-RNA systems remains unclear. Here, we systemically evaluated the capability of MM/PBSA and MM/GBSA to predict the binding affinities and recognize the near-native binding structures for protein-RNA systems with different solvent models and interior dielectric constants (ϵ in ). For predicting the binding affinities, the predictions given by MM/GBSA based on the minimized structures in explicit solvent and the GBGBn1 model with ϵ in = 2 yielded the highest correlation with the experimental data. Moreover, the MM/GBSA calculations based on the minimized structures in implicit solvent and the GBGBn1 model distinguished the near-native binding structures within the top 10 decoys for 118 out of the 149 protein-RNA systems (79.2%). This performance is better than all docking scoring functions studied here. Therefore, the MM/GBSA rescoring is an efficient way to improve the prediction capability of scoring functions for protein-RNA systems. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Molecular docking and simulation studies of 3-(1-chloropiperidin-4-yl)-6-fluoro benzisoxazole 2 against VP26 and VP28 proteins of white spot syndrome virus.

PubMed

Sudharsana, S; Rajashekar Reddy, C B; Dinesh, S; Rajasekhara Reddy, S; Mohanapriya, A; Itami, T; Sudhakaran, R

2016-10-01

White spot syndrome virus (WSSV), an aquatic virus infecting shrimps and other crustaceans, is widely distributed in Asian subcontinents including India. The infection has led to a serious economic loss in shrimp farming. The WSSV genome is approximately 300 kb and codes for several proteins mediating the infection. The envelope proteins VP26 and VP28 play a major role in infection process and also in the interaction with the host cells. A comprehensive study on the viral proteins leading to the development of safe and potent antiviral therapeutic is of adverse need. The novel synthesized compound 3-(1-chloropiperidin-4-yl)-6-fluoro benzisoxazole 2 is proved to have potent antiviral activity against WSSV. The compound antiviral activity is validated in freshwater crabs (Paratelphusa hydrodomous). An in silico molecular docking and simulation analysis of the envelope proteins VP26 and VP28 with the ligand 3-(1-chloropiperidin-4-yl)-6-fluoro benzisoxazole 2 are carried out. The docking analysis reveals that the polar amino acids in the pore region of the envelope proteins were involved in the ligand binding. The influence of the ligand binding on the proteins is validated by the molecular dynamics and simulation study. These in silico approaches together demonstrate the ligand's efficiency in preventing the trimers from exhibiting their physiological function. © 2016 John Wiley & Sons Ltd.

Theoretical modeling of multiprotein complexes by iSPOT: Integration of small-angle X-ray scattering, hydroxyl radical footprinting, and computational docking.

PubMed

Huang, Wei; Ravikumar, Krishnakumar M; Parisien, Marc; Yang, Sichun

2016-12-01

Structural determination of protein-protein complexes such as multidomain nuclear receptors has been challenging for high-resolution structural techniques. Here, we present a combined use of multiple biophysical methods, termed iSPOT, an integration of shape information from small-angle X-ray scattering (SAXS), protection factors probed by hydroxyl radical footprinting, and a large series of computationally docked conformations from rigid-body or molecular dynamics (MD) simulations. Specifically tested on two model systems, the power of iSPOT is demonstrated to accurately predict the structures of a large protein-protein complex (TGFβ-FKBP12) and a multidomain nuclear receptor homodimer (HNF-4α), based on the structures of individual components of the complexes. Although neither SAXS nor footprinting alone can yield an unambiguous picture for each complex, the combination of both, seamlessly integrated in iSPOT, narrows down the best-fit structures that are about 3.2Å and 4.2Å in RMSD from their corresponding crystal structures, respectively. Furthermore, this proof-of-principle study based on the data synthetically derived from available crystal structures shows that the iSPOT-using either rigid-body or MD-based flexible docking-is capable of overcoming the shortcomings of standalone computational methods, especially for HNF-4α. By taking advantage of the integration of SAXS-based shape information and footprinting-based protection/accessibility as well as computational docking, this iSPOT platform is set to be a powerful approach towards accurate integrated modeling of many challenging multiprotein complexes. Copyright © 2016 Elsevier Inc. All rights reserved.

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

NASA Astrophysics Data System (ADS)

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations.

PubMed

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

PubMed Central

De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944

PtdIns(4,5)P2 is not required for secretory granule docking.

PubMed

Omar-Hmeadi, Muhmmad; Gandasi, Nikhil R; Barg, Sebastian

2018-06-01

Phosphoinositides (PtdIns) play important roles in exocytosis and are thought to regulate secretory granule docking by co-clustering with the SNARE protein syntaxin to form a docking receptor in the plasma membrane. Here we tested this idea by high-resolution total internal reflection imaging of EGFP-labeled PtdIns markers or syntaxin-1 at secretory granule release sites in live insulin-secreting cells. In intact cells, PtdIns markers distributed evenly across the plasma membrane with no preference for granule docking sites. In contrast, syntaxin-1 was found clustered in the plasma membrane, mostly beneath docked granules. We also observed rapid accumulation of syntaxin-1 at sites where granules arrived to dock. Acute depletion of plasma membrane phosphatidylinositol (4,5) bisphosphate (PtdIns(4,5)P 2 ) by recruitment of a 5'-phosphatase strongly inhibited Ca 2+ -dependent exocytosis, but had no effect on docked granules or the distribution and clustering of syntaxin-1. Cell permeabilization by α-toxin or formaldehyde-fixation caused PtdIns marker to slowly cluster, in part near docked granules. In summary, our data indicate that PtdIns(4,5)P 2 accelerates granule priming, but challenge a role of PtdIns in secretory granule docking or clustering of syntaxin-1 at the release site. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Steric-inhibition model for regulation of nucleotide exchange via the Dock180 family of GEFs.

PubMed

Lu, Mingjian; Kinchen, Jason M; Rossman, Kent L; Grimsley, Cynthia; Hall, Matthew; Sondek, John; Hengartner, Michael O; Yajnik, Vijay; Ravichandran, Kodi S

2005-02-22

CDM (CED-5, Dock180, Myoblast city) family members have been recently identified as novel, evolutionarily conserved guanine nucleotide exchange factors (GEFs) for Rho-family GTPases . They regulate multiple processes, including embryonic development, cell migration, apoptotic-cell engulfment, tumor invasion, and HIV-1 infection, in diverse model systems . However, the mechanism(s) of regulation of CDM proteins has not been well understood. Here, our studies on the prototype member Dock180 reveal a steric-inhibition model for regulating the Dock180 family of GEFs. At basal state, the N-terminal SH3 domain of Dock180 binds to the distant catalytic Docker domain and negatively regulates the function of Dock180. Further studies revealed that the SH3:Docker interaction sterically blocks Rac access to the Docker domain. Interestingly, ELMO binding to the SH3 domain of Dock180 disrupted the SH3:Docker interaction, facilitated Rac access to the Docker domain, and contributed to the GEF activity of the Dock180/ELMO complex. Additional genetic rescue studies in C. elegans suggested that the regulation of the Docker-domain-mediated GEF activity by the SH3 domain and its adjoining region is evolutionarily conserved. This steric-inhibition model may be a general mechanism for regulating multiple SH3-domain-containing Dock180 family members and may have implications for a variety of biological processes.

Uncovering potential anti-neuroinflammatory components of Modified Wuziyanzong Prescription through a target-directed molecular docking fingerprint strategy.

PubMed

Chen, Jinfeng; Wang, Jinlong; Lu, Yingyuan; Zhao, Shaoyang; Yu, Qian; Wang, Xuemei; Tu, Pengfei; Zeng, Kewu; Jiang, Yong

2018-05-01

Neuroinflammation is a main factor in the pathogenesis of neurodegenerative diseases, such as Alzheimer disease. Our previous studies indicated that the modified Wuziyanzong Prescription (MWP) can suppress neuroinflammatory responses via nuclear factor-kappa B (NF-κB) and mitogen-activated protein kinases (MAPKs) signaling pathways. However, the anti-neuroinflammatory components of MWP remain unclear. Herein, a target-directed molecular docking fingerprint (TMDF) strategy, via integrating the chemical profiling and molecular docking approaches, was developed to identify the potential anti-neuroinflammatory components of MWP. First, as many as 120 possible structures, including 49 flavonoids, 28 phenylpropionic acids, 18 amides, 10 carotenoids, eight phenylethanoid glycosides, four lignans, two iridoids, and one triterpenoid were deduced by the source attribution and structural classification-assisted strategy. Then, their geometries were docked against five major targets of the NF-κB and MAPKs signaling cascades, including p38-α, IKKβ, ERK1, ERK2, and TRAF6. The docking results revealed diverse contributions of different components towards the protein targets. Collectively, prenylated flavonoids showed intensive or moderate anti-neuroinflammatory activities, while phenylpropanoids, amides, phenylethanoid glycosides, lignans, and triterpenoids exhibited moderate or weak anti-neuroinflammatory effects. The anti-neuroinflammatory activities of four retrieved prenylated flavonoids were tested by Western blotting assay, and the results mostly agreed with those predicted by the docking method. These gained information demonstrates that the established TMDF strategy could be a rapid and feasible methodology to investigate the potential active components in herbal compound prescriptions. Copyright © 2018 Elsevier B.V. All rights reserved.

In-Silico Analysis of Amotosalen Hydrochloride Binding to CD-61 of Platelets.

PubMed

Chaudhary, Hammad Tufail

2016-11-01

To determine the docking of Amotosalen hydrochloride (AH) at CD-61 of platelets, and to suggest the cause of bleeding in AH treated platelets transfusion. Descriptive study. Medical College, Taif University, Taif, Saudi Arabia, from October 2014 to May 2015. The study was carried out in-silico. PDB (protein data bank) code of Tirofiban bound to CD-61 was 2vdm. CD-61 was docked with Tirofiban using online docking tools, i.e. Patchdock and Firedock. Then, Amotosalen hydrochloride and CD-61 were also docked. Best docking poses to active sites of 2vdm were found. Ligplot of interactions of ligands and CD-61 were obtained. Then comparison of hydrogen bonds, hydrogen bond lengths, and hydrophobic bonds of 2vdm molecule and best poses of docking results were done. Patchdock and Firedock results of best poses were also analysed using SPSS version 16. More amino acids were involved in hydrogen and hydrophobic bonds in Patchdock and Firedock docking of Amotosalen hydrochloride with CD-61 than Patchdock and Firedock docking of CD-61 with Tirofiban. The binding energy was more in latter than former. Amotosalen hydrochloride binds to the active site of CD-61 with weaker binding force. Haemorrhage seen in Amotosalen hydrochloride-treated platelets might be due to binding of Amotosalen hydrochloride to CD-61.

Kinetics of DNA-mediated docking reactions between vesicles tethered to supported lipid bilayers

PubMed Central

Chan, Yee-Hung M.; Lenz, Peter; Boxer, Steven G.

2007-01-01

Membrane–membrane recognition and binding are crucial in many biological processes. We report an approach to studying the dynamics of such reactions by using DNA-tethered vesicles as a general scaffold for displaying membrane components. This system was used to characterize the docking reaction between two populations of tethered vesicles that display complementary DNA. Deposition of vesicles onto a supported lipid bilayer was performed by using a microfluidic device to prevent mixing of the vesicles in bulk during sample preparation. Once tethered onto the surface, vesicles mixed via two-dimensional diffusion. DNA-mediated docking of two reacting vesicles results in their colocalization after collision and their subsequent tandem motion. Individual docking events and population kinetics were observed via epifluorescence microscopy. A lattice-diffusion simulation was implemented to extract from experimental data the probability, Pdock, that a collision leads to docking. For individual vesicles displaying small numbers of docking DNA, Pdock shows a first-order relationship with copy number as well as a strong dependence on the DNA sequence. Both trends are explained by a model that includes both tethered vesicle diffusion on the supported bilayer and docking DNA diffusion over each vesicle's surface. These results provide the basis for the application of tethered vesicles to study other membrane reactions including protein-mediated docking and fusion. PMID:18025472

Combined spectroscopic, molecular docking and quantum mechanics study of β-casein and p-coumaric acid interactions following thermal treatment.

PubMed

Kaur, Jasmeet; Katopo, Lita; Hung, Andrew; Ashton, John; Kasapis, Stefan

2018-06-30

The molecular nature of interactions between β-casein and p-coumaric acid was studied following exposure of their solutions to ultra-high temperature (UHT at 145 °C). Interactions were characterised by employing multi-spectroscopic methods, molecular docking and quantum mechanics calculations. FTIR demonstrates that the ligand lies in the vicinity of the protein, hence inverting the absorbance spectrum of the complex. This outcome changes the conformational characteristics of the protein leading to a flexible and open structure that accommodates the phenolic microconstituent. Results are supported by UV-vis, CD and fluorescence quenching showing considerable shifts in spectra with complexation. Molecular docking indicates that there is at least a hydrogen bond between p-coumaric acid and the peptide backbone of isoleucine (Ile27). Quantum mechanics calculations further argue that changes in experimental observations are also due to a covalent interaction in the protein-phenolic adduct, which according to the best predicted binding pose involves the side chain of lysine 47. Copyright © 2018. Published by Elsevier Ltd.

Docking and Virtual Screening Strategies for GPCR Drug Discovery.

PubMed

Beuming, Thijs; Lenselink, Bart; Pala, Daniele; McRobb, Fiona; Repasky, Matt; Sherman, Woody

2015-01-01

Progress in structure determination of G protein-coupled receptors (GPCRs) has made it possible to apply structure-based drug design (SBDD) methods to this pharmaceutically important target class. The quality of GPCR structures available for SBDD projects fall on a spectrum ranging from high resolution crystal structures (<2 Å), where all water molecules in the binding pocket are resolved, to lower resolution (>3 Å) where some protein residues are not resolved, and finally to homology models that are built using distantly related templates. Each GPCR project involves a distinct set of opportunities and challenges, and requires different approaches to model the interaction between the receptor and the ligands. In this review we will discuss docking and virtual screening to GPCRs, and highlight several refinement and post-processing steps that can be used to improve the accuracy of these calculations. Several examples are discussed that illustrate specific steps that can be taken to improve upon the docking and virtual screening accuracy. While GPCRs are a unique target class, many of the methods and strategies outlined in this review are general and therefore applicable to other protein families.

Operator learning effects in teleoperated rendezvous & docking

NASA Astrophysics Data System (ADS)

Wilde, M.; Harder, J.; Purschke, R.

Teleoperation of spacecraft proximity operations and docking requires delicate timing and coordination of spacecraft maneuvers. Experience has shown that human operators show large performance fluctuations in these areas, which are a major factor to be addressed in operator training. In order to allow the quantification of the impact of these human fluctuations on control system performance and the human perception of this performance, a learning curve study was conducted with teleoperated final approach and docking scenarios. Over a period of ten experiment days, three test participants were tasked with repeatedly completing a set of three training scenarios. The scenarios were designed to contain different combinations of the major elements of any final approach and docking situation, and to feature an increasing difficulty level. The individual difficulty levels for the three operators furthermore differed in the level of operator support functions available in their human-machine interfaces. Operator performance in the test scenarios were evaluated in the fields approach success and precision, docking safety, and approach efficiency by a combination of recorded maneuver data and questionnaires. The results show that operator experience and the associated learning curves increase operator performance substantially, regardless of the support system used. The paper also shows that the fluctuations in operator performance and self-perception are substantial between as well as within experiment days, and must be reckoned with in teleoperation system design and mission planning.

Molecular modeling of NK-CT1, from Indian monocellate cobra (Naja kaouthia) and its docking interaction with human DNA topoisomerase II alpha

PubMed Central

Bandopadhyay, Pathikrit; Halder, Soma; Sarkar, Mrinmoy; Kumar Bhunia, Sujay; Dey, Sananda; Gomes, Antony; Giri, Biplab

2016-01-01

A 6.76 kDa molecular weight cardio and cytotoxic protein of 60 amino acids in length called NK-CT1, was purified from the venom of Indian monocellate cobra (Naja kaouthia) by ion-exchange chromatography and HPLC as described in our earlier report. Therefore it is of interest to utlize the sequence of NK-CT1 for further functional inference using molecular modeling and docking. Thus homology model of NK-CT1 is described in this report. The anti-proliferative activity of the protein, binding with human DNA topoisomerase-II alpha was demonstrated using docking data with AUTODOCK and AUTODOCK MGL tools. Data shows that M26, V27 and S28 of NK-CT1 is in close contact with the nucleotides of the oligonucleotide, bound with topoisomerase-II alpha complex. PMID:28149043

Grid heterogeneity in in-silico experiments: an exploration of drug screening using DOCK on cloud environments.

PubMed

Yim, Wen-Wai; Chien, Shu; Kusumoto, Yasuyuki; Date, Susumu; Haga, Jason

2010-01-01

Large-scale in-silico screening is a necessary part of drug discovery and Grid computing is one answer to this demand. A disadvantage of using Grid computing is the heterogeneous computational environments characteristic of a Grid. In our study, we have found that for the molecular docking simulation program DOCK, different clusters within a Grid organization can yield inconsistent results. Because DOCK in-silico virtual screening (VS) is currently used to help select chemical compounds to test with in-vitro experiments, such differences have little effect on the validity of using virtual screening before subsequent steps in the drug discovery process. However, it is difficult to predict whether the accumulation of these discrepancies over sequentially repeated VS experiments will significantly alter the results if VS is used as the primary means for identifying potential drugs. Moreover, such discrepancies may be unacceptable for other applications requiring more stringent thresholds. This highlights the need for establishing a more complete solution to provide the best scientific accuracy when executing an application across Grids. One possible solution to platform heterogeneity in DOCK performance explored in our study involved the use of virtual machines as a layer of abstraction. This study investigated the feasibility and practicality of using virtual machine and recent cloud computing technologies in a biological research application. We examined the differences and variations of DOCK VS variables, across a Grid environment composed of different clusters, with and without virtualization. The uniform computer environment provided by virtual machines eliminated inconsistent DOCK VS results caused by heterogeneous clusters, however, the execution time for the DOCK VS increased. In our particular experiments, overhead costs were found to be an average of 41% and 2% in execution time for two different clusters, while the actual magnitudes of the execution time costs were minimal. Despite the increase in overhead, virtual clusters are an ideal solution for Grid heterogeneity. With greater development of virtual cluster technology in Grid environments, the problem of platform heterogeneity may be eliminated through virtualization, allowing greater usage of VS, and will benefit all Grid applications in general.

Leptospira borgpetersenii hybrid leucine-rich repeat protein: Cloning and expression, immunogenic identification and molecular docking evaluation.

PubMed

Sritrakul, Tepyuda; Nitipan, Supachai; Wajjwalku, Worawidh; La-Ard, Anchalee; Suphatpahirapol, Chattip; Petkarnjanapong, Wimol; Ongphiphadhanakul, Boonsong; Prapong, Siriwan

2017-11-01

Leptospirosis is an important zoonotic disease, and the major outbreak of this disease in Thailand in 1999 was due largely to the Leptospira borgpetersenii serovar Sejroe. Identification of the leucine-rich repeat (LRR) LBJ_2271 protein containing immunogenic epitopes and the discovery of the LBJ_2271 ortholog in Leptospira serovar Sejroe, KU_Sej_R21_2271, led to further studies of the antigenic immune properties of KU_Sej_LRR_2271. The recombinant hybrid (rh) protein was created and expressed from a hybrid PCR fragment of KU_Sej_R21_2271 fused with DNA encoding the LBJ_2271 signal sequence for targeting protein as a membrane-anchoring protein. The fusion DNA was cloned into pET160/GW/D-TOPO® to form the pET160_hKU_R21_2271 plasmid. The plasmid was used to express the rhKU_Sej_LRR_2271 protein in Escherichia coli BL21 Star™ (DE3). The expressed protein was immunologically detected by Western blotting and immunoreactivity detection with hyperimmune sera, T cell epitope prediction by HLA allele and epitope peptide binding affinity, and potential T cell reactivity analysis. The immunogenic epitopes of the protein were evaluated and verified by HLA allele and epitope peptide complex structure molecular docking. Among fourteen best allele epitopes of this protein, binding affinity values of 12 allele epitopes remained unchanged compared to LBJ_2271. Two epitopes for alleles HLA-A0202 and -A0301 had higher IC 50 values, while T cell reactivity values of these peptides were better than values from LBJ_2271 epitopes. Eight of twelve epitope peptides had positive T-cell reactivity scores. Although the molecular docking of two epitopes, 3FPLLKEFLV11/47FPLLKEFLV55 and 50KLSTVPEGV58, into an HLA-A0202 model revealed a good fit in the docked structures, 50KLSTVPEGV58 and 94KLSTVPEEV102 are still considered as the proteins' best epitopes for allele HLA-A0202. The results of this study showed that rhKU_Sej_LRR_2271 protein contained natural immunological properties that should be further examined with respect to antigenic immune stimulation for vaccine development to prevent prevalent leptospiral serovar infection in Thailand. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular simulation and docking studies of Gal1p and Gal3p proteins in the presence and absence of ligands ATP and galactose: implication for transcriptional activation of GAL genes

NASA Astrophysics Data System (ADS)

Upadhyay, Sanjay K.; Sasidhar, Yellamraju U.

2012-07-01

The Gal4p mediated transcriptional activation of GAL genes requires the interaction between Gal3p bound with ATP and galactose and Gal80p. Though numerous studies suggest that galactose and ATP activate Gal3p/Gal1p interaction with Gal80p, neither the mechanism of activation nor the interacting surface that binds to Gal80p is well understood. In this study we investigated the dynamics of Gal3p and Gal1p in the presence and absence of ligands ATP and galactose to understand the role played by dynamics in the function of these proteins through molecular dynamics simulation and protein-protein docking studies. We performed simulations totaling to 510 ns on both Gal1p and Gal3p proteins in the presence and absence of ligands ATP and galactose. We find that, while binding of ligands ATP and galactose to Gal3p/Gal1p do not affect the global conformation of proteins, some local conformational changes around upper-lip helix including insertion domain are observed. We observed that only in the presence of ATP and galactose, Gal3p displays opening and closing motion between the two domains. And because of this motion, a binding interface, which is largely hydrophobic, opens up on the surface of Gal3p and this surface can bind to Gal80p. From our simulation studies we infer probable docking sites for Gal80p on Gal3p/Gal1p, which were further ascertained by the docking of Gal80p on to ligand bound Gal1p and Gal3p proteins, and the residues at the interface between Gal3p and Gal80p are identified. Our results correlate quite well with the existing body of literature on functional and dynamical aspects of Gal1p and Gal3p proteins.

Molecular simulation and docking studies of Gal1p and Gal3p proteins in the presence and absence of ligands ATP and galactose: implication for transcriptional activation of GAL genes.

PubMed

Upadhyay, Sanjay K; Sasidhar, Yellamraju U

2012-07-01

The Gal4p mediated transcriptional activation of GAL genes requires the interaction between Gal3p bound with ATP and galactose and Gal80p. Though numerous studies suggest that galactose and ATP activate Gal3p/Gal1p interaction with Gal80p, neither the mechanism of activation nor the interacting surface that binds to Gal80p is well understood. In this study we investigated the dynamics of Gal3p and Gal1p in the presence and absence of ligands ATP and galactose to understand the role played by dynamics in the function of these proteins through molecular dynamics simulation and protein-protein docking studies. We performed simulations totaling to 510 ns on both Gal1p and Gal3p proteins in the presence and absence of ligands ATP and galactose. We find that, while binding of ligands ATP and galactose to Gal3p/Gal1p do not affect the global conformation of proteins, some local conformational changes around upper-lip helix including insertion domain are observed. We observed that only in the presence of ATP and galactose, Gal3p displays opening and closing motion between the two domains. And because of this motion, a binding interface, which is largely hydrophobic, opens up on the surface of Gal3p and this surface can bind to Gal80p. From our simulation studies we infer probable docking sites for Gal80p on Gal3p/Gal1p, which were further ascertained by the docking of Gal80p on to ligand bound Gal1p and Gal3p proteins, and the residues at the interface between Gal3p and Gal80p are identified. Our results correlate quite well with the existing body of literature on functional and dynamical aspects of Gal1p and Gal3p proteins.

Escherichia coli Ribosomal Protein S1 Unfolds Structured mRNAs Onto the Ribosome for Active Translation Initiation

PubMed Central

Duval, Mélodie; Korepanov, Alexey; Fuchsbauer, Olivier; Fechter, Pierre; Haller, Andrea; Fabbretti, Attilio; Choulier, Laurence; Micura, Ronald; Klaholz, Bruno P.; Romby, Pascale; Springer, Mathias; Marzi, Stefano

2013-01-01

Regulation of translation initiation is well appropriate to adapt cell growth in response to stress and environmental changes. Many bacterial mRNAs adopt structures in their 5′ untranslated regions that modulate the accessibility of the 30S ribosomal subunit. Structured mRNAs interact with the 30S in a two-step process where the docking of a folded mRNA precedes an accommodation step. Here, we used a combination of experimental approaches in vitro (kinetic of mRNA unfolding and binding experiments to analyze mRNA–protein or mRNA–ribosome complexes, toeprinting assays to follow the formation of ribosomal initiation complexes) and in vivo (genetic) to monitor the action of ribosomal protein S1 on the initiation of structured and regulated mRNAs. We demonstrate that r-protein S1 endows the 30S with an RNA chaperone activity that is essential for the docking and the unfolding of structured mRNAs, and for the correct positioning of the initiation codon inside the decoding channel. The first three OB-fold domains of S1 retain all its activities (mRNA and 30S binding, RNA melting activity) on the 30S subunit. S1 is not required for all mRNAs and acts differently on mRNAs according to the signals present at their 5′ ends. This work shows that S1 confers to the ribosome dynamic properties to initiate translation of a large set of mRNAs with diverse structural features. PMID:24339747

Binding interaction of ramipril with bovine serum albumin (BSA): Insights from multi-spectroscopy and molecular docking methods.

PubMed

Shi, Jie-Hua; Pan, Dong-Qi; Jiang, Min; Liu, Ting-Ting; Wang, Qi

2016-11-01

The binding interaction between a typical angiotensin-converting enzyme inhibitor (ACEI), ramipril, and a transport protein, bovine serum albumin (BSA), was studied in vitro using UV-vis absorption spectroscopy, steady-state fluorescence spectroscopic titration, synchronous fluorescence spectroscopy, three dimensional fluorescence spectroscopy, circular dichroism and molecular docking under the imitated physiological conditions (pH=7.4). The experimental results suggested that the intrinsic fluorescence of BSA was quenched by ramipril thought a static quenching mechanism, indicating that the stable ramipril-BSA complex was formed by the intermolecular interaction. The number of binding sites (n) and binding constant of ramipril-BSA complex were about 1 and 3.50×10 4 M -1 at 298K, respectively, suggesting that there was stronger binding interaction of ramipril with BSA. The thermodynamic parameters together with molecular docking study revealed that both van der Waal's forces and hydrogen bonding interaction dominated the formation of the ramipril-BSA complex and the binding interaction of BSA with ramipril is enthalpy-driven processes due to |ΔH°|>|TΔS°| and ΔG°<0. The spatial distance between ramipril and BSA was calculated to be 3.56nm based on Förster's non-radiative energy transfer theory. The results of the competitive displacement experiments and molecular docking confirmed that ramipril inserted into the subdomain IIA (site I) of BSA, resulting in a slight change in the conformation of BSA but BSA still retained its secondary structure α-helicity. Copyright © 2016 Elsevier B.V. All rights reserved.

Skylab checkout operations. [from multiple docking adapter contractor viewpoint

NASA Technical Reports Server (NTRS)

Timmons, K. P.

1973-01-01

The Skylab Program at Kennedy Space Center presented many opportunities for interesting and profound test and checkout experience. It also offered a compilation of challenges and promises for the Center and for the contractors responsible for the various modules making up Skylab. It is very probable that the various contractors had common experiences during the module and combined systems tests, but this paper will discuss those experiences from the viewpoint of the Multiple Docking Adapter contractor. The experience will consider personnel, procedures, and hardware.

Experimental evaluation of model predictive control and inverse dynamics control for spacecraft proximity and docking maneuvers

NASA Astrophysics Data System (ADS)

Virgili-Llop, Josep; Zagaris, Costantinos; Park, Hyeongjun; Zappulla, Richard; Romano, Marcello

2018-03-01

An experimental campaign has been conducted to evaluate the performance of two different guidance and control algorithms on a multi-constrained docking maneuver. The evaluated algorithms are model predictive control (MPC) and inverse dynamics in the virtual domain (IDVD). A linear-quadratic approach with a quadratic programming solver is used for the MPC approach. A nonconvex optimization problem results from the IDVD approach, and a nonlinear programming solver is used. The docking scenario is constrained by the presence of a keep-out zone, an entry cone, and by the chaser's maximum actuation level. The performance metrics for the experiments and numerical simulations include the required control effort and time to dock. The experiments have been conducted in a ground-based air-bearing test bed, using spacecraft simulators that float over a granite table.

First Principles Predictions of the Structure and Function of G-Protein-Coupled Receptors: Validation for Bovine Rhodopsin

PubMed Central

Trabanino, Rene J.; Hall, Spencer E.; Vaidehi, Nagarajan; Floriano, Wely B.; Kam, Victor W. T.; Goddard, William A.

2004-01-01

G-protein-coupled receptors (GPCRs) are involved in cell communication processes and with mediating such senses as vision, smell, taste, and pain. They constitute a prominent superfamily of drug targets, but an atomic-level structure is available for only one GPCR, bovine rhodopsin, making it difficult to use structure-based methods to design receptor-specific drugs. We have developed the MembStruk first principles computational method for predicting the three-dimensional structure of GPCRs. In this article we validate the MembStruk procedure by comparing its predictions with the high-resolution crystal structure of bovine rhodopsin. The crystal structure of bovine rhodopsin has the second extracellular (EC-II) loop closed over the transmembrane regions by making a disulfide linkage between Cys-110 and Cys-187, but we speculate that opening this loop may play a role in the activation process of the receptor through the cysteine linkage with helix 3. Consequently we predicted two structures for bovine rhodopsin from the primary sequence (with no input from the crystal structure)—one with the EC-II loop closed as in the crystal structure, and the other with the EC-II loop open. The MembStruk-predicted structure of bovine rhodopsin with the closed EC-II loop deviates from the crystal by 2.84 Å coordinate root mean-square (CRMS) in the transmembrane region main-chain atoms. The predicted three-dimensional structures for other GPCRs can be validated only by predicting binding sites and energies for various ligands. For such predictions we developed the HierDock first principles computational method. We validate HierDock by predicting the binding site of 11-cis-retinal in the crystal structure of bovine rhodopsin. Scanning the whole protein without using any prior knowledge of the binding site, we find that the best scoring conformation in rhodopsin is 1.1 Å CRMS from the crystal structure for the ligand atoms. This predicted conformation has the carbonyl O only 2.82 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 0.62 Å CRMS from the crystal structure. We also used HierDock to predict the binding site of 11-cis-retinal in the MembStruk-predicted structure of bovine rhodopsin (closed loop). Scanning the whole protein structure leads to a structure in which the carbonyl O is only 2.85 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 2.92 Å CRMS from the crystal structure. The good agreement of the ab initio-predicted protein structures and ligand binding site with experiment validates the use of the MembStruk and HierDock first principles' methods. Since these methods are generic and applicable to any GPCR, they should be useful in predicting the structures of other GPCRs and the binding site of ligands to these proteins. PMID:15041637

Effect of the explicit flexibility of the InhA enzyme from Mycobacterium tuberculosis in molecular docking simulations.

PubMed

Cohen, Elisangela M L; Machado, Karina S; Cohen, Marcelo; de Souza, Osmar Norberto

2011-12-22

Protein/receptor explicit flexibility has recently become an important feature of molecular docking simulations. Taking the flexibility into account brings the docking simulation closer to the receptors' real behaviour in its natural environment. Several approaches have been developed to address this problem. Among them, modelling the full flexibility as an ensemble of snapshots derived from a molecular dynamics simulation (MD) of the receptor has proved very promising. Despite its potential, however, only a few studies have employed this method to probe its effect in molecular docking simulations. We hereby use ensembles of snapshots obtained from three different MD simulations of the InhA enzyme from M. tuberculosis (Mtb), the wild-type (InhA_wt), InhA_I16T, and InhA_I21V mutants to model their explicit flexibility, and to systematically explore their effect in docking simulations with three different InhA inhibitors, namely, ethionamide (ETH), triclosan (TCL), and pentacyano(isoniazid)ferrate(II) (PIF). The use of fully-flexible receptor (FFR) models of InhA_wt, InhA_I16T, and InhA_I21V mutants in docking simulation with the inhibitors ETH, TCL, and PIF revealed significant differences in the way they interact as compared to the rigid, InhA crystal structure (PDB ID: 1ENY). In the latter, only up to five receptor residues interact with the three different ligands. Conversely, in the FFR models this number grows up to an astonishing 80 different residues. The comparison between the rigid crystal structure and the FFR models showed that the inclusion of explicit flexibility, despite the limitations of the FFR models employed in this study, accounts in a substantial manner to the induced fit expected when a protein/receptor and ligand approach each other to interact in the most favourable manner. Protein/receptor explicit flexibility, or FFR models, represented as an ensemble of MD simulation snapshots, can lead to a more realistic representation of the induced fit effect expected in the encounter and proper docking of receptors to ligands. The FFR models of InhA explicitly characterizes the overall movements of the amino acid residues in helices, strands, loops, and turns, allowing the ligand to properly accommodate itself in the receptor's binding site. Utilization of the intrinsic flexibility of Mtb's InhA enzyme and its mutants in virtual screening via molecular docking simulation may provide a novel platform to guide the rational or dynamical-structure-based drug design of novel inhibitors for Mtb's InhA. We have produced a short video sequence of each ligand (ETH, TCL and PIF) docked to the FFR models of InhA_wt. These videos are available at http://www.inf.pucrs.br/~osmarns/LABIO/Videos_Cohen_et_al_19_07_2011.htm.

ACTP: A webserver for predicting potential targets and relevant pathways of autophagy-modulating compounds

PubMed Central

Ouyang, Liang; Cai, Haoyang; Liu, Bo

2016-01-01

Autophagy (macroautophagy) is well known as an evolutionarily conserved lysosomal degradation process for long-lived proteins and damaged organelles. Recently, accumulating evidence has revealed a series of small-molecule compounds that may activate or inhibit autophagy for therapeutic potential on human diseases. However, targeting autophagy for drug discovery still remains in its infancy. In this study, we developed a webserver called Autophagic Compound-Target Prediction (ACTP) (http://actp.liu-lab.com/) that could predict autophagic targets and relevant pathways for a given compound. The flexible docking of submitted small-molecule compound (s) to potential autophagic targets could be performed by backend reverse docking. The webpage would return structure-based scores and relevant pathways for each predicted target. Thus, these results provide a basis for the rapid prediction of potential targets/pathways of possible autophagy-activating or autophagy-inhibiting compounds without labor-intensive experiments. Moreover, ACTP will be helpful to shed light on identifying more novel autophagy-activating or autophagy-inhibiting compounds for future therapeutic implications. PMID:26824420

Grid-based Molecular Footprint Comparison Method for Docking and De Novo Design: Application to HIVgp41

PubMed Central

Mukherjee, Sudipto; Rizzo, Robert C.

2014-01-01

Scoring functions are a critically important component of computer-aided screening methods for the identification of lead compounds during early stages of drug discovery. Here, we present a new multi-grid implementation of the footprint similarity (FPS) scoring function that was recently developed in our laboratory which has proven useful for identification of compounds which bind to a protein on a per-residue basis in a way that resembles a known reference. The grid-based FPS method is much faster than its Cartesian-space counterpart which makes it computationally tractable for on-the-fly docking, virtual screening, or de novo design. In this work, we establish that: (i) relatively few grids can be used to accurately approximate Cartesian space footprint similarity, (ii) the method yields improved success over the standard DOCK energy function for pose identification across a large test set of experimental co-crystal structures, for crossdocking, and for database enrichment, and (iii) grid-based FPS scoring can be used to tailor construction of new molecules to have specific properties, as demonstrated in a series of test cases targeting the viral protein HIVgp41. The method will be made available in the program DOCK6. PMID:23436713

Structural study of biologically significant ligands with major birch pollen allergen Betv1 by docking and molecular dynamics simulation

PubMed Central

Kundu, Sangeeta; Roy, Debjani

2010-01-01

The major birch pollen allergen, Betv1 of Betula verrucosa is the main causative agent of birch pollen allergy in humans. Betv1 is capable of binding several physiological ligands including fatty acids, flavones, cytokinins and sterols. Until now, no structural information from crystallography or NMR is available regarding binding mode of any of these ligands into the binding pocket of Betv1. In the present study thirteen ligands have been successfully docked into the hydrophobic cavity of Betv1 and binding free energies of the complexes have been calculated using AutoDock 3.0.5. A linear relationship with correlation coefficient (R2) of 0.6 is obtained between ΔGbs values plotted against their corresponding IC50 values. The complex formed between Betv1 and the best docking pose for each ligand has been optimized by molecular dynamics simulation. Here, we describe the ligand binding of Betv1, which provides insight into the biological function of this protein. This knowledge is required for structural alteration or inhibition of some of these ligands in order to modify the allergenic properties of this protein. PMID:20978606

Computational Insight into Protein Tyrosine Phosphatase 1B Inhibition: A Case Study of the Combined Ligand- and Structure-Based Approach.

PubMed

Zhang, Xiangyu; Jiang, Hailun; Li, Wei; Wang, Jian; Cheng, Maosheng

2017-01-01

Protein tyrosine phosphatase 1B (PTP1B) is an attractive target for treating cancer, obesity, and type 2 diabetes. In our work, the way of combined ligand- and structure-based approach was applied to analyze the characteristics of PTP1B enzyme and its interaction with competitive inhibitors. Firstly, the pharmacophore model of PTP1B inhibitors was built based on the common feature of sixteen compounds. It was found that the pharmacophore model consisted of five chemical features: one aromatic ring (R) region, two hydrophobic (H) groups, and two hydrogen bond acceptors (A). To further elucidate the binding modes of these inhibitors with PTP1B active sites, four docking programs (AutoDock 4.0, AutoDock Vina 1.0, standard precision (SP) Glide 9.7, and extra precision (XP) Glide 9.7) were used. The characteristics of the active sites were then described by the conformations of the docking results. In conclusion, a combination of various pharmacophore features and the integration information of structure activity relationship (SAR) can be used to design novel potent PTP1B inhibitors.

Implementation of the Hungarian Algorithm to Account for Ligand Symmetry and Similarity in Structure-Based Design

PubMed Central

2015-01-01

False negative docking outcomes for highly symmetric molecules are a barrier to the accurate evaluation of docking programs, scoring functions, and protocols. This work describes an implementation of a symmetry-corrected root-mean-square deviation (RMSD) method into the program DOCK based on the Hungarian algorithm for solving the minimum assignment problem, which dynamically assigns atom correspondence in molecules with symmetry. The algorithm adds only a trivial amount of computation time to the RMSD calculations and is shown to increase the reported overall docking success rate by approximately 5% when tested over 1043 receptor–ligand systems. For some families of protein systems the results are even more dramatic, with success rate increases up to 16.7%. Several additional applications of the method are also presented including as a pairwise similarity metric to compare molecules during de novo design, as a scoring function to rank-order virtual screening results, and for the analysis of trajectories from molecular dynamics simulation. The new method, including source code, is available to registered users of DOCK6 (http://dock.compbio.ucsf.edu). PMID:24410429

A machine learning approach for ranking clusters of docked protein‐protein complexes by pairwise cluster comparison

PubMed Central

Pfeiffenberger, Erik; Chaleil, Raphael A.G.; Moal, Iain H.

2017-01-01

ABSTRACT Reliable identification of near‐native poses of docked protein–protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein–protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near‐native from incorrect clusters. The results show that our approach is able to identify clusters containing near‐native protein–protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528–543. © 2016 Wiley Periodicals, Inc. PMID:27935158

Small-GTPase-associated signaling by the guanine nucleotide exchange factors CpDock180 and CpCdc24, the GTPase effector CpSte20, and the scaffold protein CpBem1 in Claviceps purpurea.

PubMed

Herrmann, Andrea; Tillmann, Britta A M; Schürmann, Janine; Bölker, Michael; Tudzynski, Paul

2014-04-01

Monomeric GTPases of the Rho subfamily are important mediators of polar growth and NADPH (Nox) signaling in a variety of organisms. These pathways influence the ability of Claviceps purpurea to infect host plants. GTPase regulators contribute to the nucleotide loading cycle that is essential for proper functionality of the GTPases. Scaffold proteins gather GTPase complexes to facilitate proper function. The guanine nucleotide exchange factors (GEFs) CpCdc24 and CpDock180 activate GTPase signaling by triggering nucleotide exchange of the GTPases. Here we show that CpCdc24 harbors nucleotide exchange activity for both Rac and Cdc42 homologues. The GEFs partly share the cellular distribution of the GTPases and interact with the putative upstream GTPase CpRas1. Interaction studies show the formation of higher-order protein complexes, mediated by the scaffold protein CpBem1. Besides the GTPases and GEFs, these complexes also contain the GTPase effectors CpSte20 and CpCla4, as well as the regulatory protein CpNoxR. Functional characterizations suggest a role of CpCdc24 mainly in polarity, whereas CpDock180 is involved in stress tolerance mechanisms. These findings indicate the dynamic formation of small GTPase complexes and improve the model for GTPase-associated signaling in C. purpurea.

Recovery of known T-cell epitopes by computational scanning of a viral genome

NASA Astrophysics Data System (ADS)

Logean, Antoine; Rognan, Didier

2002-04-01

A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list. The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.

RosettaScripts: a scripting language interface to the Rosetta macromolecular modeling suite.

PubMed

Fleishman, Sarel J; Leaver-Fay, Andrew; Corn, Jacob E; Strauch, Eva-Maria; Khare, Sagar D; Koga, Nobuyasu; Ashworth, Justin; Murphy, Paul; Richter, Florian; Lemmon, Gordon; Meiler, Jens; Baker, David

2011-01-01

Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins.

Influence of Ficoll on urea induced denaturation of fibrinogen

NASA Astrophysics Data System (ADS)

Sankaranarayanan, Kamatchi; Meenakshisundaram, N.

2016-03-01

Ficoll is a neutral, highly branched polymer used as a molecular crowder in the study of proteins. Ficoll is also part of Ficoll-Paque used in biology laboratories to separate blood to its components (erythrocytes, leukocytes etc.,). Role of Ficoll in the urea induced denaturation of protein Fibrinogen (Fg) has been analyzed using fluorescence, circular dichroism, molecular docking and interfacial studies. Fluorescence studies show that Ficoll prevents quenching of Fg in the presence of urea. From the circular dichroism spectra, Fg shows conformational transition to random coil with urea of 6 M concentration. Ficoll helps to shift this denaturation concentration to 8 M and thus constraints by shielding Fg during the process. Molecular docking studies indicate that Ficoll interacts favorably with the protein than urea. The surface tension and shear viscosity analysis shows clearly that the protein is shielded by Ficoll.

Energy Fluctuations Shape Free Energy of Nonspecific Biomolecular Interactions

NASA Astrophysics Data System (ADS)

Elkin, Michael; Andre, Ingemar; Lukatsky, David B.

2012-01-01

Understanding design principles of biomolecular recognition is a key question of molecular biology. Yet the enormous complexity and diversity of biological molecules hamper the efforts to gain a predictive ability for the free energy of protein-protein, protein-DNA, and protein-RNA binding. Here, using a variant of the Derrida model, we predict that for a large class of biomolecular interactions, it is possible to accurately estimate the relative free energy of binding based on the fluctuation properties of their energy spectra, even if a finite number of the energy levels is known. We show that the free energy of the system possessing a wider binding energy spectrum is almost surely lower compared with the system possessing a narrower energy spectrum. Our predictions imply that low-affinity binding scores, usually wasted in protein-protein and protein-DNA docking algorithms, can be efficiently utilized to compute the free energy. Using the results of Rosetta docking simulations of protein-protein interactions from Andre et al. (Proc. Natl. Acad. Sci. USA 105:16148, 2008), we demonstrate the power of our predictions.

First report on 3D-QSAR and molecular dynamics based docking studies of GCPII inhibitors for targeted drug delivery applications

NASA Astrophysics Data System (ADS)

Pandit, Amit; Sengupta, Sagnik; Krishnan, Mena Asha; Reddy, Ramesh B.; Sharma, Rajesh; Venkatesh, Chelvam

2018-05-01

Prostate Specific Membrane Antigen (PSMA) or Glutamate carboxypeptidase II (GCPII) has been identified as an important target in diagnosis and therapy of prostate cancer. Among several types of inhibitors, urea based inhibitors are the most common and widely employed in preclinical and clinical studies. Computational studies have been carried out to uncover active sites and interaction of PSMA inhibitors with the protein by modifying the core structure of the ligand. Analysis of the literature, however, show lack of 3-D quantitative structure activity relationship (QSAR) and molecular dynamics based molecular docking study to identify structural modifications responsible for better GCPII inhibitory activity. The present study aims to fulfil this gap by analysing well known PSMA inhibitors reported in the literature with known experimental PSMA inhibition constants. Also in order to validate the in silico study, a new GCPII inhibitor 7 was designed, synthesized and experimental PSMA enzyme inhibition was evaluated by using freshly isolated PSMA protein from human cancer cell line derived from lymph node, LNCaP. 3D-QSAR CoMFA models on 58 urea based GCPII inhibitors were generated, and the best correlation was obtained in Gast-Huck charge assigning method with q2, r2 and predictive r2 values as 0.592, 0.995 and 0.842 respectively. Moreover, steric, electrostatic, and hydrogen bond donor field contribution analysis provided best statistical values from CoMSIA model (q2, r2 and predictive r2 as 0.527, 0.981 and 0.713 respectively). Contour maps study revealed that electrostatic field contribution is the major factor for discovering better binding affinity ligands. Further molecular dynamic assisted molecular docking was also performed on GCPII receptor (PDB ID 4NGM) and most active GCPII inhibitor, DCIBzL. 4NGM co-crystallised ligand, JB7 was used to validate the docking procedure and the amino acid interactions present in JB7 are compared with DCIBzL. The results suggest that Arg210, Asn257, Gly518, Tyr552, Lys699, and Tyr700 amino acid residues may play a crucial role in GCPII inhibition. Molecular Dynamics Simulation provides information about docked pose stability of DCIBzL. By combination of CoMFA-CoMSIA field analysis and docking interaction analysis studies, conclusive SAR was generated for urea based derivatives based on which GCPII inhibitor 7 was designed and chemically synthesized in our laboratory. Evaluation of GCPII inhibitory activity of 7 by performing NAALADase assay provided IC50 value of 113 nM which is in close agreement with in silico predicted value (119 nM). Thus we have successfully validated our 3D-QSAR and molecular docking based designing of GCPII inhibitors methodology through biological experiments. This conclusive SAR would be helpful to generate novel and more potent GCPII inhibitors for drug delivery applications.

Effective screening strategy using ensembled pharmacophore models combined with cascade docking: application to p53-MDM2 interaction inhibitors.

PubMed

Xue, Xin; Wei, Jin-Lian; Xu, Li-Li; Xi, Mei-Yang; Xu, Xiao-Li; Liu, Fang; Guo, Xiao-Ke; Wang, Lei; Zhang, Xiao-Jin; Zhang, Ming-Ye; Lu, Meng-Chen; Sun, Hao-Peng; You, Qi-Dong

2013-10-28

Protein-protein interactions (PPIs) play a crucial role in cellular function and form the backbone of almost all biochemical processes. In recent years, protein-protein interaction inhibitors (PPIIs) have represented a treasure trove of potential new drug targets. Unfortunately, there are few successful drugs of PPIIs on the market. Structure-based pharmacophore (SBP) combined with docking has been demonstrated as a useful Virtual Screening (VS) strategy in drug development projects. However, the combination of target complexity and poor binding affinity prediction has thwarted the application of this strategy in the discovery of PPIIs. Here we report an effective VS strategy on p53-MDM2 PPI. First, we built a SBP model based on p53-MDM2 complex cocrystal structures. The model was then simplified by using a Receptor-Ligand complex-based pharmacophore model considering the critical binding features between MDM2 and its small molecular inhibitors. Cascade docking was subsequently applied to improve the hit rate. Based on this strategy, we performed VS on NCI and SPECS databases and successfully discovered 6 novel compounds from 15 hits with the best, compound 1 (NSC 5359), K(i) = 180 ± 50 nM. These compounds can serve as lead compounds for further optimization.

Applying the Brakes to Multi-Site SR Protein Phosphorylation: Substrate-Induced Effects on the Splicing Kinase SRPK1†

PubMed Central

Aubol, Brandon E.; Adams, Joseph A.

2011-01-01

To investigate how a protein kinase interacts with its protein substrate during extended, multi-site phosphorylation, the kinetic mechanism of a protein kinase involved in mRNA splicing control was investigated using rapid quench flow techniques. The protein kinase SRPK1 phosphorylates approximately 10 serines in the arginine-serine-rich domain (RS domain) of the SR protein SRSF1 in a C-to-N-terminal direction, a modification that directs this essential splicing factor from the cytoplasm to the nucleus. Transient-state kinetic experiments illustrate that the first phosphate is added rapidly onto the RS domain of SRSF1 (t1/2 = 0.1 sec) followed by slower, multi-site phosphorylation at the remaining serines (t1/2 = 15 sec). Mutagenesis experiments suggest that efficient phosphorylation rates are maintained by an extensive hydrogen bonding and electrostatic network between the RS domain of the SR protein and the active site and docking groove of the kinase. Catalytic trapping and viscosometric experiments demonstrate that while the phosphoryl transfer step is fast, ADP release limits multi-site phosphorylation. By studying phosphate incorporation into selectively pre-phosphorylated forms of the enzyme-substrate complex, the kinetic mechanism for site-specific phosphorylation along the reaction coordinate was assessed. The binding affinity of the SR protein, the phosphoryl transfer rate and ADP exchange rate were found to decline significantly as a function of progressive phosphorylation in the RS domain. These findings indicate that the protein substrate actively modulates initiation, extension and termination events associated with prolonged, multi-site phosphorylation. PMID:21728354

Protein unfolding as a switch from self-recognition to high-affinity client binding

PubMed Central

Groitl, Bastian; Horowitz, Scott; Makepeace, Karl A. T.; Petrotchenko, Evgeniy V.; Borchers, Christoph H.; Reichmann, Dana; Bardwell, James C. A.; Jakob, Ursula

2016-01-01

Stress-specific activation of the chaperone Hsp33 requires the unfolding of a central linker region. This activation mechanism suggests an intriguing functional relationship between the chaperone's own partial unfolding and its ability to bind other partially folded client proteins. However, identifying where Hsp33 binds its clients has remained a major gap in our understanding of Hsp33's working mechanism. By using site-specific Fluorine-19 nuclear magnetic resonance experiments guided by in vivo crosslinking studies, we now reveal that the partial unfolding of Hsp33's linker region facilitates client binding to an amphipathic docking surface on Hsp33. Furthermore, our results provide experimental evidence for the direct involvement of conditionally disordered regions in unfolded protein binding. The observed structural similarities between Hsp33's own metastable linker region and client proteins present a possible model for how Hsp33 uses protein unfolding as a switch from self-recognition to high-affinity client binding. PMID:26787517

Intracellular signaling of the Ufo/Axl receptor tyrosine kinase is mediated mainly by a multi-substrate docking-site.

PubMed

Braunger, J; Schleithoff, L; Schulz, A S; Kessler, H; Lammers, R; Ullrich, A; Bartram, C R; Janssen, J W

1997-06-05

Ufo/Axl belongs to a new family of receptor tyrosine kinases with an extracellular structure similar to that of neural cell adhesion molecules. In order to elucidate intracellular signaling, the cytoplasmic moiety of Ufo/Axl was used to screen an expression library according to the CORT (cloning of receptor targets) method. Three putative Ufo substrates were identified: phospholipase Cgamma1 (PLCgamma), as well as p85alpha and p85beta subunits of phosphatidylinositol 3'-kinase (PI3-kinase). Subsequently, chimeric EGFR/Ufo receptors consisting of the extracellular domains of the epidermal growth factor receptor (EGFR) and the transmembrane and intracellular moiety of Ufo were engineered. Using different far-Western blot analyses and coimmunoprecipitation assays, receptor binding of PLCgamma and p85 proteins as well as GRB2, c-src and lck was examined in vitro and in vivo. Competitive inhibition of substrate binding and mutagenesis experiments with EGFR/Ufo constructs revealed C-terminal tyrosine 821 (EILpYVNMDEG) as a docking site for multiple effectors, namely PLCgamma, p85 proteins, GRB2, c-src and lck. Tyrosine 779 (DGLpYALMSRC) demonstrated an additional, but lower binding affinity for the p85 proteins in vitro. In addition, binding of PLCgamma occurred through tyrosine 866 (AGRpYVLCPST). Moreover, our in vivo data indicate that further direct or indirect binding sites for PLCgamma, GRB2, c-src and lck on the human Ufo receptor may exist.

Sex pheromone recognition and characterization of three pheromone-binding proteins in the legume pod borer, Maruca vitrata Fabricius (Lepidoptera: Crambidae)

PubMed Central

Mao, Aping; Zhou, Jing; Bin Mao; Zheng, Ya; Wang, Yufeng; Li, Daiqin; Wang, Pan; Liu, Kaiyu; Wang, Xiaoping; Ai, Hui

2016-01-01

Pheromone-binding proteins (PBPs) are essential for the filtering, binding and transporting of sex pheromones across sensillum lymph to membrane-associated pheromone receptors of moths. In this study, three novel PBP genes were expressed in Escherichia coli to examine their involvement in the sex pheromone perception of Maruca vitrata. Fluorescence binding experiments indicated that MvitPBP1-3 had strong binding affinities with four sex pheromones. Moreover, molecular docking results demonstrated that six amino acid residues of three MvitPBPs were involved in the binding of the sex pheromones. These results suggested that MvitPBP1-3 might play critical roles in the perception of female sex pheromones. Additionally, the binding capacity of MvitPBP3 with the host-plant floral volatiles was high and was similar to that of MvitGOBP2. Furthermore, sequence alignment and docking analysis showed that both MvitGOBP2 and MvitPBP3 possessed an identical key binding site (arginine, R130/R140) and a similar protein pocket structure around the binding cavity. Therefore, we hypothesized that MvitPBP3 and MvitGOBP2 might have synergistic roles in binding different volatile ligands. In combination, the use of synthetic sex pheromones and floral volatiles from host-plant may be used in the exploration for more efficient monitoring and integrated management strategies for the legume pod borer in the field. PMID:27698435

ARCADE small-scale docking mechanism for micro-satellites

NASA Astrophysics Data System (ADS)

Boesso, A.; Francesconi, A.

2013-05-01

The development of on-orbit autonomous rendezvous and docking (ARD) capabilities represents a key point for a number of appealing mission scenarios that include activities of on-orbit servicing, automated assembly of modular structures and active debris removal. As of today, especially in the field of micro-satellites ARD, many fundamental technologies are still missing or require further developments and micro-gravity testing. In this framework, the University of Padova, Centre of Studies and Activities for Space (CISAS), developed the Autonomous Rendezvous Control and Docking Experiment (ARCADE), a technology demonstrator intended to fly aboard a BEXUS stratospheric balloon. The goal was to design, build and test, in critical environment conditions, a proximity relative navigation system, a custom-made reaction wheel and a small-size docking mechanism. The ARCADE docking mechanism was designed against a comprehensive set of requirements and it can be classified as small-scale, central, gender mating and unpressurized. The large use of commercial components makes it low-cost and simple to be manufactured. Last, it features a good tolerance to off-nominal docking conditions and a by-design soft docking capability. The final design was extensively verified to be compliant with its requirements by means of numerical simulations and physical testing. In detail, the dynamic behaviour of the mechanism in both nominal and off-nominal conditions was assessed with the multibody dynamics analysis software MD ADAMS 2010 and functional tests were carried out within the fully integrated ARCADE experiment to ensure the docking system efficacy and to highlight possible issues. The most relevant results of the study will be presented and discussed in conclusion to this paper.

Energy minimization on manifolds for docking flexible molecules

PubMed Central

Mirzaei, Hanieh; Zarbafian, Shahrooz; Villar, Elizabeth; Mottarella, Scott; Beglov, Dmitri; Vajda, Sandor; Paschalidis, Ioannis Ch.; Vakili, Pirooz; Kozakov, Dima

2015-01-01

In this paper we extend a recently introduced rigid body minimization algorithm, defined on manifolds, to the problem of minimizing the energy of interacting flexible molecules. The goal is to integrate moving the ligand in six dimensional rotational/translational space with internal rotations around rotatable bonds within the two molecules. We show that adding rotational degrees of freedom to the rigid moves of the ligand results in an overall optimization search space that is a manifold to which our manifold optimization approach can be extended. The effectiveness of the method is shown for three different docking problems of increasing complexity. First we minimize the energy of fragment-size ligands with a single rotatable bond as part of a protein mapping method developed for the identification of binding hot spots. Second, we consider energy minimization for docking a flexible ligand to a rigid protein receptor, an approach frequently used in existing methods. In the third problem we account for flexibility in both the ligand and the receptor. Results show that minimization using the manifold optimization algorithm is substantially more efficient than minimization using a traditional all-atom optimization algorithm while producing solutions of comparable quality. In addition to the specific problems considered, the method is general enough to be used in a large class of applications such as docking multidomain proteins with flexible hinges. The code is available under open source license (at http://cluspro.bu.edu/Code/Code_Rigtree.tar), and with minimal effort can be incorporated into any molecular modeling package. PMID:26478722

Computational Approaches for Decoding Select Odorant-Olfactory Receptor Interactions Using Mini-Virtual Screening

PubMed Central

Harini, K.; Sowdhamini, Ramanathan

2015-01-01

Olfactory receptors (ORs) belong to the class A G-Protein Coupled Receptor superfamily of proteins. Unlike G-Protein Coupled Receptors, ORs exhibit a combinatorial response to odors/ligands. ORs display an affinity towards a range of odor molecules rather than binding to a specific set of ligands and conversely a single odorant molecule may bind to a number of olfactory receptors with varying affinities. The diversity in odor recognition is linked to the highly variable transmembrane domains of these receptors. The purpose of this study is to decode the odor-olfactory receptor interactions using in silico docking studies. In this study, a ligand (odor molecules) dataset of 125 molecules was used to carry out in silico docking using the GLIDE docking tool (SCHRODINGER Inc Pvt LTD). Previous studies, with smaller datasets of ligands, have shown that orthologous olfactory receptors respond to similarly-tuned ligands, but are dramatically different in their efficacy and potency. Ligand docking results were applied on homologous pairs (with varying sequence identity) of ORs from human and mouse genomes and ligand binding residues and the ligand profile differed among such related olfactory receptor sequences. This study revealed that homologous sequences with high sequence identity need not bind to the same/ similar ligand with a given affinity. A ligand profile has been obtained for each of the 20 receptors in this analysis which will be useful for expression and mutation studies on these receptors. PMID:26221959