Re-docking scheme for generating near-native protein complexes by assembling residue interaction fingerprints.

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Nobuyuki Uchikoga

Full Text Available Interaction profile method is a useful method for processing rigid-body docking. After the docking process, the resulting set of docking poses could be classified by calculating similarities among them using these interaction profiles to search for near-native poses. However, there are some cases where the near-native poses are not included in this set of docking poses even when the bound-state structures are used. Therefore, we have developed a method for generating near-native docking poses by introducing a re-docking process. We devised a method for calculating the profile of interaction fingerprints by assembling protein complexes after determining certain core-protein complexes. For our analysis, we used 44 bound-state protein complexes selected from the ZDOCK benchmark dataset ver. 2.0, including some protein pairs none of which generated near-native poses in the docking process. Consequently, after the re-docking process we obtained profiles of interaction fingerprints, some of which yielded near-native poses. The re-docking process involved searching for possible docking poses in a restricted area using the profile of interaction fingerprints. If the profile includes interactions identical to those in the native complex, we obtained near-native docking poses. Accordingly, near-native poses were obtained for all bound-state protein complexes examined here. Application of interaction fingerprints to the re-docking process yielded structures with more native interactions, even when a docking pose, obtained following the initial docking process, contained only a small number of native amino acid interactions. Thus, utilization of the profile of interaction fingerprints in the re-docking process yielded more near-native poses.

Re-docking scheme for generating near-native protein complexes by assembling residue interaction fingerprints.

Science.gov (United States)

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

2013-01-01

Interaction profile method is a useful method for processing rigid-body docking. After the docking process, the resulting set of docking poses could be classified by calculating similarities among them using these interaction profiles to search for near-native poses. However, there are some cases where the near-native poses are not included in this set of docking poses even when the bound-state structures are used. Therefore, we have developed a method for generating near-native docking poses by introducing a re-docking process. We devised a method for calculating the profile of interaction fingerprints by assembling protein complexes after determining certain core-protein complexes. For our analysis, we used 44 bound-state protein complexes selected from the ZDOCK benchmark dataset ver. 2.0, including some protein pairs none of which generated near-native poses in the docking process. Consequently, after the re-docking process we obtained profiles of interaction fingerprints, some of which yielded near-native poses. The re-docking process involved searching for possible docking poses in a restricted area using the profile of interaction fingerprints. If the profile includes interactions identical to those in the native complex, we obtained near-native docking poses. Accordingly, near-native poses were obtained for all bound-state protein complexes examined here. Application of interaction fingerprints to the re-docking process yielded structures with more native interactions, even when a docking pose, obtained following the initial docking process, contained only a small number of native amino acid interactions. Thus, utilization of the profile of interaction fingerprints in the re-docking process yielded more near-native poses.

AnchorDock for Blind Flexible Docking of Peptides to Proteins.

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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.

Arbitrary protein−protein docking targets biologically relevant interfaces

International Nuclear Information System (INIS)

Martin, Juliette; Lavery, Richard

2012-01-01

Protein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations. In this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking using PEBP (Phosphatidylethanolamine binding

Arbitrary protein−protein docking targets biologically relevant interfaces

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Martin Juliette

2012-05-01

Full Text Available Abstract Background Protein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations. Results In this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking

DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking

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Vakser Ilya A

2011-07-01

Full Text Available Abstract Background Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom pairs in the non-interaction state. Results The study presents a new Distance- and Environment-dependent, Coarse-grained, Knowledge-based (DECK potential for scoring of protein-protein docking predictions. Training sets of protein-protein matches were generated based on bound and unbound forms of proteins taken from the DOCKGROUND resource. Each residue was represented by a pseudo-atom in the geometric center of the side chain. To capture the long-range and the multi-body interactions, residues in different secondary structure elements at protein-protein interfaces were considered as different residue types. Five reference states for the potentials were defined and tested. The optimal reference state was selected and the cutoff effect on the distance-dependent potentials investigated. The potentials were validated on the docking decoys sets, showing better performance than the existing potentials used in scoring of protein-protein docking results. Conclusions A novel residue-based statistical potential for protein-protein docking was developed and validated on docking decoy sets. The results show that the scoring function DECK can successfully identify near-native protein-protein matches and thus is useful in protein docking. In addition to the practical application of the potentials, the study provides insights into the relative utility of the reference states, the scope of the distance dependence, and the coarse-graining of

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

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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.

Sequence alignment reveals possible MAPK docking motifs on HIV proteins.

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Perry Evans

Full Text Available Over the course of HIV infection, virus replication is facilitated by the phosphorylation of HIV proteins by human ERK1 and ERK2 mitogen-activated protein kinases (MAPKs. MAPKs are known to phosphorylate their substrates by first binding with them at a docking site. Docking site interactions could be viable drug targets because the sequences guiding them are more specific than phosphorylation consensus sites. In this study we use multiple bioinformatics tools to discover candidate MAPK docking site motifs on HIV proteins known to be phosphorylated by MAPKs, and we discuss the possibility of targeting docking sites with drugs. Using sequence alignments of HIV proteins of different subtypes, we show that MAPK docking patterns previously described for human proteins appear on the HIV matrix, Tat, and Vif proteins in a strain dependent manner, but are absent from HIV Rev and appear on all HIV Nef strains. We revise the regular expressions of previously annotated MAPK docking patterns in order to provide a subtype independent motif that annotates all HIV proteins. One revision is based on a documented human variant of one of the substrate docking motifs, and the other reduces the number of required basic amino acids in the standard docking motifs from two to one. The proposed patterns are shown to be consistent with in silico docking between ERK1 and the HIV matrix protein. The motif usage on HIV proteins is sufficiently different from human proteins in amino acid sequence similarity to allow for HIV specific targeting using small-molecule drugs.

Identifying Floppy and Rigid Regions in Proteins

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Jacobs, D. J.; Thorpe, M. F.; Kuhn, L. A.

1998-03-01

In proteins it is possible to separate hard covalent forces involving bond lengths and bond angles from other weak forces. We model the microstructure of the protein as a generic bar-joint truss framework, where the hard covalent forces and strong hydrogen bonds are regarded as rigid bar constraints. We study the mechanical stability of proteins using FIRST (Floppy Inclusions and Rigid Substructure Topography) based on a recently developed combinatorial constraint counting algorithm (the 3D Pebble Game), which is a generalization of the 2D pebble game (D. J. Jacobs and M. F. Thorpe, ``Generic Rigidity: The Pebble Game'', Phys. Rev. Lett.) 75, 4051-4054 (1995) for the special class of bond-bending networks (D. J. Jacobs, "Generic Rigidity in Three Dimensional Bond-bending Networks", Preprint Aug (1997)). This approach is useful in identifying rigid motifs and flexible linkages in proteins, and thereby determines the essential degrees of freedom. We will show some preliminary results from the FIRST analysis on the myohemerythrin and lyozyme proteins.

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

KAUST Repository

Oliva, Romina; Chermak, Edrisse; Cavallo, Luigi

2015-01-01

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

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

KAUST Repository

Oliva, Romina

2015-07-01

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

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

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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.

Multiscale weighted colored graphs for protein flexibility and rigidity analysis

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Bramer, David; Wei, Guo-Wei

2018-02-01

Protein structural fluctuation, measured by Debye-Waller factors or B-factors, is known to correlate to protein flexibility and function. A variety of methods has been developed for protein Debye-Waller factor prediction and related applications to domain separation, docking pose ranking, entropy calculation, hinge detection, stability analysis, etc. Nevertheless, none of the current methodologies are able to deliver an accuracy of 0.7 in terms of the Pearson correlation coefficients averaged over a large set of proteins. In this work, we introduce a paradigm-shifting geometric graph model, multiscale weighted colored graph (MWCG), to provide a new generation of computational algorithms to significantly change the current status of protein structural fluctuation analysis. Our MWCG model divides a protein graph into multiple subgraphs based on interaction types between graph nodes and represents the protein rigidity by generalized centralities of subgraphs. MWCGs not only predict the B-factors of protein residues but also accurately analyze the flexibility of all atoms in a protein. The MWCG model is validated over a number of protein test sets and compared with many standard methods. An extensive numerical study indicates that the proposed MWCG offers an accuracy of over 0.8 and thus provides perhaps the first reliable method for estimating protein flexibility and B-factors. It also simultaneously predicts all-atom flexibility in a molecule.

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

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Rushikesh Sable

2015-06-01

Full Text Available 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.

A simple and reliable approach to docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints

International Nuclear Information System (INIS)

Tang, Chun; Clore, G. Marius

2006-01-01

A simple and reliable approach for docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints (as few as three from a single point) in combination with a novel representation for an attractive potential between mapped interaction surfaces is described. Unambiguous assignments of very sparse intermolecular NOEs are obtained using a reverse labeling strategy in which one the components is fully deuterated with the exception of selective protonation of the δ-methyl groups of isoleucine, while the other component is uniformly 13 C-labeled. This labeling strategy can be readily extended to selective protonation of Ala, Leu, Val or Met. The attractive potential is described by a 'reduced' radius of gyration potential applied specifically to a subset of interfacial residues (those with an accessible surface area ≥ 50% in the free proteins) that have been delineated by chemical shift perturbation. Docking is achieved by rigid body minimization on the basis of a target function comprising the sparse NOE distance restraints, a van der Waals repulsion potential and the 'reduced' radius of gyration potential. The method is demonstrated for two protein-protein complexes (EIN-HPr and IIA Glc -HPr) from the bacterial phosphotransferase system. In both cases, starting from 100 different random orientations of the X-ray structures of the free proteins, 100% convergence is achieved to a single cluster (with near identical atomic positions) with an overall backbone accuracy of ∼2 A. The approach described is not limited to NMR, since interfaces can also be mapped by alanine scanning mutagenesis, and sparse intermolecular distance restraints can be derived from double cycle mutagenesis, cross-linking combined with mass spectrometry, or fluorescence energy transfer

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

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Uchikoga Nobuyuki

2010-05-01

Full Text Available Abstract Background 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. Results 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. Conclusions 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.

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

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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.

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

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Strecker, Claas; Meyer, Bernd

2018-05-02

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

A simple and reliable approach to docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints

Energy Technology Data Exchange (ETDEWEB)

Tang, Chun; Clore, G. Marius [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)], E-mail: mariusc@intra.niddk.nih.gov

2006-09-15

A simple and reliable approach for docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints (as few as three from a single point) in combination with a novel representation for an attractive potential between mapped interaction surfaces is described. Unambiguous assignments of very sparse intermolecular NOEs are obtained using a reverse labeling strategy in which one the components is fully deuterated with the exception of selective protonation of the {delta}-methyl groups of isoleucine, while the other component is uniformly {sup 13}C-labeled. This labeling strategy can be readily extended to selective protonation of Ala, Leu, Val or Met. The attractive potential is described by a 'reduced' radius of gyration potential applied specifically to a subset of interfacial residues (those with an accessible surface area {>=} 50% in the free proteins) that have been delineated by chemical shift perturbation. Docking is achieved by rigid body minimization on the basis of a target function comprising the sparse NOE distance restraints, a van der Waals repulsion potential and the 'reduced' radius of gyration potential. The method is demonstrated for two protein-protein complexes (EIN-HPr and IIA{sup Glc}-HPr) from the bacterial phosphotransferase system. In both cases, starting from 100 different random orientations of the X-ray structures of the free proteins, 100% convergence is achieved to a single cluster (with near identical atomic positions) with an overall backbone accuracy of {approx}2 A. The approach described is not limited to NMR, since interfaces can also be mapped by alanine scanning mutagenesis, and sparse intermolecular distance restraints can be derived from double cycle mutagenesis, cross-linking combined with mass spectrometry, or fluorescence energy transfer.

PSOVina: The hybrid particle swarm optimization algorithm for protein-ligand docking.

Science.gov (United States)

Ng, Marcus C K; Fong, Simon; Siu, Shirley W I

2015-06-01

Protein-ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein-ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51-60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein-ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo .

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Solvated protein-DNA docking using HADDOCK

NARCIS (Netherlands)

van Dijk, Marc; Visscher, Koen M; Bonvin, Alexandre M.J.J; Kastritis, Panagiotis L.

2013-01-01

Interfacial water molecules play an important role in many aspects of protein-DNA specificity and recognition. Yet they have been mostly neglected in the computational modeling of these complexes. We present here a solvated docking protocol that allows explicit inclusion of water molecules in the

Designing coarse grained-and atom based-potentials for protein-protein docking

Directory of Open Access Journals (Sweden)

Tobi Dror

2010-11-01

Full Text Available Abstract Background Protein-protein docking is a challenging computational problem in functional genomics, particularly when one or both proteins undergo conformational change(s upon binding. The major challenge is to define a scoring function soft enough to tolerate these changes and specific enough to distinguish between near-native and "misdocked" conformations. Results Using a linear programming (LP technique, we developed two types of potentials: (i Side chain-based and (ii Heavy atom-based. To achieve this we considered a set of 161 transient complexes and generated a large set of putative docked structures (decoys, based on a shape complementarity criterion, for each complex. The demand on the potentials was to yield, for the native (correctly docked structure, a potential energy lower than those of any of the non-native (misdocked structures. We show that the heavy atom-based potentials were able to comply with this requirement but not the side chain-based one. Thus, despite the smaller number of parameters, the capability of heavy atom-based potentials to discriminate between native and "misdocked" conformations is improved relative to those of the side chain-based potentials. The performance of the atom-based potentials was evaluated by a jackknife test on a set of 50 complexes taken from the Zdock2.3 decoys set. Conclusions Our results show that, using the LP approach, we were able to train our potentials using a dataset of transient complexes only the newly developed potentials outperform three other known potentials in this test.

Evaluation of multiple protein docking structures using correctly predicted pairwise subunits

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Esquivel-Rodríguez Juan

2012-03-01

Full Text Available Abstract Background Many functionally important proteins in a cell form complexes with multiple chains. Therefore, computational prediction of multiple protein complexes is an important task in bioinformatics. In the development of multiple protein docking methods, it is important to establish a metric for evaluating prediction results in a reasonable and practical fashion. However, since there are only few works done in developing methods for multiple protein docking, there is no study that investigates how accurate structural models of multiple protein complexes should be to allow scientists to gain biological insights. Methods We generated a series of predicted models (decoys of various accuracies by our multiple protein docking pipeline, Multi-LZerD, for three multi-chain complexes with 3, 4, and 6 chains. We analyzed the decoys in terms of the number of correctly predicted pair conformations in the decoys. Results and conclusion We found that pairs of chains with the correct mutual orientation exist even in the decoys with a large overall root mean square deviation (RMSD to the native. Therefore, in addition to a global structure similarity measure, such as the global RMSD, the quality of models for multiple chain complexes can be better evaluated by using the local measurement, the number of chain pairs with correct mutual orientation. We termed the fraction of correctly predicted pairs (RMSD at the interface of less than 4.0Å as fpair and propose to use it for evaluation of the accuracy of multiple protein docking.

Structure and Sequence Search on Aptamer-Protein Docking

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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.

Gab Docking Proteins in Cardiovascular Disease, Cancer, and Inflammation

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Yoshikazu Nakaoka

2013-01-01

Full Text Available The docking proteins of the Grb2-associated binder (Gab family have emerged as crucial signaling compartments in metazoans. In mammals, the Gab proteins, consisting of Gab1, Gab2, and Gab3, are involved in the amplification and integration of signal transduction evoked by a variety of extracellular stimuli, including growth factors, cytokines, antigens, and other molecules. Gab proteins lack the enzymatic activity themselves; however, when phosphorylated on tyrosine residues, they provide binding sites for multiple Src homology-2 (SH2 domain-containing proteins, such as SH2-containing protein tyrosine phosphatase 2 (SHP2, phosphatidylinositol 3-kinase regulatory subunit p85, phospholipase Cγ, Crk, and GC-GAP. Through these interactions, the Gab proteins transduce signals from activated receptors into pathways with distinct biological functions, thereby contributing to signal diversification. They are known to play crucial roles in numerous physiological processes through their associations with SHP2 and p85. In addition, abnormal Gab protein signaling has been linked to human diseases including cancer, cardiovascular disease, and inflammatory disorders. In this paper, we provide an overview of the structure, effector functions, and regulation of the Gab docking proteins, with a special focus on their associations with cardiovascular disease, cancer, and inflammation.

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

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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.

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

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Hongjian Li

Full Text Available 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

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

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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

Rigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein Allostery.

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Robert Kalescky

2016-04-01

Full Text Available Intra-protein information is transmitted over distances via allosteric processes. This ubiquitous protein process allows for protein function changes due to ligand binding events. Understanding protein allostery is essential to understanding protein functions. In this study, allostery in the second PDZ domain (PDZ2 in the human PTP1E protein is examined as model system to advance a recently developed rigid residue scan method combining with configurational entropy calculation and principal component analysis. The contributions from individual residues to whole-protein dynamics and allostery were systematically assessed via rigid body simulations of both unbound and ligand-bound states of the protein. The entropic contributions of individual residues to whole-protein dynamics were evaluated based on covariance-based correlation analysis of all simulations. The changes of overall protein entropy when individual residues being held rigid support that the rigidity/flexibility equilibrium in protein structure is governed by the La Châtelier's principle of chemical equilibrium. Key residues of PDZ2 allostery were identified with good agreement with NMR studies of the same protein bound to the same peptide. On the other hand, the change of entropic contribution from each residue upon perturbation revealed intrinsic differences among all the residues. The quasi-harmonic and principal component analyses of simulations without rigid residue perturbation showed a coherent allosteric mode from unbound and bound states, respectively. The projection of simulations with rigid residue perturbation onto coherent allosteric modes demonstrated the intrinsic shifting of ensemble distributions supporting the population-shift theory of protein allostery. Overall, the study presented here provides a robust and systematic approach to estimate the contribution of individual residue internal motion to overall protein dynamics and allostery.

ReFlexIn: a flexible receptor protein-ligand docking scheme evaluated on HIV-1 protease.

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Simon Leis

Full Text Available For many targets of pharmaceutical importance conformational changes of the receptor protein are relevant during the ligand binding process. A new docking approach, ReFlexIn (Receptor Flexibility by Interpolation, that combines receptor flexibility with the computationally efficient potential grid representation of receptor molecules has been evaluated on the retroviral HIV-1 (Human Immunodeficiency Virus 1 protease system. An approximate inclusion of receptor flexibility is achieved by using interpolation between grid representations of individual receptor conformations. For the retroviral protease the method was tested on an ensemble of protease structures crystallized in the presence of different ligands and on a set of structures obtained from morphing between the unbound and a ligand-bound protease structure. Docking was performed on ligands known to bind to the protease and several non-binders. For the binders the ReFlexIn method yielded in almost all cases ligand placements in similar or closer agreement with experiment than docking to any of the ensemble members without degrading the discrimination with respect to non-binders. The improved docking performance compared to docking to rigid receptors allows for systematic virtual screening applications at very small additional computational cost.

Calculating ensemble averaged descriptions of protein rigidity without sampling.

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González, Luis C; Wang, Hui; Livesay, Dennis R; Jacobs, Donald J

2012-01-01

Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG) algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology. We have developed a mean field Virtual Pebble Game (VPG) that represents the ensemble of networks by a single effective network. That is, all possible number of distance constraints (or bars) that can form between a pair of rigid bodies is replaced by the average number. The resulting effective network is viewed as having weighted edges, where the weight of an edge quantifies its capacity to absorb degrees of freedom. The VPG is interpreted as a flow problem on this effective network, which eliminates the need to sample. Across a nonredundant dataset of 272 protein structures, we apply the VPG to proteins for the first time. Our results show numerically and visually that the rigidity characterizations of the VPG accurately reflect the ensemble averaged [Formula: see text] properties. This result positions the VPG as an efficient alternative to understand the mechanical role that chemical interactions play in maintaining protein stability.

Complete cDNA sequence coding for human docking protein

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Hortsch, M; Labeit, S; Meyer, D I

1988-01-11

Docking protein (DP, or SRP receptor) is a rough endoplasmic reticulum (ER)-associated protein essential for the targeting and translocation of nascent polypeptides across this membrane. It specifically interacts with a cytoplasmic ribonucleoprotein complex, the signal recognition particle (SRP). The nucleotide sequence of cDNA encoding the entire human DP and its deduced amino acid sequence are given.

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

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Ragul Gowthaman

Full Text Available 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

Calculating ensemble averaged descriptions of protein rigidity without sampling.

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Luis C González

Full Text Available Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology. We have developed a mean field Virtual Pebble Game (VPG that represents the ensemble of networks by a single effective network. That is, all possible number of distance constraints (or bars that can form between a pair of rigid bodies is replaced by the average number. The resulting effective network is viewed as having weighted edges, where the weight of an edge quantifies its capacity to absorb degrees of freedom. The VPG is interpreted as a flow problem on this effective network, which eliminates the need to sample. Across a nonredundant dataset of 272 protein structures, we apply the VPG to proteins for the first time. Our results show numerically and visually that the rigidity characterizations of the VPG accurately reflect the ensemble averaged [Formula: see text] properties. This result positions the VPG as an efficient alternative to understand the mechanical role that chemical interactions play in maintaining protein stability.

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

OpenAIRE

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

2016-01-01

International audience; Motivation: 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 pre...

Evaluation of Docking Target Functions by the Comprehensive Investigation of Protein-Ligand Energy Minima.

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Oferkin, Igor V; Katkova, Ekaterina V; Sulimov, Alexey V; Kutov, Danil C; Sobolev, Sergey I; Voevodin, Vladimir V; Sulimov, Vladimir B

2015-01-01

The adequate choice of the docking target function impacts the accuracy of the ligand positioning as well as the accuracy of the protein-ligand binding energy calculation. To evaluate a docking target function we compared positions of its minima with the experimentally known pose of the ligand in the protein active site. We evaluated five docking target functions based on either the MMFF94 force field or the PM7 quantum-chemical method with or without implicit solvent models: PCM, COSMO, and SGB. Each function was tested on the same set of 16 protein-ligand complexes. For exhaustive low-energy minima search the novel MPI parallelized docking program FLM and large supercomputer resources were used. Protein-ligand binding energies calculated using low-energy minima were compared with experimental values. It was demonstrated that the docking target function on the base of the MMFF94 force field in vacuo can be used for discovery of native or near native ligand positions by finding the low-energy local minima spectrum of the target function. The importance of solute-solvent interaction for the correct ligand positioning is demonstrated. It is shown that docking accuracy can be improved by replacement of the MMFF94 force field by the new semiempirical quantum-chemical PM7 method.

Evaluation of Docking Target Functions by the Comprehensive Investigation of Protein-Ligand Energy Minima

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Igor V. Oferkin

2015-01-01

Full Text Available The adequate choice of the docking target function impacts the accuracy of the ligand positioning as well as the accuracy of the protein-ligand binding energy calculation. To evaluate a docking target function we compared positions of its minima with the experimentally known pose of the ligand in the protein active site. We evaluated five docking target functions based on either the MMFF94 force field or the PM7 quantum-chemical method with or without implicit solvent models: PCM, COSMO, and SGB. Each function was tested on the same set of 16 protein-ligand complexes. For exhaustive low-energy minima search the novel MPI parallelized docking program FLM and large supercomputer resources were used. Protein-ligand binding energies calculated using low-energy minima were compared with experimental values. It was demonstrated that the docking target function on the base of the MMFF94 force field in vacuo can be used for discovery of native or near native ligand positions by finding the low-energy local minima spectrum of the target function. The importance of solute-solvent interaction for the correct ligand positioning is demonstrated. It is shown that docking accuracy can be improved by replacement of the MMFF94 force field by the new semiempirical quantum-chemical PM7 method.

Parallel Evolutionary Optimization Algorithms for Peptide-Protein Docking

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Poluyan, Sergey; Ershov, Nikolay

2018-02-01

In this study we examine the possibility of using evolutionary optimization algorithms in protein-peptide docking. We present the main assumptions that reduce the docking problem to a continuous global optimization problem and provide a way of using evolutionary optimization algorithms. The Rosetta all-atom force field was used for structural representation and energy scoring. We describe the parallelization scheme and MPI/OpenMP realization of the considered algorithms. We demonstrate the efficiency and the performance for some algorithms which were applied to a set of benchmark tests.

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.

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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.

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Didier Barradas-Bautista

Full Text Available 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.

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

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

2013-01-01

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

Systematic Protein-Protein Docking and Molecular Dynamics Studies of HIV-1 gp120 and CD4: Insights for New Drug Development

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M. Rizman-Idid

2011-12-01

Full Text Available Background and the purpose of the study: The interactions between HIV-1 gp120 and mutated CD4 proteins were investigated in order to identify a lead structure for therapy based on competitive blocking of the HIV binding receptor for human T-cells. Crystal structures of HIV gp120-CD4 complexes reveal a close interaction of the virus receptor with CD4 Phe43, which is embedded in a pocket of the virus protein.Methods: This study applies computer simulations to determine the best binding of amino acid 43 CD4 mutants to HIV gp120. Besides natural CD4, three mutants carrying alternate aromatic residues His, Trp and Tyr at position 43 were investigated. Several docking programs were applied on isolated proteins based on selected crystal structures of gp120-CD4 complexes, as well as a 5 ns molecular dynamics study on the protein complexes. The initial structures were minimized in Gromacs to avoid crystal packing effects, and then subjected to docking experiments using AutoDock4, FireDock, ClusPro and ZDock. In molecular dynamics, the Gibbs free binding energy was calculated for the gp120-CD4 complexes. The docking outputs were analyzed on energy within the respective docking software.Results and conclusion: Visualization and hydrogen bonding analysis were performed using the Swiss-PdbViewer. Strong binding to HIV gp120 can be achieved with an extended aromatic group (Trp. However, the sterical demand of the interaction affects the binding kinetics. In conclusion, a ligand for an efficient blocking of HIV gp120 should involve an extended but conformational flexible aromatic group, i.e. a biphenyl. A docking study on biphenylalanine-43 confirms this expectation

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

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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 server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. PMID:28521030

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

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Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

2018-03-14

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

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

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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/.

Fast and anisotropic flexibility-rigidity index for protein flexibility and fluctuation analysis

Energy Technology Data Exchange (ETDEWEB)

Opron, Kristopher [Department of Biochemistry and Molecular Biology, Michigan State University, Michigan 48824 (United States); Xia, Kelin [Department of Mathematics, Michigan State University, Michigan 48824 (United States); Wei, Guo-Wei, E-mail: wei@math.msu.edu [Department of Biochemistry and Molecular Biology, Michigan State University, Michigan 48824 (United States); Department of Mathematics, Michigan State University, Michigan 48824 (United States); Department of Electrical and Computer Engineering, Michigan State University, Michigan 48824 (United States)

2014-06-21

Protein structural fluctuation, typically measured by Debye-Waller factors, or B-factors, is a manifestation of protein flexibility, which strongly correlates to protein function. The flexibility-rigidity index (FRI) is a newly proposed method for the construction of atomic rigidity functions required in the theory of continuum elasticity with atomic rigidity, which is a new multiscale formalism for describing excessively large biomolecular systems. The FRI method analyzes protein rigidity and flexibility and is capable of predicting protein B-factors without resorting to matrix diagonalization. A fundamental assumption used in the FRI is that protein structures are uniquely determined by various internal and external interactions, while the protein functions, such as stability and flexibility, are solely determined by the structure. As such, one can predict protein flexibility without resorting to the protein interaction Hamiltonian. Consequently, bypassing the matrix diagonalization, the original FRI has a computational complexity of O(N{sup 2}). This work introduces a fast FRI (fFRI) algorithm for the flexibility analysis of large macromolecules. The proposed fFRI further reduces the computational complexity to O(N). Additionally, we propose anisotropic FRI (aFRI) algorithms for the analysis of protein collective dynamics. The aFRI algorithms permit adaptive Hessian matrices, from a completely global 3N × 3N matrix to completely local 3 × 3 matrices. These 3 × 3 matrices, despite being calculated locally, also contain non-local correlation information. Eigenvectors obtained from the proposed aFRI algorithms are able to demonstrate collective motions. Moreover, we investigate the performance of FRI by employing four families of radial basis correlation functions. Both parameter optimized and parameter-free FRI methods are explored. Furthermore, we compare the accuracy and efficiency of FRI with some established approaches to flexibility analysis, namely

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

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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.

QSAR Study on Caffeine Derivatives Docked on Poly(ARNA Polymerase Protein Cid1

Directory of Open Access Journals (Sweden)

Teodora E. Harsa

2016-06-01

Full Text Available Caffeine is the most commonly ingested alkylxantine and is recognized as a psycho-stimulant. It improves some aspects of cognitive performance, however it reduces the cerebral blood flow both in animals and humans. In this paper a QSAR study on caffeine derivatives, docked on the Poly(ARNA polymerase protein cid1, is reported. A set of forty caffeine derivatives, downloaded from PubChem, was modeled, within the hypermolecule strategy; the predicted activity was LD50 and prediction was done on similarity clusters with the leaders chosen as the best docked ligands on the Poly(ARNA polymerase protein cid1. It was concluded that LD50 of the studied caffeines is not influenced by their binding to the target protein. This work is licensed under a Creative Commons Attribution 4.0 International License.

Matrix rigidity regulates cancer cell growth by modulating cellular metabolism and protein synthesis.

Directory of Open Access Journals (Sweden)

Robert W Tilghman

Full Text Available Tumor cells in vivo encounter diverse types of microenvironments both at the site of the primary tumor and at sites of distant metastases. Understanding how the various mechanical properties of these microenvironments affect the biology of tumor cells during disease progression is critical in identifying molecular targets for cancer therapy.This study uses flexible polyacrylamide gels as substrates for cell growth in conjunction with a novel proteomic approach to identify the properties of rigidity-dependent cancer cell lines that contribute to their differential growth on soft and rigid substrates. Compared to cells growing on more rigid/stiff substrates (>10,000 Pa, cells on soft substrates (150-300 Pa exhibited a longer cell cycle, due predominantly to an extension of the G1 phase of the cell cycle, and were metabolically less active, showing decreased levels of intracellular ATP and a marked reduction in protein synthesis. Using stable isotope labeling of amino acids in culture (SILAC and mass spectrometry, we measured the rates of protein synthesis of over 1200 cellular proteins under growth conditions on soft and rigid/stiff substrates. We identified cellular proteins whose syntheses were either preferentially inhibited or preserved on soft matrices. The former category included proteins that regulate cytoskeletal structures (e.g., tubulins and glycolysis (e.g., phosphofructokinase-1, whereas the latter category included proteins that regulate key metabolic pathways required for survival, e.g., nicotinamide phosphoribosyltransferase, a regulator of the NAD salvage pathway.The cellular properties of rigidity-dependent cancer cells growing on soft matrices are reminiscent of the properties of dormant cancer cells, e.g., slow growth rate and reduced metabolism. We suggest that the use of relatively soft gels as cell culture substrates would allow molecular pathways to be studied under conditions that reflect the different mechanical

Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs

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Ruan Jishou

2007-04-01

Full Text Available Abstract Background Traditionally, it is believed that the native structure of a protein corresponds to a global minimum of its free energy. However, with the growing number of known tertiary (3D protein structures, researchers have discovered that some proteins can alter their structures in response to a change in their surroundings or with the help of other proteins or ligands. Such structural shifts play a crucial role with respect to the protein function. To this end, we propose a machine learning method for the prediction of the flexible/rigid regions of proteins (referred to as FlexRP; the method is based on a novel sequence representation and feature selection. Knowledge of the flexible/rigid regions may provide insights into the protein folding process and the 3D structure prediction. Results The flexible/rigid regions were defined based on a dataset, which includes protein sequences that have multiple experimental structures, and which was previously used to study the structural conservation of proteins. Sequences drawn from this dataset were represented based on feature sets that were proposed in prior research, such as PSI-BLAST profiles, composition vector and binary sequence encoding, and a newly proposed representation based on frequencies of k-spaced amino acid pairs. These representations were processed by feature selection to reduce the dimensionality. Several machine learning methods for the prediction of flexible/rigid regions and two recently proposed methods for the prediction of conformational changes and unstructured regions were compared with the proposed method. The FlexRP method, which applies Logistic Regression and collocation-based representation with 95 features, obtained 79.5% accuracy. The two runner-up methods, which apply the same sequence representation and Support Vector Machines (SVM and Naïve Bayes classifiers, obtained 79.2% and 78.4% accuracy, respectively. The remaining considered methods are

Na(+),K (+)-ATPase as a docking station: protein-protein complexes of the Na(+),K (+)-ATPase.

Science.gov (United States)

Reinhard, Linda; Tidow, Henning; Clausen, Michael J; Nissen, Poul

2013-01-01

The Na(+),K(+)-ATPase, or sodium pump, is well known for its role in ion transport across the plasma membrane of animal cells. It carries out the transport of Na(+) ions out of the cell and of K(+) ions into the cell and thus maintains electrolyte and fluid balance. In addition to the fundamental ion-pumping function of the Na(+),K(+)-ATPase, recent work has suggested additional roles for Na(+),K(+)-ATPase in signal transduction and biomembrane structure. Several signaling pathways have been found to involve Na(+),K(+)-ATPase, which serves as a docking station for a fast-growing number of protein interaction partners. In this review, we focus on Na(+),K(+)-ATPase as a signal transducer, but also briefly discuss other Na(+),K(+)-ATPase protein-protein interactions, providing a comprehensive overview of the diverse signaling functions ascribed to this well-known enzyme.

NPPD: A Protein-Protein Docking Scoring Function Based on Dyadic Differences in Networks of Hydrophobic and Hydrophilic Amino Acid Residues

Directory of Open Access Journals (Sweden)

Edward S. C. Shih

2015-03-01

Full Text Available Protein-protein docking (PPD predictions usually rely on the use of a scoring function to rank docking models generated by exhaustive sampling. To rank good models higher than bad ones, a large number of scoring functions have been developed and evaluated, but the methods used for the computation of PPD predictions remain largely unsatisfactory. Here, we report a network-based PPD scoring function, the NPPD, in which the network consists of two types of network nodes, one for hydrophobic and the other for hydrophilic amino acid residues, and the nodes are connected when the residues they represent are within a certain contact distance. We showed that network parameters that compute dyadic interactions and those that compute heterophilic interactions of the amino acid networks thus constructed allowed NPPD to perform well in a benchmark evaluation of 115 PPD scoring functions, most of which, unlike NPPD, are based on some sort of protein-protein interaction energy. We also showed that NPPD was highly complementary to these energy-based scoring functions, suggesting that the combined use of conventional scoring functions and NPPD might significantly improve the accuracy of current PPD predictions.

Interaction of the minocycline with extracelluar protein and intracellular protein by multi-spectral techniques and molecular docking

Science.gov (United States)

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.

Defining the limits of homology modeling in information-driven protein docking

NARCIS (Netherlands)

Garcia Lopes Maia Rodrigues, João; Melquiond, A S J; Karaca, E; Trellet, M; van Dijk, M; van Zundert, G C P; Schmitz, C; de Vries, S J; Bordogna, A; Bonati, L; Kastritis, P L; Bonvin, Alexandre M J J; Garcia Lopes Maia Rodrigues, João

2013-01-01

Information-driven docking is currently one of the most successful approaches to obtain structural models of protein interactions as demonstrated in the latest round of CAPRI. While various experimental and computational techniques can be used to retrieve information about the binding mode, the

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Organization of functional domains in the docking protein p130Cas

International Nuclear Information System (INIS)

Nasertorabi, Fariborz; Garcia-Guzman, Miguel; Briknarova, Klara; Larsen, Elise; Havert, Marnie L.; Vuori, Kristiina; Ely, Kathryn R.

2004-01-01

The docking protein p130Cas becomes phosphorylated upon cell adhesion to extracellular matrix proteins, and is thought to play an essential role in cell transformation. Cas transmits signals through interactions with the Src-homology 3 (SH3) and Src-homology 2 domains of FAK or v-Crk signaling molecules, or with 14-3-3 protein, as well as phosphatases PTP1B and PTP-PEST. The large (130 kDa), multi-domain Cas molecule contains an SH3 domain, a Src-binding domain, a serine-rich protein interaction region, and a C-terminal region that participates in protein interactions implicated in antiestrogen resistance in breast cancer. In this study, as part of a long-term goal to examine the protein interactions of Cas by X-ray crystallography and nuclear magnetic resonance spectroscopy, molecular constructs were designed to express two adjacent domains, the serine-rich domain and the Src-binding domain, that each participate in intermolecular contacts dependent on protein phosphorylation. The protein products are soluble, homogeneous, monodisperse, and highly suitable for structural studies to define the role of Cas in integrin-mediated cell signaling

A collaborative filtering approach for protein-protein docking scoring functions.

Science.gov (United States)

Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne

2011-04-22

A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

KAUST Repository

Lensink, Marc F.; Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen-You; Schneidman-Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez-Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Rie Lee, Gyu; Seok, Chaok; Qin, Sanbo; Zhou, Huan-Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie-Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaë l A.G.; Bates, Paul A.; Ben-Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Franç oise; Guerois, Raphaë l; Vangone, Anna; Rodrigues, Joã o P.G.L.M.; van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S.J.; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M.J.J.; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung-Rae; Roy, Amit; Han, Xusi; Esquivel-Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero-Durana, Miguel; Jimé nez-Garcí a, Brian; Moal, Iain H.; Fé rnandez-Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey; Wodak, Shoshana J.

2016-01-01

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. © 2016 Wiley Periodicals, Inc.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

KAUST Repository

Lensink, Marc F.

2016-04-28

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. © 2016 Wiley Periodicals, Inc.

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

Science.gov (United States)

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

2018-05-08

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

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling : A CASP-CAPRI experiment

NARCIS (Netherlands)

Lensink, Marc F.; Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen You; Schneidman-Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez-Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Rie Lee, Gyu; Seok, Chaok; Qin, Sanbo; Zhou, Huan Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaël A G; Bates, Paul A.; Ben-Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Françoise; Guerois, Raphaël; Vangone, Anna; Garcia Lopes Maia Rodrigues, João; van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S J; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M J J; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung Rae; Roy, Amit; Han, Xusi; Esquivel-Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero-Durana, Miguel; Jiménez-García, Brian; Moal, Iain H.; Férnandez-Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey; Wodak, Shoshana J.

2016-01-01

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

NARCIS (Netherlands)

Lensink, Marc F.; Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen You; Schneidman-Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez-Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Lee, Gyu Rie; Seok, Chaok; Qin, Sanbo; Zhou, Huan Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaël A.G.; Bates, Paul A.; Ben-Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Françoise; Guerois, Raphaël; Vangone, Anna; Rodrigues, João P.G.L.M.; Van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S.J.; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M.J.J.; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung Rae; Roy, Amit; Han, Xusi; Esquivel-Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero-Durana, Miguel; Jiménez-García, Brian; Moal, Iain H.; Férnandez-Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey; Wodak, Shoshana J.

2016-01-01

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014.

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

Energy Technology Data Exchange (ETDEWEB)

Morishita, Kazushge; Anh Suong, Dang Ngoc; Yoshida, Hideki; Yamaguchi, Masamitsu, E-mail: myamaguc@kit.ac.jp

2017-05-15

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 sac 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.

Conformational Rigidity and Protein Dynamics at Distinct Timescales Regulate PTP1B Activity and Allostery.

Science.gov (United States)

Choy, Meng S; Li, Yang; Machado, Luciana E S F; Kunze, Micha B A; Connors, Christopher R; Wei, Xingyu; Lindorff-Larsen, Kresten; Page, Rebecca; Peti, Wolfgang

2017-02-16

Protein function originates from a cooperation of structural rigidity, dynamics at different timescales, and allostery. However, how these three pillars of protein function are integrated is still only poorly understood. Here we show how these pillars are connected in Protein Tyrosine Phosphatase 1B (PTP1B), a drug target for diabetes and cancer that catalyzes the dephosphorylation of numerous substrates in essential signaling pathways. By combining new experimental and computational data on WT-PTP1B and ≥10 PTP1B variants in multiple states, we discovered a fundamental and evolutionarily conserved CH/π switch that is critical for positioning the catalytically important WPD loop. Furthermore, our data show that PTP1B uses conformational and dynamic allostery to regulate its activity. This shows that both conformational rigidity and dynamics are essential for controlling protein activity. This connection between rigidity and dynamics at different timescales is likely a hallmark of all enzyme function. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Sony Malhotra

Full Text Available 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.

Specificity and affinity quantification of protein-protein interactions.

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Yan, Zhiqiang; Guo, Liyong; Hu, Liang; Wang, Jin

2013-05-01

Most biological processes are mediated by the protein-protein interactions. Determination of the protein-protein structures and insight into their interactions are vital to understand the mechanisms of protein functions. Currently, compared with the isolated protein structures, only a small fraction of protein-protein structures are experimentally solved. Therefore, the computational docking methods play an increasing role in predicting the structures and interactions of protein-protein complexes. The scoring function of protein-protein interactions is the key responsible for the accuracy of the computational docking. Previous scoring functions were mostly developed by optimizing the binding affinity which determines the stability of the protein-protein complex, but they are often lack of the consideration of specificity which determines the discrimination of native protein-protein complex against competitive ones. We developed a scoring function (named as SPA-PP, specificity and affinity of the protein-protein interactions) by incorporating both the specificity and affinity into the optimization strategy. The testing results and comparisons with other scoring functions show that SPA-PP performs remarkably on both predictions of binding pose and binding affinity. Thus, SPA-PP is a promising quantification of protein-protein interactions, which can be implemented into the protein docking tools and applied for the predictions of protein-protein structure and affinity. The algorithm is implemented in C language, and the code can be downloaded from http://dl.dropbox.com/u/1865642/Optimization.cpp.

MOLECULAR DOCKING AND DYNAMICS STUDIES ON THE PROTEIN-PROTEIN INTERACTIONS OF ELECTRICALLY ACTIVE PILIN NANOWIRES OF GEOBACTER SULFURREDUCENS.

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D. Jeya Sundara Sharmila1 *

2017-06-01

Full Text Available Molecular interactions are key aspects in biological recognitions applicable in nano/micro systems. Bacterial nanowires are pilus filament based structures that can conduct electrons. The transport of electron is proposed to be facilitated by filamentous fibers made up of polymeric assemblies of proteins called pilin. Geobacter sulfurreducens is capable of delivering electrons through extracellular electron transport (EET by employing conductive nanowires, which are pilin proteins composed of type IV subunit PilA. Protein-protein interactions play an important role in the stabilization of the pilin nanowire assembly complex and it contains transmembrane (TM domain. In current study, protein-protein docking and multiple molecular dynamic (MD simulations were performed to understand the binding mode of pilin nanowires. The MD result explains the conformational behavior and folding of pilin nanowires in water environment in different time scale duration 20, 5, 5, 10 and 20ns (total of 60ns. Direct hydrogen bonds and water mediated hydrogen bonds that play a crucial role during the simulation were investigated. The conformational state, folding, end-toend distance profile and hydrogen bonding behavior had indicated that the Geobacter sulfurreducens pilin nanowires have electrical conductivity properties.

Modeling complexes of modeled proteins.

Science.gov (United States)

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

2017-03-01

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

Application of the docking program SOL for CSAR benchmark.

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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.

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

Science.gov (United States)

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.

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

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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.

Collective Excitations in Protein as a Measure of Balance Between its Softness and Rigidity

International Nuclear Information System (INIS)

Shrestha, Utsab R.; Bhowmik, Debsindhu; Van Delinder, Kurt W.; Mamontov, Eugene; O’Neill, Hugh

2017-01-01

Here, we elucidate the protein activity from the perspective of protein softness and flexibility by studying the collective phonon-like excitations in a globular protein, human serum albumin (HSA), and taking advantage of the state-of-the-art inelastic X-ray scattering (IXS) technique. Such excitations demonstrate that the protein becomes softer upon thermal denaturation due to disruption of weak noncovalent bonds. On the other hand, no significant change in the local excitations is detected in ligand- (drugs) bound HSA compared to the ligand-free HSA. These results clearly suggest that the protein conformational flexibility and rigidity are balanced by the native protein structure for biological activity.

Collective Excitations in Protein as a Measure of Balance Between its Softness and Rigidity

Energy Technology Data Exchange (ETDEWEB)

Shrestha, Utsab R. [Wayne State Univ., Detroit, MI (United States). Dept. of Physics and Astronomy; Bhowmik, Debsindhu [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computational Science and Engineering Division; Van Delinder, Kurt W. [Wayne State Univ., Detroit, MI (United States). Dept. of Physics and Astronomy; Mamontov, Eugene [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Chemical and Engineering Materials Division; O’Neill, Hugh [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biology and Soft Matter Division; Zhang, Qiu [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biology and Soft Matter Division; Alatas, Ahmet [Argonne National Lab. (ANL), Argonne, IL (United States). Advanced Photon Source; Chu, Xiang-Qiang [Wayne State Univ., Detroit, MI (United States). Dept. of Physics and Astronomy

2017-01-12

Here, we elucidate the protein activity from the perspective of protein softness and flexibility by studying the collective phonon-like excitations in a globular protein, human serum albumin (HSA), and taking advantage of the state-of-the-art inelastic X-ray scattering (IXS) technique. Such excitations demonstrate that the protein becomes softer upon thermal denaturation due to disruption of weak noncovalent bonds. On the other hand, no significant change in the local excitations is detected in ligand- (drugs) bound HSA compared to the ligand-free HSA. These results clearly suggest that the protein conformational flexibility and rigidity are balanced by the native protein structure for biological activity.

Leptospira borgpetersenii hybrid leucine-rich repeat protein: Cloning and expression, immunogenic identification and molecular docking evaluation.

Science.gov (United States)

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

Incorporation of protein flexibility and conformational energy penalties in docking screens to improve ligand discovery

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Fischer, Marcus; Coleman, Ryan G.; Fraser, James S.; Shoichet, Brian K.

2014-07-01

Proteins fluctuate between alternative conformations, which presents a challenge for ligand discovery because such flexibility is difficult to treat computationally owing to problems with conformational sampling and energy weighting. Here we describe a flexible docking method that samples and weights protein conformations using experimentally derived conformations as a guide. The crystallographically refined occupancies of these conformations, which are observable in an apo receptor structure, define energy penalties for docking. In a large prospective library screen, we identified new ligands that target specific receptor conformations of a cavity in cytochrome c peroxidase, and we confirm both ligand pose and associated receptor conformation predictions by crystallography. The inclusion of receptor flexibility led to ligands with new chemotypes and physical properties. By exploiting experimental measures of loop and side-chain flexibility, this method can be extended to the discovery of new ligands for hundreds of targets in the Protein Data Bank for which similar experimental information is available.

Sensitivity of molecular docking to induced fit effects in influenza virus neuraminidase

Science.gov (United States)

Birch, Louise; Murray, Christopher W.; Hartshorn, Michael J.; Tickle, Ian J.; Verdonk, Marcel L.

2002-12-01

Many proteins undergo small side chain or even backbone movements on binding of different ligands into the same protein structure. This is known as induced fit and is potentially problematic for virtual screening of databases against protein targets. In this report we investigate the limits of the rigid protein approximation used by the docking program, GOLD, through cross-docking using protein structures of influenza neuraminidase. Neuraminidase is known to exhibit small but significant induced fit effects on ligand binding. Some neuraminidase crystal structures caused concern due to the bound ligand conformation and GOLD performed poorly on these complexes. A `clean' set, which contained unique, unambiguous complexes, was defined. For this set, the lowest energy structure was correctly docked (i.e. RMSD < 1.5 Å away from the crystal reference structure) in 84% of proteins, and the most promiscuous protein (1mwe) was able to dock all 15 ligands accurately including those that normally required an induced fit movement. This is considerably better than the 70% success rate seen with GOLD against general validation sets. Inclusion of specific water molecules involved in water-mediated hydrogen bonds did not significantly improve the docking performance for ligands that formed water-mediated contacts but it did prevent docking of ligands that displaced these waters. Our data supports the use of a single protein structure for virtual screening with GOLD in some applications involving induced fit effects, although care must be taken to identify the protein structure that performs best against a wide variety of ligands. The performance of GOLD was significantly better than the GOLD implementation of ChemScore and the reasons for this are discussed. Overall, GOLD has shown itself to be an extremely good, robust docking program for this system.

The focal adhesion-associated proteins DOCK5 and GIT2 comprise a rheostat in control of epithelial invasion

DEFF Research Database (Denmark)

Frank, Scott R; Köllmann, C P; van Lidth de Jeude, J F

2017-01-01

DOCK proteins are guanine nucleotide exchange factors for Rac and Cdc42 GTPases. DOCK1 is the founding member of the family and acts downstream of integrins via the canonical Crk-p130Cas complex to activate Rac GTPases in numerous contexts. In contrast, DOCK5, which possesses the greatest similar......:10.1038/onc.2016.345....

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

Science.gov (United States)

Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

2017-08-01

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

A Drosophila protein-tyrosine phosphatase associates with an adapter protein required for axonal guidance.

Science.gov (United States)

Clemens, J C; Ursuliak, Z; Clemens, K K; Price, J V; Dixon, J E

1996-07-19

We have used the yeast two-hybrid system to isolate a novel Drosophila adapter protein, which interacts with the Drosophila protein-tyrosine phosphatase (PTP) dPTP61F. Absence of this protein in Drosophila causes the mutant photoreceptor axon phenotype dreadlocks (dock) (Garrity, P. A., Rao, Y., Salecker, I., and Zipursky, S. L.(1996) Cell 85, 639-650). Dock is similar to the mammalian oncoprotein Nck and contains three Src homology 3 (SH3) domains and one Src homology 2 (SH2) domain. The interaction of dPTP61F with Dock was confirmed in vivo by immune precipitation experiments. A sequence containing five PXXP motifs from the non-catalytic domain of the PTP is sufficient for interaction with Dock. This suggests that binding to the PTP is mediated by one or more of the SH3 domains of Dock. Immune precipitations of Dock also co-precipitate two tyrosine-phosphorylated proteins having molecular masses of 190 and 145 kDa. Interactions between Dock and these tyrosine-phosphorylated proteins are likely mediated by the Dock SH2 domain. These findings identify potential signal-transducing partners of Dock and propose a role for dPTP61F and the unidentified phosphoproteins in axonal guidance.

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

OpenAIRE

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 speci...

Insight into the intermolecular recognition mechanism between Keap1 and IKKβ combining homology modelling, protein-protein docking, molecular dynamics simulations and virtual alanine mutation.

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Zheng-Yu Jiang

Full Text Available Degradation of certain proteins through the ubiquitin-proteasome pathway is a common strategy taken by the key modulators responsible for stress responses. Kelch-like ECH-associated protein-1(Keap1, a substrate adaptor component of the Cullin3 (Cul3-based ubiquitin E3 ligase complex, mediates the ubiquitination of two key modulators, NF-E2-related factor 2 (Nrf2 and IκB kinase β (IKKβ, which are involved in the redox control of gene transcription. However, compared to the Keap1-Nrf2 protein-protein interaction (PPI, the intermolecular recognition mechanism of Keap1 and IKKβ has been poorly investigated. In order to explore the binding pattern between Keap1 and IKKβ, the PPI model of Keap1 and IKKβ was investigated. The structure of human IKKβ was constructed by means of the homology modeling method and using reported crystal structure of Xenopus laevis IKKβ as the template. A protein-protein docking method was applied to develop the Keap1-IKKβ complex model. After the refinement and visual analysis of docked proteins, the chosen pose was further optimized through molecular dynamics simulations. The resulting structure was utilized to conduct the virtual alanine mutation for the exploration of hot-spots significant for the intermolecular interaction. Overall, our results provided structural insights into the PPI model of Keap1-IKKβ and suggest that the substrate specificity of Keap1 depend on the interaction with the key tyrosines, namely Tyr525, Tyr574 and Tyr334. The study presented in the current project may be useful to design molecules that selectively modulate Keap1. The selective recognition mechanism of Keap1 with IKKβ or Nrf2 will be helpful to further know the crosstalk between NF-κB and Nrf2 signaling.

DockingShop: A Tool for Interactive Molecular Docking

Energy Technology Data Exchange (ETDEWEB)

Lu, Ting-Cheng; Max, Nelson L.; Ding, Jinhui; Bethel, E. Wes; Crivelli, Silvia N.

2005-04-24

Given two independently determined molecular structures, the molecular docking problem predicts the bound association, or best fit between them, while allowing for conformational changes of the individual molecules during construction of a molecular complex. Docking Shop is an integrated environment that permits interactive molecular docking by navigating a ligand or protein to an estimated binding site of a receptor with real-time graphical feedback of scoring factors as visual guides. Our program can be used to create initial configurations for a protein docking prediction process. Its output--the structure of aprotein-ligand or protein-protein complex--may serve as an input for aprotein docking algorithm, or an optimization process. This tool provides molecular graphics interfaces for structure modeling, interactive manipulation, navigation, optimization, and dynamic visualization to aid users steer the prediction process using their biological knowledge.

Generation of 3D templates of active sites of proteins with rigid prosthetic groups.

Science.gov (United States)

Nebel, Jean-Christophe

2006-05-15

With the increasing availability of protein structures, the generation of biologically meaningful 3D patterns from the simultaneous alignment of several protein structures is an exciting prospect: active sites could be better understood, protein functions and protein 3D structures could be predicted more accurately. Although patterns can already be generated at the fold and topological levels, no system produces high-resolution 3D patterns including atom and cavity positions. To address this challenge, our research focuses on generating patterns from proteins with rigid prosthetic groups. Since these groups are key elements of protein active sites, the generated 3D patterns are expected to be biologically meaningful. In this paper, we present a new approach which allows the generation of 3D patterns from proteins with rigid prosthetic groups. Using 237 protein chains representing proteins containing porphyrin rings, our method was validated by comparing 3D templates generated from homologues with the 3D structure of the proteins they model. Atom positions were predicted reliably: 93% of them had an accuracy of 1.00 A or less. Moreover, similar results were obtained regarding chemical group and cavity positions. Results also suggested our system could contribute to the validation of 3D protein models. Finally, a 3D template was generated for the active site of human cytochrome P450 CYP17, the 3D structure of which is unknown. Its analysis showed that it is biologically meaningful: our method detected the main patterns of the cytochrome P450 superfamily and the motifs linked to catalytic reactions. The 3D template also suggested the position of a residue, which could be involved in a hydrogen bond with CYP17 substrates and the shape and location of a cavity. Comparisons with independently generated 3D models comforted these hypotheses. Alignment software (Nestor3D) is available at http://www.kingston.ac.uk/~ku33185/Nestor3D.html

From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions.

Directory of Open Access Journals (Sweden)

Mu Gao

2009-03-01

Full Text Available DNA-protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA-protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA-protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA-protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA-protein interaction modes exhibit some similarity to specific DNA-protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Calpha deviation from native is up to 5 A from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA-protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein.

The development of an affinity evaluation and prediction system by using protein–protein docking simulations and parameter tuning

Directory of Open Access Journals (Sweden)

Koki Tsukamoto

2009-01-01

Full Text Available Koki Tsukamoto1, Tatsuya Yoshikawa1,2, Kiyonobu Yokota1, Yuichiro Hourai1, Kazuhiko Fukui11Computational Biology Research Center (CBRC, National Institute of Advanced Industrial Science and Technology (AIST, Koto-ku, Tokyo, Japan; 2Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, Toyonaka, Osaka, JapanAbstract: A system was developed to evaluate and predict the interaction between protein pairs by using the widely used shape complementarity search method as the algorithm for docking simulations between the proteins. We used this system, which we call the affinity evaluation and prediction (AEP system, to evaluate the interaction between 20 protein pairs. The system first executes a “round robin” shape complementarity search of the target protein group, and evaluates the interaction between the complex structures obtained by the search. These complex structures are selected by using a statistical procedure that we developed called ‘grouping’. At a prevalence of 5.0%, our AEP system predicted protein–protein interactions with a 50.0% recall, 55.6% precision, 95.5% accuracy, and an F-measure of 0.526. By optimizing the grouping process, our AEP system successfully predicted 10 protein pairs (among 20 pairs that were biologically relevant combinations. Our ultimate goal is to construct an affinity database that will provide cell biologists and drug designers with crucial information obtained using our AEP system.Keywords: protein–protein interaction, affinity analysis, protein–protein docking, FFT, massive parallel computing

GPCR-Bench: A Benchmarking Set and Practitioners' Guide for G Protein-Coupled Receptor Docking.

Science.gov (United States)

Weiss, Dahlia R; Bortolato, Andrea; Tehan, Benjamin; Mason, Jonathan S

2016-04-25

Virtual screening is routinely used to discover new ligands and in particular new ligand chemotypes for G protein-coupled receptors (GPCRs). To prepare for a virtual screen, we often tailor a docking protocol that will enable us to select the best candidates for further screening. To aid this, we created GPCR-Bench, a publically available docking benchmarking set in the spirit of the DUD and DUD-E reference data sets for validation studies, containing 25 nonredundant high-resolution GPCR costructures with an accompanying set of diverse ligands and computational decoy molecules for each target. Benchmarking sets are often used to compare docking protocols; however, it is important to evaluate docking methods not by "retrospective" hit rates but by the actual likelihood that they will produce novel prospective hits. Therefore, docking protocols must not only rank active molecules highly but also produce good poses that a chemist will select for purchase and screening. Currently, no simple objective machine-scriptable function exists that can do this; instead, docking hit lists must be subjectively examined in a consistent way to compare between docking methods. We present here a case study highlighting considerations we feel are of importance when evaluating a method, intended to be useful as a practitioners' guide.

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

Science.gov (United States)

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

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

Directory of Open Access Journals (Sweden)

Montiago X LaBute

Full Text Available 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

A docking study of enhanced intracellular survival protein from Mycobacterium tuberculosis with human DUSP16/MKP-7

International Nuclear Information System (INIS)

Yoon, Hye-Jin; Kim, Kyoung Hoon; Yang, Jin Kuk; Suh, Se Won; Kim, Hyunsik; Jang, Soonmin

2013-01-01

A docking study of Mtb Eis with its substrate DUSP16/MKP-7 was performed. The docking model suggests dissociation of hexameric Mtb Eis into dimers or monomers. The intracellular pathogen Mycobacterium tuberculosis (Mtb) causes tuberculosis, and one of its secreted effector proteins, called enhanced intracellular survival (Eis) protein, enhances its survival in macrophages. Mtb Eis activates JNK-specific dual-specificity protein phosphatase 16 (DUSP16)/mitogen-activated protein kinase phosphatase-7 (MKP-7) through the acetylation on Lys55, thus inactivating JNK by dephosphorylation. Based on the recently reported crystal structure of Mtb Eis, a docking model for the binding of Mtb Eis to DUSP16/MKP-7 was generated. In the docking model, the substrate helix containing Lys55 of DUSP16/MKP-7 fits nicely into the active-site cleft of Mtb Eis; the twisted β-sheet of Eis domain II embraces the substrate helix from one side. Most importantly, the side-chain of Lys55 is inserted toward acetyl-CoA and the resulting distance is 4.6 Å between the NZ atom of Lys55 and the carbonyl carbon of the acetyl group in acetyl-CoA. The binding of Mtb Eis and DUSP16/MKP-7 is maintained by strong electrostatic interactions. The active-site cleft of Mtb Eis has a negatively charged surface formed by Asp25, Glu138, Asp286, Glu395 and the terminal carboxylic group of Phe396. In contrast, DUSP16/MKP-7 contains five basic residues, Lys52, Lys55, Arg56, Arg57 and Lys62, which point toward the negatively charged surface of the active-site pocket of Mtb Eis. Thus, the current docking model suggests that the binding of DUSP16/MKP-7 to Mtb Eis should be established by charge complementarity in addition to a very favorable geometric arrangement. The suggested mode of binding requires the dissociation of the hexameric Mtb Eis into dimers or monomers. This study may be useful for future studies aiming to develop inhibitors of Mtb Eis as a new anti-tuberculosis drug candidate

A docking study of enhanced intracellular survival protein from Mycobacterium tuberculosis with human DUSP16/MKP-7

Energy Technology Data Exchange (ETDEWEB)

Yoon, Hye-Jin, E-mail: yoonhj@snu.ac.kr; Kim, Kyoung Hoon [Seoul National University, Seoul 151-747 (Korea, Republic of); Yang, Jin Kuk [Soongsil University, Seoul 156-743 (Korea, Republic of); Suh, Se Won [Seoul National University, Seoul 151-747 (Korea, Republic of); Seoul National University, Seoul 151-747 (Korea, Republic of); Kim, Hyunsik; Jang, Soonmin, E-mail: yoonhj@snu.ac.kr [Sejong University, Seoul 143-747 (Korea, Republic of)

2013-11-01

A docking study of Mtb Eis with its substrate DUSP16/MKP-7 was performed. The docking model suggests dissociation of hexameric Mtb Eis into dimers or monomers. The intracellular pathogen Mycobacterium tuberculosis (Mtb) causes tuberculosis, and one of its secreted effector proteins, called enhanced intracellular survival (Eis) protein, enhances its survival in macrophages. Mtb Eis activates JNK-specific dual-specificity protein phosphatase 16 (DUSP16)/mitogen-activated protein kinase phosphatase-7 (MKP-7) through the acetylation on Lys55, thus inactivating JNK by dephosphorylation. Based on the recently reported crystal structure of Mtb Eis, a docking model for the binding of Mtb Eis to DUSP16/MKP-7 was generated. In the docking model, the substrate helix containing Lys55 of DUSP16/MKP-7 fits nicely into the active-site cleft of Mtb Eis; the twisted β-sheet of Eis domain II embraces the substrate helix from one side. Most importantly, the side-chain of Lys55 is inserted toward acetyl-CoA and the resulting distance is 4.6 Å between the NZ atom of Lys55 and the carbonyl carbon of the acetyl group in acetyl-CoA. The binding of Mtb Eis and DUSP16/MKP-7 is maintained by strong electrostatic interactions. The active-site cleft of Mtb Eis has a negatively charged surface formed by Asp25, Glu138, Asp286, Glu395 and the terminal carboxylic group of Phe396. In contrast, DUSP16/MKP-7 contains five basic residues, Lys52, Lys55, Arg56, Arg57 and Lys62, which point toward the negatively charged surface of the active-site pocket of Mtb Eis. Thus, the current docking model suggests that the binding of DUSP16/MKP-7 to Mtb Eis should be established by charge complementarity in addition to a very favorable geometric arrangement. The suggested mode of binding requires the dissociation of the hexameric Mtb Eis into dimers or monomers. This study may be useful for future studies aiming to develop inhibitors of Mtb Eis as a new anti-tuberculosis drug candidate.

Predicting Protein-Protein Interactions Using BiGGER: Case Studies

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Rui M. Almeida

2016-08-01

Full Text Available The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER docking algorithm, which stands at the interface of these two approaches. BiGGER is a user-friendly docking algorithm that was specifically designed to incorporate experimental data at different stages of the simulation, to either guide the search for correct structures or help evaluate the results, in order to combine the reliability of hard data with the convenience of simulations. Herein, the applications of BiGGER are described by illustrative applications divided in three Case Studies: (Case Study A in which no specific contact data is available; (Case Study B when different experimental data (e.g., site-directed mutagenesis, properties of the complex, NMR chemical shift perturbation mapping, electron tunneling on one of the partners is available; and (Case Study C when experimental data are available for both interacting surfaces, which are used during the search and/or evaluation stage of the docking. This algorithm has been extensively used, evidencing its usefulness in a wide range of different biological research fields.

Convenient method for resolving degeneracies due to symmetry of the magnetic susceptibility tensor and its application to pseudo contact shift-based protein-protein complex structure determination

Energy Technology Data Exchange (ETDEWEB)

Kobashigawa, Yoshihiro; Saio, Tomohide [Hokkaido University, Department of Structural Biology, Faculty of Advanced Life Science (Japan); Ushio, Masahiro [Hokkaido University, Graduate School of Life Science (Japan); Sekiguchi, Mitsuhiro [Astellas Pharma Inc., Analysis and Pharmacokinetics Research Labs, Department of Drug Discovery (Japan); Yokochi, Masashi; Ogura, Kenji; Inagaki, Fuyuhiko, E-mail: finagaki@pharm.hokudai.ac.jp [Hokkaido University, Department of Structural Biology, Faculty of Advanced Life Science (Japan)

2012-05-15

Pseudo contact shifts (PCSs) induced by paramagnetic lanthanide ions fixed in a protein frame provide long-range distance and angular information, and are valuable for the structure determination of protein-protein and protein-ligand complexes. We have been developing a lanthanide-binding peptide tag (hereafter LBT) anchored at two points via a peptide bond and a disulfide bond to the target proteins. However, the magnetic susceptibility tensor displays symmetry, which can cause multiple degenerated solutions in a structure calculation based solely on PCSs. Here we show a convenient method for resolving this degeneracy by changing the spacer length between the LBT and target protein. We applied this approach to PCS-based rigid body docking between the FKBP12-rapamycin complex and the mTOR FRB domain, and demonstrated that degeneracy could be resolved using the PCS restraints obtained from two-point anchored LBT with two different spacer lengths. The present strategy will markedly increase the usefulness of two-point anchored LBT for protein complex structure determination.

Solvated protein-protein docking using Kyte-Doolittle-based water preferences

NARCIS (Netherlands)

Kastritis, P.; Visscher, K.M.; van Dijk, A.D.J.; Bonvin, A.M.J.J.

2013-01-01

HADDOCK is one of the few docking programs that can explicitly account for water molecules in the docking process. Its solvated docking protocol starts from hydrated molecules and a fraction of the resulting interfacial waters is subsequently removed in a biased Monte Carlo procedure based on

Solvated protein-protein docking using Kyte-Doolittle-based water preferences

NARCIS (Netherlands)

Kastritis, Panagiotis L.; Visscher, Koen M.; van Dijk, Aalt D.J.; Bonvin, Alexandre M.J.J.

HADDOCK is one of the few docking programs that can explicitly account for water molecules in the docking process. Its solvated docking protocol starts from hydrated molecules and a fraction of the resulting interfacial waters is subsequently removed in a biased Monte Carlo procedure based on

Homology modeling, molecular docking and DNA binding studies of nucleotide excision repair UvrC protein from M. tuberculosis.

Science.gov (United States)

Parulekar, Rishikesh S; Barage, Sagar H; Jalkute, Chidambar B; Dhanavade, Maruti J; Fandilolu, Prayagraj M; Sonawane, Kailas D

2013-08-01

Mycobacterium tuberculosis is a Gram positive, acid-fast bacteria belonging to genus Mycobacterium, is the leading causative agent of most cases of tuberculosis. The pathogenicity of the bacteria is enhanced by its developed DNA repair mechanism which consists of machineries such as nucleotide excision repair. Nucleotide excision repair consists of excinuclease protein UvrABC endonuclease, multi-enzymatic complex which carries out repair of damaged DNA in sequential manner. UvrC protein is a part of this complex and thus helps to repair the damaged DNA of M. tuberculosis. Hence, structural bioinformatics study of UvrC protein from M. tuberculosis was carried out using homology modeling and molecular docking techniques. Assessment of the reliability of the homology model was carried out by predicting its secondary structure along with its model validation. The predicted structure was docked with the ATP and the interacting amino acid residues of UvrC protein with the ATP were found to be TRP539, PHE89, GLU536, ILE402 and ARG575. The binding of UvrC protein with the DNA showed two different domains. The residues from domain I of the protein VAL526, THR524 and LEU521 interact with the DNA whereas, amino acids interacting from the domain II of the UvrC protein included ARG597, GLU595, GLY594 and GLY592 residues. This predicted model could be useful to design new inhibitors of UvrC enzyme to prevent pathogenesis of Mycobacterium and so the tuberculosis.

Combined Docking with Classical Force Field and Quantum Chemical Semiempirical Method PM7

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A. V. Sulimov

2017-01-01

Full Text Available Results of the combined use of the classical force field and the recent quantum chemical PM7 method for docking are presented. Initially the gridless docking of a flexible low molecular weight ligand into the rigid target protein is performed with the energy function calculated in the MMFF94 force field with implicit water solvent in the PCM model. Among several hundred thousand local minima, which are found in the docking procedure, about eight thousand lowest energy minima are chosen and then energies of these minima are recalculated with the recent quantum chemical semiempirical PM7 method. This procedure is applied to 16 test complexes with different proteins and ligands. For almost all test complexes such energy recalculation results in the global energy minimum configuration corresponding to the ligand pose near the native ligand position in the crystalized protein-ligand complex. A significant improvement of the ligand positioning accuracy comparing with MMFF94 energy calculations is demonstrated.

Combined Docking with Classical Force Field and Quantum Chemical Semiempirical Method PM7.

Science.gov (United States)

Sulimov, A V; Kutov, D C; Katkova, E V; Sulimov, V B

2017-01-01

Results of the combined use of the classical force field and the recent quantum chemical PM7 method for docking are presented. Initially the gridless docking of a flexible low molecular weight ligand into the rigid target protein is performed with the energy function calculated in the MMFF94 force field with implicit water solvent in the PCM model. Among several hundred thousand local minima, which are found in the docking procedure, about eight thousand lowest energy minima are chosen and then energies of these minima are recalculated with the recent quantum chemical semiempirical PM7 method. This procedure is applied to 16 test complexes with different proteins and ligands. For almost all test complexes such energy recalculation results in the global energy minimum configuration corresponding to the ligand pose near the native ligand position in the crystalized protein-ligand complex. A significant improvement of the ligand positioning accuracy comparing with MMFF94 energy calculations is demonstrated.

Empirical scoring functions for advanced protein-ligand docking with PLANTS.

Science.gov (United States)

Korb, Oliver; Stützle, Thomas; Exner, Thomas E

2009-01-01

In this paper we present two empirical scoring functions, PLANTS(CHEMPLP) and PLANTS(PLP), designed for our docking algorithm PLANTS (Protein-Ligand ANT System), which is based on ant colony optimization (ACO). They are related, regarding their functional form, to parts of already published scoring functions and force fields. The parametrization procedure described here was able to identify several parameter settings showing an excellent performance for the task of pose prediction on two test sets comprising 298 complexes in total. Up to 87% of the complexes of the Astex diverse set and 77% of the CCDC/Astex clean listnc (noncovalently bound complexes of the clean list) could be reproduced with root-mean-square deviations of less than 2 A with respect to the experimentally determined structures. A comparison with the state-of-the-art docking tool GOLD clearly shows that this is, especially for the druglike Astex diverse set, an improvement in pose prediction performance. Additionally, optimized parameter settings for the search algorithm were identified, which can be used to balance pose prediction reliability and search speed.

Domain wise docking analyses of the modular chitin binding protein CBP50 from Bacillus thuringiensis serovar konkukian S4.

Science.gov (United States)

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.

Towards ligand docking including explicit interface water molecules.

Directory of Open Access Journals (Sweden)

Gordon Lemmon

Full Text Available Small molecule docking predicts the interaction of a small molecule ligand with a protein at atomic-detail accuracy including position and conformation the ligand but also conformational changes of the protein upon ligand binding. While successful in the majority of cases, docking algorithms including RosettaLigand fail in some cases to predict the correct protein/ligand complex structure. In this study we show that simultaneous docking of explicit interface water molecules greatly improves Rosetta's ability to distinguish correct from incorrect ligand poses. This result holds true for both protein-centric water docking wherein waters are located relative to the protein binding site and ligand-centric water docking wherein waters move with the ligand during docking. Protein-centric docking is used to model 99 HIV-1 protease/protease inhibitor structures. We find protease inhibitor placement improving at a ratio of 9:1 when one critical interface water molecule is included in the docking simulation. Ligand-centric docking is applied to 341 structures from the CSAR benchmark of diverse protein/ligand complexes [1]. Across this diverse dataset we see up to 56% recovery of failed docking studies, when waters are included in the docking simulation.

Molecular docking.

Science.gov (United States)

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.

Structural Bioinformatics and Protein Docking Analysis of the Molecular Chaperone-Kinase Interactions: Towards Allosteric Inhibition of Protein Kinases by Targeting the Hsp90-Cdc37 Chaperone Machinery

Directory of Open Access Journals (Sweden)

Gennady Verkhivker

2013-11-01

Full Text Available A fundamental role of the Hsp90-Cdc37 chaperone system in mediating maturation of protein kinase clients and supporting kinase functional activity is essential for the integrity and viability of signaling pathways involved in cell cycle control and organism development. Despite significant advances in understanding structure and function of molecular chaperones, the molecular mechanisms and guiding principles of kinase recruitment to the chaperone system are lacking quantitative characterization. Structural and thermodynamic characterization of Hsp90-Cdc37 binding with protein kinase clients by modern experimental techniques is highly challenging, owing to a transient nature of chaperone-mediated interactions. In this work, we used experimentally-guided protein docking to probe the allosteric nature of the Hsp90-Cdc37 binding with the cyclin-dependent kinase 4 (Cdk4 kinase clients. The results of docking simulations suggest that the kinase recognition and recruitment to the chaperone system may be primarily determined by Cdc37 targeting of the N-terminal kinase lobe. The interactions of Hsp90 with the C-terminal kinase lobe may provide additional “molecular brakes” that can lock (or unlock kinase from the system during client loading (release stages. The results of this study support a central role of the Cdc37 chaperone in recognition and recruitment of the kinase clients. Structural analysis may have useful implications in developing strategies for allosteric inhibition of protein kinases by targeting the Hsp90-Cdc37 chaperone machinery.

Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2

Science.gov (United States)

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.

Combination of scoring schemes for protein docking

Directory of Open Access Journals (Sweden)

Schomburg Dietmar

2007-08-01

Full Text Available Abstract Background Docking algorithms are developed to predict in which orientation two proteins are likely to bind under natural conditions. The currently used methods usually consist of a sampling step followed by a scoring step. We developed a weighted geometric correlation based on optimised atom specific weighting factors and combined them with our previously published amino acid specific scoring and with a comprehensive SVM-based scoring function. Results The scoring with the atom specific weighting factors yields better results than the amino acid specific scoring. In combination with SVM-based scoring functions the percentage of complexes for which a near native structure can be predicted within the top 100 ranks increased from 14% with the geometric scoring to 54% with the combination of all scoring functions. Especially for the enzyme-inhibitor complexes the results of the ranking are excellent. For half of these complexes a near-native structure can be predicted within the first 10 proposed structures and for more than 86% of all enzyme-inhibitor complexes within the first 50 predicted structures. Conclusion We were able to develop a combination of different scoring schemes which considers a series of previously described and some new scoring criteria yielding a remarkable improvement of prediction quality.

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

NARCIS (Netherlands)

Xue, Li C; Garcia Lopes Maia Rodrigues, João; Dobbs, Drena; Honavar, Vasant; Bonvin, Alexandre M J J

2016-01-01

Although many advanced and sophisticatedab initioapproaches 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

Stable and rigid DTPA-like paramagnetic tags suitable for in vitro and in situ protein NMR analysis.

Science.gov (United States)

Chen, Jia-Liang; Zhao, Yu; Gong, Yan-Jun; Pan, Bin-Bin; Wang, Xiao; Su, Xun-Cheng

2018-02-01

Organic synthesis of a ligand with high binding affinities for paramagnetic lanthanide ions is an effective way of generating paramagnetic effects on proteins. These paramagnetic effects manifested in high-resolution NMR spectroscopy are valuable dynamic and structural restraints of proteins and protein-ligand complexes. A paramagnetic tag generally contains a metal chelating moiety and a reactive group for protein modification. Herein we report two new DTPA-like tags, 4PS-PyDTTA and 4PS-6M-PyDTTA that can be site-specifically attached to a protein with a stable thioether bond. Both protein-tag adducts form stable lanthanide complexes, of which the binding affinities and paramagnetic tensors are tunable with respect to the 6-methyl group in pyridine. Paramagnetic relaxation enhancement (PRE) effects of Gd(III) complex on protein-tag adducts were evaluated in comparison with pseudocontact shift (PCS), and the results indicated that both 4PS-PyDTTA and 4PS-6M-PyDTTA tags are rigid and present high-quality PREs that are crucially important in elucidation of the dynamics and interactions of proteins and protein-ligand complexes. We also show that these two tags are suitable for in-situ protein NMR analysis.

Introducing a Clustering Step in a Consensus Approach for the Scoring of Protein-Protein Docking Models

KAUST Repository

Chermak, Edrisse; De Donato, Renato; Lensink, Marc F.; Petta, Andrea; Serra, Luigi; Scarano, Vittorio; Cavallo, Luigi; Oliva, Romina

2016-01-01

Correctly scoring protein-protein docking models to single out native-like ones is an open challenge. It is also an object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), the community-wide blind docking experiment. We introduced in the field the first pure consensus method, CONSRANK, which ranks models based on their ability to match the most conserved contacts in the ensemble they belong to. In CAPRI, scorers are asked to evaluate a set of available models and select the top ten ones, based on their own scoring approach. Scorers' performance is ranked based on the number of targets/interfaces for which they could provide at least one correct solution. In such terms, blind testing in CAPRI Round 30 (a joint prediction round with CASP11) has shown that critical cases for CONSRANK are represented by targets showing multiple interfaces or for which only a very small number of correct solutions are available. To address these challenging cases, CONSRANK has now been modified to include a contact-based clustering of the models as a preliminary step of the scoring process. We used an agglomerative hierarchical clustering based on the number of common inter-residue contacts within the models. Two criteria, with different thresholds, were explored in the cluster generation, setting either the number of common contacts or of total clusters. For each clustering approach, after selecting the top (most populated) ten clusters, CONSRANK was run on these clusters and the top-ranked model for each cluster was selected, in the limit of 10 models per target. We have applied our modified scoring approach, Clust-CONSRANK, to SCORE_SET, a set of CAPRI scoring models made recently available by CAPRI assessors, and to the subset of homodimeric targets in CAPRI Round 30 for which CONSRANK failed to include a correct solution within the ten selected models. Results show that, for the challenging cases, the clustering step typically enriches the ten top ranked

Introducing a Clustering Step in a Consensus Approach for the Scoring of Protein-Protein Docking Models

KAUST Repository

Chermak, Edrisse

2016-11-15

Correctly scoring protein-protein docking models to single out native-like ones is an open challenge. It is also an object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), the community-wide blind docking experiment. We introduced in the field the first pure consensus method, CONSRANK, which ranks models based on their ability to match the most conserved contacts in the ensemble they belong to. In CAPRI, scorers are asked to evaluate a set of available models and select the top ten ones, based on their own scoring approach. Scorers\\' performance is ranked based on the number of targets/interfaces for which they could provide at least one correct solution. In such terms, blind testing in CAPRI Round 30 (a joint prediction round with CASP11) has shown that critical cases for CONSRANK are represented by targets showing multiple interfaces or for which only a very small number of correct solutions are available. To address these challenging cases, CONSRANK has now been modified to include a contact-based clustering of the models as a preliminary step of the scoring process. We used an agglomerative hierarchical clustering based on the number of common inter-residue contacts within the models. Two criteria, with different thresholds, were explored in the cluster generation, setting either the number of common contacts or of total clusters. For each clustering approach, after selecting the top (most populated) ten clusters, CONSRANK was run on these clusters and the top-ranked model for each cluster was selected, in the limit of 10 models per target. We have applied our modified scoring approach, Clust-CONSRANK, to SCORE_SET, a set of CAPRI scoring models made recently available by CAPRI assessors, and to the subset of homodimeric targets in CAPRI Round 30 for which CONSRANK failed to include a correct solution within the ten selected models. Results show that, for the challenging cases, the clustering step typically enriches the ten top ranked

AnchorDock: Blind and Flexible Anchor-Driven Peptide Docking.

Science.gov (United States)

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.

Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

DEFF Research Database (Denmark)

Nguyen, E.D.; Meiler, J.; Norn, C.

2013-01-01

screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone...... extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves...

Combinatorial multispectral, thermodynamics, docking and site-directed mutagenesis reveal the cognitive characteristics of honey bee chemosensory protein to plant semiochemical.

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Tan, Jing; Song, Xinmi; Fu, Xiaobin; Wu, Fan; Hu, Fuliang; Li, Hongliang

2018-05-09

In the chemoreceptive system of insects, there are always some soluble binding proteins, such as some antennal-specific chemosensory proteins (CSPs), which are abundantly distributed in the chemosensory sensillar lymph. The antennal-specific CSPs usually have strong capability to bind diverse semiochemicals, while the detailed interaction between CSPs and the semiochemicals remain unclear. Here, by means of the combinatorial multispectral, thermodynamics, docking and site-directed mutagenesis, we detailedly interpreted a binding interaction between a plant semiochemical β-ionone and antennal-specific CSP1 from the worker honey bee. Thermodynamic parameters (ΔH  0) indicate that the interaction is mainly driven by hydrophobic forces and electrostatic interactions. Docking prediction results showed that there are two key amino acids, Phe44 and Gln63, may be involved in the interacting process of CSP1 to β-ionone. In order to confirm the two key amino acids, site-directed mutagenesis were performed and the binding constant (K A ) for two CSP1 mutant proteins was reduced by 60.82% and 46.80% compared to wild-type CSP1. The thermodynamic analysis of mutant proteins furtherly verified that Phe44 maintained an electrostatic interaction and Gln63 contributes hydrophobic and electrostatic forces. Our investigation initially elucidates the physicochemical mechanism of the interaction between antennal-special CSPs in insects including bees to plant semiochemicals, as well as the development of twice thermodynamic analysis (wild type and mutant proteins) combined with multispectral and site-directed mutagenesis methods. Copyright © 2018. Published by Elsevier B.V.

A general approach for developing system-specific functions to score protein-ligand docked complexes using support vector inductive logic programming.

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Amini, Ata; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2007-12-01

Despite the increased recent use of protein-ligand and protein-protein docking in the drug discovery process due to the increases in computational power, the difficulty of accurately ranking the binding affinities of a series of ligands or a series of proteins docked to a protein receptor remains largely unsolved. This problem is of major concern in lead optimization procedures and has lead to the development of scoring functions tailored to rank the binding affinities of a series of ligands to a specific system. However, such methods can take a long time to develop and their transferability to other systems remains open to question. Here we demonstrate that given a suitable amount of background information a new approach using support vector inductive logic programming (SVILP) can be used to produce system-specific scoring functions. Inductive logic programming (ILP) learns logic-based rules for a given dataset that can be used to describe properties of each member of the set in a qualitative manner. By combining ILP with support vector machine regression, a quantitative set of rules can be obtained. SVILP has previously been used in a biological context to examine datasets containing a series of singular molecular structures and properties. Here we describe the use of SVILP to produce binding affinity predictions of a series of ligands to a particular protein. We also for the first time examine the applicability of SVILP techniques to datasets consisting of protein-ligand complexes. Our results show that SVILP performs comparably with other state-of-the-art methods on five protein-ligand systems as judged by similar cross-validated squares of their correlation coefficients. A McNemar test comparing SVILP to CoMFA and CoMSIA across the five systems indicates our method to be significantly better on one occasion. The ability to graphically display and understand the SVILP-produced rules is demonstrated and this feature of ILP can be used to derive hypothesis for

Dimerization of the docking/adaptor protein HEF1 via a carboxy-terminal helix-loop-helix domain.

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Law, S F; Zhang, Y Z; Fashena, S J; Toby, G; Estojak, J; Golemis, E A

1999-10-10

HEF1, p130(Cas), and Efs define a family of multidomain docking proteins which plays a central coordinating role for tyrosine-kinase-based signaling related to cell adhesion. HEF1 function has been specifically implicated in signaling pathways important for cell adhesion and differentiation in lymphoid and epithelial cells. While the SH3 domains and SH2-binding site domains (substrate domains) of HEF1 family proteins are well characterized and binding partners known, to date the highly conserved carboxy-terminal domains of the three proteins have lacked functional definition. In this study, we have determined that the carboxy-terminal domain of HEF1 contains a divergent helix-loop-helix (HLH) motif. This motif mediates HEF1 homodimerization and HEF1 heterodimerization with a recognition specificity similar to that of the transcriptional regulatory HLH proteins Id2, E12, and E47. We had previously demonstrated that the HEF1 carboxy-terminus expressed as a separate domain in yeast reprograms cell division patterns, inducing constitutive pseudohyphal growth. Here we show that pseudohyphal induction by HEF1 requires an intact HLH, further supporting the idea that this motif has an effector activity for HEF1, and implying that HEF1 pseudohyphal activity derives in part from interactions with yeast helix-loop-helix proteins. These combined results provide initial insight into the mode of function of the HEF1 carboxy-terminal domain and suggest that the HEF1 protein may interact with cellular proteins which control differentiation. Copyright 1999 Academic Press.

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

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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.

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

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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.

Multi-template homology based structure prediction and molecular docking studies of protein ‘L’ of Zaire ebolavirus (EBOV

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Jayasree Ganugapati

2017-01-01

Full Text Available Ebola is one of the most dangerous pathogenic RNA virus that causes severe hemorrhagic fever in humans and is considered to be a threat to humanity. The RNA genome of EBOV encodes seven proteins viz., glycoprotein (GP, nucleoprotein (NP, RNA-dependent RNA polymerase (protein ‘L’, VP35, VP30, VP40 andVP24. The objective of the present study is to find a suitable inhibitor for protein ‘L’. The large structural protein ‘L’, is made up of 2212 amino acid residues. This protein works as an RNA-dependent RNA polymerase (RdRp and a methyl transferase. It is carried by the virus during the infection as the host mechanisms cannot be used to transcribe the –ss RNA genome of the virus. As the protein is crucial for the replication of the viral genome and no other host enzyme can perform the same function, this viral protein ‘L’ was considered as a potential drug target to design inhibitors. The 3D structure of protein ‘L’ is not available to date. This is a limitation in understanding the protein's function. Hence, the present work is aimed at predicting the first homology-based model of protein ‘L’ and elucidating the function by providing insight into the molecular details of the protein. As there is no drug available for the treatment of EBOV infection our findings play a crucial a role to identify an inhibitor of the protein ‘L’ of EBOV. HTS against ZINC database resulted in identification of few possible inhibitors. Molecular docking studies resulted in finding a suitable inhibitor for protein ‘L’.

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

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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.

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

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Haiou Li

Full Text Available 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.

In Silico Generation of Peptides by Replica Exchange Monte Carlo: Docking-Based Optimization of Maltose-Binding-Protein Ligands.

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Anna Russo

Full Text Available Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition. We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the ex-novo optimization of peptide based binders.

Molecular dynamics and docking simulation of a natural variant of Activated Protein C with impaired protease activity: implications for integrin-mediated antiseptic function.

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D'Ursi, Pasqualina; Orro, Alessandro; Morra, Giulia; Moscatelli, Marco; Trombetti, Gabriele; Milanesi, Luciano; Rovida, Ermanna

2015-01-01

Activated Protein C (APC) is a multifunctional serine protease, primarily known for its anticoagulant function in the coagulation system. Several studies have already elucidated its role in counteracting apoptosis and inflammation in cells, while significant effort is still ongoing for defining its involvement in sepsis. Earlier literature has shown that the antiseptic function of APC is mediated by its binding to leukocyte integrins, which is due to the presence of the integrin binding motif Arg-Gly-Asp at the N-terminus of the APC catalytic chain. Many natural mutants have been identified in patients with Protein C deficiency diagnosis including a variant of specificity pocket (Gly216Asp). In this work, we present a molecular model of the complex of APC with αVβ3 integrin obtained by protein-protein docking approach. A computational analysis of this variant is hereby presented, based on molecular dynamics and docking simulations, aiming at investigating the effects of the Gly216Asp mutation on the protein conformation and inferring its functional implications. Our study shows that such mutation is likely to impair the protease activity while preserving the overall protein fold. Moreover, superposition of the integrin binding motifs in wild-type and mutant forms suggests that the interaction with integrin can still occur and thus the mutant is likely to retain its antiseptic function related to the neutrophyl integrin binding. Therapeutic applications could result in this APC mutant which retains antiseptic function without anticoagulant side effects.

Using the multi-objective optimization replica exchange Monte Carlo enhanced sampling method for protein-small molecule docking.

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Wang, Hongrui; Liu, Hongwei; Cai, Leixin; Wang, Caixia; Lv, Qiang

2017-07-10

In this study, we extended the replica exchange Monte Carlo (REMC) sampling method to protein-small molecule docking conformational prediction using RosettaLigand. In contrast to the traditional Monte Carlo (MC) and REMC sampling methods, these methods use multi-objective optimization Pareto front information to facilitate the selection of replicas for exchange. The Pareto front information generated to select lower energy conformations as representative conformation structure replicas can facilitate the convergence of the available conformational space, including available near-native structures. Furthermore, our approach directly provides min-min scenario Pareto optimal solutions, as well as a hybrid of the min-min and max-min scenario Pareto optimal solutions with lower energy conformations for use as structure templates in the REMC sampling method. These methods were validated based on a thorough analysis of a benchmark data set containing 16 benchmark test cases. An in-depth comparison between MC, REMC, multi-objective optimization-REMC (MO-REMC), and hybrid MO-REMC (HMO-REMC) sampling methods was performed to illustrate the differences between the four conformational search strategies. Our findings demonstrate that the MO-REMC and HMO-REMC conformational sampling methods are powerful approaches for obtaining protein-small molecule docking conformational predictions based on the binding energy of complexes in RosettaLigand.

Scoring functions for protein-protein interactions.

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Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Three-dimensional models of Mycobacterium tuberculosis proteins Rv1555, Rv1554 and their docking analyses with sildenafil, tadalafil, vardenafil drugs, suggest interference with quinol binding likely to affect protein's function.

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Dash, Pallabini; Bala Divya, M; Guruprasad, Lalitha; Guruprasad, Kunchur

2018-04-18

Earlier based on bioinformatics analyses, we had predicted the Mycobacterium tuberculosis (M.tb) proteins; Rv1555 and Rv1554, among the potential new tuberculosis drug targets. According to the 'TB-drugome' the Rv1555 protein is 'druggable' with sildenafil (Viagra), tadalafil (Cialis) and vardenafil (Levitra) drugs. In the present work, we intended to understand via computer modeling studies, how the above drugs are likely to inhibit the M.tb protein's function. The three-dimensional computer models for M.tb proteins; Rv1555 and Rv1554 constructed on the template of equivalent membrane anchor subunits of the homologous E.coli quinol fumarate reductase respiratory protein complex, followed by drug docking analyses, suggested that the binding of above drugs interferes with quinol binding sites. Also, we experimentally observed the in-vitro growth inhibition of E.coli bacteria containing the homologous M.tb protein sequences with sildenafil and tadalafil drugs. The predicted binding sites of the drugs is likely to affect the above M.tb proteins function as quinol binding is known to be essential for electron transfer function during anaerobic respiration in the homologous E.coli protein complex. Therefore, sildenafil and related drugs currently used in the treatment of male erectile dysfunction targeting the human phosphodiesterase 5 enzyme may be evaluated for their plausible role as repurposed drugs to treat human tuberculosis.

Rosetta FlexPepDock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors.

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Raveh, Barak; London, Nir; Zimmerman, Lior; Schueler-Furman, Ora

2011-04-29

Flexible peptides that fold upon binding to another protein molecule mediate a large number of regulatory interactions in the living cell and may provide highly specific recognition modules. We present Rosetta FlexPepDock ab-initio, a protocol for simultaneous docking and de-novo folding of peptides, starting from an approximate specification of the peptide binding site. Using the Rosetta fragments library and a coarse-grained structural representation of the peptide and the receptor, FlexPepDock ab-initio samples efficiently and simultaneously the space of possible peptide backbone conformations and rigid-body orientations over the receptor surface of a given binding site. The subsequent all-atom refinement of the coarse-grained models includes full side-chain modeling of both the receptor and the peptide, resulting in high-resolution models in which key side-chain interactions are recapitulated. The protocol was applied to a benchmark in which peptides were modeled over receptors in either their bound backbone conformations or in their free, unbound form. Near-native peptide conformations were identified in 18/26 of the bound cases and 7/14 of the unbound cases. The protocol performs well on peptides from various classes of secondary structures, including coiled peptides with unusual turns and kinks. The results presented here significantly extend the scope of state-of-the-art methods for high-resolution peptide modeling, which can now be applied to a wide variety of peptide-protein interactions where no prior information about the peptide backbone conformation is available, enabling detailed structure-based studies and manipulation of those interactions. © 2011 Raveh et al.

Cell adhesion controlled by adhesion G protein-coupled receptor GPR124/ADGRA2 is mediated by a protein complex comprising intersectins and Elmo-Dock.

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Hernández-Vásquez, Magda Nohemí; Adame-García, Sendi Rafael; Hamoud, Noumeira; Chidiac, Rony; Reyes-Cruz, Guadalupe; Gratton, Jean Philippe; Côté, Jean-François; Vázquez-Prado, José

2017-07-21

Developmental angiogenesis and the maintenance of the blood-brain barrier involve endothelial cell adhesion, which is linked to cytoskeletal dynamics. GPR124 (also known as TEM5/ADGRA2) is an adhesion G protein-coupled receptor family member that plays a pivotal role in brain angiogenesis and in ensuring a tight blood-brain barrier. However, the signaling properties of GPR124 remain poorly defined. Here, we show that ectopic expression of GPR124 promotes cell adhesion, additive to extracellular matrix-dependent effect, coupled with filopodia and lamellipodia formation and an enrichment of a pool of the G protein-coupled receptor at actin-rich cellular protrusions containing VASP, a filopodial marker. Accordingly, GPR124-expressing cells also displayed increased activation of both Rac and Cdc42 GTPases. Mechanistically, we uncover novel direct interactions between endogenous GPR124 and the Rho guanine nucleotide exchange factors Elmo/Dock and intersectin (ITSN). Small fragments of either Elmo or ITSN1 that bind GPR124 blocked GPR124-induced cell adhesion. In addition, Gβγ interacts with the C-terminal tail of GPR124 and promotes the formation of a GPR124-Elmo complex. Furthermore, GPR124 also promotes the activation of the Elmo-Dock complex, as measured by Elmo phosphorylation on a conserved C-terminal tyrosine residue. Interestingly, Elmo and ITSN1 also interact with each other independently of their GPR124-recognition regions. Moreover, endogenous phospho-Elmo and ITSN1 co-localize with GPR124 at lamellipodia of adhering endothelial cells, where GPR124 expression contributes to polarity acquisition during wound healing. Collectively, our results indicate that GPR124 promotes cell adhesion via Elmo-Dock and ITSN. This constitutes a previously unrecognized complex formed of atypical and conventional Rho guanine nucleotide exchange factors for Rac and Cdc42 that is putatively involved in GPR124-dependent angiogenic responses. © 2017 by The American Society for

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

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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…

PDTD: a web-accessible protein database for drug target identification

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Gao Zhenting

2008-02-01

Full Text Available Abstract Background Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD, and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation. Description PDTD is a web-accessible protein database for in silico target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores. Conclusion PDTD serves as a comprehensive and

Evaluating the binding efficiency of pheromone binding protein with its natural ligand using molecular docking and fluorescence analysis

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Ilayaraja, Renganathan; Rajkumar, Ramalingam; Rajesh, Durairaj; Muralidharan, Arumugam Ramachandran; Padmanabhan, Parasuraman; Archunan, Govindaraju

2014-06-01

Chemosignals play a crucial role in social and sexual communication among inter- and intra-species. Chemical cues are bound with protein that is present in the pheromones irrespective of sex are commonly called as pheromone binding protein (PBP). In rats, the pheromone compounds are bound with low molecular lipocalin protein α2u-globulin (α2u). We reported farnesol is a natural endogenous ligand (compound) present in rat preputial gland as a bound volatile compound. In the present study, an attempt has been made through computational method to evaluating the binding efficiency of α2u with the natural ligand (farnesol) and standard fluorescent molecule (2-naphthol). The docking analysis revealed that the binding energy of farnesol and 2-naphthol was almost equal and likely to share some binding pocket of protein. Further, to extrapolate the results generated through computational approach, the α2u protein was purified and subjected to fluorescence titration and binding assay. The results showed that the farnesol is replaced by 2-naphthol with high hydrophobicity of TYR120 in binding sites of α2u providing an acceptable dissociation constant indicating the binding efficiency of α2u. The obtained results are in corroboration with the data made through computational approach.

Protein design using continuous rotamers.

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Pablo Gainza

2012-01-01

Full Text Available Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE.Software is available under the Lesser GNU Public License v3. Contact the authors for source code.

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

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Waqasuddin Khan

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

The Interaction Pattern between a Homology Model of 40S Ribosomal S9 Protein of Rhizoctonia solani and 1-Hydroxyphenaize by Docking Study

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Seema Dharni

2014-01-01

Full Text Available 1-Hydroxyphenazine (1-OH-PHZ, a natural product from Pseudomonas aeruginosa strain SD12, was earlier reported to have potent antifungal activity against Rhizoctonia solani. In the present work, the antifungal activity of 1-OH-PHZ on 40S ribosomal S9 protein was validated by molecular docking approach. 1-OH-PHZ showed interaction with two polar contacts with residues, Arg69 and Phe19, which inhibits the synthesis of fungal protein. Our study reveals that 1-OH-PHZ can be a potent inhibitor of 40S ribosomal S9 protein of R. solani that may be a promising approach for the management of fungal diseases.

CNA web server: rigidity theory-based thermal unfolding simulations of proteins for linking structure, (thermo-)stability, and function.

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Krüger, Dennis M; Rathi, Prakash Chandra; Pfleger, Christopher; Gohlke, Holger

2013-07-01

The Constraint Network Analysis (CNA) web server provides a user-friendly interface to the CNA approach developed in our laboratory for linking results from rigidity analyses to biologically relevant characteristics of a biomolecular structure. The CNA web server provides a refined modeling of thermal unfolding simulations that considers the temperature dependence of hydrophobic tethers and computes a set of global and local indices for quantifying biomacromolecular stability. From the global indices, phase transition points are identified where the structure switches from a rigid to a floppy state; these phase transition points can be related to a protein's (thermo-)stability. Structural weak spots (unfolding nuclei) are automatically identified, too; this knowledge can be exploited in data-driven protein engineering. The local indices are useful in linking flexibility and function and to understand the impact of ligand binding on protein flexibility. The CNA web server robustly handles small-molecule ligands in general. To overcome issues of sensitivity with respect to the input structure, the CNA web server allows performing two ensemble-based variants of thermal unfolding simulations. The web server output is provided as raw data, plots and/or Jmol representations. The CNA web server, accessible at http://cpclab.uni-duesseldorf.de/cna or http://www.cnanalysis.de, is free and open to all users with no login requirement.

Covalent docking of selected boron-based serine beta-lactamase inhibitors

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Sgrignani, Jacopo; Novati, Beatrice; Colombo, Giorgio; Grazioso, Giovanni

2015-05-01

AmpC β-lactamase is a hydrolytic enzyme conferring resistance to β-lactam antibiotics in multiple Gram-negative bacteria. Therefore, identification of non-β-lactam compounds able to inhibit the enzyme is crucial for the development of novel antibacterial therapies. In general, AmpC inhibitors have to engage the highly solvent-exposed catalytic site of the enzyme. Therefore, understanding the implications of ligand-protein induced-fit and water-mediated interactions behind the inhibitor-enzyme recognition process is fundamental for undertaking structure-based drug design process. Here, we focus on boronic acids, a promising class of beta-lactamase covalent inhibitors. First, we optimized a docking protocol able to reproduce the experimentally determined binding mode of AmpC inhibitors bearing a boronic group. This goal was pursued (1) performing rigid and flexible docking calculations aiming to establish the role of the side chain conformations; and (2) investigating the role of specific water molecules in shaping the enzyme active site and mediating ligand protein interactions. Our calculations showed that some water molecules, conserved in the majority of the considered X-ray structures, are needed to correctly predict the binding pose of known covalent AmpC inhibitors. On this basis, we formalized our findings in a docking and scoring protocol that could be useful for the structure-based design of new boronic acid AmpC inhibitors.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

In-silico determination of insecticidal potential of Vip3Aa-Cry1Ac fusion protein against Lepidopteran targets using molecular docking

Directory of Open Access Journals (Sweden)

Aftab eAhmad

2015-12-01

Full Text Available Study and research of Bt (Bacillus thuringiensis transgenic plants have opened new ways to combat insect pests. Over the decades, however, insect pests, especially the Lepidopteran, have developed tolerance against Bt delta-endotoxins. Such issues can be addressed through the development of novel toxins with greater toxicity and affinity against a broad range of insect receptors. In this computational study, functional domains of Bacillus thuringiensis crystal delta-endotoxin (Cry1Ac insecticidal protein and vegetative insecticidal protein (Vip3Aa have been fused to develop a broad-range Vip3Aa-Cry1Ac fusion protein. Cry1Ac and Vip3Aa are non-homologous insecticidal proteins possessing receptors against different targets within the midgut of insects. The insecticidal proteins were fused to broaden the insecticidal activity. Molecular docking analysis of the fusion protein against aminopeptidase-N (APN and cadherin receptors of five Lepidopteran insects (Agrotis ipsilon, Helicoverpa armigera, Pectinophora gossypiella, Spodoptera exigua and Spodoptera litura revealed that the Ser290, Ser293, Leu337, Thr340 and Arg437 residues of the fusion protein are involved in the interaction with insect receptors. The Helicoverpa armigera cadherin receptor, however, showed no interaction, which might be due to either loss or burial of interactive residues inside the fusion protein. These findings revealed that the Vip3Aa-Cry1Ac fusion protein has a strong affinity against Lepidopteran insect receptors and hence has a potential to be an efficient broad-range insecticidal protein.

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

Science.gov (United States)

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.

Ultrafast protein structure-based virtual screening with Panther

Science.gov (United States)

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 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.

Regulation of the interaction between protein kinase C-related protein kinase 2 (PRK2) and its upstream kinase, 3-phosphoinositide-dependent protein kinase 1 (PDK1)

DEFF Research Database (Denmark)

Dettori, Rosalia; Sonzogni, Silvina; Meyer, Lucas

2009-01-01

of numerous AGC kinases, including the protein kinase C-related protein kinases (PRKs). Here we studied the docking interaction between PDK1 and PRK2 and analyzed the mechanisms that regulate this interaction. In vivo labeling of recombinant PRK2 by (32)P(i) revealed phosphorylation at two sites......, the activation loop and the Z/TM in the C-terminal extension. We provide evidence that phosphorylation of the Z/TM site of PRK2 inhibits its interaction with PDK1. Our studies further provide a mechanistic model to explain different steps in the docking interaction and regulation. Interestingly, we found...... that the mechanism that negatively regulates the docking interaction of PRK2 to the upstream kinase PDK1 is directly linked to the activation mechanism of PRK2 itself. Finally, our results indicate that the mechanisms underlying the regulation of the interaction between PRK2 and PDK1 are specific for PRK2 and do...

Production of antioxidant and ACE-inhibitory peptides from Kluyveromyces marxianus protein hydrolysates: Purification and molecular docking

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Mahta Mirzaei

2018-04-01

Full Text Available Kluyveromyces marxianus protein hydrolysates were prepared by two different sonicated-enzymatic (trypsin and chymotrypsin hydrolysis treatments to obtain antioxidant and ACE-inhibitory peptides. Trypsin and chymotrypsin hydrolysates obtained by 5 h, exhibited the highest antioxidant and ACE-inhibitory activities. After fractionation using ultrafiltration and reverse phase high performance liquid chromatography (RP-HPLC techniques, two new peptides were identified. One fragment (LL-9, MW = 1180 Da with the amino acid sequence of Leu-Pro-Glu-Ser-Val-His-Leu-Asp-Lys showed significant ACE inhibitory activity (IC50 = 22.88 μM while another peptide fragment (VL-9, MW = 1118 Da with the amino acid sequence of Val-Leu-Ser-Thr-Ser-Phe-Pro-Pro-Lys showed the highest antioxidant and ACE inhibitory properties (IC50 = 15.20 μM, 5568 μM TE/mg protein. The molecular docking studies revealed that the ACE inhibitory activities of VL-9 is due to interaction with the S2 (His513, His353, Glu281 and S′1 (Glu162 pockets of ACE and LL-9 can fit perfectly into the S1 (Thr345 and S2 (Tyr520, Lys511, Gln281 pockets of ACE. Keywords: K. marxianus, Bioactive peptides, Antioxidant, ACE inhibitory, Protein hydrolysate

Virtual screening of natural inhibitors to the predicted HBx protein structure of Hepatitis B Virus using molecular docking for identification of potential lead molecules for liver cancer

Science.gov (United States)

Pathak, Rajesh Kumar; Baunthiyal, Mamta; Taj, Gohar; Kumar, Anil

2014-01-01

The HBx protein in Hepatitis B Virus (HBV) is a potential target for anti-liver cancer molecules. Therefore, it is of interest to screen known natural compounds against the HBx protein using molecular docking. However, the structure of HBx is not yet known. Therefore, the predicted structure of HBx using threading in LOMET was used for docking against plant derived natural compounds (curcumin, oleanolic acid, resveratrol, bilobetin, luteoline, ellagic acid, betulinic acid and rutin) by Molegro Virtual Docker. The screening identified rutin with binding energy of -161.65 Kcal/mol. Thus, twenty derivatives of rutin were further designed and screened against HBx. These in silico experiments identified compounds rutin01 (-163.16 Kcal/mol) and rutin08 (- 165.76 Kcal/mol) for further consideration and downstream validation. PMID:25187683

Role of rab proteins in epithelial membrane traffic

NARCIS (Netherlands)

van Ijzendoorn, SCD; Mostov, KE; Hoekstra, D

2003-01-01

Small GTPase rab proteins play an important role in various aspects of membrane traffic, including cargo selection, vesicle budding, vesicle motility, tethering, docking, and fusion. Recent data suggest also that rabs, and their divalent effector proteins, organize organelle subdomains and as such

Site-specific tagging proteins with a rigid, small and stable transition metal chelator, 8-hydroxyquinoline, for paramagnetic NMR analysis

Energy Technology Data Exchange (ETDEWEB)

Yang, Yin; Huang, Feng [Nankai University, State Key Laboratory of Elemento-Organic Chemistry, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin) (China); Huber, Thomas [Australian National University, Research School of Chemistry (Australia); Su, Xun-Cheng, E-mail: xunchengsu@nankai.edu.cn [Nankai University, State Key Laboratory of Elemento-Organic Chemistry, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin) (China)

2016-02-15

Design of a paramagnetic metal binding motif in a protein is a valuable way for understanding the function, dynamics and interactions of a protein by paramagnetic NMR spectroscopy. Several strategies have been proposed to site-specifically tag proteins with paramagnetic lanthanide ions. Here we report a simple approach of engineering a transition metal binding motif via site-specific labelling of a protein with 2-vinyl-8-hydroxyquinoline (2V-8HQ). The protein-2V-8HQ adduct forms a stable complex with transition metal ions, Mn(II), Co(II), Ni(II), Cu(II) and Zn(II). The paramagnetic effects generated by these transition metal ions were evaluated by NMR spectroscopy. We show that 2V-8HQ is a rigid and stable transition metal binding tag. The coordination of the metal ion can be assisted by protein sidechains. More importantly, tunable paramagnetic tensors are simply obtained in an α-helix that possesses solvent exposed residues in positions i and i + 3, where i is the residue to be mutated to cysteine, i + 3 is Gln or Glu or i − 4 is His. The coordination of a sidechain carboxylate/amide or imidazole to cobalt(II) results in different structural geometries, leading to different paramagnetic tensors as shown by experimental data.

How does symmetry impact the flexibility of proteins?

Science.gov (United States)

Schulze, Bernd; Sljoka, Adnan; Whiteley, Walter

2014-02-13

It is well known that (i) the flexibility and rigidity of proteins are central to their function, (ii) a number of oligomers with several copies of individual protein chains assemble with symmetry in the native state and (iii) added symmetry sometimes leads to added flexibility in structures. We observe that the most common symmetry classes of protein oligomers are also the symmetry classes that lead to increased flexibility in certain three-dimensional structures-and investigate the possible significance of this coincidence. This builds on the well-developed theory of generic rigidity of body-bar frameworks, which permits an analysis of the rigidity and flexibility of molecular structures such as proteins via fast combinatorial algorithms. In particular, we outline some very simple counting rules and possible algorithmic extensions that allow us to predict continuous symmetry-preserving motions in body-bar frameworks that possess non-trivial point-group symmetry. For simplicity, we focus on dimers, which typically assemble with twofold rotational axes, and often have allosteric function that requires motions to link distant sites on the two protein chains.

Dendrimer-protein interactions versus dendrimer-based nanomedicine.

Science.gov (United States)

Shcharbin, Dzmitry; Shcharbina, Natallia; Dzmitruk, Volha; Pedziwiatr-Werbicka, Elzbieta; Ionov, Maksim; Mignani, Serge; de la Mata, F Javier; Gómez, Rafael; Muñoz-Fernández, Maria Angeles; Majoral, Jean-Pierre; Bryszewska, Maria

2017-04-01

Dendrimers are hyperbranched polymers belonging to the huge class of nanomedical devices. Their wide application in biology and medicine requires understanding of the fundamental mechanisms of their interactions with biological systems. Summarizing, electrostatic force plays the predominant role in dendrimer-protein interactions, especially with charged dendrimers. Other kinds of interactions have been proven, such as H-bonding, van der Waals forces, and even hydrophobic interactions. These interactions depend on the characteristics of both participants: flexibility and surface charge of a dendrimer, rigidity of protein structure and the localization of charged amino acids at its surface. pH and ionic strength of solutions can significantly modulate interactions. Ligands and cofactors attached to a protein can also change dendrimer-protein interactions. Binding of dendrimers to a protein can change its secondary structure, conformation, intramolecular mobility and functional activity. However, this strongly depends on rigidity versus flexibility of a protein's structure. In addition, the potential applications of dendrimers to nanomedicine are reviwed related to dendrimer-protein interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

Manipulating fatty acid biosynthesis in microalgae for biofuel through protein-protein interactions.

Directory of Open Access Journals (Sweden)

Jillian L Blatti

Full Text Available Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP and thioesterase (TE govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes.

MORPH-PRO: a novel algorithm and web server for protein morphing.

Science.gov (United States)

Castellana, Natalie E; Lushnikov, Andrey; Rotkiewicz, Piotr; Sefcovic, Natasha; Pevzner, Pavel A; Godzik, Adam; Vyatkina, Kira

2013-07-11

Proteins are known to be dynamic in nature, changing from one conformation to another while performing vital cellular tasks. It is important to understand these movements in order to better understand protein function. At the same time, experimental techniques provide us with only single snapshots of the whole ensemble of available conformations. Computational protein morphing provides a visualization of a protein structure transitioning from one conformation to another by producing a series of intermediate conformations. We present a novel, efficient morphing algorithm, Morph-Pro based on linear interpolation. We also show that apart from visualization, morphing can be used to provide plausible intermediate structures. We test this by using the intermediate structures of a c-Jun N-terminal kinase (JNK1) conformational change in a virtual docking experiment. The structures are shown to dock with higher score to known JNK1-binding ligands than structures solved using X-Ray crystallography. This experiment demonstrates the potential applications of the intermediate structures in modeling or virtual screening efforts. Visualization of protein conformational changes is important for characterization of protein function. Furthermore, the intermediate structures produced by our algorithm are good approximations to true structures. We believe there is great potential for these computationally predicted structures in protein-ligand docking experiments and virtual screening. The Morph-Pro web server can be accessed at http://morph-pro.bioinf.spbau.ru.

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

Science.gov (United States)

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.

The low molecular weight protein PsaI stabilizes the light-harvesting complex II docking site of photosystem I

DEFF Research Database (Denmark)

Plöchinger, Magdalena; Torabi, Salar; Rantala, Marjaana

2016-01-01

PsaI represents one of three low molecular weight peptides of PSI. Targeted inactivation of the plastid PsaI gene in Nicotiana tabacum has no measurable effect on photosynthetic electron transport around PSI or on accumulation of proteins involved in photosynthesis. Instead, the lack of Psa......I destabilizes the association of PsaL and PsaH to PSI, both forming the light-harvesting complex (LHC)II docking site of PSI. These alterations at the LHCII binding site surprisingly did not prevent state transition but led to an increased incidence of PSI-LHCII complexes, coinciding with an elevated...

Coarse-grained versus atomistic simulations : realistic interaction free energies for real proteins

NARCIS (Netherlands)

May, Ali; Pool, René; van Dijk, Erik; Bijlard, Jochem; Abeln, Sanne; Heringa, Jaap; Feenstra, K Anton

2014-01-01

MOTIVATION: To assess whether two proteins will interact under physiological conditions, information on the interaction free energy is needed. Statistical learning techniques and docking methods for predicting protein-protein interactions cannot quantitatively estimate binding free energies. Full

Coarse-grained versus atomistic simulations: realistic interaction free energies for real proteins

NARCIS (Netherlands)

May, A.; Pool, R.; van Dijk, E.; Bijlard, J.; Abeln, S.; Heringa, J.; Feenstra, K.A.

2014-01-01

MOTIVATION: To assess whether two proteins will interact under physiological conditions, information on the interaction free energy is needed. Statistical learning techniques and docking methods for predicting protein-protein interactions cannot quantitatively estimate binding free energies. Full

Structural deformation upon protein-protein interaction: a structural alphabet approach.

Science.gov (United States)

Martin, Juliette; Regad, Leslie; Lecornet, Hélène; Camproux, Anne-Claude

2008-02-28

In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%). This proportion is even greater in the interface regions (41%). Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

Structural deformation upon protein-protein interaction: A structural alphabet approach

Directory of Open Access Journals (Sweden)

Lecornet Hélène

2008-02-01

Full Text Available Abstract Background In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. Results In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%. This proportion is even greater in the interface regions (41%. Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Conclusion Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

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

Science.gov (United States)

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

Convenient method for resolving degeneracies due to symmetry of the magnetic susceptibility tensor and its application to pseudo contact shift-based protein–protein complex structure determination

International Nuclear Information System (INIS)

Kobashigawa, Yoshihiro; Saio, Tomohide; Ushio, Masahiro; Sekiguchi, Mitsuhiro; Yokochi, Masashi; Ogura, Kenji; Inagaki, Fuyuhiko

2012-01-01

Pseudo contact shifts (PCSs) induced by paramagnetic lanthanide ions fixed in a protein frame provide long-range distance and angular information, and are valuable for the structure determination of protein–protein and protein–ligand complexes. We have been developing a lanthanide-binding peptide tag (hereafter LBT) anchored at two points via a peptide bond and a disulfide bond to the target proteins. However, the magnetic susceptibility tensor displays symmetry, which can cause multiple degenerated solutions in a structure calculation based solely on PCSs. Here we show a convenient method for resolving this degeneracy by changing the spacer length between the LBT and target protein. We applied this approach to PCS-based rigid body docking between the FKBP12-rapamycin complex and the mTOR FRB domain, and demonstrated that degeneracy could be resolved using the PCS restraints obtained from two-point anchored LBT with two different spacer lengths. The present strategy will markedly increase the usefulness of two-point anchored LBT for protein complex structure determination.

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

Science.gov (United States)

Kapoor, Abhijeet; Travesset, Alex

2014-03-01

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

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

Science.gov (United States)

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.

Discovery of a new chemical series of BRD4(1) inhibitors using protein-ligand docking and structure-guided design.

Science.gov (United States)

Duffy, Bryan C; Liu, Shuang; Martin, Gregory S; Wang, Ruifang; Hsia, Ming Min; Zhao, He; Guo, Cheng; Ellis, Michael; Quinn, John F; Kharenko, Olesya A; Norek, Karen; Gesner, Emily M; Young, Peter R; McLure, Kevin G; Wagner, Gregory S; Lakshminarasimhan, Damodharan; White, Andre; Suto, Robert K; Hansen, Henrik C; Kitchen, Douglas B

2015-07-15

Bromodomains are key transcriptional regulators that are thought to be druggable epigenetic targets for cancer, inflammation, diabetes and cardiovascular therapeutics. Of particular importance is the first of two bromodomains in bromodomain containing 4 protein (BRD4(1)). Protein-ligand docking in BRD4(1) was used to purchase a small, focused screening set of compounds possessing a large variety of core structures. Within this set, a small number of weak hits each contained a dihydroquinoxalinone ring system. We purchased other analogs with this ring system and further validated the new hit series and obtained improvement in binding inhibition. Limited exploration by new analog synthesis showed that the binding inhibition in a FRET assay could be improved to the low μM level making this new core a potential hit-to-lead series. Additionally, the predicted geometries of the initial hit and an improved analog were confirmed by X-ray co-crystallography with BRD4(1). Copyright © 2015 Elsevier Ltd. All rights reserved.

Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.

Directory of Open Access Journals (Sweden)

Amin R Mazloom

2011-12-01

Full Text Available Coregulator proteins (CoRegs are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP followed by mass spectrometry (MS applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/.

Protein-protein interface detection using the energy centrality relationship (ECR characteristic of proteins.

Directory of Open Access Journals (Sweden)

Sanjana Sudarshan

Full Text Available Specific protein interactions are responsible for most biological functions. Distinguishing Functionally Linked Interfaces of Proteins (FLIPs, from Functionally uncorrelated Contacts (FunCs, is therefore important to characterizing these interactions. To achieve this goal, we have created a database of protein structures called FLIPdb, containing proteins belonging to various functional sub-categories. Here, we use geometric features coupled with Kortemme and Baker's computational alanine scanning method to calculate the energetic sensitivity of each amino acid at the interface to substitution, identify hotspots, and identify other factors that may contribute towards an interface being FLIP or FunC. Using Principal Component Analysis and K-means clustering on a training set of 160 interfaces, we could distinguish FLIPs from FunCs with an accuracy of 76%. When these methods were applied to two test sets of 18 and 170 interfaces, we achieved similar accuracies of 78% and 80%. We have identified that FLIP interfaces have a stronger central organizing tendency than FunCs, due, we suggest, to greater specificity. We also observe that certain functional sub-categories, such as enzymes, antibody-heavy-light, antibody-antigen, and enzyme-inhibitors form distinct sub-clusters. The antibody-antigen and enzyme-inhibitors interfaces have patterns of physical characteristics similar to those of FunCs, which is in agreement with the fact that the selection pressures of these interfaces is differently evolutionarily driven. As such, our ECR model also successfully describes the impact of evolution and natural selection on protein-protein interfaces. Finally, we indicate how our ECR method may be of use in reducing the false positive rate of docking calculations.

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

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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.

Prediction of Protein Configurational Entropy (Popcoen).

Science.gov (United States)

Goethe, Martin; Gleixner, Jan; Fita, Ignacio; Rubi, J Miguel

2018-03-13

A knowledge-based method for configurational entropy prediction of proteins is presented; this methodology is extremely fast, compared to previous approaches, because it does not involve any type of configurational sampling. Instead, the configurational entropy of a query fold is estimated by evaluating an artificial neural network, which was trained on molecular-dynamics simulations of ∼1000 proteins. The predicted entropy can be incorporated into a large class of protein software based on cost-function minimization/evaluation, in which configurational entropy is currently neglected for performance reasons. Software of this type is used for all major protein tasks such as structure predictions, proteins design, NMR and X-ray refinement, docking, and mutation effect predictions. Integrating the predicted entropy can yield a significant accuracy increase as we show exemplarily for native-state identification with the prominent protein software FoldX. The method has been termed Popcoen for Prediction of Protein Configurational Entropy. An implementation is freely available at http://fmc.ub.edu/popcoen/ .

Mathematical aspects of molecular replacement. III. Properties of space groups preferred by proteins in the Protein Data Bank.

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Chirikjian, G; Sajjadi, S; Toptygin, D; Yan, Y

2015-03-01

The main goal of molecular replacement in macromolecular crystallography is to find the appropriate rigid-body transformations that situate identical copies of model proteins in the crystallographic unit cell. The search for such transformations can be thought of as taking place in the coset space Γ\\G where Γ is the Sohncke group of the macromolecular crystal and G is the continuous group of rigid-body motions in Euclidean space. This paper, the third in a series, is concerned with viewing nonsymmorphic Γ in a new way. These space groups, rather than symmorphic ones, are the most common ones for protein crystals. Moreover, their properties impact the structure of the space Γ\\G. In particular, nonsymmorphic space groups contain both Bieberbach subgroups and symmorphic subgroups. A number of new theorems focusing on these subgroups are proven, and it is shown that these concepts are related to the preferences that proteins have for crystallizing in different space groups, as observed in the Protein Data Bank.

Mechanical Modeling and Computer Simulation of Protein Folding

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

2014-01-01

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

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

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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.

1H-detected MAS solid-state NMR experiments enable the simultaneous mapping of rigid and dynamic domains of membrane proteins

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Gopinath, T.; Nelson, Sarah E. D.; Veglia, Gianluigi

2017-12-01

Magic angle spinning (MAS) solid-state NMR (ssNMR) spectroscopy is emerging as a unique method for the atomic resolution structure determination of native membrane proteins in lipid bilayers. Although 13C-detected ssNMR experiments continue to play a major role, recent technological developments have made it possible to carry out 1H-detected experiments, boosting both sensitivity and resolution. Here, we describe a new set of 1H-detected hybrid pulse sequences that combine through-bond and through-space correlation elements into single experiments, enabling the simultaneous detection of rigid and dynamic domains of membrane proteins. As proof-of-principle, we applied these new pulse sequences to the membrane protein phospholamban (PLN) reconstituted in lipid bilayers under moderate MAS conditions. The cross-polarization (CP) based elements enabled the detection of the relatively immobile residues of PLN in the transmembrane domain using through-space correlations; whereas the most dynamic region, which is in equilibrium between folded and unfolded states, was mapped by through-bond INEPT-based elements. These new 1H-detected experiments will enable one to detect not only the most populated (ground) states of biomacromolecules, but also sparsely populated high-energy (excited) states for a complete characterization of protein free energy landscapes.

Plant plasma membrane 14-3-3 proteins differ in solubility and form fusicoccin-dependent complexes

NARCIS (Netherlands)

Korthout, H.A.A.J.; de Boer, A.H.

1998-01-01

The binding protein for the phytotoxin fusicoccin belongs to the class of highly conserved 14-3-3 proteins. A general principle for the mode of action of 14-3-3 proteins is that they serve as docking clamps in order to facilitate protein interactions. This implies that 14-3-3 proteins may behave

Modification of -Adenosyl--Homocysteine as Inhibitor of Nonstructural Protein 5 Methyltransferase Dengue Virus Through Molecular Docking and Molecular Dynamics Simulation

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Usman Sumo Friend Tambunan

2017-04-01

Full Text Available Dengue fever is still a major threat worldwide, approximately threatening two-fifths of the world’s population in tropical and subtropical countries. Nonstructural protein 5 (NS5 methyltransferase enzyme plays a vital role in the process of messenger RNA capping of dengue by transferring methyl groups from S -adenosyl- l -methionine to N7 atom of the guanine bases of RNA and the RNA ribose group of 2′OH, resulting in S -adenosyl- l -homocysteine (SAH. The modification of SAH compound was screened using molecular docking and molecular dynamics simulation, along with computational ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity test. The 2 simulations were performed using Molecular Operating Environment (MOE 2008.10 software, whereas the ADME-Tox test was performed using various software. The modification of SAH compound was done using several functional groups that possess different polarities and properties, resulting in 3460 ligands to be docked. After conducting docking simulation, we earned 3 best ligands (SAH-M331, SAH-M2696, and SAH-M1356 based on ΔG binding and molecular interactions, which show better results than the standard ligands. Moreover, the results of molecular dynamics simulation show that the best ligands are still able to maintain the active site residue interaction with the binding site until the end of the simulation. After a series of molecular docking and molecular dynamics simulation were performed, we concluded that SAH-M1356 ligand is the most potential SAH-based compound to inhibit NS5 methyltransferase enzyme for treating dengue fever.

Enrichment of Druggable Conformations from Apo Protein Structures Using Cosolvent-Accelerated Molecular Dynamics

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Andrew Kalenkiewicz

2015-04-01

Full Text Available Here we describe the development of an improved workflow for utilizing experimental and simulated protein conformations in the structure-based design of inhibitors for anti-apoptotic Bcl-2 family proteins. Traditional structure-based approaches on similar targets are often constrained by the sparsity of available structures and difficulties in finding lead compounds that dock against flat, flexible protein-protein interaction surfaces. By employing computational docking of known small molecule inhibitors, we have demonstrated that structural ensembles derived from either accelerated MD (aMD or MD in the presence of an organic cosolvent generally give better scores than those assessed from analogous conventional MD. Furthermore, conformations obtained from combined cosolvent aMD simulations started with the apo-Bcl-xL structure yielded better average and minimum docking scores for known binders than an ensemble of 72 experimental apo- and ligand-bound Bcl-xL structures. A detailed analysis of the simulated conformations indicates that the aMD effectively enhanced conformational sampling of the flexible helices flanking the main Bcl-xL binding groove, permitting the cosolvent acting as small ligands to penetrate more deeply into the binding pocket and shape ligand-bound conformations not evident in conventional simulations. We believe this approach could be useful for identifying inhibitors against other protein-protein interaction systems involving highly flexible binding sites, particularly for targets with less accumulated structural data.

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

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Pons, Jean-Luc; Labesse, Gilles

2009-07-01

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

Curating viscoelastic properties of icosahedral viruses, virus-based nanomaterials, and protein cages.

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Kant, Ravi; Rayaprolu, Vamseedhar; McDonald, Kaitlyn; Bothner, Brian

2018-06-01

The beauty, symmetry, and functionality of icosahedral virus capsids has attracted the attention of biologists, physicists, and mathematicians ever since they were first observed. Viruses and protein cages assemble into functional architectures in a range of sizes, shapes, and symmetries. To fulfill their biological roles, these structures must self-assemble, resist stress, and are often dynamic. The increasing use of icosahedral capsids and cages in materials science has driven the need to quantify them in terms of structural properties such as rigidity, stiffness, and viscoelasticity. In this study, we employed Quartz Crystal Microbalance with Dissipation technology (QCM-D) to characterize and compare the mechanical rigidity of different protein cages and viruses. We attempted to unveil the relationships between rigidity, radius, shell thickness, and triangulation number. We show that the rigidity and triangulation numbers are inversely related to each other and the comparison of rigidity and radius also follows the same trend. Our results suggest that subunit orientation, protein-protein interactions, and protein-nucleic acid interactions are important for the resistance to deformation of these complexes, however, the relationships are complex and need to be explored further. The QCM-D based viscoelastic measurements presented here help us elucidate these relationships and show the future prospect of this technique in the field of physical virology and nano-biotechnology.

Molecular docking study of Papaver alkaloids to some alkaloid receptors

Directory of Open Access Journals (Sweden)

A. Nofallah

2017-11-01

Full Text Available Background and objectives: More than 40 different alkaloids have been obtained from opium the most important of which are morphine, codeine, papaverine, noscapine and tabaine. Opioid alkaloids produce analgesia by affecting areas of the brain that have peptides with pharmacological pseudo-opioid properties. These alkaloids show important effects on some intracellular peptides like mu, delta, and kappa receptors. Therefore, studying the effects of these alkaloids on different receptors is essential. Methods: Molecular docking is a well-known method in exploring the protein-ligand interactions. In this research, five important alkaloids were docked to crystal structure of human mu opioid receptor (4DKL, human delta opioid receptor (4EJ4 and human kappa opioid receptor (4DJH which were retrieved from protein databank. The 3D-structures of alkaloids were drawn by chembiooffice2010 and minimized with hyperchem package and submitted to molecular docking utilizing autodock-vina. Flexibility of the proteins was considered. The docking studies were performed to compare the affinity of these five alkaloids to the mentioned receptors. Results: We computationally docked each alkaloid compound onto each receptor structure and estimated their binding affinity based on dock scores. Dock score is a criteria including binding energy which utilized here for prediction and comparison of the binding affinities. Binding interactions of the docked alkaloids in receptor pockets were also visually inspected and compared. Conclusion: In this approach, using docking study as a computational method provided a valuable insight of opioid receptor pocket structures which would be essential to design more efficient drugs in pain managements and addiction treatments.

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

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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.

Nitrate as a probe of cytochrome c surface : crystallographic identification of crucial "hot spots" for protein-protein recognition

NARCIS (Netherlands)

De March, Matteo; Demitri, Nicola; De Zorzi, Rita; Casini, Angela; Gabbiani, Chiara; Guerri, Annalisa; Messori, Luigi; Geremia, Silvano

The electrostatic surface of cytochrome c and its changes with the iron oxidation state are involved in the docking and undocking processes of this protein to its biological partners in the mitochondrial respiratory pathway. To investigate the subtle mechanisms of formation of productive

Improving Docking Performance Using Negative Image-Based Rescoring.

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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.

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

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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.

GENIUS In Silico Screening Technology for HCV Drug Discovery.

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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.

GOMoDo: A GPCRs online modeling and docking webserver.

Directory of Open Access Journals (Sweden)

Massimo Sandal

Full Text Available G-protein coupled receptors (GPCRs are a superfamily of cell signaling membrane proteins that include >750 members in the human genome alone. They are the largest family of drug targets. The vast diversity and relevance of GPCRs contrasts with the paucity of structures available: only 21 unique GPCR structures have been experimentally determined as of the beginning of 2013. User-friendly modeling and small molecule docking tools are thus in great demand. While both GPCR structural predictions and docking servers exist separately, with GOMoDo (GPCR Online Modeling and Docking, we provide a web server to seamlessly model GPCR structures and dock ligands to the models in a single consistent pipeline. GOMoDo can automatically perform template choice, homology modeling and either blind or information-driven docking by combining together proven, state of the art bioinformatic tools. The web server gives the user the possibility of guiding the whole procedure. The GOMoDo server is freely accessible at http://molsim.sci.univr.it/gomodo.

THE APPLICATION OF PASS-COMPUTER PROGRAMME AND MOLECULAR DOCKING FOR THE SEARCH OF NEW ANTICONVULSANTS

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Perekhoda L.O.

2014-12-01

Full Text Available Introduction. Currently the priority goal of designing drugs is the integration of the methods of organic chemistry and pharmacology. The application of computer programmes which can predict interaction of Annals of potential drugs with molecules of biological targets makes possible to decrease the number of experiments on laboratory animals. Thereby the economic efficiency of production of new medicines increases. Models of the research the anticonvulsant activity (in particular, korazol, thiosemikarbazid, strychnine, etc. are the most rigid experimental models of pharmacological screening, which basically entails the pains of laboratory animals or their death. The application of computer programmes in the research of potential anticonvulsants has economic and social desirability and high level of importance for the pharmaceutical science and health care. The most perspective methods of research are the virtual screening, molecular docking. These methods allow to evaluate the affinity of a substance to a specific biological target, i.e. to identify an inhibitor of a particular enzyme or protein. Material and methods. We have carried out the construction of 50 groups substances (507 hypothetical structures. We have chosen the five-membered di(threeazaheterocycle as basic pharmacophores to form virtual structures because firstly their structure is similar to cyclic conformation of neurotransmitter and secondly according to the literature perspective anticonvulsants had already found among these derivatives. Computer prediction of pharmacological activity for all compounds of virtual database was performed using the PASS (Prediction of Activity Spectra for Substances computer programme. Results obtained by PASS-computer programme showed prospects of search the anticonvulsants among 10 groups of derivatives di(threeazaheterocycles (probable activity (Pa of substances of these groups are from 0.5 to 0.84. In order to determine the potential

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

KAUST Repository

Chen, Peng

2015-12-03

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

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

KAUST Repository

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

2015-01-01

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

A Class of Rigid Linker-bearing Glucosides for Membrane Protein Structural Study.

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Sadaf, Aiman; Mortensen, Jonas S; Capaldi, Stefano; Tikhonova, Elena; Hariharan, Parameswaran; de Castro Ribeiro, Orquidea; Loland, Claus J; Guan, Lan; Byrne, Bernadette; Chae, Pil Seok

2016-03-01

Membrane proteins are amphipathic bio-macromolecules incompatible with the polar environments of aqueous media. Conventional detergents encapsulate the hydrophobic surfaces of membrane proteins allowing them to exist in aqueous solution. Membrane proteins stabilized by detergent micelles are used for structural and functional analysis. Despite the availability of a large number of detergents, only a few agents are sufficiently effective at maintaining the integrity of membrane proteins to allow successful crystallization. In the present study, we describe a novel class of synthetic amphiphiles with a branched tail group and a triglucoside head group. These head and tail groups were connected via an amide or ether linkage by using a tris(hydroxylmethyl)aminomethane (TRIS) or neopentyl glycol (NPG) linker to produce TRIS-derived triglucosides (TDTs) and NPG-derived triglucosides (NDTs), respectively. Members of this class conferred enhanced stability on target membrane proteins compared to conventional detergents. Because of straightforward synthesis of the novel agents and their favourable effects on a range of membrane proteins, these agents should be of wide applicability to membrane protein science.

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

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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.

Texturized dairy proteins.

Science.gov (United States)

Onwulata, Charles I; Phillips, John G; Tunick, Michael H; Qi, Phoebi X; Cooke, Peter H

2010-03-01

Dairy proteins are amenable to structural modifications induced by high temperature, shear, and moisture; in particular, whey proteins can change conformation to new unfolded states. The change in protein state is a basis for creating new foods. The dairy products, nonfat dried milk (NDM), whey protein concentrate (WPC), and whey protein isolate (WPI) were modified using a twin-screw extruder at melt temperatures of 50, 75, and 100 degrees C, and moistures ranging from 20 to 70 wt%. Viscoelasticity and solubility measurements showed that extrusion temperature was a more significant (P extruded dairy protein ranged from rigid (2500 N) to soft (2.7 N). Extruding at or above 75 degrees C resulted in increased peak force for WPC (138 to 2500 N) and WPI (2.7 to 147.1 N). NDM was marginally texturized; the presence of lactose interfered with its texturization. WPI products extruded at 50 degrees C were not texturized; their solubility values ranged from 71.8% to 92.6%. A wide possibility exists for creating new foods with texturized dairy proteins due to the extensive range of states achievable. Dairy proteins can be used to boost the protein content in puffed snacks made from corn meal, but unmodified, they bind water and form doughy pastes with starch. To minimize the water binding property of dairy proteins, WPI, or WPC, or NDM were modified by extrusion processing. Extrusion temperature conditions were adjusted to 50, 75, or 100 degrees C, sufficient to change the structure of the dairy proteins, but not destroy them. Extrusion modified the structures of these dairy proteins for ease of use in starchy foods to boost nutrient levels. Dairy proteins can be used to boost the protein content in puffed snacks made from corn meal, but unmodified, they bind water and form doughy pastes with starch. To minimize the water binding property of dairy proteins, whey protein isolate, whey protein concentrate, or nonfat dried milk were modified by extrusion processing. Extrusion

Computational multiscale modeling in protein--ligand docking.

Science.gov (United States)

Taufer, Michela; Armen, Roger; Chen, Jianhan; Teller, Patricia; Brooks, Charles

2009-01-01

In biological systems, the binding of small molecule ligands to proteins is a crucial process for almost every aspect of biochemistry and molecular biology. Enzymes are proteins that function by catalyzing specific biochemical reactions that convert reactants into products. Complex organisms are typically composed of cells in which thousands of enzymes participate in complex and interconnected biochemical pathways. Some enzymes serve as sequential steps in specific pathways (such as energy metabolism), while others function to regulate entire pathways and cellular functions [1]. Small molecule ligands can be designed to bind to a specific enzyme and inhibit the biochemical reaction. Inhibiting the activity of key enzymes may result in the entire biochemical pathways being turned on or off [2], [3]. Many small molecule drugs marketed today function in this generic way as enzyme inhibitors. If research identifies a specific enzyme as being crucial to the progress of disease, then this enzyme may be targeted with an inhibitor, which may slow down or reverse the progress of disease. In this way, enzymes are targeted from specific pathogens (e.g., virus, bacteria, fungi) for infectious diseases [4], [5], and human enzymes are targeted for noninfectious diseases such as cardiovascular disease, cancer, diabetes, and neurodegenerative diseases [6].

A method for fast energy estimation and visualization of protein-ligand interaction

Science.gov (United States)

Tomioka, Nobuo; Itai, Akiko; Iitaka, Yoichi

1987-10-01

A new computational and graphical method for facilitating ligand-protein docking studies is developed on a three-dimensional computer graphics display. Various physical and chemical properties inside the ligand binding pocket of a receptor protein, whose structure is elucidated by X-ray crystal analysis, are calculated on three-dimensional grid points and are stored in advance. By utilizing those tabulated data, it is possible to estimate the non-bonded and electrostatic interaction energy and the number of possible hydrogen bonds between protein and ligand molecules in real time during an interactive docking operation. The method also provides a comprehensive visualization of the local environment inside the binding pocket. With this method, it becomes easier to find a roughly stable geometry of ligand molecules, and one can therefore make a rapid survey of the binding capability of many drug candidates. The method will be useful for drug design as well as for the examination of protein-ligand interactions.

DNA looping by FokI: the impact of twisting and bending rigidity on protein-induced looping dynamics

Science.gov (United States)

Laurens, Niels; Rusling, David A.; Pernstich, Christian; Brouwer, Ineke; Halford, Stephen E.; Wuite, Gijs J. L.

2012-01-01

Protein-induced DNA looping is crucial for many genetic processes such as transcription, gene regulation and DNA replication. Here, we use tethered-particle motion to examine the impact of DNA bending and twisting rigidity on loop capture and release, using the restriction endonuclease FokI as a test system. To cleave DNA efficiently, FokI bridges two copies of an asymmetric sequence, invariably aligning the sites in parallel. On account of the fixed alignment, the topology of the DNA loop is set by the orientation of the sites along the DNA. We show that both the separation of the FokI sites and their orientation, altering, respectively, the twisting and the bending of the DNA needed to juxtapose the sites, have profound effects on the dynamics of the looping interaction. Surprisingly, the presence of a nick within the loop does not affect the observed rigidity of the DNA. In contrast, the introduction of a 4-nt gap fully relaxes all of the torque present in the system but does not necessarily enhance loop stability. FokI therefore employs torque to stabilise its DNA-looping interaction by acting as a ‘torsional’ catch bond. PMID:22373924

Single-Point Mutation with a Rotamer Library Toolkit: Toward Protein Engineering.

Science.gov (United States)

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

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

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Françoise Paquet

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

Prediction of localization and interactions of apoptotic proteins

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Matula Pavel

2009-07-01

Full Text Available Abstract During apoptosis several mitochondrial proteins are released. Some of them participate in caspase-independent nuclear DNA degradation, especially apoptosis-inducing factor (AIF and endonuclease G (endoG. Another interesting protein, which was expected to act similarly as AIF due to the high sequence homology with AIF is AIF-homologous mitochondrion-associated inducer of death (AMID. We studied the structure, cellular localization, and interactions of several proteins in silico and also in cells using fluorescent microscopy. We found the AMID protein to be cytoplasmic, most probably incorporated into the cytoplasmic side of the lipid membranes. Bioinformatic predictions were conducted to analyze the interactions of the studied proteins with each other and with other possible partners. We conducted molecular modeling of proteins with unknown 3D structures. These models were then refined by MolProbity server and employed in molecular docking simulations of interactions. Our results show data acquired using a combination of modern in silico methods and image analysis to understand the localization, interactions and functions of proteins AMID, AIF, endonuclease G, and other apoptosis-related proteins.

A New Approach for Flexible Molecular Docking Based on Swarm Intelligence

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Yi Fu

2015-01-01

Full Text Available Molecular docking methods play an important role in the field of computer-aided drug design. In the work, on the basis of the molecular docking program AutoDock, we present QLDock as a tool for flexible molecular docking. For the energy evaluation, the algorithm uses the binding free energy function that is provided by the AutoDock 4.2 tool. The new search algorithm combines the features of a quantum-behaved particle swarm optimization (QPSO algorithm and local search method of Solis and Wets for solving the highly flexible protein-ligand docking problem. We compute the interaction of 23 protein-ligand complexes and compare the results with those of the QDock and AutoDock programs. The experimental results show that our approach leads to substantially lower docking energy and higher docking precision in comparison to Lamarckian genetic algorithm and QPSO algorithm alone. QPSO-ls algorithm was able to identify the correct binding mode of 74% of the complexes. In comparison, the accuracy of QPSO and LGA is 52% and 61%, respectively. This difference in performance rises with increasing complexity of the ligand. Thus, the novel algorithm QPSO-ls may be used to dock ligand with many rotatable bonds with high accuracy.

Modification of S-Adenosyl-l-Homocysteine as Inhibitor of Nonstructural Protein 5 Methyltransferase Dengue Virus Through Molecular Docking and Molecular Dynamics Simulation.

Science.gov (United States)

Tambunan, Usman Sumo Friend; Nasution, Mochammad Arfin Fardiansyah; Azhima, Fauziah; Parikesit, Arli Aditya; Toepak, Erwin Prasetya; Idrus, Syarifuddin; Kerami, Djati

2017-01-01

Dengue fever is still a major threat worldwide, approximately threatening two-fifths of the world's population in tropical and subtropical countries. Nonstructural protein 5 (NS5) methyltransferase enzyme plays a vital role in the process of messenger RNA capping of dengue by transferring methyl groups from S -adenosyl-l-methionine to N7 atom of the guanine bases of RNA and the RNA ribose group of 2'OH, resulting in S -adenosyl-l-homocysteine (SAH). The modification of SAH compound was screened using molecular docking and molecular dynamics simulation, along with computational ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity) test. The 2 simulations were performed using Molecular Operating Environment (MOE) 2008.10 software, whereas the ADME-Tox test was performed using various software. The modification of SAH compound was done using several functional groups that possess different polarities and properties, resulting in 3460 ligands to be docked. After conducting docking simulation, we earned 3 best ligands (SAH-M331, SAH-M2696, and SAH-M1356) based on ΔG binding and molecular interactions, which show better results than the standard ligands. Moreover, the results of molecular dynamics simulation show that the best ligands are still able to maintain the active site residue interaction with the binding site until the end of the simulation. After a series of molecular docking and molecular dynamics simulation were performed, we concluded that SAH-M1356 ligand is the most potential SAH-based compound to inhibit NS5 methyltransferase enzyme for treating dengue fever.

Molecular Docking Explains Atomic Interaction between Plant-originated Ligands and Oncogenic E7 Protein of High Risk Human Papillomavirus Type 16

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Satish Kumar

2014-12-01

Full Text Available Cervical cancer caused by Human papillomavirus (HPV is one of the leading causes of cancer mortality in women worldwide, particularly in the developing countries. In the last few decades, various compounds from plant origin such as Curcumin, Epigallocatechin gallate (EGCG, Jaceosidin, Resveratrol etc. have been used as anti cancer therapeutic agents. Different studies have shown these plant-originated compounds are able to suppress HPV infection. The E6 and E7 oncoproteins of high-risk HPV play a key role in HPV related cancers. In this study, we explored these ligands from plants origin against E7 oncoprotein of high risk HPV 16, which is known to inactivate tumor suppressor pRb protein. A robust homology model of HPV 16 E7 was built to foresee the interaction mechanism of E7 oncoprotein with these ligands using structure-based drug designing approach. Docking studies demonstrate the interaction of these ligands with pRb binding site of E7 protein by residues Tyr52, Asn53, Val55, Phe57, Cys59, Ser63, Thr64, Thr72, Arg77, Glu80 and Asp81 and help restoration of pRb functioning. This in silico based atomic interaction between these ligands and E7 protein may assist in validating the plant-originated ligands as effective drugs against HPV.

Epididymosomes: transfer of fertility-modulating proteins to the sperm surface.

Science.gov (United States)

Martin-DeLeon, Patricia A

2015-01-01

A variety of glycosylphosphatidylinositol (GPI)-linked proteins are acquired on spermatozoa from epididymal luminal fluids (ELF) during sperm maturation. These proteins serve roles in immunoprotection and in key steps of fertilization such as capacitation, acrosomal exocytosis and sperm-egg interactions. Their acquisition on sperm cells is mediated both by membrane vesicles (epididymosomes, EP) which were first reported to dock on the sperm surface, and by lipid carriers which facilitate the transfer of proteins associated with the membrane-free fraction of ELF. While the nonvesicular fraction is more efficient, both pathways are dependent on hydrophobic interactions between the GPI-anchor and the external lipid layer of the sperm surface. More recently proteomic and hypothesis-driven studies have shown that EP from several mammals carry transmembrane (TM) proteins, including plasma membrane Ca 2 + -ATPase 4 (PMCA4). Synthesized in the testis, PMCA4 is an essential protein and the major Ca 2 + efflux pump in murine spermatozoa. Delivery of PMCA4 to spermatozoa from bovine and mouse EP during epididymal maturation and in vitro suggests that the docking of EP on the sperm surface precedes fusion, and experimental evidence supports a fusogenic mechanism for TM proteins. Fusion is facilitated by CD9, which generates fusion-competent sites on membranes. On the basis of knowledge of PMCA4's interacting partners a number of TM and membrane-associated proteins have been identified or are predicted to be present, in the epididymosomal cargo deliverable to spermatozoa. These Ca 2 + -dependent proteins, undetected in proteomic studies, play essential roles in sperm motility and fertility, and their detection highlights the usefulness of the hypothesis-driven approach.

Epididymosomes: transfer of fertility-modulating proteins to the sperm surface

Directory of Open Access Journals (Sweden)

Patricia A Martin-DeLeon

2015-01-01

Full Text Available A variety of glycosylphosphatidylinositol (GPI-linked proteins are acquired on spermatozoa from epididymal luminal fluids (ELF during sperm maturation. These proteins serve roles in immunoprotection and in key steps of fertilization such as capacitation, acrosomal exocytosis and sperm-egg interactions. Their acquisition on sperm cells is mediated both by membrane vesicles (epididymosomes, EP which were first reported to dock on the sperm surface, and by lipid carriers which facilitate the transfer of proteins associated with the membrane-free fraction of ELF. While the nonvesicular fraction is more efficient, both pathways are dependent on hydrophobic interactions between the GPI-anchor and the external lipid layer of the sperm surface. More recently proteomic and hypothesis-driven studies have shown that EP from several mammals carry transmembrane (TM proteins, including plasma membrane Ca 2 + -ATPase 4 (PMCA4. Synthesized in the testis, PMCA4 is an essential protein and the major Ca 2 + efflux pump in murine spermatozoa. Delivery of PMCA4 to spermatozoa from bovine and mouse EP during epididymal maturation and in vitro suggests that the docking of EP on the sperm surface precedes fusion, and experimental evidence supports a fusogenic mechanism for TM proteins. Fusion is facilitated by CD9, which generates fusion-competent sites on membranes. On the basis of knowledge of PMCA4′s interacting partners a number of TM and membrane-associated proteins have been identified or are predicted to be present, in the epididymosomal cargo deliverable to spermatozoa. These Ca 2 + -dependent proteins, undetected in proteomic studies, play essential roles in sperm motility and fertility, and their detection highlights the usefulness of the hypothesis-driven approach.

Designing sequence to control protein function in an EF-hand protein.

Science.gov (United States)

Bunick, Christopher G; Nelson, Melanie R; Mangahas, Sheryll; Hunter, Michael J; Sheehan, Jonathan H; Mizoue, Laura S; Bunick, Gerard J; Chazin, Walter J

2004-05-19

The extent of conformational change that calcium binding induces in EF-hand proteins is a key biochemical property specifying Ca(2+) sensor versus signal modulator function. To understand how differences in amino acid sequence lead to differences in the response to Ca(2+) binding, comparative analyses of sequence and structures, combined with model building, were used to develop hypotheses about which amino acid residues control Ca(2+)-induced conformational changes. These results were used to generate a first design of calbindomodulin (CBM-1), a calbindin D(9k) re-engineered with 15 mutations to respond to Ca(2+) binding with a conformational change similar to that of calmodulin. The gene for CBM-1 was synthesized, and the protein was expressed and purified. Remarkably, this protein did not exhibit any non-native-like molten globule properties despite the large number of mutations and the nonconservative nature of some of them. Ca(2+)-induced changes in CD intensity and in the binding of the hydrophobic probe, ANS, implied that CBM-1 does undergo Ca(2+) sensorlike conformational changes. The X-ray crystal structure of Ca(2+)-CBM-1 determined at 1.44 A resolution reveals the anticipated increase in hydrophobic surface area relative to the wild-type protein. A nascent calmodulin-like hydrophobic docking surface was also found, though it is occluded by the inter-EF-hand loop. The results from this first calbindomodulin design are discussed in terms of progress toward understanding the relationships between amino acid sequence, protein structure, and protein function for EF-hand CaBPs, as well as the additional mutations for the next CBM design.

Fitting multimeric protein complexes into electron microscopy maps using 3D Zernike descriptors.

Science.gov (United States)

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2012-06-14

A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three-dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root-mean-square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases.

CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.

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Qingzhen Hou

Full Text Available Large-scale identification of native binding orientations is crucial for understanding the role of protein-protein interactions in their biological context. Measuring binding free energy is the method of choice to estimate binding strength and reveal the relevance of particular conformations in which proteins interact. In a recent study, we successfully applied coarse-grained molecular dynamics simulations to measure binding free energy for two protein complexes with similar accuracy to full-atomistic simulation, but 500-fold less time consuming. Here, we investigate the efficacy of this approach as a scoring method to identify stable binding conformations from thousands of docking decoys produced by protein docking programs. To test our method, we first applied it to calculate binding free energies of all protein conformations in a CAPRI (Critical Assessment of PRedicted Interactions benchmark dataset, which included over 19000 protein docking solutions for 15 benchmark targets. Based on the binding free energies, we ranked all docking solutions to select the near-native binding modes under the assumption that the native-solutions have lowest binding free energies. In our top 100 ranked structures, for the 'easy' targets that have many near-native conformations, we obtain a strong enrichment of acceptable or better quality structures; for the 'hard' targets without near-native decoys, our method is still able to retain structures which have native binding contacts. Moreover, in our top 10 selections, CLUB-MARTINI shows a comparable performance when compared with other state-of-the-art docking scoring functions. As a proof of concept, CLUB-MARTINI performs remarkably well for many targets and is able to pinpoint near-native binding modes in the top selections. To the best of our knowledge, this is the first time interaction free energy calculated from MD simulations have been used to rank docking solutions at a large scale.

DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites.

Science.gov (United States)

Gowthaman, Ragul; Miller, Sven A; Rogers, Steven; Khowsathit, Jittasak; Lan, Lan; Bai, Nan; Johnson, David K; Liu, Chunjing; Xu, Liang; Anbanandam, Asokan; Aubé, Jeffrey; Roy, Anuradha; Karanicolas, John

2016-05-12

Protein-protein interactions represent an exciting and challenging target class for therapeutic intervention using small molecules. Protein interaction sites are often devoid of the deep surface pockets presented by "traditional" drug targets, and crystal structures reveal that inhibitors typically engage these sites using very shallow binding modes. As a consequence, modern virtual screening tools developed to identify inhibitors of traditional drug targets do not perform as well when they are instead deployed at protein interaction sites. To address the need for novel inhibitors of important protein interactions, here we introduce an alternate docking strategy specifically designed for this regime. Our method, termed DARC (Docking Approach using Ray-Casting), matches the topography of a surface pocket "observed" from within the protein to the topography "observed" when viewing a potential ligand from the same vantage point. We applied DARC to carry out a virtual screen against the protein interaction site of human antiapoptotic protein Mcl-1 and found that four of the top-scoring 21 compounds showed clear inhibition in a biochemical assay. The Ki values for these compounds ranged from 1.2 to 21 μM, and each had ligand efficiency comparable to promising small-molecule inhibitors of other protein-protein interactions. These hit compounds do not resemble the natural (protein) binding partner of Mcl-1, nor do they resemble any known inhibitors of Mcl-1. Our results thus demonstrate the utility of DARC for identifying novel inhibitors of protein-protein interactions.

Epididymosomes: transfer of fertility-modulating proteins to the sperm surface

OpenAIRE

Patricia A Martin-DeLeon

2015-01-01

A variety of glycosylphosphatidylinositol (GPI)-linked proteins are acquired on spermatozoa from epididymal luminal fluids (ELF) during sperm maturation. These proteins serve roles in immunoprotection and in key steps of fertilization such as capacitation, acrosomal exocytosis and sperm-egg interactions. Their acquisition on sperm cells is mediated both by membrane vesicles (epididymosomes, EP) which were first reported to dock on the sperm surface, and by lipid carriers which facilitate the ...

Protein adsorption at nanopatterned surfaces studied by QCM-D and SPR

DEFF Research Database (Denmark)

Kristensen, Stine; Pedersen, Gitte Albinus; Nejsum, Lene Niemann

2013-01-01

This paper presents the use of the quartz microbalance with dissipation combined with surface plasmon resonance to probe protein adsorption at nanopatterned surfaces. Three different types of adsorbing materials, representing rigid discrete nanoparticles, dense protein films and soft low density ...

Rosetta Ligand docking with flexible XML protocols.

Science.gov (United States)

Lemmon, Gordon; Meiler, Jens

2012-01-01

RosettaLigand is premiere software for predicting how a protein and a small molecule interact. Benchmark studies demonstrate that 70% of the top scoring RosettaLigand predicted interfaces are within 2Å RMSD from the crystal structure [1]. The latest release of Rosetta ligand software includes many new features, such as (1) docking of multiple ligands simultaneously, (2) representing ligands as fragments for greater flexibility, (3) redesign of the interface during docking, and (4) an XML script based interface that gives the user full control of the ligand docking protocol.

Backbone dynamics of the EIAV-Tat protein from 15N relaxation studies

International Nuclear Information System (INIS)

Ejchart, A.; Herrmann, F.; Roesch, P.; Sticht, H.; Willbold, D.

1994-01-01

The work investigates the mobility of EIAV-Tat protein backbone by measuring the relaxation parameters of the 15 N nitrogens. High degree of the flexibility, non-typical of rigid, well structured proteins was shown

Corruption of host seven-transmembrane proteins by pathogenic microbes: a common theme in animals and plants?

Science.gov (United States)

Panstruga, Ralph; Schulze-Lefert, Paul

2003-04-01

Human diseases like AIDS, malaria, and pneumonia are caused by pathogens that corrupt host chemokine G-protein coupled receptors for molecular docking. Comparatively, little is known about plant host factors that are required for pathogenesis and that may serve as receptors for the entry of pathogenic microbes. Here, we review potential analogies between human chemokine receptors and the plant seven-transmembrane MLO protein, a candidate serving a dual role as docking molecule and defence modulator for the phytopathogenic powdery mildew fungus.

Comparative Molecular Dynamics Simulations of Mitogen-Activated Protein Kinase-Activated Protein Kinase 5

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Inger Lindin

2014-03-01

Full Text Available The mitogen-activated protein kinase-activated protein kinase MK5 is a substrate of the mitogen-activated protein kinases p38, ERK3 and ERK4. Cell culture and animal studies have demonstrated that MK5 is involved in tumour suppression and promotion, embryogenesis, anxiety, cell motility and cell cycle regulation. In the present study, homology models of MK5 were used for molecular dynamics (MD simulations of: (1 MK5 alone; (2 MK5 in complex with an inhibitor; and (3 MK5 in complex with the interaction partner p38α. The calculations showed that the inhibitor occupied the active site and disrupted the intramolecular network of amino acids. However, intramolecular interactions consistent with an inactive protein kinase fold were not formed. MD with p38α showed that not only the p38 docking region, but also amino acids in the activation segment, αH helix, P-loop, regulatory phosphorylation region and the C-terminal of MK5 may be involved in forming a very stable MK5-p38α complex, and that p38α binding decreases the residual fluctuation of the MK5 model. Electrostatic Potential Surface (EPS calculations of MK5 and p38α showed that electrostatic interactions are important for recognition and binding.

Conformational dynamics data bank: a database for conformational dynamics of proteins and supramolecular protein assemblies.

Science.gov (United States)

Kim, Do-Nyun; Altschuler, Josiah; Strong, Campbell; McGill, Gaël; Bathe, Mark

2011-01-01

The conformational dynamics data bank (CDDB, http://www.cdyn.org) is a database that aims to provide comprehensive results on the conformational dynamics of high molecular weight proteins and protein assemblies. Analysis is performed using a recently introduced coarse-grained computational approach that is applied to the majority of structures present in the electron microscopy data bank (EMDB). Results include equilibrium thermal fluctuations and elastic strain energy distributions that identify rigid versus flexible protein domains generally, as well as those associated with specific functional transitions, and correlations in molecular motions that identify molecular regions that are highly coupled dynamically, with implications for allosteric mechanisms. A practical web-based search interface enables users to easily collect conformational dynamics data in various formats. The data bank is maintained and updated automatically to include conformational dynamics results for new structural entries as they become available in the EMDB. The CDDB complements static structural information to facilitate the investigation and interpretation of the biological function of proteins and protein assemblies essential to cell function.

Compare local pocket and global protein structure models by small structure patterns

KAUST Repository

Cui, Xuefeng

2015-09-09

Researchers proposed several criteria to assess the quality of predicted protein structures because it is one of the essential tasks in the Critical Assessment of Techniques for Protein Structure Prediction (CASP) competitions. Popular criteria include root mean squared deviation (RMSD), MaxSub score, TM-score, GDT-TS and GDT-HA scores. All these criteria require calculation of rigid transformations to superimpose the the predicted protein structure to the native protein structure. Yet, how to obtain the rigid transformations is unknown or with high time complexity, and, hence, heuristic algorithms were proposed. In this work, we carefully design various small structure patterns, including the ones specifically tuned for local pockets. Such structure patterns are biologically meaningful, and address the issue of relying on a sufficient number of backbone residue fragments for existing methods. We sample the rigid transformations from these small structure patterns; and the optimal superpositions yield by these small structures are refined and reported. As a result, among 11; 669 pairs of predicted and native local protein pocket models from the CASP10 dataset, the GDT-TS scores calculated by our method are significantly higher than those calculated by LGA. Moreover, our program is computationally much more efficient. Source codes and executables are publicly available at http://www.cbrc.kaust.edu.sa/prosta/

Anisotropy of the Coulomb Interaction between Folded Proteins: Consequences for Mesoscopic Aggregation of Lysozyme

Science.gov (United States)

Chan, Ho Yin; Lankevich, Vladimir; Vekilov, Peter G.; Lubchenko, Vassiliy

2012-01-01

Toward quantitative description of protein aggregation, we develop a computationally efficient method to evaluate the potential of mean force between two folded protein molecules that allows for complete sampling of their mutual orientation. Our model is valid at moderate ionic strengths and accounts for the actual charge distribution on the surface of the molecules, the dielectric discontinuity at the protein-solvent interface, and the possibility of protonation or deprotonation of surface residues induced by the electric field due to the other protein molecule. We apply the model to the protein lysozyme, whose solutions exhibit both mesoscopic clusters of protein-rich liquid and liquid-liquid separation; the former requires that protein form complexes with typical lifetimes of approximately milliseconds. We find the electrostatic repulsion is typically lower than the prediction of the Derjaguin-Landau-Verwey-Overbeek theory. The Coulomb interaction in the lowest-energy docking configuration is nonrepulsive, despite the high positive charge on the molecules. Typical docking configurations barely involve protonation or deprotonation of surface residues. The obtained potential of mean force between folded lysozyme molecules is consistent with the location of the liquid-liquid coexistence, but produces dimers that are too short-lived for clusters to exist, suggesting lysozyme undergoes conformational changes during cluster formation. PMID:22768950

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.

Science.gov (United States)

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.

A Flexible Domain-Domain Hinge Promotes an Induced-fit Dominant Mechanism for the Loading of Guide-DNA into Argonaute Protein in Thermus thermophilus

KAUST Repository

Zhu, Lizhe

2016-02-24

Argonaute proteins (Ago) are core components of the RNA Induced Silencing Complex (RISC) that load and utilize small guide nucleic acids to silence mRNAs or cleave foreign DNAs. Despite the essential role of Ago in gene regulation and defense against virus, the molecular mechanism of guide-strand loading into Ago remains unclear. We explore such a mechanism in the bacterium Thermus thermophilus Ago (TtAgo), via a computational approach combining molecular dynamics, bias-exchange metadynamics, and protein-DNA docking. We show that apo TtAgo adopts multiple closed states that are unable to accommodate guide-DNA. Conformations able to accommodate the guide are beyond the reach of thermal fluctuations from the closed states. These results suggest an induced-fit dominant mechanism for guide-strand loading in TtAgo, drastically different from the two-step mechanism for human Ago 2 (hAgo2) identified in our previous study. Such a difference between TtAgo and hAgo2 is found to mainly originate from the distinct rigidity of their L1-PAZ hinge. Further comparison among known Ago structures from various species indicates that the L1-PAZ hinge may be flexible in general for prokaryotic Agos but rigid for eukaryotic Agos. © 2016 American Chemical Society.

A Flexible Domain-Domain Hinge Promotes an Induced-fit Dominant Mechanism for the Loading of Guide-DNA into Argonaute Protein in Thermus thermophilus.

Science.gov (United States)

Zhu, Lizhe; Jiang, Hanlun; Sheong, Fu Kit; Cui, Xuefeng; Gao, Xin; Wang, Yanli; Huang, Xuhui

2016-03-17

Argonaute proteins (Ago) are core components of the RNA Induced Silencing Complex (RISC) that load and utilize small guide nucleic acids to silence mRNAs or cleave foreign DNAs. Despite the essential role of Ago in gene regulation and defense against virus, the molecular mechanism of guide-strand loading into Ago remains unclear. We explore such a mechanism in the bacterium Thermus thermophilus Ago (TtAgo), via a computational approach combining molecular dynamics, bias-exchange metadynamics, and protein-DNA docking. We show that apo TtAgo adopts multiple closed states that are unable to accommodate guide-DNA. Conformations able to accommodate the guide are beyond the reach of thermal fluctuations from the closed states. These results suggest an induced-fit dominant mechanism for guide-strand loading in TtAgo, drastically different from the two-step mechanism for human Ago 2 (hAgo2) identified in our previous study. Such a difference between TtAgo and hAgo2 is found to mainly originate from the distinct rigidity of their L1-PAZ hinge. Further comparison among known Ago structures from various species indicates that the L1-PAZ hinge may be flexible in general for prokaryotic Ago's but rigid for eukaryotic Ago's.

Membrane and Protein Interactions of the Pleckstrin Homology Domain Superfamily

Directory of Open Access Journals (Sweden)

Marc Lenoir

2015-10-01

Full Text Available The human genome encodes about 285 proteins that contain at least one annotated pleckstrin homology (PH domain. As the first phosphoinositide binding module domain to be discovered, the PH domain recruits diverse protein architectures to cellular membranes. PH domains constitute one of the largest protein superfamilies, and have diverged to regulate many different signaling proteins and modules such as Dbl homology (DH and Tec homology (TH domains. The ligands of approximately 70 PH domains have been validated by binding assays and complexed structures, allowing meaningful extrapolation across the entire superfamily. Here the Membrane Optimal Docking Area (MODA program is used at a genome-wide level to identify all membrane docking PH structures and map their lipid-binding determinants. In addition to the linear sequence motifs which are employed for phosphoinositide recognition, the three dimensional structural features that allow peripheral membrane domains to approach and insert into the bilayer are pinpointed and can be predicted ab initio. The analysis shows that conserved structural surfaces distinguish which PH domains associate with membrane from those that do not. Moreover, the results indicate that lipid-binding PH domains can be classified into different functional subgroups based on the type of membrane insertion elements they project towards the bilayer.

Membrane and Protein Interactions of the Pleckstrin Homology Domain Superfamily.

Science.gov (United States)

Lenoir, Marc; Kufareva, Irina; Abagyan, Ruben; Overduin, Michael

2015-10-23

The human genome encodes about 285 proteins that contain at least one annotated pleckstrin homology (PH) domain. As the first phosphoinositide binding module domain to be discovered, the PH domain recruits diverse protein architectures to cellular membranes. PH domains constitute one of the largest protein superfamilies, and have diverged to regulate many different signaling proteins and modules such as Dbl homology (DH) and Tec homology (TH) domains. The ligands of approximately 70 PH domains have been validated by binding assays and complexed structures, allowing meaningful extrapolation across the entire superfamily. Here the Membrane Optimal Docking Area (MODA) program is used at a genome-wide level to identify all membrane docking PH structures and map their lipid-binding determinants. In addition to the linear sequence motifs which are employed for phosphoinositide recognition, the three dimensional structural features that allow peripheral membrane domains to approach and insert into the bilayer are pinpointed and can be predicted ab initio. The analysis shows that conserved structural surfaces distinguish which PH domains associate with membrane from those that do not. Moreover, the results indicate that lipid-binding PH domains can be classified into different functional subgroups based on the type of membrane insertion elements they project towards the bilayer.

Protein-x of hepatitis B virus in interaction with CCAAT/enhancer-binding protein α (C/EBPα - an in silico analysis approach

Directory of Open Access Journals (Sweden)

Mohamadkhani Ashraf

2011-10-01

Full Text Available Abstract Background Even though many functions of protein-x from the Hepatitis B virus (HBV have been revealed, the nature of protein-x is yet unknown. This protein is well-known for its transactivation activity through interaction with several cellular transcription factors, it is also known as an oncogene. In this work, we have presented computational approaches to design a model to show the structure of protein-x and its respective binding sites associated with the CCAAT/enhancer-binding protein α (C/EBPα. C/EBPα belongs to the bZip family of transcription factors, which activates transcription of several genes through its binding sites in liver and fat cells. The C/EBPα has been shown to bind and modulate enhancer I and the enhancer II/core promoter of HBV. In this study using the bioinformatics tools we tried to present a reliable model for the protein-x interaction with C/EBPα. Results The amino acid sequence of protein-x was extracted from UniProt [UniProt:Q80IU5] and the x-ray crystal structure of the partial CCAAT-enhancer α [PDB:1NWQ] was retrieved from the Protein Data Bank (PDB. Similarity search for protein-x was carried out by psi-blast and bl2seq using NCBI [GenBank: BAC65106.1] and Local Meta-Threading-Server (LOMETS was used as a threading server for determining the maximum tertiary structure similarities. Advanced MODELLER was implemented to design a comparative model, however, due to the lack of a suitable template, Quark was used for ab initio tertiary structure prediction. The PDB-blast search indicated a maximum of 23% sequence identity and 33% similarity with crystal structure of the porcine reproductive and respiratory syndrome virus leader protease Nsp1α [PDB:3IFU]. This meant that protein-x does not have a suitable template to predict its tertiary structure using comparative modeling tools, therefore we used QUARK as an ab initio 3D prediction approach. Docking results from the ab initio tertiary structure of

Effect of fullerenol surface chemistry on nanoparticle binding-induced protein misfolding

Science.gov (United States)

Radic, Slaven; Nedumpully-Govindan, Praveen; Chen, Ran; Salonen, Emppu; Brown, Jared M.; Ke, Pu Chun; Ding, Feng

2014-06-01

Fullerene and its derivatives with different surface chemistry have great potential in biomedical applications. Accordingly, it is important to delineate the impact of these carbon-based nanoparticles on protein structure, dynamics, and subsequently function. Here, we focused on the effect of hydroxylation -- a common strategy for solubilizing and functionalizing fullerene -- on protein-nanoparticle interactions using a model protein, ubiquitin. We applied a set of complementary computational modeling methods, including docking and molecular dynamics simulations with both explicit and implicit solvent, to illustrate the impact of hydroxylated fullerenes on the structure and dynamics of ubiquitin. We found that all derivatives bound to the model protein. Specifically, the more hydrophilic nanoparticles with a higher number of hydroxyl groups bound to the surface of the protein via hydrogen bonds, which stabilized the protein without inducing large conformational changes in the protein structure. In contrast, fullerene derivatives with a smaller number of hydroxyl groups buried their hydrophobic surface inside the protein, thereby causing protein denaturation. Overall, our results revealed a distinct role of surface chemistry on nanoparticle-protein binding and binding-induced protein misfolding.Fullerene and its derivatives with different surface chemistry have great potential in biomedical applications. Accordingly, it is important to delineate the impact of these carbon-based nanoparticles on protein structure, dynamics, and subsequently function. Here, we focused on the effect of hydroxylation -- a common strategy for solubilizing and functionalizing fullerene -- on protein-nanoparticle interactions using a model protein, ubiquitin. We applied a set of complementary computational modeling methods, including docking and molecular dynamics simulations with both explicit and implicit solvent, to illustrate the impact of hydroxylated fullerenes on the structure and

Low-Resolution Structure of the Full-Length Barley (Hordeum vulgare) SGT1 Protein in Solution, Obtained Using Small-Angle X-Ray Scattering

Science.gov (United States)

Taube, Michał; Pieńkowska, Joanna R.; Jarmołowski, Artur; Kozak, Maciej

2014-01-01

SGT1 is an evolutionarily conserved eukaryotic protein involved in many important cellular processes. In plants, SGT1 is involved in resistance to disease. In a low ionic strength environment, the SGT1 protein tends to form dimers. The protein consists of three structurally independent domains (the tetratricopeptide repeats domain (TPR), the CHORD- and SGT1-containing domain (CS), and the SGT1-specific domain (SGS)), and two less conserved variable regions (VR1 and VR2). In the present study, we provide the low-resolution structure of the barley (Hordeum vulgare) SGT1 protein in solution and its dimer/monomer equilibrium using small-angle scattering of synchrotron radiation, ab-initio modeling and circular dichroism spectroscopy. The multivariate curve resolution least-square method (MCR-ALS) was applied to separate the scattering data of the monomeric and dimeric species from a complex mixture. The models of the barley SGT1 dimer and monomer were formulated using rigid body modeling with ab-initio structure prediction. Both oligomeric forms of barley SGT1 have elongated shapes with unfolded inter-domain regions. Circular dichroism spectroscopy confirmed that the barley SGT1 protein had a modular architecture, with an α-helical TPR domain, a β-sheet sandwich CS domain, and a disordered SGS domain separated by VR1 and VR2 regions. Using molecular docking and ab-initio protein structure prediction, a model of dimerization of the TPR domains was proposed. PMID:24714665

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

Science.gov (United States)

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.

Room temperature phosphorescence study on the structural flexibility of single tryptophan containing proteins

Science.gov (United States)

Kowalska-Baron, Agnieszka; Gałęcki, Krystian; Wysocki, Stanisław

2015-01-01

In this study, we have undertaken efforts to find correlation between phosphorescence lifetimes of single tryptophan containing proteins and some structural indicators of protein flexibility/rigidity, such as the degree of tryptophan burial or its exposure to solvent, protein secondary and tertiary structure of the region of localization of tryptophan as well as B factors for tryptophan residue and its immediate surroundings. Bearing in mind that, apart from effective local viscosity of the protein/solvent matrix, the other factor that concur in determining room temperature tryptophan phosphorescence (RTTP) lifetime in proteins is the extent of intramolecular quenching by His, Cys, Tyr and Trp side chains, the crystallographic structures derived from the Brookhaven Protein Data Bank were also analyzed concentrating on the presence of potentially quenching amino acid side chains in the close proximity of the indole chromophore. The obtained results indicated that, in most cases, the phosphorescence lifetimes of tryptophan containing proteins studied tend to correlate with the above mentioned structural indicators of protein rigidity/flexibility. This correlation is expected to provide guidelines for the future development of phosphorescence lifetime-based method for the prediction of structural flexibility of proteins, which is directly linked to their biological function.

Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.

Science.gov (United States)

Daberdaku, Sebastian; Ferrari, Carlo

2018-02-06

The correct determination of protein-protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been developed, but the interface prediction problem is still not fully understood. Experimental evidence suggests that the location of binding sites is imprinted in the protein structure, but there are major differences among the interfaces of the various protein types: the characterising properties can vary a lot depending on the interaction type and function. The selection of an optimal set of features characterising the protein interface and the development of an effective method to represent and capture the complex protein recognition patterns are of paramount importance for this task. In this work we investigate the potential of a novel local surface descriptor based on 3D Zernike moments for the interface prediction task. Descriptors invariant to roto-translations are extracted from circular patches of the protein surface enriched with physico-chemical properties from the HQI8 amino acid index set, and are used as samples for a binary classification problem. Support Vector Machines are used as a classifier to distinguish interface local surface patches from non-interface ones. The proposed method was validated on 16 classes of proteins extracted from the Protein-Protein Docking Benchmark 5.0 and compared to other state-of-the-art protein interface predictors (SPPIDER, PrISE and NPS-HomPPI). The 3D Zernike descriptors are able to capture the similarity among patterns of physico-chemical and biochemical properties mapped on the protein surface arising from the various spatial arrangements of the underlying residues, and their usage can be easily extended to other sets of amino acid properties. The results suggest that the choice of a proper set of features characterising the protein interface is crucial for the interface prediction

Computational methods for molecular docking

Energy Technology Data Exchange (ETDEWEB)

Klebe, G. [BASF AG, Ludwigshafen (Germany); Lengauer, T.

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Recently, it has been demonstrated that the knowledge of the three-dimensional structure of the protein can be used to derive new protein ligands with improved binding properties. This tutorial focuses on the following questions: What is its binding affinity toward a particular receptor? What are putative conformations of a ligand at the binding site? What are the similarities of different ligands in terms of their recognition capabilities? Where and in which orientation will a ligand bind to the active site? How is a new putative protein ligand selected? An overview is presented of the algorithms which are presently used to handle and predict protein-ligand interactions and to dock small molecule ligands into proteins.

A hydrazone Schiff base single crystal (E)-Methyl N"′-(3,4,5-trimethoxybenzylidene) hydrazine carboxylate: Physicochemical, in vitro investigation of antimicrobial activities and molecular docking with DNA gyrase protein

International Nuclear Information System (INIS)

Gomathi, G.; Gopalakrishnan, R.

2016-01-01

Hydrazone Schiff bases have been widely explored for their antimicrobial, anticancer, anticonvulsant properties. The aim of the present work is to investigate the spectroscopic, electrochemical, thermal properties, in vitro study of antimicrobial activity and molecular docking studies of the MBHC compound. Slow evaporation solution growth technique was used to grow the single crystal of the MBHC compound. Single crystal X-ray diffraction, FTIR and FT-Raman spectroscopic studies are performed and confirmed the grown MBHC compound. UV–Vis spectroscopy and electrochemical studies deduced the absorption region and HOMO-LUMO band gap value of the compound. Resazurin reduction assay method was utilized to perform antibacterial and antifungal studies which resulted in lesser effectiveness of the MBHC compound compared to the erythromycin and fluconazole tablets. Molecular docking of the MBHC compound with the DNA gyrase protein exhibited the good binding affinity with energy of − 43.196 kcal/mol and docking score of − 6.266 and having good interaction with aminoacids – ASP81 and ARG84. - Highlights: • MBHC single crystal was grown by employing slow evaporation solution growth technique. • The compound crystallizes in monoclinic crystal system with space group P2_1/c. • The HOMO-LUMO band gap value was found to be 1.96 eV. • The compound has lesser antimicrobial activity when compared to erythromycin and fluconazole. • MBHC shows better binding affinity towards DNA gyrase protein.

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

NARCIS (Netherlands)

Trellet, M.; Melquiond, A.S.J.; Bonvin, A.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

Improving protein-protein interaction prediction using evolutionary information from low-quality MSAs.

Science.gov (United States)

Várnai, Csilla; Burkoff, Nikolas S; Wild, David L

2017-01-01

Evolutionary information stored in multiple sequence alignments (MSAs) has been used to identify the interaction interface of protein complexes, by measuring either co-conservation or co-mutation of amino acid residues across the interface. Recently, maximum entropy related correlated mutation measures (CMMs) such as direct information, decoupling direct from indirect interactions, have been developed to identify residue pairs interacting across the protein complex interface. These studies have focussed on carefully selected protein complexes with large, good-quality MSAs. In this work, we study protein complexes with a more typical MSA consisting of fewer than 400 sequences, using a set of 79 intramolecular protein complexes. Using a maximum entropy based CMM at the residue level, we develop an interface level CMM score to be used in re-ranking docking decoys. We demonstrate that our interface level CMM score compares favourably to the complementarity trace score, an evolutionary information-based score measuring co-conservation, when combined with the number of interface residues, a knowledge-based potential and the variability score of individual amino acid sites. We also demonstrate, that, since co-mutation and co-complementarity in the MSA contain orthogonal information, the best prediction performance using evolutionary information can be achieved by combining the co-mutation information of the CMM with co-conservation information of a complementarity trace score, predicting a near-native structure as the top prediction for 41% of the dataset. The method presented is not restricted to small MSAs, and will likely improve interface prediction also for complexes with large and good-quality MSAs.

Evolution of pH buffers and water homeostasis in eukaryotes: homology between humans and Acanthamoeba proteins.

Science.gov (United States)

Baig, Abdul M; Zohaib, R; Tariq, S; Ahmad, H R

2018-02-01

This study intended to trace the evolution of acid-base buffers and water homeostasis in eukaryotes. Acanthamoeba castellanii  was selected as a model unicellular eukaryote for this purpose. Homologies of proteins involved in pH and water regulatory mechanisms at cellular levels were compared between humans and A. castellanii. Amino acid sequence homology, structural homology, 3D modeling and docking prediction were done to show the extent of similarities between carbonic anhydrase 1 (CA1), aquaporin (AQP), band-3 protein and H + pump. Experimental assays were done with acetazolamide (AZM), brinzolamide and mannitol to observe their effects on the trophozoites of  A. castellanii.  The human CA1, AQP, band-3 protein and H + -transport proteins revealed similar proteins in Acanthamoeba. Docking showed the binding of AZM on amoebal AQP-like proteins.  Acanthamoeba showed transient shape changes and encystation at differential doses of brinzolamide, mannitol and AZM.  Conclusion: Water and pH regulating adapter proteins in Acanthamoeba and humans show significant homology, these mechanisms evolved early in the primitive unicellular eukaryotes and have remained conserved in multicellular eukaryotes.

Optimization of memory use of fragment extension-based protein-ligand docking with an original fast minimum cost flow algorithm.

Science.gov (United States)

Yanagisawa, Keisuke; Komine, Shunta; Kubota, Rikuto; Ohue, Masahito; Akiyama, Yutaka

2018-03-16

The need to accelerate large-scale protein-ligand docking in virtual screening against a huge compound database led researchers to propose a strategy that entails memorizing the evaluation result of the partial structure of a compound and reusing it to evaluate other compounds. However, the previous method required frequent disk accesses, resulting in insufficient acceleration. Thus, more efficient memory usage can be expected to lead to further acceleration, and optimal memory usage could be achieved by solving the minimum cost flow problem. In this research, we propose a fast algorithm for the minimum cost flow problem utilizing the characteristics of the graph generated for this problem as constraints. The proposed algorithm, which optimized memory usage, was approximately seven times faster compared to existing minimum cost flow algorithms. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

Science.gov (United States)

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.

Exponential Repulsion Improves Structural Predictability of Molecular Docking

Czech Academy of Sciences Publication Activity Database

Bazgier, Václav; Berka, K.; Otyepka, M.; Banáš, P.

2016-01-01

Roč. 37, č. 28 (2016), s. 2485-2494 ISSN 0192-8651 Institutional support: RVO:61389030 Keywords : cyclin-dependent kinases * structure-based design * scoring functions * cdk2 inhibitors * force-field * ligand interactions * drug discovery * purine * potent * protein-kinase-2 * molecular docking * dock 6.6 * drug design * cyclin-dependent kinase 2 * directory of decoys Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 3.229, year: 2016

Fluorescent sensors based on bacterial fusion proteins

International Nuclear Information System (INIS)

Mateu, Batirtze Prats; Pum, Dietmar; Sleytr, Uwe B; Toca-Herrera, José L; Kainz, Birgit

2014-01-01

Fluorescence proteins are widely used as markers for biomedical and technological purposes. Therefore, the aim of this project was to create a fluorescent sensor, based in the green and cyan fluorescent protein, using bacterial S-layers proteins as scaffold for the fluorescent tag. We report the cloning, expression and purification of three S-layer fluorescent proteins: SgsE-EGFP, SgsE-ECFP and SgsE-13aa-ECFP, this last containing a 13-amino acid rigid linker. The pH dependence of the fluorescence intensity of the S-layer fusion proteins, monitored by fluorescence spectroscopy, showed that the ECFP tag was more stable than EGFP. Furthermore, the fluorescent fusion proteins were reassembled on silica particles modified with cationic and anionic polyelectrolytes. Zeta potential measurements confirmed the particle coatings and indicated their colloidal stability. Flow cytometry and fluorescence microscopy showed that the fluorescence of the fusion proteins was pH dependent and sensitive to the underlying polyelectrolyte coating. This might suggest that the fluorescent tag is not completely exposed to the bulk media as an independent moiety. Finally, it was found out that viscosity enhanced the fluorescence intensity of the three fluorescent S-layer proteins. (paper)

Heterotrimeric G protein beta1gamma2 subunits change orientation upon complex formation with G protein-coupled receptor kinase 2 (GRK2) on a model membrane.

Science.gov (United States)

Boughton, Andrew P; Yang, Pei; Tesmer, Valerie M; Ding, Bei; Tesmer, John J G; Chen, Zhan

2011-09-13

Few experimental techniques can assess the orientation of peripheral membrane proteins in their native environment. Sum Frequency Generation (SFG) vibrational spectroscopy was applied to study the formation of the complex between G protein-coupled receptor (GPCR) kinase 2 (GRK2) and heterotrimeric G protein β(1)γ(2) subunits (Gβγ) at a lipid bilayer, without any exogenous labels. The most likely membrane orientation of the GRK2-Gβγ complex differs from that predicted from the known protein crystal structure, and positions the predicted receptor docking site of GRK2 such that it would more optimally interact with GPCRs. Gβγ also appears to change its orientation after binding to GRK2. The developed methodology is widely applicable for the study of other membrane proteins in situ.

A hydrazone Schiff base single crystal (E)-Methyl N{sup ′}-(3,4,5-trimethoxybenzylidene) hydrazine carboxylate: Physicochemical, in vitro investigation of antimicrobial activities and molecular docking with DNA gyrase protein

Energy Technology Data Exchange (ETDEWEB)

Gomathi, G.; Gopalakrishnan, R., E-mail: krgkrishnan@annauniv.edu

2016-07-01

Hydrazone Schiff bases have been widely explored for their antimicrobial, anticancer, anticonvulsant properties. The aim of the present work is to investigate the spectroscopic, electrochemical, thermal properties, in vitro study of antimicrobial activity and molecular docking studies of the MBHC compound. Slow evaporation solution growth technique was used to grow the single crystal of the MBHC compound. Single crystal X-ray diffraction, FTIR and FT-Raman spectroscopic studies are performed and confirmed the grown MBHC compound. UV–Vis spectroscopy and electrochemical studies deduced the absorption region and HOMO-LUMO band gap value of the compound. Resazurin reduction assay method was utilized to perform antibacterial and antifungal studies which resulted in lesser effectiveness of the MBHC compound compared to the erythromycin and fluconazole tablets. Molecular docking of the MBHC compound with the DNA gyrase protein exhibited the good binding affinity with energy of − 43.196 kcal/mol and docking score of − 6.266 and having good interaction with aminoacids – ASP81 and ARG84. - Highlights: • MBHC single crystal was grown by employing slow evaporation solution growth technique. • The compound crystallizes in monoclinic crystal system with space group P2{sub 1}/c. • The HOMO-LUMO band gap value was found to be 1.96 eV. • The compound has lesser antimicrobial activity when compared to erythromycin and fluconazole. • MBHC shows better binding affinity towards DNA gyrase protein.

Displacement affinity chromatography of protein phosphatase one (PP1 complexes

Directory of Open Access Journals (Sweden)

Gourlay Robert

2008-11-01

Full Text Available Abstract Background Protein phosphatase one (PP1 is a ubiquitously expressed, highly conserved protein phosphatase that dephosphorylates target protein serine and threonine residues. PP1 is localized to its site of action by interacting with targeting or regulatory proteins, a majority of which contains a primary docking site referred to as the RVXF/W motif. Results We demonstrate that a peptide based on the RVXF/W motif can effectively displace PP1 bound proteins from PP1 retained on the phosphatase affinity matrix microcystin-Sepharose. Subsequent co-immunoprecipitation experiments confirmed that each identified binding protein was either a direct PP1 interactor or was in a complex that contains PP1. Our results have linked PP1 to numerous new nuclear functions and proteins, including Ki-67, Rif-1, topoisomerase IIα, several nuclear helicases, NUP153 and the TRRAP complex. Conclusion This modification of the microcystin-Sepharose technique offers an effective means of purifying novel PP1 regulatory subunits and associated proteins and provides a simple method to uncover a link between PP1 and additional cellular processes.

Generation of 3D templates of active sites of proteins with rigid prosthetic groups

OpenAIRE

Nebel, Jean-Christophe

2006-01-01

MOTIVATION: With the increasing availability of protein structures, the generation of biologically meaningful 3D patterns from the simultaneous alignment of several protein structures is an exciting prospect: active sites could be better understood, protein functions and protein 3D structures could be predicted more accurately. Although patterns can already be generated at the fold and topological levels, no system produces high-resolution 3D patterns including atom and cavity positions. To a...

Modeling and Docking Studies on Novel Mutants (K71L and T204V of the ATPase Domain of Human Heat Shock 70 kDa Protein 1

Directory of Open Access Journals (Sweden)

Asita Elengoe

2014-04-01

Full Text Available The purpose of exploring protein interactions between human adenovirus and heat shock protein 70 is to exploit a potentially synergistic interaction to enhance anti-tumoral efficacy and decrease toxicity in cancer treatment. However, the protein interaction of Hsp70 with E1A32 kDa of human adenovirus serotype 5 remains to be elucidated. In this study, two residues of ATPase domain of human heat shock 70 kDa protein 1 (PDB: 1 HJO were mutated. 3D mutant models (K71L and T204V using PyMol software were then constructed. The structures were evaluated by PROCHECK, ProQ, ERRAT, Verify 3D and ProSA modules. All evidence suggests that all protein models are acceptable and of good quality. The E1A32 kDa motif was retrieved from UniProt (P03255, as well as subjected to docking interaction with NBD, K71L and T204V, using the Autodock 4.2 program. The best lowest binding energy value of −9.09 kcal/mol was selected for novel T204V. Moreover, the protein-ligand complex structures were validated by RMSD, RMSF, hydrogen bonds and salt bridge analysis. This revealed that the T204V-E1A32 kDa motif complex was the most stable among all three complex structures. This study provides information about the interaction between Hsp70 and the E1A32 kDa motif, which emphasizes future perspectives to design rational drugs and vaccines in cancer therapy.

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

Science.gov (United States)

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 flexibility: coordinate uncertainties and interpretation of structural differences

Energy Technology Data Exchange (ETDEWEB)

Rashin, Alexander A., E-mail: alexander-rashin@hotmail.com [BioChemComp Inc., 543 Sagamore Avenue, Teaneck, NJ 07666 (United States); LH Baker Center for Bioinformatics and Department of Biochemistry, Biophysics and Molecular Biology, 112 Office and Lab Building, Iowa State University, Ames, IA 50011-3020 (United States); Rashin, Abraham H. L. [BioChemComp Inc., 543 Sagamore Avenue, Teaneck, NJ 07666 (United States); Rutgers, The State University of New Jersey, 22371 BPO WAY, Piscataway, NJ 08854-8123 (United States); Jernigan, Robert L. [LH Baker Center for Bioinformatics and Department of Biochemistry, Biophysics and Molecular Biology, 112 Office and Lab Building, Iowa State University, Ames, IA 50011-3020 (United States); BioChemComp Inc., 543 Sagamore Avenue, Teaneck, NJ 07666 (United States)

2009-11-01

Criteria for the interpretability of coordinate differences and a new method for identifying rigid-body motions and nonrigid deformations in protein conformational changes are developed and applied to functionally induced and crystallization-induced conformational changes. Valid interpretations of conformational movements in protein structures determined by X-ray crystallography require that the movement magnitudes exceed their uncertainty threshold. Here, it is shown that such thresholds can be obtained from the distance difference matrices (DDMs) of 1014 pairs of independently determined structures of bovine ribonuclease A and sperm whale myoglobin, with no explanations provided for reportedly minor coordinate differences. The smallest magnitudes of reportedly functional motions are just above these thresholds. Uncertainty thresholds can provide objective criteria that distinguish between true conformational changes and apparent ‘noise’, showing that some previous interpretations of protein coordinate changes attributed to external conditions or mutations may be doubtful or erroneous. The use of uncertainty thresholds, DDMs, the newly introduced CDDMs (contact distance difference matrices) and a novel simple rotation algorithm allows a more meaningful classification and description of protein motions, distinguishing between various rigid-fragment motions and nonrigid conformational deformations. It is also shown that half of 75 pairs of identical molecules, each from the same asymmetric crystallographic cell, exhibit coordinate differences that range from just outside the coordinate uncertainty threshold to the full magnitude of large functional movements. Thus, crystallization might often induce protein conformational changes that are comparable to those related to or induced by the protein function.

Scoring protein interaction decoys using exposed residues (SPIDER): a novel multibody interaction scoring function based on frequent geometric patterns of interfacial residues.

Science.gov (United States)

Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

2012-08-01

Accurate prediction of the structure of protein-protein complexes in computational docking experiments remains a formidable challenge. It has been recognized that identifying native or native-like poses among multiple decoys is the major bottleneck of the current scoring functions used in docking. We have developed a novel multibody pose-scoring function that has no theoretical limit on the number of residues contributing to the individual interaction terms. We use a coarse-grain representation of a protein-protein complex where each residue is represented by its side chain centroid. We apply a computational geometry approach called Almost-Delaunay tessellation that transforms protein-protein complexes into a residue contact network, or an undirectional graph where vertex-residues are nodes connected by edges. This treatment forms a family of interfacial graphs representing a dataset of protein-protein complexes. We then employ frequent subgraph mining approach to identify common interfacial residue patterns that appear in at least a subset of native protein-protein interfaces. The geometrical parameters and frequency of occurrence of each "native" pattern in the training set are used to develop the new SPIDER scoring function. SPIDER was validated using standard "ZDOCK" benchmark dataset that was not used in the development of SPIDER. We demonstrate that SPIDER scoring function ranks native and native-like poses above geometrical decoys and that it exceeds in performance a popular ZRANK scoring function. SPIDER was ranked among the top scoring functions in a recent round of CAPRI (Critical Assessment of PRedicted Interactions) blind test of protein-protein docking methods. Copyright © 2012 Wiley Periodicals, Inc.

Sampling protein motion and solvent effect during ligand binding

Science.gov (United States)

Limongelli, Vittorio; Marinelli, Luciana; Cosconati, Sandro; La Motta, Concettina; Sartini, Stefania; Mugnaini, Laura; Da Settimo, Federico; Novellino, Ettore; Parrinello, Michele

2012-01-01

An exhaustive description of the molecular recognition mechanism between a ligand and its biological target is of great value because it provides the opportunity for an exogenous control of the related process. Very often this aim can be pursued using high resolution structures of the complex in combination with inexpensive computational protocols such as docking algorithms. Unfortunately, in many other cases a number of factors, like protein flexibility or solvent effects, increase the degree of complexity of ligand/protein interaction and these standard techniques are no longer sufficient to describe the binding event. We have experienced and tested these limits in the present study in which we have developed and revealed the mechanism of binding of a new series of potent inhibitors of Adenosine Deaminase. We have first performed a large number of docking calculations, which unfortunately failed to yield reliable results due to the dynamical character of the enzyme and the complex role of the solvent. Thus, we have stepped up the computational strategy using a protocol based on metadynamics. Our approach has allowed dealing with protein motion and solvation during ligand binding and finally identifying the lowest energy binding modes of the most potent compound of the series, 4-decyl-pyrazolo[1,5-a]pyrimidin-7-one. PMID:22238423

Multiscale multiphysics and multidomain models—Flexibility and rigidity

International Nuclear Information System (INIS)

Xia, Kelin; Opron, Kristopher; Wei, Guo-Wei

2013-01-01

The emerging complexity of large macromolecules has led to challenges in their full scale theoretical description and computer simulation. Multiscale multiphysics and multidomain models have been introduced to reduce the number of degrees of freedom while maintaining modeling accuracy and achieving computational efficiency. A total energy functional is constructed to put energies for polar and nonpolar solvation, chemical potential, fluid flow, molecular mechanics, and elastic dynamics on an equal footing. The variational principle is utilized to derive coupled governing equations for the above mentioned multiphysical descriptions. Among these governing equations is the Poisson-Boltzmann equation which describes continuum electrostatics with atomic charges. The present work introduces the theory of continuum elasticity with atomic rigidity (CEWAR). The essence of CEWAR is to formulate the shear modulus as a continuous function of atomic rigidity. As a result, the dynamics complexity of a macromolecular system is separated from its static complexity so that the more time-consuming dynamics is handled with continuum elasticity theory, while the less time-consuming static analysis is pursued with atomic approaches. We propose a simple method, flexibility-rigidity index (FRI), to analyze macromolecular flexibility and rigidity in atomic detail. The construction of FRI relies on the fundamental assumption that protein functions, such as flexibility, rigidity, and energy, are entirely determined by the structure of the protein and its environment, although the structure is in turn determined by all the interactions. As such, the FRI measures the topological connectivity of protein atoms or residues and characterizes the geometric compactness of the protein structure. As a consequence, the FRI does not resort to the interaction Hamiltonian and bypasses matrix diagonalization, which underpins most other flexibility analysis methods. FRI's computational complexity is of O

Revealing Surface Waters on an Antifreeze Protein by Fusion Protein Crystallography Combined with Molecular Dynamic Simulations.

Science.gov (United States)

Sun, Tianjun; Gauthier, Sherry Y; Campbell, Robert L; Davies, Peter L

2015-10-08

Antifreeze proteins (AFPs) adsorb to ice through an extensive, flat, relatively hydrophobic surface. It has been suggested that this ice-binding site (IBS) organizes surface waters into an ice-like clathrate arrangement that matches and fuses to the quasi-liquid layer on the ice surface. On cooling, these waters join the ice lattice and freeze the AFP to its ligand. Evidence for the generality of this binding mechanism is limited because AFPs tend to crystallize with their IBS as a preferred protein-protein contact surface, which displaces some bound waters. Type III AFP is a 7 kDa globular protein with an IBS made up two adjacent surfaces. In the crystal structure of the most active isoform (QAE1), the part of the IBS that docks to the primary prism plane of ice is partially exposed to solvent and has clathrate waters present that match this plane of ice. The adjacent IBS, which matches the pyramidal plane of ice, is involved in protein-protein crystal contacts with few surface waters. Here we have changed the protein-protein contacts in the ice-binding region by crystallizing a fusion of QAE1 to maltose-binding protein. In this 1.9 Å structure, the IBS that fits the pyramidal plane of ice is exposed to solvent. By combining crystallography data with MD simulations, the surface waters on both sides of the IBS were revealed and match well with the target ice planes. The waters on the pyramidal plane IBS were loosely constrained, which might explain why other isoforms of type III AFP that lack the prism plane IBS are less active than QAE1. The AFP fusion crystallization method can potentially be used to force the exposure to solvent of the IBS on other AFPs to reveal the locations of key surface waters.

Steady-state structural fluctuation is a predictor of the necessity of pausing-mediated co-translational folding for small proteins.

Science.gov (United States)

Huang, Wenxi; Liu, Wanting; Jin, Jingjie; Xiao, Qilan; Lu, Ruibin; Chen, Wei; Xiong, Sheng; Zhang, Gong

2018-03-25

Translational pausing coordinates protein synthesis and co-translational folding. It is a common factor that facilitates the correct folding of large, multi-domain proteins. For small proteins, pausing sites rarely occurs in the gene body, and the 3'-end pausing sites are only essential for the folding of a fraction of proteins. The determinant of the necessity of the pausings remains obscure. In this study, we demonstrated that the steady-state structural fluctuation is a predictor of the necessity of pausing-mediated co-translational folding for small proteins. Validated by experiments with 5 model proteins, we found that the rigid protein structures do not, while the flexible structures do need 3'-end pausings to fold correctly. Therefore, rational optimization of translational pausing can improve soluble expression of small proteins with flexible structures, but not the rigid ones. The rigidity of the structure can be quantitatively estimated in silico using molecular dynamic simulation. Nevertheless, we also found that the translational pausing optimization increases the fitness of the expression host, and thus benefits the recombinant protein production, independent from the soluble expression. These results shed light on the structural basis of the translational pausing and provided a practical tool for industrial protein fermentation. Copyright © 2017. Published by Elsevier Inc.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Ibrahim Torktaz

2013-12-01

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

Structural and functional studies of a 50 kDa antigenic protein from Salmonella enterica serovar Typhi.

Science.gov (United States)

Choong, Yee Siew; Lim, Theam Soon; Chew, Ai Lan; Aziah, Ismail; Ismail, Asma

2011-04-01

The high typhoid incidence rate in developing and under-developed countries emphasizes the need for a rapid, affordable and accessible diagnostic test for effective therapy and disease management. TYPHIDOT®, a rapid dot enzyme immunoassay test for typhoid, was developed from the discovery of a ∼50 kDa protein specific for Salmonella enterica serovar Typhi. However, the structure of this antigen remains unknown till today. Studies on the structure of this antigen are important to elucidate its function, which will in turn increase the efficiency of the development and improvement of the typhoid detection test. This paper described the predictive structure and function of the antigenically specific protein. The homology modeling approach was employed to construct the three-dimensional structure of the antigen. The built structure possesses the features of TolC-like outer membrane protein. Molecular docking simulation was also performed to further probe the functionality of the antigen. Docking results showed that hexamminecobalt, Co(NH(3))(6)(3+), as an inhibitor of TolC protein, formed favorable hydrogen bonds with D368 and D371 of the antigen. The single point (D368A, D371A) and double point (D368A and D371A) mutations of the antigen showed a decrease (single point mutation) and loss (double point mutations) of binding affinity towards hexamminecobalt. The architecture features of the built model and the docking simulation reinforced and supported that this antigen is indeed the variant of outer membrane protein, TolC. As channel proteins are important for the virulence and survival of bacteria, therefore this ∼50 kDa channel protein is a good specific target for typhoid detection test. Copyright © 2011 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

Compressibility of the protein-water interface

Science.gov (United States)

Persson, Filip; Halle, Bertil

2018-06-01

bulk water, whereas its self part is 15%-20% lower. These large reductions are caused mainly by the proximity to the more rigid protein and are not a consequence of the perturbed water structure.

Compressibility of the protein-water interface.

Science.gov (United States)

Persson, Filip; Halle, Bertil

2018-06-07

in bulk water, whereas its self part is 15%-20% lower. These large reductions are caused mainly by the proximity to the more rigid protein and are not a consequence of the perturbed water structure.

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

Science.gov (United States)

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.

Structural and Functional Annotation of Hypothetical Proteins of O139

Directory of Open Access Journals (Sweden)

Md. Saiful Islam

2015-06-01

Full Text Available In developing countries threat of cholera is a significant health concern whenever water purification and sewage disposal systems are inadequate. Vibrio cholerae is one of the responsible bacteria involved in cholera disease. The complete genome sequence of V. cholerae deciphers the presence of various genes and hypothetical proteins whose function are not yet understood. Hence analyzing and annotating the structure and function of hypothetical proteins is important for understanding the V. cholerae. V. cholerae O139 is the most common and pathogenic bacterial strain among various V. cholerae strains. In this study sequence of six hypothetical proteins of V. cholerae O139 has been annotated from NCBI. Various computational tools and databases have been used to determine domain family, protein-protein interaction, solubility of protein, ligand binding sites etc. The three dimensional structure of two proteins were modeled and their ligand binding sites were identified. We have found domains and families of only one protein. The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera.

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

Directory of Open Access Journals (Sweden)

Priya Antony

Full Text Available 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.

Science.gov (United States)

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.

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

Science.gov (United States)

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

The role of oligomerization and cooperative regulation in protein function: the case of tryptophan synthase.

Directory of Open Access Journals (Sweden)

M Qaiser Fatmi

Full Text Available The oligomerization/co-localization of protein complexes and their cooperative regulation in protein function is a key feature in many biological systems. The synergistic regulation in different subunits often enhances the functional properties of the multi-enzyme complex. The present study used molecular dynamics and Brownian dynamics simulations to study the effects of allostery, oligomerization and intermediate channeling on enhancing the protein function of tryptophan synthase (TRPS. TRPS uses a set of α/β-dimeric units to catalyze the last two steps of L-tryptophan biosynthesis, and the rate is remarkably slower in the isolated monomers. Our work shows that without their binding partner, the isolated monomers are stable and more rigid. The substrates can form fairly stable interactions with the protein in both forms when the protein reaches the final ligand-bound conformations. Our simulations also revealed that the α/β-dimeric unit stabilizes the substrate-protein conformation in the ligand binding process, which lowers the conformation transition barrier and helps the protein conformations shift from an open/inactive form to a closed/active form. Brownian dynamics simulations with a coarse-grained model illustrate how protein conformations affect substrate channeling. The results highlight the complex roles of protein oligomerization and the fine balance between rigidity and dynamics in protein function.

Synthesis and molecular docking of pyrimidine incorporated novel ...

Indian Academy of Sciences (India)

APOORVA MISRA

2018-03-09

Mar 9, 2018 ... aDepartment of Chemistry, Banasthali Vidyapith, Banasthali, Rajasthan 304 022, India ... serotonin 5-HT6 receptor antagonist,22 hepatitis-A virus ..... Molecular docking structure and ligand protein binding sites of MTX- (a) ...

Docking to flexible nicotinic acetylcholine receptors

DEFF Research Database (Denmark)

Sander, Tommy; Bruun, Anne T; Balle, Thomas

2010-01-01

Computational docking to nicotinic acetylcholine receptors (nAChRs) and other members of the Cys-loop receptor family is complicated by the flexibility of the so-called C-loop. As observed in the large number of published crystal structures of the acetylcholine binding protein (AChBP), a structural...

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

Science.gov (United States)

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

2018-01-01

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

An Integrated Framework Advancing Membrane Protein Modeling and Design.

Directory of Open Access Journals (Sweden)

Rebecca F Alford

2015-09-01

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

Protein stability and enzyme activity at extreme biological temperatures

International Nuclear Information System (INIS)

Feller, Georges

2010-01-01

Psychrophilic microorganisms thrive in permanently cold environments, even at subzero temperatures. To maintain metabolic rates compatible with sustained life, they have improved the dynamics of their protein structures, thereby enabling appropriate molecular motions required for biological activity at low temperatures. As a consequence of this structural flexibility, psychrophilic proteins are unstable and heat-labile. In the upper range of biological temperatures, thermophiles and hyperthermophiles grow at temperatures > 100 0 C and synthesize ultra-stable proteins. However, thermophilic enzymes are nearly inactive at room temperature as a result of their compactness and rigidity. At the molecular level, both types of extremophilic proteins have adapted the same structural factors, but in opposite directions, to address either activity at low temperatures or stability in hot environments. A model based on folding funnels is proposed accounting for the stability-activity relationships in extremophilic proteins. (topical review)

Determining Complex Structures using Docking Method with Single Particle Scattering Data

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Haiguang Liu

2017-04-01

Full Text Available Protein complexes are critical for many molecular functions. Due to intrinsic flexibility and dynamics of complexes, their structures are more difficult to determine using conventional experimental methods, in contrast to individual subunits. One of the major challenges is the crystallization of protein complexes. Using X-ray free electron lasers (XFELs, it is possible to collect scattering signals from non-crystalline protein complexes, but data interpretation is more difficult because of unknown orientations. Here, we propose a hybrid approach to determine protein complex structures by combining XFEL single particle scattering data with computational docking methods. Using simulations data, we demonstrate that a small set of single particle scattering data collected at random orientations can be used to distinguish the native complex structure from the decoys generated using docking algorithms. The results also indicate that a small set of single particle scattering data is superior to spherically averaged intensity profile in distinguishing complex structures. Given the fact that XFEL experimental data are difficult to acquire and at low abundance, this hybrid approach should find wide applications in data interpretations.

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

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Stefania Correale

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

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

Directory of Open Access Journals (Sweden)

Gregory A Ross

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

SHARPEN-Systematic Hierarchical Algorithms for Rotamers and Proteins on an Extended Network

KAUST Repository

Loksha, Ilya V.

2009-04-30

Algorithms for discrete optimization of proteins play a central role in recent advances in protein structure prediction and design. We wish to improve the resources available for computational biologists to rapidly prototype such algorithms and to easily scale these algorithms to many processors. To that end, we describe the implementation and use of two new open source resources, citing potential benefits over existing software. We discuss CHOMP, a new object-oriented library for macromolecular optimization, and SHARPEN, a framework for scaling CHOMP scripts to many computers. These tools allow users to develop new algorithms for a variety of applications including protein repacking, protein-protein docking, loop rebuilding, or homology model remediation. Particular care was taken to allow modular energy function design; protein conformations may currently be scored using either the OPLSaa molecular mechanical energy function or an all-atom semiempirical energy function employed by Rosetta. © 2009 Wiley Periodicals, Inc.

SH2/SH3 adaptor proteins can link tyrosine kinases to a Ste20-related protein kinase, HPK1.

Science.gov (United States)

Anafi, M; Kiefer, F; Gish, G D; Mbamalu, G; Iscove, N N; Pawson, T

1997-10-31

Ste20-related protein kinases have been implicated as regulating a range of cellular responses, including stress-activated protein kinase pathways and the control of cytoskeletal architecture. An important issue involves the identities of the upstream signals and regulators that might control the biological functions of mammalian Ste20-related protein kinases. HPK1 is a protein-serine/threonine kinase that possesses a Ste20-like kinase domain, and in transfected cells activates a protein kinase pathway leading to the stress-activated protein kinase SAPK/JNK. Here we have investigated candidate upstream regulators that might interact with HPK1. HPK1 possesses an N-terminal catalytic domain and an extended C-terminal tail with four proline-rich motifs. The SH3 domains of Grb2 bound in vitro to specific proline-rich motifs in the HPK1 tail and functioned synergistically to direct the stable binding of Grb2 to HPK1 in transfected Cos1 cells. Epidermal growth factor (EGF) stimulation did not affect the binding of Grb2 to HPK1 but induced recruitment of the Grb2.HPK1 complex to the autophosphorylated EGF receptor and to the Shc docking protein. Several activated receptor and cytoplasmic tyrosine kinases, including the EGF receptor, stimulated the tyrosine phosphorylation of the HPK1 serine/threonine kinase. These results suggest that HPK1, a mammalian Ste20-related protein-serine/threonine kinase, can potentially associate with protein-tyrosine kinases through interactions mediated by SH2/SH3 adaptors such as Grb2. Such interaction may provide a possible mechanism for cross-talk between distinct biochemical pathways following the activation of tyrosine kinases.

Automated docking screens: a feasibility study.

Science.gov (United States)

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 .

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

Science.gov (United States)

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.

Directory of Open Access Journals (Sweden)

Ye Fang

Full Text Available 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.

Solvated protein–DNA docking using HADDOCK

International Nuclear Information System (INIS)

Dijk, Marc van; Visscher, Koen M.; Kastritis, Panagiotis L.; Bonvin, Alexandre M. J. J.

2013-01-01

Interfacial water molecules play an important role in many aspects of protein–DNA specificity and recognition. Yet they have been mostly neglected in the computational modeling of these complexes. We present here a solvated docking protocol that allows explicit inclusion of water molecules in the docking of protein–DNA complexes and demonstrate its feasibility on a benchmark of 30 high-resolution protein–DNA complexes containing crystallographically-determined water molecules at their interfaces. Our protocol is capable of reproducing the solvation pattern at the interface and recovers hydrogen-bonded water-mediated contacts in many of the benchmark cases. Solvated docking leads to an overall improvement in the quality of the generated protein–DNA models for cases with limited conformational change of the partners upon complex formation. The applicability of this approach is demonstrated on real cases by docking a representative set of 6 complexes using unbound protein coordinates, model-built DNA and knowledge-based restraints. As HADDOCK supports the inclusion of a variety of NMR restraints, solvated docking is also applicable for NMR-based structure calculations of protein–DNA complexes.

Nitrate as a probe of cytochrome c surface: crystallographic identification of crucial "hot spots" for protein-protein recognition.

Science.gov (United States)

De March, Matteo; Demitri, Nicola; De Zorzi, Rita; Casini, Angela; Gabbiani, Chiara; Guerri, Annalisa; Messori, Luigi; Geremia, Silvano

2014-06-01

The electrostatic surface of cytochrome c and its changes with the iron oxidation state are involved in the docking and undocking processes of this protein to its biological partners in the mitochondrial respiratory pathway. To investigate the subtle mechanisms of formation of productive macromolecular complexes and of their breakage following the electron transfer process, the X-ray structures of horse heart ferri-cytochrome c (trigonal form) and ferro-cytochrome c (monoclinic form) were obtained using nitrate ions both as a crystallizing agent and an anionic probe for mapping the electrostatic surface changes. Both crystal forms contain three protein molecules in the asymmetric unit. In addition, a total of 21.5 and 18 crystallographically independent nitrate ions were identified for the trigonal and monoclinic forms, respectively. By matching all the six crystallographically independent protein molecules, 26 different anion-protein interaction sites were identified on the surfaces of cytochrome c, 10 of which were found in both forms, 8 present only in the oxidized and 8 only in the reduced form. The structural analysis of the electron transfer complexes, based on this new information, suggests a specific exit strategy for cytochrome c after formation of productive protein-protein complexes: a directional sliding mechanism for the electron shuttle on the surface of the redox partner is proposed to take place after the electron transfer process has occurred. Copyright © 2014 Elsevier Inc. All rights reserved.

Protein Kinase C-{delta} mediates down-regulation of heterogeneous nuclear ribonucleoprotein K protein: involvement in apoptosis induction

Energy Technology Data Exchange (ETDEWEB)

Gao, Feng-Hou [NO.3 People' s Hospital affiliated to Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 201900 (China); The Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200025 (China); Wu, Ying-Li [The Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200025 (China); Zhao, Meng [Institute of Health Science, SJTU-SM/Shanghai Institutes for Biological Science, Chinese Academy of Sciences, Shanghai (China); Liu, Chuan-Xu; Wang, Li-Shun [The Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200025 (China); Chen, Guo-Qiang, E-mail: chengq@shsmu.edu.cn [The Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200025 (China); Institute of Health Science, SJTU-SM/Shanghai Institutes for Biological Science, Chinese Academy of Sciences, Shanghai (China)

2009-11-15

We reported previously that NSC606985, a camptothecin analogue, induces apoptosis of acute myeloid leukemia (AML) cells through proteolytic activation of protein kinase C delta ({Delta}PKC-{delta}). By subcellular proteome analysis, heterogeneous nuclear ribonucleoprotein K (hnRNP K) was identified as being significantly down-regulated in NSC606985-treated leukemic NB4 cells. HnRNP K, a docking protein for DNA, RNA, and transcriptional or translational molecules, is implicated in a host of processes involving the regulation of gene expression. However, the molecular mechanisms of hnRNP K reduction and its roles during apoptosis are still not understood. In the present study, we found that, following the appearance of the {Delta}PKC-{delta}, hnRNP K protein was significantly down-regulated in NSC606985, doxorubicin, arsenic trioxide and ultraviolet-induced apoptosis. We further provided evidence that {Delta}PKC-{delta} mediated the down-regulation of hnRNP K protein during apoptosis: PKC-{delta} inhibitor could rescue the reduction of hnRNP K; hnRNP K failed to be decreased in PKC-{delta}-deficient apoptotic KG1a cells; conditional induction of {Delta}PKC-{delta} in U937T cells directly down-regulated hnRNP K protein. Moreover, the proteasome inhibitor also inhibited the down-regulation of hnRNP K protein by apoptosis inducer and the conditional expression of {Delta}PKC-{delta}. More intriguingly, the suppression of hnRNP K with siRNA transfection significantly induced apoptosis. To our knowledge, this is the first demonstration that proteolytically activated PKC-{delta} down-regulates hnRNP K protein in a proteasome-dependent manner, which plays an important role in apoptosis induction.

Surface charge effects in protein adsorption on nanodiamonds

Science.gov (United States)

Aramesh, M.; Shimoni, O.; Ostrikov, K.; Prawer, S.; Cervenka, J.

2015-03-01

Understanding the interaction of proteins with charged diamond nanoparticles is of fundamental importance for diverse biomedical applications. Here we present a thorough study of protein binding, adsorption kinetics and structure on strongly positively (hydrogen-terminated) and negatively (oxygen-terminated) charged nanodiamond particles using a quartz crystal microbalance by dissipation and infrared spectroscopy. By using two model proteins (bovine serum albumin and lysozyme) of different properties (charge, molecular weight and rigidity), the main driving mechanism responsible for the protein binding to the charged nanoparticles was identified. Electrostatic interactions were found to dominate the protein adsorption dynamics, attachment and conformation. We developed a simple electrostatic model that can qualitatively explain the observed adsorption behaviour based on charge-induced pH modifications near the charged nanoparticle surfaces. Under neutral conditions, the local pH around the positively and negatively charged nanodiamonds becomes very high (11-12) and low (1-3) respectively, which has a profound impact on the protein charge, hydration and affinity to the nanodiamonds. Small proteins (lysozyme) were found to form multilayers with significant conformational changes to screen the surface charge, while larger proteins (albumin) formed monolayers with minor conformational changes. The findings of this study provide a step forward toward understanding and eventually predicting nanoparticle interactions with biofluids.Understanding the interaction of proteins with charged diamond nanoparticles is of fundamental importance for diverse biomedical applications. Here we present a thorough study of protein binding, adsorption kinetics and structure on strongly positively (hydrogen-terminated) and negatively (oxygen-terminated) charged nanodiamond particles using a quartz crystal microbalance by dissipation and infrared spectroscopy. By using two model proteins

PCNA Structure and Interactions with Partner Proteins

KAUST Repository

Oke, Muse; Zaher, Manal S.; Hamdan, Samir

2018-01-01

Proliferating cell nuclear antigen (PCNA) consists of three identical monomers that topologically encircle double-stranded DNA. PCNA stimulates the processivity of DNA polymerase δ and, to a less extent, the intrinsically highly processive DNA polymerase ε. It also functions as a platform that recruits and coordinates the activities of a large number of DNA processing proteins. Emerging structural and biochemical studies suggest that the nature of PCNA-partner proteins interactions is complex. A hydrophobic groove at the front side of PCNA serves as a primary docking site for the consensus PIP box motifs present in many PCNA-binding partners. Sequences that immediately flank the PIP box motif or regions that are distant from it could also interact with the hydrophobic groove and other regions of PCNA. Posttranslational modifications on the backside of PCNA could add another dimension to its interaction with partner proteins. An encounter of PCNA with different DNA structures might also be involved in coordinating its interactions. Finally, the ability of PCNA to bind up to three proteins while topologically linked to DNA suggests that it would be a versatile toolbox in many different DNA processing reactions.

PCNA Structure and Interactions with Partner Proteins

KAUST Repository

Oke, Muse

2018-01-29

Proliferating cell nuclear antigen (PCNA) consists of three identical monomers that topologically encircle double-stranded DNA. PCNA stimulates the processivity of DNA polymerase δ and, to a less extent, the intrinsically highly processive DNA polymerase ε. It also functions as a platform that recruits and coordinates the activities of a large number of DNA processing proteins. Emerging structural and biochemical studies suggest that the nature of PCNA-partner proteins interactions is complex. A hydrophobic groove at the front side of PCNA serves as a primary docking site for the consensus PIP box motifs present in many PCNA-binding partners. Sequences that immediately flank the PIP box motif or regions that are distant from it could also interact with the hydrophobic groove and other regions of PCNA. Posttranslational modifications on the backside of PCNA could add another dimension to its interaction with partner proteins. An encounter of PCNA with different DNA structures might also be involved in coordinating its interactions. Finally, the ability of PCNA to bind up to three proteins while topologically linked to DNA suggests that it would be a versatile toolbox in many different DNA processing reactions.

A Novel Protein Interaction between Nucleotide Binding Domain of Hsp70 and p53 Motif

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Asita Elengoe

2015-01-01

Full Text Available Currently, protein interaction of Homo sapiens nucleotide binding domain (NBD of heat shock 70 kDa protein (PDB: 1HJO with p53 motif remains to be elucidated. The NBD-p53 motif complex enhances the p53 stabilization, thereby increasing the tumor suppression activity in cancer treatment. Therefore, we identified the interaction between NBD and p53 using STRING version 9.1 program. Then, we modeled the three-dimensional structure of p53 motif through homology modeling and determined the binding affinity and stability of NBD-p53 motif complex structure via molecular docking and dynamics (MD simulation. Human DNA binding domain of p53 motif (SCMGGMNR retrieved from UniProt (UniProtKB: P04637 was docked with the NBD protein, using the Autodock version 4.2 program. The binding energy and intermolecular energy for the NBD-p53 motif complex were −0.44 Kcal/mol and −9.90 Kcal/mol, respectively. Moreover, RMSD, RMSF, hydrogen bonds, salt bridge, and secondary structure analyses revealed that the NBD protein had a strong bond with p53 motif and the protein-ligand complex was stable. Thus, the current data would be highly encouraging for designing Hsp70 structure based drug in cancer therapy.

Slit stimulation recruits Dock and Pak to the roundabout receptor and increases Rac activity to regulate axon repulsion at the CNS midline.

Science.gov (United States)

Fan, Xueping; Labrador, Juan Pablo; Hing, Huey; Bashaw, Greg J

2003-09-25

Drosophila Roundabout (Robo) is the founding member of a conserved family of repulsive axon guidance receptors that respond to secreted Slit proteins. Here we present evidence that the SH3-SH2 adaptor protein Dreadlocks (Dock), the p21-activated serine-threonine kinase (Pak), and the Rac1/Rac2/Mtl small GTPases can function during Robo repulsion. Loss-of-function and genetic interaction experiments suggest that limiting the function of Dock, Pak, or Rac partially disrupts Robo repulsion. In addition, Dock can directly bind to Robo's cytoplasmic domain, and the association of Dock and Robo is enhanced by stimulation with Slit. Furthermore, Slit stimulation can recruit a complex of Dock and Pak to the Robo receptor and trigger an increase in Rac1 activity. These results provide a direct physical link between the Robo receptor and an important cytoskeletal regulatory protein complex and suggest that Rac can function in both attractive and repulsive axon guidance.

The role of shape vs. patches in protein crystallization

Science.gov (United States)

Glaser, Jens; Glotzer, Sharon C.

Proteins fold into a multitude of three-dimensional native structures. The structures of over 100,000 known proteins are deposited in the protein data bank, and most of them have been determined through X-ray crystallography. We ask the question if the role of shape in protein crystallization can be isolated using simulation. Current computational studies show that patchy complementary contacts stabilize experimentally observed P212121 crystal structures for relatively globular protein using spherical protein models. Here we study an anisotropic rigid shape model of green fluorescent protein based on a coarse-grained representation of the atomic coordinates. Using GPU-accelerated molecular dynamics simulations, we find that the experimentally found crystal structure can be stabilized in self-assembly by using complementary attractive patches, confirming the earlier findings. However, we discuss the additional roles of solvent mediated and electrostatic interactions, depletion effects and the self-assembly properties of a purely hard shape model in stabilizing different assemblies. Our findings shed light on fundamental assembly mechanisms in colloidal systems with many competing interactions.

Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2

Science.gov (United States)

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.

Surface charge effects in protein adsorption on nanodiamonds.

Science.gov (United States)

Aramesh, M; Shimoni, O; Ostrikov, K; Prawer, S; Cervenka, J

2015-03-19

Understanding the interaction of proteins with charged diamond nanoparticles is of fundamental importance for diverse biomedical applications. Here we present a thorough study of protein binding, adsorption kinetics and structure on strongly positively (hydrogen-terminated) and negatively (oxygen-terminated) charged nanodiamond particles using a quartz crystal microbalance by dissipation and infrared spectroscopy. By using two model proteins (bovine serum albumin and lysozyme) of different properties (charge, molecular weight and rigidity), the main driving mechanism responsible for the protein binding to the charged nanoparticles was identified. Electrostatic interactions were found to dominate the protein adsorption dynamics, attachment and conformation. We developed a simple electrostatic model that can qualitatively explain the observed adsorption behaviour based on charge-induced pH modifications near the charged nanoparticle surfaces. Under neutral conditions, the local pH around the positively and negatively charged nanodiamonds becomes very high (11-12) and low (1-3) respectively, which has a profound impact on the protein charge, hydration and affinity to the nanodiamonds. Small proteins (lysozyme) were found to form multilayers with significant conformational changes to screen the surface charge, while larger proteins (albumin) formed monolayers with minor conformational changes. The findings of this study provide a step forward toward understanding and eventually predicting nanoparticle interactions with biofluids.

Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins.

Science.gov (United States)

Gaines, J C; Acebes, S; Virrueta, A; Butler, M; Regan, L; O'Hern, C S

2018-05-01

We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins. © 2018 Wiley Periodicals, Inc.

Antigenicity of envelop and non-structural proteins of dengue serotypes and their potentiality to elicit specifi antibody

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Ramesh Venkatachalam

2015-06-01

Full Text Available Objective: To find out the antigenic nature of envelop (E and non-structural (NS proteins and their ability to induce specific antibodies, and to investigate specific antibody produced by specific dengue virus (DENV serotypes. Methods: Amino acid sequences of E and NS proteins of dengue serotypes were analysed by using VaxiJen antigen predicition server. The transmembrane of topology analyses were conducted by using transmembrane prediction using hidden markov models. The Hex dock server was used for docking. Results: The antigenicity score and exomembrane potentiality of E and NS proteins were calculated. All those proteins were antigenic; these antigens were made to interact with antibodies such as immunoglobulin A, immunoglobulin G and immunoglobulin M. Higher energy values of immunoglobulin M were found in DENV-1 and DENV-2, and more energy values were found in immunoglobulin G of DENV-3, DENV-4, NS-1, NS-3 and NS-5. Conclusions: In the present study, DENV-1 and DENV-2 are positive to immunoglobulin M and involved in the primary infection. DENV 3, DENV 4 and all the NS proteins (NS-1, NS-3, NS-5 which elicit immunoglobulin G are involved in the secondary infection.

Biallelic loss-of-function variants in DOCK3 cause muscle hypotonia, ataxia, and intellectual disability.

Science.gov (United States)

Helbig, K L; Mroske, C; Moorthy, D; Sajan, S A; Velinov, M

2017-10-01

DOCK3 encodes the dedicator of cytokinesis 3 protein, a member of the DOCK180 family of proteins that are characterized by guanine-nucleotide exchange factor activity. DOCK3 is expressed exclusively in the central nervous system and plays an important role in axonal outgrowth and cytoskeleton reorganization. Dock3 knockout mice exhibit motor deficiencies with abnormal ataxic gait and impaired learning. We report 2 siblings with biallelic loss-of-function variants in DOCK3. Diagnostic whole-exome sequencing (WES) and chromosomal microarray were performed on a proband with severe developmental disability, hypotonia, and ataxic gait. Testing was also performed on the proband's similarly affected brother. A paternally inherited 458 kb deletion in chromosomal region 3p21.2 disrupting the DOCK3 gene was identified in both affected siblings. WES identified a nonsense variant c.382C>G (p.Gln128*) in the DOCK3 gene (NM_004947) on the maternal allele in both siblings. Common features in both affected individuals include severe developmental disability, ataxic gait, and severe hypotonia, which recapitulates the Dock3 knockout mouse phenotype. We show that complete DOCK3 deficiency in humans leads to developmental disability with significant hypotonia and gait ataxia, probably due to abnormal axonal development. © 2017 The Authors. Clinical Genetics published by John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Molecular Analysis of AFP and HSA Interactions with PTEN Protein

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Mingyue Zhu

2015-01-01

Full Text Available Human cytoplasmic alpha-fetoprotein (AFP has been classified as a member of the albuminoid gene family. The protein sequence of AFP has significant homology to that of human serum albumin (HSA, but its biological characteristics are vastly different from HSA. The AFP functions as a regulator in the phosphatidylinositol 3-kinase (PI3K/protein kinase B (AKT pathway, but HSA plays a key role as a transport protein. To probe their molecular mechanisms, we have applied colocalization, coimmunoprecipitation (co-IP, and molecular docking approaches to analyze the differences between AFP and HSA. The data from colocalization and co-IP displayed a strong interaction between AFP and PTEN (phosphatase and tensin homolog, demonstrating that AFP did bind to PTEN, but HSA did not. The molecular docking study further showed that the AFP domains I and III could contact with PTEN. In silicon substitutions of AFP binding site residues at position 490M/K and 105L/R corresponding to residues K490 and R105 in HSA resulted in steric clashes with PTEN residues R150 and K46, respectively. These steric clashes may explain the reason why HSA cannot bind to PTEN. Ultimately, the experimental results and the molecular modeling data from the interactions of AFP and HSA with PTEN will help us to identify targets for designing drugs and vaccines against human hepatocellular carcinoma.

Intra-membrane molecular interactions of K+ channel proteins :

Energy Technology Data Exchange (ETDEWEB)

Moczydlowski, Edward G.

2013-07-01

Ion channel proteins regulate complex patterns of cellular electrical activity and ionic signaling. Certain K+ channels play an important role in immunological biodefense mechanisms of adaptive and innate immunity. Most ion channel proteins are oligomeric complexes with the conductive pore located at the central subunit interface. The long-term activity of many K+ channel proteins is dependent on the concentration of extracellular K+; however, the mechanism is unclear. Thus, this project focused on mechanisms underlying structural stability of tetrameric K+ channels. Using KcsA of Streptomyces lividans as a model K+ channel of known structure, the molecular basis of tetramer stability was investigated by: 1. Bioinformatic analysis of the tetramer interface. 2. Effect of two local anesthetics (lidocaine, tetracaine) on tetramer stability. 3. Molecular simulation of drug docking to the ion conduction pore. The results provide new insights regarding the structural stability of K+ channels and its possible role in cell physiology.

Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

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Peng Liu

2015-01-01

Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

Effect of Bovine Plasma Protein on Autolysis and Gelation of Protein Extracted from Giant Squid (Dosidicus gigas Mantle

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Laura Raquel Marquez-Alvarez

2015-01-01

Full Text Available The effect of bovine plasma protein (BPP on the inhibition of autolytic activity and its effect on the gelling properties of a protein concentrate (PC obtained from jumbo squid (Dosidicus gigas mantle were investigated. Sols and gels were prepared from the PC by adding different amounts of BPP (0, 1, and 2%. Dynamic oscillatory measurements indicated that systems with 1% BPP had a higher elastic modulus (G′, in which hydrophobic interactions were favored. Concerning the technological and textural quality of the gels, BPP caused a greater water holding capacity (WHC, force, cohesiveness, and elasticity, probably due to improvement of the electrostatic and hydrophobic interactions during gel formation. Scanning electron microscopy (SEM allowed visualization of the formation of more rigid and ordered gels with less porosity when BPP was added. Therefore, the addition of BPP improved the gelling capacity of proteins extracted from giant squid.

Crystal structure of human protein kinase CK2

DEFF Research Database (Denmark)

Niefind, K; Guerra, B; Ermakowa, I

2001-01-01

The crystal structure of a fully active form of human protein kinase CK2 (casein kinase 2) consisting of two C-terminally truncated catalytic and two regulatory subunits has been determined at 3.1 A resolution. In the CK2 complex the regulatory subunits form a stable dimer linking the two catalyt...... as a docking partner for various protein kinases. Furthermore it shows an inter-domain mobility in the catalytic subunit known to be functionally important in protein kinases and detected here for the first time directly within one crystal structure.......The crystal structure of a fully active form of human protein kinase CK2 (casein kinase 2) consisting of two C-terminally truncated catalytic and two regulatory subunits has been determined at 3.1 A resolution. In the CK2 complex the regulatory subunits form a stable dimer linking the two catalytic...... subunits, which make no direct contact with one another. Each catalytic subunit interacts with both regulatory chains, predominantly via an extended C-terminal tail of the regulatory subunit. The CK2 structure is consistent with its constitutive activity and with a flexible role of the regulatory subunit...

Molecular modeling of the conformational dynamics of the cellular prion protein

Science.gov (United States)

Nguyen, Charles; Colling, Ian; Bartz, Jason; Soto, Patricia

2014-03-01

Prions are infectious agents responsible for transmissible spongiform encephalopathies (TSEs), a type of fatal neurodegenerative disease in mammals. Prions propagate biological information by conversion of the non-pathological version of the prion protein to the infectious conformation, PrPSc. A wealth of knowledge has shed light on the nature and mechanism of prion protein conversion. In spite of the significance of this problem, we are far from fully understanding the conformational dynamics of the cellular isoform. To remedy this situation we employ multiple biomolecular modeling techniques such as docking and molecular dynamics simulations to map the free energy landscape and determine what specific regions of the prion protein are most conductive to binding. The overall goal is to characterize the conformational dynamics of the cell form of the prion protein, PrPc, to gain insight into inhibition pathways against misfolding. NE EPSCoR FIRST Award to Patricia Soto.

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

Science.gov (United States)

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.

Theory and Applications of Covalent Docking in Drug Discovery: Merits and Pitfalls

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Hezekiel Mathambo Kumalo

2015-01-01

Full Text Available he present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed some significant advantages over non-covalent inhibitors such as covalent warheads can target rare, non-conserved residue of a particular target protein and thus led to development of highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with shallow binding cleavage which will led to development of novel inhibitors with increased potency than non-covalent inhibitors. Several computational approaches have been developed to simulate covalent interactions; however, this is still a challenging area to explore. Covalent molecular docking has been recently implemented in the computer-aided drug design workflows to describe covalent interactions between inhibitors and biological targets. In this review we highlight: (i covalent interactions in biomolecular systems; (ii the mathematical framework of covalent molecular docking; (iii implementation of covalent docking protocol in drug design workflows; (iv applications covalent docking: case studies and (v shortcomings and future perspectives of covalent docking. To the best of our knowledge; this review is the first account that highlights different aspects of covalent docking with its merits and pitfalls. We believe that the method and applications highlighted in this study will help future efforts towards the design of irreversible inhibitors.

Oligomerization of G protein-coupled receptors: computational methods.

Science.gov (United States)

Selent, J; Kaczor, A A

2011-01-01

Recent research has unveiled the complexity of mechanisms involved in G protein-coupled receptor (GPCR) functioning in which receptor dimerization/oligomerization may play an important role. Although the first high-resolution X-ray structure for a likely functional chemokine receptor dimer has been deposited in the Protein Data Bank, the interactions and mechanisms of dimer formation are not yet fully understood. In this respect, computational methods play a key role for predicting accurate GPCR complexes. This review outlines computational approaches focusing on sequence- and structure-based methodologies as well as discusses their advantages and limitations. Sequence-based approaches that search for possible protein-protein interfaces in GPCR complexes have been applied with success in several studies, but did not yield always consistent results. Structure-based methodologies are a potent complement to sequence-based approaches. For instance, protein-protein docking is a valuable method especially when guided by experimental constraints. Some disadvantages like limited receptor flexibility and non-consideration of the membrane environment have to be taken into account. Molecular dynamics simulation can overcome these drawbacks giving a detailed description of conformational changes in a native-like membrane. Successful prediction of GPCR complexes using computational approaches combined with experimental efforts may help to understand the role of dimeric/oligomeric GPCR complexes for fine-tuning receptor signaling. Moreover, since such GPCR complexes have attracted interest as potential drug target for diverse diseases, unveiling molecular determinants of dimerization/oligomerization can provide important implications for drug discovery.

Novel Penicillin Analogues as Potential Antimicrobial Agents; Design, Synthesis and Docking Studies.

Science.gov (United States)

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.

TOPICAL REVIEW: Protein stability and enzyme activity at extreme biological temperatures

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Feller, Georges

2010-08-01

Psychrophilic microorganisms thrive in permanently cold environments, even at subzero temperatures. To maintain metabolic rates compatible with sustained life, they have improved the dynamics of their protein structures, thereby enabling appropriate molecular motions required for biological activity at low temperatures. As a consequence of this structural flexibility, psychrophilic proteins are unstable and heat-labile. In the upper range of biological temperatures, thermophiles and hyperthermophiles grow at temperatures > 100 °C and synthesize ultra-stable proteins. However, thermophilic enzymes are nearly inactive at room temperature as a result of their compactness and rigidity. At the molecular level, both types of extremophilic proteins have adapted the same structural factors, but in opposite directions, to address either activity at low temperatures or stability in hot environments. A model based on folding funnels is proposed accounting for the stability-activity relationships in extremophilic proteins.

Forging the Basis for Developing Protein-Ligand Interaction Scoring Functions.

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Liu, Zhihai; Su, Minyi; Han, Li; Liu, Jie; Yang, Qifan; Li, Yan; Wang, Renxiao

2017-02-21

In structure-based drug design, scoring functions are widely used for fast evaluation of protein-ligand interactions. They are often applied in combination with molecular docking and de novo design methods. Since the early 1990s, a whole spectrum of protein-ligand interaction scoring functions have been developed. Regardless of their technical difference, scoring functions all need data sets combining protein-ligand complex structures and binding affinity data for parametrization and validation. However, data sets of this kind used to be rather limited in terms of size and quality. On the other hand, standard metrics for evaluating scoring function used to be ambiguous. Scoring functions are often tested in molecular docking or even virtual screening trials, which do not directly reflect the genuine quality of scoring functions. Collectively, these underlying obstacles have impeded the invention of more advanced scoring functions. In this Account, we describe our long-lasting efforts to overcome these obstacles, which involve two related projects. On the first project, we have created the PDBbind database. It is the first database that systematically annotates the protein-ligand complexes in the Protein Data Bank (PDB) with experimental binding data. This database has been updated annually since its first public release in 2004. The latest release (version 2016) provides binding data for 16 179 biomolecular complexes in PDB. Data sets provided by PDBbind have been applied to many computational and statistical studies on protein-ligand interaction and various subjects. In particular, it has become a major data resource for scoring function development. On the second project, we have established the Comparative Assessment of Scoring Functions (CASF) benchmark for scoring function evaluation. Our key idea is to decouple the "scoring" process from the "sampling" process, so scoring functions can be tested in a relatively pure context to reflect their quality. In our

Structural determinants for protein adsorption/non-adsorption to silica surface

International Nuclear Information System (INIS)

Mathe, Christelle; Devineau, Stephanie; Aude, Jean-Christophe; Lagniel, Gilles; Chedin, Stephane; Legros, Veronique; Mathon, Marie-Helene; Renault, Jean-Philippe; Pin, Serge; Boulard, Yves; Labarre, Jean

2013-01-01

The understanding of the mechanisms involved in the interaction of proteins with inorganic surfaces is of major interest in both fundamental research and applications such as nano-technology. However, despite intense research, the mechanisms and the structural determinants of protein/surface interactions are still unclear. We developed a strategy consisting in identifying, in a mixture of hundreds of soluble proteins, those proteins that are adsorbed on the surface and those that are not. If the two protein subsets are large enough, their statistical comparative analysis must reveal the physicochemical determinants relevant for adsorption versus non-adsorption. This methodology was tested with silica nanoparticles. We found that the adsorbed proteins contain a higher number of charged amino acids, particularly arginine, which is consistent with involvement of this basic amino acid in electrostatic interactions with silica. The analysis also identified a marked bias toward low aromatic amino acid content (phenylalanine, tryptophan, tyrosine and histidine) in adsorbed proteins. Structural analyses and molecular dynamics simulations of proteins from the two groups indicate that non-adsorbed proteins have twice as many p-p interactions and higher structural rigidity. The data are consistent with the notion that adsorption is correlated with the flexibility of the protein and with its ability to spread on the surface. Our findings led us to propose a refined model of protein adsorption. (authors)

Structural determinants for protein adsorption/non-adsorption to silica surface.

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Christelle Mathé

Full Text Available The understanding of the mechanisms involved in the interaction of proteins with inorganic surfaces is of major interest in both fundamental research and applications such as nanotechnology. However, despite intense research, the mechanisms and the structural determinants of protein/surface interactions are still unclear. We developed a strategy consisting in identifying, in a mixture of hundreds of soluble proteins, those proteins that are adsorbed on the surface and those that are not. If the two protein subsets are large enough, their statistical comparative analysis must reveal the physicochemical determinants relevant for adsorption versus non-adsorption. This methodology was tested with silica nanoparticles. We found that the adsorbed proteins contain a higher number of charged amino acids, particularly arginine, which is consistent with involvement of this basic amino acid in electrostatic interactions with silica. The analysis also identified a marked bias toward low aromatic amino acid content (phenylalanine, tryptophan, tyrosine and histidine in adsorbed proteins. Structural analyses and molecular dynamics simulations of proteins from the two groups indicate that non-adsorbed proteins have twice as many π-π interactions and higher structural rigidity. The data are consistent with the notion that adsorption is correlated with the flexibility of the protein and with its ability to spread on the surface. Our findings led us to propose a refined model of protein adsorption.

Computational Studies of Protein Hydration Methods

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Morozenko, Aleksandr

It is widely appreciated that water plays a vital role in proteins' functions. The long-range proton transfer inside proteins is usually carried out by the Grotthuss mechanism and requires a chain of hydrogen bonds that is composed of internal water molecules and amino acid residues of the protein. In other cases, water molecules can facilitate the enzymes catalytic reactions by becoming a temporary proton donor/acceptor. Yet a reliable way of predicting water protein interior is still not available to the biophysics community. This thesis presents computational studies that have been performed to gain insights into the problems of fast and accurate prediction of potential water sites inside internal cavities of protein. Specifically, we focus on the task of attainment of correspondence between results obtained from computational experiments and experimental data available from X-ray structures. An overview of existing methods of predicting water molecules in the interior of a protein along with a discussion of the trustworthiness of these predictions is a second major subject of this thesis. A description of differences of water molecules in various media, particularly, gas, liquid and protein interior, and theoretical aspects of designing an adequate model of water for the protein environment are widely discussed in chapters 3 and 4. In chapter 5, we discuss recently developed methods of placement of water molecules into internal cavities of a protein. We propose a new methodology based on the principle of docking water molecules to a protein body which allows to achieve a higher degree of matching experimental data reported in protein crystal structures than other techniques available in the world of biophysical software. The new methodology is tested on a set of high-resolution crystal structures of oligopeptide-binding protein (OppA) containing a large number of resolved internal water molecules and applied to bovine heart cytochrome c oxidase in the fully

Synthesis, biological evaluation and molecular docking studies of ...

African Journals Online (AJOL)

Synthesis, biological evaluation and molecular docking studies of Mannich bases derived from 1, 3, 4-oxadiazole- 2-thiones as potential urease inhibitors. ... Mannich bases (5-17) were subjected to in silico screening as urease inhibitors, using crystal structure of urease (Protein Data Bank ID: 5FSE) as a model enzyme.

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

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P. Srinivasan

2014-01-01

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

Conserved chemosensory proteins in the proboscis and eyes of Lepidoptera.

Science.gov (United States)

Zhu, Jiao; Iovinella, Immacolata; Dani, Francesca Romana; Liu, Yu-Ling; Huang, Ling-Qiao; Liu, Yang; Wang, Chen-Zhu; Pelosi, Paolo; Wang, Guirong

2016-01-01

Odorant-binding proteins (OBPs) and chemosensory proteins (CSPs) are endowed with several different functions besides being carriers for pheromones and odorants. Based on a previous report of a CSP acting as surfactant in the proboscis of the moth Helicoverpa armigera , we revealed the presence of orthologue proteins in two other moths Plutella xylostella and Chilo suppressalis , as well as two butterflies Papilio machaon and Pieris rapae , using immunodetection and proteomic analysis. The unusual conservation of these proteins across large phylogenetic distances indicated a common specific function for these CSPs. This fact prompted us to search for other functions of these proteins and discovered that CSPs are abundantly expressed in the eyes of H. armigera and possibly involved as carriers for carotenoids and visual pigments. This hypothesis is supported by ligand-binding experiments and docking simulations with retinol and β-carotene. This last orange pigment, occurring in many fruits and vegetables, is an antioxidant and the precursor of visual pigments. We propose that structurally related CSPs solubilise nutritionally important carotenoids in the proboscis, while they act as carriers of both β-carotene and its derived products 3-hydroxyretinol and 3-hydroxyretinal in the eye. The use of soluble olfactory proteins, such as CSPs, as carriers for visual pigments in insects, here reported for the first time, parallels the function of retinol-binding protein in vertebrates, a lipocalin structurally related to vertebrate odorant-binding proteins.

Oligomeric protein structure networks: insights into protein-protein interactions

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Brinda KV

2005-12-01

Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

Dynamic Docking: A Paradigm Shift in Computational Drug Discovery

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Dario Gioia

2017-11-01

Full Text Available Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. During the last decade, methods based on full atomistic molecular dynamics (MD have emerged as a valid alternative for simulating macromolecular complexes. In principle, compared to traditional docking, MD allows the full exploration of drug-target recognition and binding from both the mechanistic and energetic points of view (dynamic docking. Binding and unbinding kinetic constants can also be determined. While dynamic docking is still too computationally expensive to be routinely used in fast-paced drug discovery programs, the advent of faster computing architectures and advanced simulation methodologies are changing this scenario. It is feasible that dynamic docking will replace static docking approaches in the near future, leading to a major paradigm shift in in silico drug discovery. Against this background, we review the key achievements that have paved the way for this progress.

A Rational Approach to Identify Inhibitors of Mycobacterium tuberculosis Enoyl Acyl Carrier Protein Reductase

Czech Academy of Sciences Publication Activity Database

Chhabria, M. T.; Parmar, K. B.; Brahmkshatriya, Pathik

2013-01-01

Roč. 19, č. 21 (2013), s. 3878-3883 ISSN 1381-6128 Institutional support: RVO:61388963 Keywords : mycobacterium tuberculosis * enoyl acyl carrier protein reductase * pharmacophore modeling * molecular docking * binding interactions Subject RIV: FR - Pharmacology ; Medidal Chemistry Impact factor: 3.288, year: 2013

Molecular Docking Study on Galantamine Derivatives as Cholinesterase Inhibitors.

Science.gov (United States)

Atanasova, Mariyana; Yordanov, Nikola; Dimitrov, Ivan; Berkov, Strahil; Doytchinova, Irini

2015-06-01

A training set of 22 synthetic galantamine derivatives binding to acetylcholinesterase was docked by GOLD and the protocol was optimized in terms of scoring function, rigidity/flexibility of the binding site, presence/absence of a water molecule inside and radius of the binding site. A moderate correlation was found between the affinities of compounds expressed as pIC50 values and their docking scores. The optimized docking protocol was validated by an external test set of 11 natural galantamine derivatives and the correlation coefficient between the docking scores and the pIC50 values was 0.800. The derived relationship was used to analyze the interactions between galantamine derivatives and AChE. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

iview: an interactive WebGL visualizer for protein-ligand complex.

Science.gov (United States)

Li, Hongjian; Leung, Kwong-Sak; Nakane, Takanori; Wong, Man-Hon

2014-02-25

Visualization of protein-ligand complex plays an important role in elaborating protein-ligand interactions and aiding novel drug design. Most existing web visualizers either rely on slow software rendering, or lack virtual reality support. The vital feature of macromolecular surface construction is also unavailable. We have developed iview, an easy-to-use interactive WebGL visualizer of protein-ligand complex. It exploits hardware acceleration rather than software rendering. It features three special effects in virtual reality settings, namely anaglyph, parallax barrier and oculus rift, resulting in visually appealing identification of intermolecular interactions. It supports four surface representations including Van der Waals surface, solvent excluded surface, solvent accessible surface and molecular surface. Moreover, based on the feature-rich version of iview, we have also developed a neat and tailor-made version specifically for our istar web platform for protein-ligand docking purpose. This demonstrates the excellent portability of iview. Using innovative 3D techniques, we provide a user friendly visualizer that is not intended to compete with professional visualizers, but to enable easy accessibility and platform independence.

Protein-Ligand Empirical Interaction Components for Virtual Screening.

Science.gov (United States)

Yan, Yuna; Wang, Weijun; Sun, Zhaoxi; Zhang, John Z H; Ji, Changge

2017-08-28

A major shortcoming of empirical scoring functions is that they often fail to predict binding affinity properly. Removing false positives of docking results is one of the most challenging works in structure-based virtual screening. Postdocking filters, making use of all kinds of experimental structure and activity information, may help in solving the issue. We describe a new method based on detailed protein-ligand interaction decomposition and machine learning. Protein-ligand empirical interaction components (PLEIC) are used as descriptors for support vector machine learning to develop a classification model (PLEIC-SVM) to discriminate false positives from true positives. Experimentally derived activity information is used for model training. An extensive benchmark study on 36 diverse data sets from the DUD-E database has been performed to evaluate the performance of the new method. The results show that the new method performs much better than standard empirical scoring functions in structure-based virtual screening. The trained PLEIC-SVM model is able to capture important interaction patterns between ligand and protein residues for one specific target, which is helpful in discarding false positives in postdocking filtering.

Proteins with Novel Structure, Function and Dynamics

Science.gov (United States)

Pohorille, Andrew

2014-01-01

Recently, a small enzyme that ligates two RNA fragments with the rate of 10(exp 6) above background was evolved in vitro (Seelig and Szostak, Nature 448:828-831, 2007). This enzyme does not resemble any contemporary protein (Chao et al., Nature Chem. Biol. 9:81-83, 2013). It consists of a dynamic, catalytic loop, a small, rigid core containing two zinc ions coordinated by neighboring amino acids, and two highly flexible tails that might be unimportant for protein function. In contrast to other proteins, this enzyme does not contain ordered secondary structure elements, such as alpha-helix or beta-sheet. The loop is kept together by just two interactions of a charged residue and a histidine with a zinc ion, which they coordinate on the opposite side of the loop. Such structure appears to be very fragile. Surprisingly, computer simulations indicate otherwise. As the coordinating, charged residue is mutated to alanine, another, nearby charged residue takes its place, thus keeping the structure nearly intact. If this residue is also substituted by alanine a salt bridge involving two other, charged residues on the opposite sides of the loop keeps the loop in place. These adjustments are facilitated by high flexibility of the protein. Computational predictions have been confirmed experimentally, as both mutants retain full activity and overall structure. These results challenge our notions about what is required for protein activity and about the relationship between protein dynamics, stability and robustness. We hypothesize that small, highly dynamic proteins could be both active and fault tolerant in ways that many other proteins are not, i.e. they can adjust to retain their structure and activity even if subjected to mutations in structurally critical regions. This opens the doors for designing proteins with novel functions, structures and dynamics that have not been yet considered.

Protein nanoparticles for therapeutic protein delivery.

Science.gov (United States)

Herrera Estrada, L P; Champion, J A

2015-06-01

Therapeutic proteins can face substantial challenges to their activity, requiring protein modification or use of a delivery vehicle. Nanoparticles can significantly enhance delivery of encapsulated cargo, but traditional small molecule carriers have some limitations in their use for protein delivery. Nanoparticles made from protein have been proposed as alternative carriers and have benefits specific to therapeutic protein delivery. This review describes protein nanoparticles made by self-assembly, including protein cages, protein polymers, and charged or amphipathic peptides, and by desolvation. It presents particle fabrication and delivery characterization for a variety of therapeutic and model proteins, as well as comparison of the features of different protein nanoparticles.

Modelling substrate specificity and enantioselectivity for lipases and esterases by substrate-imprinted docking

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Tyagi Sadhna

2009-06-01

Full Text Available Abstract Background Previously, ways to adapt docking programs that were developed for modelling inhibitor-receptor interaction have been explored. Two main issues were discussed. First, when trying to model catalysis a reaction intermediate of the substrate is expected to provide more valid information than the ground state of the substrate. Second, the incorporation of protein flexibility is essential for reliable predictions. Results Here we present a predictive and robust method to model substrate specificity and enantioselectivity of lipases and esterases that uses reaction intermediates and incorporates protein flexibility. Substrate-imprinted docking starts with covalent docking of reaction intermediates, followed by geometry optimisation of the resulting enzyme-substrate complex. After a second round of docking the same substrate into the geometry-optimised structures, productive poses are identified by geometric filter criteria and ranked by their docking scores. Substrate-imprinted docking was applied in order to model (i enantioselectivity of Candida antarctica lipase B and a W104A mutant, (ii enantioselectivity and substrate specificity of Candida rugosa lipase and Burkholderia cepacia lipase, and (iii substrate specificity of an acetyl- and a butyrylcholine esterase toward the substrates acetyl- and butyrylcholine. Conclusion The experimentally observed differences in selectivity and specificity of the enzymes were reproduced with an accuracy of 81%. The method was robust toward small differences in initial structures (different crystallisation conditions or a co-crystallised ligand, although large displacements of catalytic residues often resulted in substrate poses that did not pass the geometric filter criteria.

Lead Discovery for Alzheimer’s Disease Related Target Protein RbAp48 from Traditional Chinese Medicine

Directory of Open Access Journals (Sweden)

Hung-Jin Huang

2014-01-01

Full Text Available Deficiency or loss of function of Retinoblastoma-associated proteins (RbAp48 is related with Alzheimer’s disease (AD, and AD disease is associated with age-related memory loss. During normal function, RbAp48 forms a complex with the peptide FOG-1 (friend of GATA-1 and has a role in gene transcription, but an unstable complex may affect the function of RbAp48. This study utilizes the world’s largest traditional Chinese medicine (TCM database and virtual screening to provide potential compounds for RbAp48 binding. A molecular dynamics (MD simulation was employed to understand the variations after protein-ligand interaction. FOG1 was found to exhibit low stability after RbAp48 binding; the peptide displayed significant movement from the initial docking position, a phenomenon which matched the docking results. The protein structure of the other TCM candidates was not variable during MD simulation and had a greater stable affinity for RbAp48 binding than FOG1. Our results reveal that the protein structure does not affect ligand binding, and the top three TCM candidates Bittersweet alkaloid II, Eicosandioic acid, and Perivine might resolve the instability of the RbAp48-FOG1 complex and thus be used in AD therapy.

Combining NMR and small angle X-ray and neutron scattering in the structural analysis of a ternary protein-RNA complex

International Nuclear Information System (INIS)

Hennig, Janosch; Wang, Iren; Sonntag, Miriam; Gabel, Frank; Sattler, Michael

2013-01-01

Many processes in the regulation of gene expression and signaling involve the formation of protein complexes involving multi-domain proteins. Individual domains that mediate protein-protein and protein-nucleic acid interactions are typically connected by flexible linkers, which contribute to conformational dynamics and enable the formation of complexes with distinct binding partners. Solution techniques are therefore required for structural analysis and to characterize potential conformational dynamics. Nuclear magnetic resonance spectroscopy (NMR) provides such information but often only sparse data are obtained with increasing molecular weight of the complexes. It is therefore beneficial to combine NMR data with additional structural restraints from complementary solution techniques. Small angle X-ray/neutron scattering (SAXS/SANS) data can be efficiently combined with NMR-derived information, either for validation or by providing additional restraints for structural analysis. Here, we show that the combination of SAXS and SANS data can help to refine structural models obtained from data-driven docking using HADDOCK based on sparse NMR data. The approach is demonstrated with the ternary protein-protein-RNA complex involving two RNA recognition motif (RRM) domains of Sex-lethal, the N-terminal cold shock domain of Upstream-to-N-Ras, and msl-2 mRNA. Based on chemical shift perturbations we have mapped protein-protein and protein-RNA interfaces and complemented this NMR-derived information with SAXS data, as well as SANS measurements on subunit-selectively deuterated samples of the ternary complex. Our results show that, while the use of SAXS data is beneficial, the additional combination with contrast variation in SANS data resolves remaining ambiguities and improves the docking based on chemical shift perturbations of the ternary protein-RNA complex.

Combining NMR and small angle X-ray and neutron scattering in the structural analysis of a ternary protein-RNA complex

Energy Technology Data Exchange (ETDEWEB)

Hennig, Janosch; Wang, Iren; Sonntag, Miriam [Institute of Structural Biology, Helmholtz Zentrum Muenchen (Germany); Gabel, Frank [Extremophiles and Large Molecular Assemblies Group (ELMA), Institut de Biologie Structurale (IBS) CEA-CNRS-UJF (France); Sattler, Michael, E-mail: sattler@helmholtz-muenchen.de [Institute of Structural Biology, Helmholtz Zentrum Muenchen (Germany)

2013-05-15

Many processes in the regulation of gene expression and signaling involve the formation of protein complexes involving multi-domain proteins. Individual domains that mediate protein-protein and protein-nucleic acid interactions are typically connected by flexible linkers, which contribute to conformational dynamics and enable the formation of complexes with distinct binding partners. Solution techniques are therefore required for structural analysis and to characterize potential conformational dynamics. Nuclear magnetic resonance spectroscopy (NMR) provides such information but often only sparse data are obtained with increasing molecular weight of the complexes. It is therefore beneficial to combine NMR data with additional structural restraints from complementary solution techniques. Small angle X-ray/neutron scattering (SAXS/SANS) data can be efficiently combined with NMR-derived information, either for validation or by providing additional restraints for structural analysis. Here, we show that the combination of SAXS and SANS data can help to refine structural models obtained from data-driven docking using HADDOCK based on sparse NMR data. The approach is demonstrated with the ternary protein-protein-RNA complex involving two RNA recognition motif (RRM) domains of Sex-lethal, the N-terminal cold shock domain of Upstream-to-N-Ras, and msl-2 mRNA. Based on chemical shift perturbations we have mapped protein-protein and protein-RNA interfaces and complemented this NMR-derived information with SAXS data, as well as SANS measurements on subunit-selectively deuterated samples of the ternary complex. Our results show that, while the use of SAXS data is beneficial, the additional combination with contrast variation in SANS data resolves remaining ambiguities and improves the docking based on chemical shift perturbations of the ternary protein-RNA complex.

Solution Structure of an Antifreeze Protein CfAFP-501 from Choristoneura fumiferana

International Nuclear Information System (INIS)

Li Congmin; Guo Xianrong; Jia Zongchao; Xia Bin; Jin Changwen

2005-01-01

Antifreeze proteins (AFPs) are widely employed by various organisms as part of their overwintering survival strategy. AFPs have the unique ability to suppress the freezing point of aqueous solution and inhibit ice recrystallization through binding to the ice seed crystals and restricting their growth. The solution structure of CfAFP-501 from spruce budworm has been determined by NMR spectroscopy. Our result demonstrates that CfAFP-501 retains its rigid and highly regular structure in solution. Overall, the solution structure is similar to the crystal structure except the N- and C-terminal regions. NMR spin-relaxation experiments further indicate the overall rigidity of the protein and identify a collection of residues with greater flexibilities. Furthermore, Pro91 shows a cis conformation in solution instead of the trans conformation determined in the crystal structure

Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.

Science.gov (United States)

Su, Min-Gang; Weng, Julia Tzu-Ya; Hsu, Justin Bo-Kai; Huang, Kai-Yao; Chi, Yu-Hsiang; Lee, Tzong-Yi

2017-12-21

Protein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in. This is particularly important in light of the fact that most protein-based pharmaceuticals deliver their therapeutic effects through some form of PTM. Yet, our understanding is still limited with respect to the local effects and frequency of PTM sites near pharmaceutical binding sites and the interfaces of protein-protein interaction (PPI). Understanding PTM's function is critical to our ability to manipulate the biological mechanisms of protein. In this study, to understand the regulation of protein functions by PTMs, we mapped 25,835 PTM sites to proteins with available three-dimensional (3D) structural information in the Protein Data Bank (PDB), including 1785 modified PTM sites on the 3D structure. Based on the acquired structural PTM sites, we proposed to use five properties for the structural characterization of PTM substrate sites: the spatial composition of amino acids, residues and side-chain orientations surrounding the PTM substrate sites, as well as the secondary structure, division of acidity and alkaline residues, and solvent-accessible surface area. We further mapped the structural PTM sites to the structures of drug binding and PPI sites, identifying a total of 1917 PTM sites that may affect PPI and 3951 PTM sites associated with drug-target binding. An integrated analytical platform (CruxPTM), with a variety of methods and online molecular docking

A New Class of Amphiphiles Bearing Rigid Hydrophobic Groups for Solubilization and Stabilization of Membrane Proteins

DEFF Research Database (Denmark)

Chae, Pil Seok; Rasmussen, Søren G F; Rana, Rohini R

2012-01-01

Non-traditional amphiphiles: Conferring aqueous solubility on membrane proteins generally requires the use of a detergent or other amphiphilic agent. A new class of amphiphiles was synthesized, based on steroidal lipophilic groups, and evaluated with several membrane proteins. The results show th...... that the new amphiphile, "glyco-diosgenin" (GDN; see figure), confers enhanced stability to a variety of membrane proteins in solution relative to popular conventional detergents, such as dodecylmaltoside (DDM)....

Protein-protein interactions: an application of Tus-Ter mediated protein microarray system.

Science.gov (United States)

Sitaraman, Kalavathy; Chatterjee, Deb K

2011-01-01

In this chapter, we present a novel, cost-effective microarray strategy that utilizes expression-ready plasmid DNAs to generate protein arrays on-demand and its use to validate protein-protein interactions. These expression plasmids were constructed in such a way so as to serve a dual purpose of synthesizing the protein of interest as well as capturing the synthesized protein. The microarray system is based on the high affinity binding of Escherichia coli "Tus" protein to "Ter," a 20 bp DNA sequence involved in the regulation of DNA replication. The protein expression is carried out in a cell-free protein synthesis system, with rabbit reticulocyte lysates, and the target proteins are detected either by labeled incorporated tag specific or by gene-specific antibodies. This microarray system has been successfully used for the detection of protein-protein interaction because both the target protein and the query protein can be transcribed and translated simultaneously in the microarray slides. The utility of this system for detecting protein-protein interaction is demonstrated by a few well-known examples: Jun/Fos, FRB/FKBP12, p53/MDM2, and CDK4/p16. In all these cases, the presence of protein complexes resulted in the localization of fluorophores at the specific sites of the immobilized target plasmids. Interestingly, during our interactions studies we also detected a previously unknown interaction between CDK2 and p16. Thus, this Tus-Ter based system of protein microarray can be used for the validation of known protein interactions as well as for identifying new protein-protein interactions. In addition, it can be used to examine and identify targets of nucleic acid-protein, ligand-receptor, enzyme-substrate, and drug-protein interactions.

Truly Absorbed Microbial Protein Synthesis, Rumen Bypass Protein, Endogenous Protein, and Total Metabolizable Protein from Starchy and Protein-Rich Raw Materials

NARCIS (Netherlands)

Parand, Ehsan; Vakili, Alireza; Mesgaran, Mohsen Danesh; Duinkerken, Van Gert; Yu, Peiqiang

2015-01-01

This study was carried out to measure truly absorbed microbial protein synthesis, rumen bypass protein, and endogenous protein loss, as well as total metabolizable protein, from starchy and protein-rich raw feed materials with model comparisons. Predictions by the DVE2010 system as a more

Novel Penicillin Analogues as Potential Antimicrobial Agents; Design, Synthesis and Docking Studies.

Directory of Open Access Journals (Sweden)

Zaman Ashraf

Full Text Available 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.

DockBench: An Integrated Informatic Platform Bridging the Gap between the Robust Validation of Docking Protocols and Virtual Screening Simulations

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Alberto Cuzzolin

2015-05-01

Full Text Available Virtual screening (VS is a computational methodology that streamlines the drug discovery process by reducing costs and required resources through the in silico identification of potential drug candidates. Structure-based VS (SBVS exploits knowledge about the three-dimensional (3D structure of protein targets and uses the docking methodology as search engine for novel hits. The success of a SBVS campaign strongly depends upon the accuracy of the docking protocol used to select the candidates from large chemical libraries. The identification of suitable protocols is therefore a crucial step in the setup of SBVS experiments. Carrying out extensive benchmark studies, however, is usually a tangled task that requires users’ proficiency in handling different file formats and philosophies at the basis of the plethora of existing software packages. We present here DockBench 1.0, a platform available free of charge that eases the pipeline by automating the entire procedure, from docking benchmark to VS setups. In its current implementation, DockBench 1.0 handles seven docking software packages and offers the possibility to test up to seventeen different protocols. The main features of our platform are presented here and the results of the benchmark study of human Checkpoint kinase 1 (hChk1 are discussed as validation test.

Binding of ethyl pyruvate to bovine serum albumin: Calorimetric, spectroscopic and molecular docking studies

Energy Technology Data Exchange (ETDEWEB)

Pathak, Mallika [Department of Chemistry, Miranda House, University of Delhi, Delhi 11007 (India); Mishra, Rashmi; Agarwala, Paban K. [Department of Radiation Genetics and Epigenetics, Division of Radioprotective Drug Development Research, Institute of Nuclear Medicine and Allied Sciences, Delhi 110054 (India); Ojha, Himanshu, E-mail: himanshu.drdo@gmail.com [Department of Radiation Genetics and Epigenetics, Division of Radioprotective Drug Development Research, Institute of Nuclear Medicine and Allied Sciences, Delhi 110054 (India); Singh, Bhawna [Department of Radiation Genetics and Epigenetics, Division of Radioprotective Drug Development Research, Institute of Nuclear Medicine and Allied Sciences, Delhi 110054 (India); Singh, Anju; Kukreti, Shrikant [Nucleic Acid Research Laboratory, Department of Chemistry, University of Delhi, Delhi 11007 (India)

2016-06-10

Highlights: • ITC study showed binding of ethyl pyruvate with BSA with high binding affinity. • Ethyl pyruvate binding caused conformation alteration of BSA. • Fluorescence quenching mechanism is static in nature. • Electrostatic, hydrogen bonding and hydrophobic forces involved in binding. • Docking confirmed role of electrostatic, hydrogen bonding and hydrophobic forces. - Abstract: Various in vitro and in vivo studies have shown the anti-inflammatory and anticancer potential role of ethyl pyruvate. Bio-distribution of drugs is significantly influenced by the drug-serum protein binding. Therefore, the binding mechanism of the ethyl pyruvate with bovine serum albumin was investigated using UV–vis absorption, fluorescence, circular dichroism, isothermal titration calorimetry and molecular docking techniques. Absorption and fluorescence quenching studies indicated the binding of ethyl pyruvate with protein. Circular dichroism spectra of bovine serum albumin confirmed significant change in the conformation of protein upon binding. Thermodynamic data confirmed that ethyl pyruvate binds to bovine serum albumin at the two different sites with high affinity. Binding of ethyl pyruvate to bovine serum albumin involves hydrogen bonding, van der Waal and hydrophobic interactions. Further, docking studies indicated that ethyl pyruvate could bind significantly at the three binding sites. The results will definitely contribute to the development of ethyl pyruvate as drug.

In silico studies on structure-function of DNA GCC- box binding domain of brassica napus DREB1 protein

International Nuclear Information System (INIS)

Qamarunnisa, S.; Hussain, M.

2012-01-01

DREB1 is a transcriptional factor, which selectively binds with the promoters of the genes involved in stress response in the plants. Homology of DREB protein and its binding element have been detected in the genome of many plants. However, only a few reports exist that discusses the binding properties of this protein with the gene (s) promoter. In the present study, we have undertaken studies exploring the structure-function relationship of Brassica napus DREB1. Multiple sequence alignment, protein homology modeling and intermolecular docking of GCC-box binding domain (GBD) of the said protein was carried out using atomic coordinates of GBD from Arabdiopsis thaliana and GCC-box containing DNA respectively. Similarities and/or identities in multiple, sequence alignment, particularly at the functionally important amino acids, strongly suggested the binding specificity of B. napus DREB1 to GCC-box. Similarly, despite 56% sequence homology, tertiary structures of both template and modeled protein were found to be extremely similar as indicated by root mean square deviation of 0.34 A. More similarities were established between GBD of both A. thaliana and B. napus DREB1 by conducting protein docking with the DNA containing GCC-box. It appears that both proteins interact through their beta-sheet with the major DNA groove including both nitrogen bases and phosphate and sugar moieties. Additionally, in most cases the interacting residues were also found to be identical. Briefly, this study attempts to elucidate the molecular basis of DREB1 interaction with its target sequence in the promoter. (author)

Using Molecular Docking Analysis to Discovery Dregea sinensis Hemsl. Potential Mechanism of Anticancer, Antidepression, and Immunoregulation.

Science.gov (United States)

Liu, Xiujie; Shi, Yu; Deng, Yulin; Dai, Rongji

2017-01-01

Dregea sinensis Hemsl. plant of the genus Dregea volubilis (Asclepiadaceae), plays a vital role in anticancer, antidepression, and immunoregulation. Steroidal glycosides are the main constituents of this herb, which were significant biological active ingredients. The objective of this study is to recognize the mechanism of anticancer, antidepression, and immunoregulation of D. sinensis Hemsl. Seventy-two steroidal glycosides of D. sinensis Hemsl. were evaluated on the docking behavior of tumor-associated proteins (PI3K, Akt, mTOR), depression-related proteins (MAO-A, MAO-B) and immune-related proteins (tumor necrosis factor-α [TNF-α], tumor necrosis factor receptor 2 [TNFR2], interleukin-2Rα [IL-2Rα]) using Discovery Studio version 3.1 (Accelrys, San Diego, USA). The molecular docking analysis revealed that mostly steroidal glycosides of D. sinensis Hemsl. exhibited powerful interaction with the depression-related protein (MAO-A) and the immune-related proteins (TNFR2, IL-2Rα). Some ligands exhibited high binding energy for the tumor-associated proteins (PI3K, Akt, mTOR) and the immune-related protein (TNF-α), but MAO-B showed none interaction with the ligands. This study has paved better understanding of steroidal glycosides from D. sinensis Hemsl. as potential constituents to the prevention of associated cancer, depression and disorders of immunoregulation. The ligand database was consist of 72 steroidal glycosides from Dregea sinensis HemslSteroidal glycosides had the potential to dock with the tumor-associated proteins (PI3K, Akt, mTOR)Steroidal glycosides were bounded with MAO-A rather than MAO-B, accorded with the inhibitor selectivity of MAOs, can be considered as potent candidate inhibitors of MAO-A72 ligands got high interaction with TNFR2 and IL-2Rα, regard the steroidal glycoside as powerful candidate inhibitors of TNFR2 and IL-2Rα. Abbreviations used: PI3K: Phosphatidyl inositol 3-kinase; Akt: Protein kinase B; mTOR: Mammalian target of

Rab proteins: The key regulators of intracellular vesicle transport

International Nuclear Information System (INIS)

Bhuin, Tanmay; Roy, Jagat Kumar

2014-01-01

Vesicular/membrane trafficking essentially regulates the compartmentalization and abundance of proteins within the cells and contributes in many signalling pathways. This membrane transport in eukaryotic cells is a complex process regulated by a large and diverse array of proteins. A large group of monomeric small GTPases; the Rabs are essential components of this membrane trafficking route. Most of the Rabs are ubiquitously expressed proteins and have been implicated in vesicle formation, vesicle motility/delivery along cytoskeleton elements and docking/fusion at target membranes through the recruitment of effectors. Functional impairments of Rabs affecting transport pathways manifest different diseases. Rab functions are accompanied by cyclical activation and inactivation of GTP-bound and GDP-bound forms between the cytosol and membranes which is regulated by upstream regulators. Rab proteins are characterized by their distinct sub-cellular localization and regulate a wide variety of endocytic, transcytic and exocytic transport pathways. Mutations of Rabs affect cell growth, motility and other biological processes. - Highlights: • Rab proteins regulate different signalling pathways. • Deregulation of Rabs is the fundamental causes of a variety of human diseases. • This paper gives potential directions in developing therapeutic targets. • This paper also gives ample directions for modulating pathways central to normal physiology. • These are the huge challenges for drug discovery and delivery in near future

Rab proteins: The key regulators of intracellular vesicle transport

Energy Technology Data Exchange (ETDEWEB)

Bhuin, Tanmay [Cell and Developmental Biology Unit, Department of Zoology, The University of Burdwan, Golapbag 713104 (India); Roy, Jagat Kumar, E-mail: jkroy@bhu.ac.in [Cytogenetics Laboratory, Department of Zoology, Banaras Hindu University, Varanasi 221005 (India)

2014-10-15

Vesicular/membrane trafficking essentially regulates the compartmentalization and abundance of proteins within the cells and contributes in many signalling pathways. This membrane transport in eukaryotic cells is a complex process regulated by a large and diverse array of proteins. A large group of monomeric small GTPases; the Rabs are essential components of this membrane trafficking route. Most of the Rabs are ubiquitously expressed proteins and have been implicated in vesicle formation, vesicle motility/delivery along cytoskeleton elements and docking/fusion at target membranes through the recruitment of effectors. Functional impairments of Rabs affecting transport pathways manifest different diseases. Rab functions are accompanied by cyclical activation and inactivation of GTP-bound and GDP-bound forms between the cytosol and membranes which is regulated by upstream regulators. Rab proteins are characterized by their distinct sub-cellular localization and regulate a wide variety of endocytic, transcytic and exocytic transport pathways. Mutations of Rabs affect cell growth, motility and other biological processes. - Highlights: • Rab proteins regulate different signalling pathways. • Deregulation of Rabs is the fundamental causes of a variety of human diseases. • This paper gives potential directions in developing therapeutic targets. • This paper also gives ample directions for modulating pathways central to normal physiology. • These are the huge challenges for drug discovery and delivery in near future.

Composition of Overlapping Protein-Protein and Protein-Ligand Interfaces.

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Ruzianisra Mohamed

Full Text Available Protein-protein interactions (PPIs play a major role in many biological processes and they represent an important class of targets for therapeutic intervention. However, targeting PPIs is challenging because often no convenient natural substrates are available as starting point for small-molecule design. Here, we explored the characteristics of protein interfaces in five non-redundant datasets of 174 protein-protein (PP complexes, and 161 protein-ligand (PL complexes from the ABC database, 436 PP complexes, and 196 PL complexes from the PIBASE database and a dataset of 89 PL complexes from the Timbal database. In all cases, the small molecule ligands must bind at the respective PP interface. We observed similar amino acid frequencies in all three datasets. Remarkably, also the characteristics of PP contacts and overlapping PL contacts are highly similar.

Protein biosynthesis in cultured human hair follicle cells.

Science.gov (United States)

Weterings, P J; Vermorken, A J; Bloemendal, H

1980-10-31

A new technique has been used for culturing human keratinocytes. The cells grow on the basement membrane-like capsules of bovine lenses. Lens cells were removed from the capsules by rigid trypsinization. In order to exclude any contamination with remaining living cells the isolated capsules were irradiated with X-rays at a dose of 10,000 rad. In this way human epithelial cells can be brought in culture from individual hair follicles. Since feeder cells are not used in this culture technique, the biosynthesis of keratinocyte proteins can be studied in these cultures. The newly synthesized proteins can be separated into a water-soluble, a urea-soluble, and a urea-insoluble fraction. Product analysis has been performed on the first two fractions revealing protein patterns identical to those of intact hair follicles. Product analysis of the urea-soluble fractions of microdissected hair follicles shows that the protein pattern of the cultured keratinocytes resembles the protein pattern of the hair follicle sheath. Studies on the metabolism of benzo(a)pyrene revealed that the enzyme aryl hydrocarbon hydroxylase (AHH) is present in cultured hair follicle cells. A possible use of our culture system for eventual detection of inherited predisposition for smoking-dependent lung cancer is discussed.

Phospholipid liposomes functionalized by protein

Science.gov (United States)

Glukhova, O. E.; Savostyanov, G. V.; Grishina, O. A.

2015-03-01

Finding new ways to deliver neurotrophic drugs to the brain in newborns is one of the contemporary problems of medicine and pharmaceutical industry. Modern researches in this field indicate the promising prospects of supramolecular transport systems for targeted drug delivery to the brain which can overcome the blood-brain barrier (BBB). Thus, the solution of this problem is actual not only for medicine, but also for society as a whole because it determines the health of future generations. Phospholipid liposomes due to combination of lipo- and hydrophilic properties are considered as the main future objects in medicine for drug delivery through the BBB as well as increasing their bioavailability and toxicity. Liposomes functionalized by various proteins were used as transport systems for ease of liposomes use. Designing of modification oligosaccharide of liposomes surface is promising in the last decade because it enables the delivery of liposomes to specific receptor of human cells by selecting ligand and it is widely used in pharmacology for the treatment of several diseases. The purpose of this work is creation of a coarse-grained model of bilayer of phospholipid liposomes, functionalized by specific to the structural elements of the BBB proteins, as well as prediction of the most favorable orientation and position of the molecules in the generated complex by methods of molecular docking for the formation of the structure. Investigation of activity of the ligand molecule to protein receptor of human cells by the methods of molecular dynamics was carried out.

Screening of Potential Inhibitor against Coat Protein of Apple Chlorotic Leaf Spot Virus.

Science.gov (United States)

Purohit, Rituraj; Kumar, Sachin; Hallan, Vipin

2018-06-01

In this study, we analyzed Coat protein (CP) of Apple chlorotic leaf spot virus (ACLSV), an important latent virus on Apple. Incidence of the virus is upto 60% in various apple cultivars, affecting yield losses of the order of 10-40% (depending upon the cultivar). CP plays an important role as the sole building block of the viral capsid. Homology approach was used to model 193 amino acid sequence of the coat protein. We used various servers such as ConSurf, TargetS, OSML, COACH, COFACTOR for the prediction of active site residues in coat protein. Virtual screening strategy was employed to search potential inhibitors for CP. Top twenty screened molecules considered for drugability, and toxicity analysis and one potential molecule was further analyzed by docking analysis. Here, we reported a potent molecule which could inhibit the formation of viron assembly by targeting the CP protein of virus.

Lactoferrin binding protein B - a bi-functional bacterial receptor protein.

Directory of Open Access Journals (Sweden)

Nicholas K H Ostan

2017-03-01

Full Text Available Lactoferrin binding protein B (LbpB is a bi-lobed outer membrane-bound lipoprotein that comprises part of the lactoferrin (Lf receptor complex in Neisseria meningitidis and other Gram-negative pathogens. Recent studies have demonstrated that LbpB plays a role in protecting the bacteria from cationic antimicrobial peptides due to large regions rich in anionic residues in the C-terminal lobe. Relative to its homolog, transferrin-binding protein B (TbpB, there currently is little evidence for its role in iron acquisition and relatively little structural and biophysical information on its interaction with Lf. In this study, a combination of crosslinking and deuterium exchange coupled to mass spectrometry, information-driven computational docking, bio-layer interferometry, and site-directed mutagenesis was used to probe LbpB:hLf complexes. The formation of a 1:1 complex of iron-loaded Lf and LbpB involves an interaction between the Lf C-lobe and LbpB N-lobe, comparable to TbpB, consistent with a potential role in iron acquisition. The Lf N-lobe is also capable of binding to negatively charged regions of the LbpB C-lobe and possibly other sites such that a variety of higher order complexes are formed. Our results are consistent with LbpB serving dual roles focused primarily on iron acquisition when exposed to limited levels of iron-loaded Lf on the mucosal surface and effectively binding apo Lf when exposed to high levels at sites of inflammation.

Protein- protein interaction detection system using fluorescent protein microdomains

Science.gov (United States)

Waldo, Geoffrey S.; Cabantous, Stephanie

2010-02-23

The invention provides a protein labeling and interaction detection system based on engineered fragments of fluorescent and chromophoric proteins that require fused interacting polypeptides to drive the association of the fragments, and further are soluble and stable, and do not change the solubility of polypeptides to which they are fused. In one embodiment, a test protein X is fused to a sixteen amino acid fragment of GFP (.beta.-strand 10, amino acids 198-214), engineered to not perturb fusion protein solubility. A second test protein Y is fused to a sixteen amino acid fragment of GFP (.beta.-strand 11, amino acids 215-230), engineered to not perturb fusion protein solubility. When X and Y interact, they bring the GFP strands into proximity, and are detected by complementation with a third GFP fragment consisting of GFP amino acids 1-198 (strands 1-9). When GFP strands 10 and 11 are held together by interaction of protein X and Y, they spontaneous association with GFP strands 1-9, resulting in structural complementation, folding, and concomitant GFP fluorescence.

Prediction of methyl-side Chain Dynamics in Proteins

International Nuclear Information System (INIS)

Ming Dengming; Brueschweiler, Rafael

2004-01-01

A simple analytical model is presented for the prediction of methyl-side chain dynamics in comparison with S 2 order parameters obtained by NMR relaxation spectroscopy. The model, which is an extension of the local contact model for backbone order parameter prediction, uses a static 3D protein structure as input. It expresses the methyl-group S 2 order parameters as a function of local contacts of the methyl carbon with respect to the neighboring atoms in combination with the number of consecutive mobile dihedral angles between the methyl group and the protein backbone. For six out of seven proteins the prediction results are good when compared with experimentally determined methyl-group S 2 values with an average correlation coefficient r-bar=0.65±0.14. For the unusually rigid cytochrome c 2 no significant correlation between prediction and experiment is found. The presented model provides independent support for the reliability of current side-chain relaxation methods along with their interpretation by the model-free formalism

Identification of Protein-Protein Interactions with Glutathione-S-Transferase (GST) Fusion Proteins.

Science.gov (United States)

Einarson, Margret B; Pugacheva, Elena N; Orlinick, Jason R

2007-08-01

INTRODUCTIONGlutathione-S-transferase (GST) fusion proteins have had a wide range of applications since their introduction as tools for synthesis of recombinant proteins in bacteria. GST was originally selected as a fusion moiety because of several desirable properties. First and foremost, when expressed in bacteria alone, or as a fusion, GST is not sequestered in inclusion bodies (in contrast to previous fusion protein systems). Second, GST can be affinity-purified without denaturation because it binds to immobilized glutathione, which provides the basis for simple purification. Consequently, GST fusion proteins are routinely used for antibody generation and purification, protein-protein interaction studies, and biochemical analysis. This article describes the use of GST fusion proteins as probes for the identification of protein-protein interactions.

Protein-protein interaction network-based detection of functionally similar proteins within species.

Science.gov (United States)

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets.

Science.gov (United States)

Allen, William J; Fochtman, Brian C; Balius, Trent E; Rizzo, Robert C

2017-11-15

De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from-scratch construction of molecules is not limited to compounds in pre-existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X-ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug-like compounds (generic libraries), and (3) application to a challenging protein-protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Structure and DNA-binding of meiosis-specific protein Hop2

Science.gov (United States)

Zhou, Donghua; Moktan, Hem; Pezza, Roberto

2014-03-01

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

Thermodynamic effects of proline introduction on protein stability.

Science.gov (United States)

Prajapati, Ravindra Singh; Das, Mili; Sreeramulu, Sridhar; Sirajuddin, Minhajuddin; Srinivasan, Sankaranarayanan; Krishnamurthy, Vaishnavi; Ranjani, Ranganathan; Ramakrishnan, C; Varadarajan, Raghavan

2007-02-01

The amino acid Pro is more rigid than other naturally occurring amino acids and, in proteins, lacks an amide hydrogen. To understand the structural and thermodynamic effects of Pro substitutions, it was introduced at 13 different positions in four different proteins, leucine-isoleucine-valine binding protein, maltose binding protein, ribose binding protein, and thioredoxin. Three of the maltose binding protein mutants were characterized by X-ray crystallography to confirm that no structural changes had occurred upon mutation. In the remaining cases, fluorescence and CD spectroscopy were used to show the absence of structural change. Stabilities of wild type and mutant proteins were characterized by chemical denaturation at neutral pH and by differential scanning calorimetry as a function of pH. The mutants did not show enhanced stability with respect to chemical denaturation at room temperature. However, 6 of the 13 single mutants showed a small but significant increase in the free energy of thermal unfolding in the range of 0.3-2.4 kcal/mol, 2 mutants showed no change, and 5 were destabilized. In five of the six cases, the stabilization was because of reduced entropy of unfolding. However, the magnitude of the reduction in entropy of unfolding was typically several fold larger than the theoretical estimate of -4 cal K(-1) mol(-1) derived from the relative areas in the Ramachandran map accessible to Pro and Ala residues, respectively. Two double mutants were constructed. In both cases, the effects of the single mutations on the free energy of thermal unfolding were nonadditive. Copyright 2006 Wiley-Liss, Inc.

Bio-inspired algorithms applied to molecular docking simulations.

Science.gov (United States)

Heberlé, G; de Azevedo, W F

2011-01-01

Nature as a source of inspiration has been shown to have a great beneficial impact on the development of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a ligand can be simulated by biologically inspired algorithms (BIAs). These algorithms mimic biological systems to create new paradigms for computation, such as neural networks, evolutionary computing, and swarm intelligence. This review provides a description of the main concepts behind BIAs applied to molecular docking simulations. Special attention is devoted to evolutionary algorithms, guided-directed evolutionary algorithms, and Lamarckian genetic algorithms. Recent applications of these methodologies to protein targets identified in the Mycobacterium tuberculosis genome are described.

Modeling and protein engineering studies of active and inactive states of human dopamine D2 receptor (D2R) and investigation of drug/receptor interactions.

Science.gov (United States)

Salmas, Ramin Ekhteiari; Yurtsever, Mine; Stein, Matthias; Durdagi, Serdar

2015-05-01

Homology model structures of the dopamine D2 receptor (D2R) were generated starting from the active and inactive states of β2-adrenergic crystal structure templates. To the best of our knowledge, the active conformation of D2R was modeled for the first time in this study. The homology models are built and refined using MODELLER and ROSETTA programs. Top-ranked models have been validated with ligand docking simulations and in silico Alanine-scanning mutagenesis studies. The derived extra-cellular loop region of the protein models is directed toward the binding site cavity which is often involved in ligand binding. The binding sites of protein models were refined using induced fit docking to enable the side-chain refinement during ligand docking simulations. The derived models were then tested using molecular modeling techniques on several marketed drugs for schizophrenia. Alanine-scanning mutagenesis and molecular docking studies gave similar results for marketed drugs tested. We believe that these new D2 receptor models will be very useful for a better understanding of the mechanisms of action of drugs to be targeted to the binding sites of D2Rs and they will contribute significantly to drug design studies involving G-protein-coupled receptors in the future.

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

Science.gov (United States)

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

2012-01-01

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

Evolution of protein-protein interactions

Indian Academy of Sciences (India)

Evolution of protein-protein interactions · Our interests in protein-protein interactions · Slide 3 · Slide 4 · Slide 5 · Slide 6 · Slide 7 · Slide 8 · Slide 9 · Slide 10 · Slide 11 · Slide 12 · Slide 13 · Slide 14 · Slide 15 · Slide 16 · Slide 17 · Slide 18 · Slide 19 · Slide 20.

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

Science.gov (United States)

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

2016-01-01

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

An NMR-based scoring function improves the accuracy of binding pose predictions by docking by two orders of magnitude

Energy Technology Data Exchange (ETDEWEB)

Orts, Julien [EMBL, Structure and Computational Biology Unit (Germany); Bartoschek, Stefan [Industriepark Hoechst, Sanofi-Aventis Deutschland GmbH, R and D LGCR/Parallel Synthesis and Natural Products (Germany); Griesinger, Christian [Max Planck Institute for Biophysical Chemistry (Germany); Monecke, Peter [Industriepark Hoechst, Sanofi-Aventis Deutschland GmbH, R and D LGCR/Structure, Design and Informatics (Germany); Carlomagno, Teresa, E-mail: teresa.carlomagno@embl.de [EMBL, Structure and Computational Biology Unit (Germany)

2012-01-15

Low-affinity ligands can be efficiently optimized into high-affinity drug leads by structure based drug design when atomic-resolution structural information on the protein/ligand complexes is available. In this work we show that the use of a few, easily obtainable, experimental restraints improves the accuracy of the docking experiments by two orders of magnitude. The experimental data are measured in nuclear magnetic resonance spectra and consist of protein-mediated NOEs between two competitively binding ligands. The methodology can be widely applied as the data are readily obtained for low-affinity ligands in the presence of non-labelled receptor at low concentration. The experimental inter-ligand NOEs are efficiently used to filter and rank complex model structures that have been pre-selected by docking protocols. This approach dramatically reduces the degeneracy and inaccuracy of the chosen model in docking experiments, is robust with respect to inaccuracy of the structural model used to represent the free receptor and is suitable for high-throughput docking campaigns.

Protein function prediction using neighbor relativity in protein-protein interaction network.

Science.gov (United States)

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Protein Structure Prediction by Protein Threading

Science.gov (United States)

Xu, Ying; Liu, Zhijie; Cai, Liming; Xu, Dong

The seminal work of Bowie, Lüthy, and Eisenberg (Bowie et al., 1991) on "the inverse protein folding problem" laid the foundation of protein structure prediction by protein threading. By using simple measures for fitness of different amino acid types to local structural environments defined in terms of solvent accessibility and protein secondary structure, the authors derived a simple and yet profoundly novel approach to assessing if a protein sequence fits well with a given protein structural fold. Their follow-up work (Elofsson et al., 1996; Fischer and Eisenberg, 1996; Fischer et al., 1996a,b) and the work by Jones, Taylor, and Thornton (Jones et al., 1992) on protein fold recognition led to the development of a new brand of powerful tools for protein structure prediction, which we now term "protein threading." These computational tools have played a key role in extending the utility of all the experimentally solved structures by X-ray crystallography and nuclear magnetic resonance (NMR), providing structural models and functional predictions for many of the proteins encoded in the hundreds of genomes that have been sequenced up to now.

Molecular Dynamics and Docking of Biphenyl: A Potential ...

African Journals Online (AJOL)

Purpose: To develop a new drug that inhibits viral attachment and entry for the treatment of HIV/AIDS patients. Methods: Two Protein Databank (PDB) crystal structures of HIV-1 gp120-CD4 complexes, namely, 1RZK and 1G9N, were mutated at amino acid position 43 to a biphenylalanine (biPhe-43) residue. FireDock web ...

Fast and accurate grid representations for atom-based docking with partner flexibility.

Science.gov (United States)

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.

Rigidity of Glasses and Macromolecules

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Thorpe, M. F.

1998-03-01

The simple yet powerful ideas of percolation theory have found their way into many different areas of research. In this talk we show how RIGIDITY PERCOLATION can be studied at a similar level of sophistication, using a powerful new program THE PEBBLE GAME (D. J. Jacobs and M. F. Thorpe, Phys. Rev. E) 53, 3682 (1996). that uses an integer algorithm. This program can analyse the rigidity of two and three dimensional networks containing more than one million bars and joints. We find the total number of floppy modes, and find the critical behavior as the network goes from floppy to rigid as more bars are added. We discuss the relevance of this work to network glasses, and how it relates to experiments that involve the mechanical properties like hardness and elasticity of covalent glassy networks like Ge_xAs_ySe_1-x-y and dicuss recent experiments that suggest that the rigidity transition may be first order (Xingwei Feng, W. J.Bresser and P. Boolchand, Phys. Rev. Lett 78), 4422 (1997).. This approach is also useful in macromolecules and proteins, where detailed information about the rigid domain structure can be obtained.

Detection of protein complex from protein-protein interaction network using Markov clustering

International Nuclear Information System (INIS)

Ochieng, P J; Kusuma, W A; Haryanto, T

2017-01-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

Beyond BLASTing: Tertiary and Quaternary Structure Analysis Helps Identify Major Vault Proteins

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Daly, Toni K.; Sutherland-Smith, Andrew J.; Penny, David

2013-01-01

We examine the advantages of going beyond sequence similarity and use both protein three-dimensional (3D) structure prediction and then quaternary structure (docking) of inferred 3D structures to help evaluate whether comparable sequences can fold into homologous structures with sufficient lateral associations for quaternary structure formation. Our test case is the major vault protein (MVP) that oligomerizes in multiple copies to form barrel-like vault particles and is relatively widespread among eukaryotes. We used the iterative threading assembly refinement server (I-TASSER) to predict whether putative MVP sequences identified by BLASTp and PSI Basic Local Alignment Search Tool are structurally similar to the experimentally determined rodent MVP tertiary structures. Then two identical predicted quaternary structures from I-TASSER are analyzed by RosettaDock to test whether a pair-wise association occurs, and hence whether the oligomeric vault complex is likely to form for a given MVP sequence. Positive controls for the method are the experimentally determined rat (Rattus norvegicus) vault X-ray crystal structure and the purple sea urchin (Strongylocentrotus purpuratus) MVP sequence that forms experimentally observed vaults. These and two kinetoplast MVP structural homologs were predicted with high confidence value, and RosettaDock predicted that these MVP sequences would dock laterally and therefore could form oligomeric vaults. As the negative control, I-TASSER did not predict an MVP-like structure from a randomized rat MVP sequence, even when constrained to the rat MVP crystal structure (PDB:2ZUO), thus further validating the method. The protocol identified six putative homologous MVP sequences in the heterobolosean Naegleria gruberi within the excavate kingdom. Two of these sequences are predicted to be structurally similar to rat MVP, despite being in excess of 300 residues shorter. The method can be used generally to help test predictions of homology via

Elucidating the interaction of clofazimine with bovine liver catalase; a comprehensive spectroscopic and molecular docking approach.

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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.

A non-docking intraoperative electron beam applicator system

International Nuclear Information System (INIS)

Palta, J.R.; Suntharalingam, N.

1989-01-01

A non-docking intraoperative radiation therapy electron beam applicator system for a linear accelerator has been designed to minimize the mechanical, electrical, and tumor visualization problems associated with a docking system. A number of technical innovations have been used in the design of this system. These include: (a) a new intraoperative radiation therapy cone design that gives a better dose uniformity in the treatment volume at all depths; (b) a collimation system which reduces the leakage radiation dose to tissues outside the intraoperative radiation therapy cone; (c) a non-docking system with a translational accuracy of 2 mm and a rotational accuracy of 0.5 degrees; and (d) a rigid clamping system for the cones. A comprehensive set of dosimetric characteristics of the intraoperative radiation therapy applicator system is presented

Strategies for specifically directing metal functionalization of protein nanotubes: constructing protein coated silver nanowires

International Nuclear Information System (INIS)

Carreño-Fuentes, Liliana; Palomares, Laura A; Ramírez, Octavio T; Ascencio, Jorge A; Medina, Ariosto; Aguila, Sergio

2013-01-01

Biological molecules that self-assemble in the nanoscale range are useful multifunctional materials. Rotavirus VP6 protein self-assembles into tubular structures in the absence of other rotavirus proteins. Here, we present strategies for selectively directing metal functionalization to the lumen of VP6 nanotubes. The specific in situ metal reduction in the inner surface of nanotube walls was achieved by the simple modification of a method previously reported to functionalize the nanotube outer surface. Silver nanorods and nanowires as long as 1.5 μm were formed inside the nanotubes by coalescence of nanoparticles. Such one-dimensional structures were longer than others previously obtained using bioscaffolds. The interactions between silver ions and the nanotube were simulated to understand the conditions that allowed nanowire formation. Molecular docking showed that a naturally occurring arrangement of aspartate residues enabled the stabilization of silver ions on the internal surface of the VP6 nanotubes. This is the first time that such a spatial arrangement has been proposed for the nucleation of silver nanoparticles, opening the possibility of using such an array to direct functionalization of other biomolecules. These results demonstrate the natural capabilities of VP6 nanotubes to function as a versatile biotemplate for nanomaterials. (paper)

Reverse screening methods to search for the protein targets of chemopreventive compounds

Science.gov (United States)

Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan

2018-05-01

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and

Activated Cdc42 kinase regulates Dock localization in male germ cells during Drosophila spermatogenesis.

Science.gov (United States)

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.

"Flexible Ligand Docking Studies of Matrix Metalloproteinase Inhibitors Using Lamarckian Genetic Algorithm "

Directory of Open Access Journals (Sweden)

lOrkideh Ghorban Dadrass

2004-06-01

Full Text Available As important therapeutic drug targets, matrix metalloproteinases (MMPs have recently attracted great interest in the search for potent and selective inhibitors using computer-aided molecular modelling and docking techniques. Availability of more than 60 X-ray crystal structures or NMR solution structures related to MMPs in Protein Data Bank (PDB of which more than half of them are in complex with various MMP inhibitors (MMPIs, provides a great opportunity for docking studies. In this study AutoDock 3.0.5 along with its LGA algorithm were used for automated flexible ligand docking of 32 MMPI-MMP complexes and docking accuracy and reliability of the estimated inhibition constants were evaluated. Twenty-six out of 32 docks had RMSD less than 3.0 Å which is considered as well-docked, however, for the most of the cases (15 out of 27, predicted pKi values were considerably overestimated in comparison to experimental values. To improve pKi prediction regarding MMPI-MMP complexes, inclusion of at least one such a complex in calibration of empirical free energy function in the next release of AutoDock is highly recommended.

Caffeine and sulfadiazine interact differently with human serum albumin: A combined fluorescence and molecular docking study

Science.gov (United States)

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.

Coarse-grain modelling of protein-protein interactions

NARCIS (Netherlands)

Baaden, Marc; Marrink, Siewert J.

2013-01-01

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

Reduced expression of exocytotic proteins caused by anti-cholinesterase pesticides in Brachionus calyciflorus (Rotifera: Monogononta

Directory of Open Access Journals (Sweden)

IA Pérez-Legaspi

Full Text Available AbstractThe organophosphate and carbamate pesticides methyl-parathion and carbaryl have a common action mechanism: they inhibit acetylcholinesterase enzyme by blocking the transmission of nerve impulses. However, they can alter the expression of exocytotic membrane proteins (SNARE, by modifying release of neurotransmitters and other substances. This study evaluated the adverse effects of the pesticides methyl-parathion and carbaryl on expression of SNARE proteins: Syntaxin-1, Syntaxin-4 and SNAP-23 in freshwater rotifer Brachionus calyciflorus. Protein expression of these three proteins was analyzed before and after exposure to these two pesticides by Western Blot. The expression of Syntaxin-1, Syntaxin-4 and SNAP-23 proteins in B. calyciflorussignificantly decreases with increasing concentration of either pesticides. This suggests that organophosphates and carbamates have adverse effects on expression of membrane proteins of exocytosis by altering the recognition, docking and fusion of presynaptic and vesicular membranes involved in exocytosis of neurotransmitters. Our results demonstrate that the neurotoxic effect of anticholinesterase pesticides influences the interaction of syntaxins and SNAP-25 and the proper assembly of the SNARE complex.

Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

Science.gov (United States)

He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

2009-12-31

We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

Enhanced plastic deformations of nanofibrillated cellulose film by adsorbed moisture and protein-mediated interactions.

Science.gov (United States)

Malho, Jani-Markus; Ouellet-Plamondon, Claudiane; Rüggeberg, Markus; Laaksonen, Päivi; Ikkala, Olli; Burgert, Ingo; Linder, Markus B

2015-01-12

Biological composites are typically based on an adhesive matrix that interlocks rigid reinforcing elements in fiber composite or brick-and-mortar assemblies. In nature, the adhesive matrix is often made up of proteins, which are also interesting model systems, as they are unique among polymers in that we know how to engineer their structures with atomic detail and to select protein elements for specific interactions with other components. Here we studied how fusion proteins that consist of cellulose binding proteins linked to proteins that show a natural tendency to form multimer complexes act as an adhesive matrix in combination with nanofibrillated cellulose. We found that the fusion proteins are retained with the cellulose and that the proteins mainly affect the plastic yield behavior of the cellulose material as a function of water content. Interestingly, the proteins increased the moisture absorption of the composite, but the well-known plastifying effect of water was clearly decreased. The work helps to understand the functional basis of nanocellulose composites as materials and aims toward building model systems for molecular biomimetic materials.

Coevolution study of mitochondria respiratory chain proteins: toward the understanding of protein--protein interaction.

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Yang, Ming; Ge, Yan; Wu, Jiayan; Xiao, Jingfa; Yu, Jun

2011-05-20

Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein--protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein--protein interaction in intra-complex and the binary protein--protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 × 10(-6)). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein--protein interaction. Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study. Copyright © 2011. Published by Elsevier Ltd.