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PubMed2003

Packing optimization for automated generation of complex system's initial configurations for molecular dynamics and docking.

Molecular Dynamics is a powerful methodology for the comprehension at molecular level of many chemical and biochemical systems. The theories and techniques developed for structural and thermodynamic analyses are well established, and many software packages are available. However, designing starting configurations for dynamics can be cumbersome. Easily generated regular lattices can be used when simple liquids or mixtures are studied. However, for complex mixtures, polymer solutions or solid adsorbed liquids (for example) this approach is inefficient, and it turns out to be very hard to obtain an adequate coordinate file. In this article, the problem of obtaining an adequate initial configuration is treated as a "packing" problem and solved by an optimization procedure. The initial configuration is chosen in such a way that the minimum distance between atoms of different molecules is greater than a fixed tolerance. The optimization uses a well-known algorithm for box-constrained minimization. Applications are given for biomolecule solvation, many-component mixtures, and interfaces. This approach can reduce the work of designing starting configurations from days or weeks to few minutes or hours, in an automated fashion. Packing optimization is also shown to be a powerful methodology for space search in docking of small ligands to proteins. This is demonstrated by docking of the thyroid hormone to its nuclear receptor.

Journal Article↗
PubMed2004

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

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

Algorithms↗
PubMed1994

Docking of nitrogenase iron- and molybdenum-iron proteins for electron transfer and MgATP hydrolysis: the role of arginine 140 and lysine 143 of the Azotobacter vinelandii iron protein.

Docking of the nitrogenase component proteins, the iron protein (FeP) and the molybdenum-iron protein (MoFeP), is required for MgATP hydrolysis, electron transfer between the component proteins, and substrate reductions catalyzed by nitrogenase. The present work examines the function of 3 charged amino acids, Arg 140, Glu 141, and Lys 143, of the Azotobacter vinelandii FeP in nitrogenase component protein docking. The function of these amino acids was probed by changing each to the neutral amino acid glutamine using site-directed mutagenesis. The altered FePs were expressed in A. vinelandii in place of the wild-type FeP. Changing Glu 141 to Gln (E141Q) had no adverse effects on the function of nitrogenase in whole cells, indicating that this charged residue is not essential to nitrogenase function. In contrast, changing Arg 140 or Lys 143 to Gln (R140Q and K143Q) resulted in a significant decrease in nitrogenase activity, suggesting that these charged amino acid residues play an important role in some function of the FeP. The function of each amino acid was deduced by analysis of the properties of the purified R140Q and K143Q FePs. Both altered proteins were found to support reduced substrate reduction rates when coupled to wild-type MoFeP. Detailed analysis revealed that changing these residues to Gln resulted in a dramatic reduction in the affinity of the altered FeP for binding to the MoFeP. This was deduced in FeP titration, NaCl inhibition, and MoFeP protection from Fe2+ chelation experiments.(ABSTRACT TRUNCATED AT 250 WORDS)

Adenosine Triphosphate↗
PubMed2002

Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock.

Protein motion and heterogeneity of structural waters are approximated in ligand-docking simulations, using an ensemble of protein structures. Four methods of combining multiple target structures within a single grid-based lookup table of interaction energies are tested. The method is evaluated using complexes of 21 peptidomimetic inhibitors with human immunodeficiency virus type 1 (HIV-1) protease. Several of these structures show motion of an arginine residue, which is essential for binding of large inhibitors. A structural water is also present in 20 of the structures, but it must be absent in the remaining one for proper binding. Mean and minimum methods perform poorly, but two weighted average methods permit consistent and accurate ligand docking, using a single grid representation of the target protein structures.

Computer Simulation↗
PubMed2003

A protein-protein docking benchmark.

We have developed a nonredundant benchmark for testing protein-protein docking algorithms. Currently it contains 59 test cases: 22 enzyme-inhibitor complexes, 19 antibody-antigen complexes, 11 other complexes, and 7 difficult test cases. Thirty-one of the test cases, for which the unbound structures of both the receptor and ligand are available, are classified as follows: 16 enzyme-inhibitor, 5 antibody-antigen, 5 others, and 5 difficult. Such a centralized resource should benefit the docking community not only as a large curated test set but also as a common ground for comparing different algorithms. The benchmark is available at (http://zlab.bu.edu/~rong/dock/benchmark.shtml).

Algorithms↗
PubMed2003

Assessment of blind predictions of protein-protein interactions: current status of docking methods.

The current status of docking procedures for predicting protein-protein interactions starting from their three-dimensional structure is assessed from a first major evaluation of blind predictions. This evaluation was performed as part of a communitywide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Seven newly determined structures of protein-protein complexes were available as targets for this experiment. These were the complexes between a kinase and its protein substrate, between a T-cell receptor beta-chain and a superantigen, and five antigen-antibody complexes. For each target, the predictors were given the experimental structures of the free components, or of one free and one bound component in a random orientation. The structure of the complex was revealed only at the time of the evaluation. A total of 465 predictions submitted by 19 groups were evaluated. These groups used a wide range of algorithms and scoring functions, some of which were completely novel. The quality of the predicted interactions was evaluated by comparing residue-residue contacts and interface residues to those in the X-ray structures and by analyzing the fit of the ligand molecules (the smaller of the two proteins in the complex) or of interface residues only, in the predicted versus target complexes. A total of 14 groups produced predictions, ranking from acceptable to highly accurate for five of the seven targets. The use of available biochemical and biological information, and in one instance structural information, played a key role in achieving this result. It was essential for identifying the native binding modes for the five correctly predicted targets, including the kinase-substrate complex where the enzyme changes conformation on association. But it was also the cause for missing the correct solution for the two remaining unpredicted targets, which involve unexpected antigen-antibody binding modes. Overall, this analysis reveals genuine progress in docking procedures but also illustrates the remaining serious limitations and points out the need for better scoring functions and more effective ways for handling conformational flexibility.

Algorithms↗
PubMed2003

Taking geometry to its edge: fast unbound rigid (and hinge-bent) docking.

We present a very efficient rigid "unbound" soft docking methodology, which is based on detection of geometric shape complementarity, allowing liberal steric clash at the interface. The method is based on local shape feature matching, avoiding the exhaustive search of the 6D transformation space. Our experiments at CAPRI rounds 1 and 2 show that although the method does not perform an exhaustive search of the 6D transformation space, the "correct" solution is never lost. However, such a solution might rank low for large proteins, because there are alternatives with significantly larger geometrically compatible interfaces. In many cases this problem can be resolved by successful a priori focusing on the vicinity of potential binding sites as well as the extension of the technique to flexible (hinge-bent) docking. This is demonstrated in the experiments performed as a lesson from our CAPRI experience.

Algorithms↗
PubMed2003

RDOCK: refinement of rigid-body protein docking predictions.

We present a simple and effective algorithm RDOCK for refining unbound predictions generated by a rigid-body docking algorithm ZDOCK, which has been developed earlier by our group. The main component of RDOCK is a three-stage energy minimization scheme, followed by the evaluation of electrostatic and desolvation energies. Ionic side chains are kept neutral in the first two stages of minimization, and reverted to their full charge states in the last stage of brief minimization. Without side chain conformational search or filtering/clustering of resulting structures, RDOCK represents the simplest approach toward refining unbound docking predictions. Despite its simplicity, RDOCK makes substantial improvement upon the top predictions by ZDOCK with all three scoring functions and the improvement is observed across all three categories of test cases in a large benchmark of 49 non-redundant unbound test cases. RDOCK makes the most powerful combination with ZDOCK2.1, which uses pairwise shape complementarity as the scoring function. Collectively, they rank a near-native structure as the number-one prediction for 18 test cases (37% of the benchmark), and within the top 4 predictions for 24 test cases (49% of the benchmark). To various degrees, funnel-like energy landscapes are observed for these 24 test cases. To the best of our knowledge, this is the first report of binding funnels starting from global searches for a broad range of test cases. These results are particularly exciting, given that we have not used any biological information that is specific to individual test cases and the whole process is entirely automated. Among three categories of test cases, the best results are seen for enzyme/inhibitor, with a near-native structure ranked as the number-one prediction for 48% test cases, and within the top 10 predictions for 78% test cases. RDOCK is freely available to academic users at http://zlab.bu.edu/ approximately rong/dock.

Algorithms↗
PubMed2003

Construction of molecular assemblies via docking: modeling of tetramers with D2 symmetry.

Comparative modeling methods are commonly used to construct models of homologous proteins or oligomers. However, comparative modeling may be inapplicable when the number of subunits in a modeled oligomer is different than in the modeling template. Thus, a dimer cannot be a template for a tetramer because a new monomer-monomer interface must be predicted. We present in this study a new prediction approach, which combines protein-protein docking with either of two tetramer-forming algorithms designed to predict the structures of tetramers with D2 symmetry. Both algorithms impose symmetry constraints. However, one of them requires identification of two of the C2 dimers within the tetramer in the docking step, whereas the other, less demanding algorithm, requires identification of only one such dimer. Starting from the structure of one subunit, the procedures successfully reconstructed 16 known D2 tetramers, which crystallize with either a monomer, a dimer or a tetramer in the asymmetric unit. In some cases we obtained clusters of native-like tetramers that differ in the relative rotation of the two identical dimers within the tetramer. The predicted structural pliability for concanavalin-A, phosphofructokinase, and fructose-1,6-bisphosphatase agrees semiquantitatively with the observed differences between the several experimental structures of these tetramers. Hence, our procedure identifies a structural soft-mode that allows regulation via relative rigid-body movements of the dimers within these tetramers. The algorithm also predicted three nearly correct tetramers from model structures of single subunits, which were constructed by comparative modeling from subunits of homologous tetrameric, dimeric, or hexameric systems.

Algorithms↗
PubMed2004

Docking studies and model development of tea polyphenol proteasome inhibitors: applications to rational drug design.

Previously, we demonstrated that natural and synthetic ester bond-containing green tea polyphenols were potent and specific non-peptide proteasome inhibitors. However, the molecular mechanism of inhibition is currently unknown. Here, we report that inhibition of the chymotrypsin activity of the 20S proteasome by (-)-epigallocatechin-3-gallate (EGCG) is time-dependent and irreversible, implicating acylation of the beta5-subunit's catalytic N-terminal threonine (Thr 1). This knowledge is used, along with in silico docking experiments, to aid in the understanding of binding and inhibition. On the basis of these docking experiments, we propose that (-)-EGCG binds the chymotrypsin site in an orientation and conformation that is suitable for a nucleophilic attack by Thr 1. Consistently, the distance from the electrophilic carbonyl carbon of (-)-EGCG to the hydroxyl group of Thr 1 was measured as 3.18 A. Furthermore, the A ring of (-)-EGCG acts as a tyrosine mimic, binding to the hydrophobic S1 pocket of the beta5-subunit. In the process, the (-)-EGCG scissile bond may become strained, which could lower the activation energy for attack by the hydroxyl group of Thr 1. This model is validated by comparison of predicted and actual activities of several EGCG analogs, either naturally occurring, previously synthesized, or rationally synthesized.

Amides↗
PubMed2001

Protein docking using a genetic algorithm.

A genetic algorithm (GA) for protein-protein docking is described, in which the proteins are represented by dot surfaces calculated using the Connolly program. The GA is used to move the surface of one protein relative to the other to locate the area of greatest surface complementarity between the two. Surface dots are deemed complementary if their normals are opposed, their Connolly shape type is complementary, and their hydrogen bonding or hydrophobic potential is fulfilled. Overlap of the protein interiors is penalized. The GA is tested on 34 large protein-protein complexes where one or both proteins has been crystallized separately. Parameters are established for which 30 of the complexes have at least one near-native solution ranked in the top 100. We have also successfully reassembled a 1,400-residue heptamer based on the top-ranking GA solution obtained when docking two bound subunits.

Algorithms↗
PubMed2004

Apolipoprotein E-low density lipoprotein receptor binding: study of protein-protein interaction in rationally selected docked complexes.

Apolipoprotein E (apoE) is an important protein involved in lipid metabolism due to its interaction with members of the low-density lipoprotein receptor (LDLR) family. To further understand the molecular basis for this receptor-binding activity, an apoE fragment containing the receptor binding region (residues 135-151) was docked onto the fifth LDLR ligand binding repeat (LR5) by computational methods. A subset of structures generated by the docking was rationally selected on the grounds of experimental data combined with modeling and was used for further analysis. The application and comparison of two different experimental structures for the apoE fragment underlines the local structural changes occurring in apoE when switching from a receptor-inactive to a receptor-active conformation. The body of interactions occurring at the interface between the two proteins is in very good agreement with the biochemical data available for both apoE and LDLR. Charged residues are involved in numerous ionic interactions and might therefore be important for the specificity of the interaction between apoE and LR5. In addition, the interface also features a tryptophan and a stacking of histidine residues, revealing that the association between the two proteins is not entirely governed by ionic interactions. In particular, the presence of histidine residues in the interface gives a structural basis for the pH-regulated release mechanism of apoE in the endosomes. The proposed molecular basis for apoE binding to LDLR could aid the design of strategies for targeting alterations in lipid transport and metabolism.

Apolipoproteins E↗
PubMed2004

Saturation transfer difference (STD) 1H-NMR experiments and in silico docking experiments to probe the binding of N-acetylneuraminic acid and derivatives to Vibrio cholerae sialidase.

Saturation transfer difference (STD) (1)H NMR experiments were used to probe the epitope binding characteristics of the sialidase [EC 3.2.1.18] from the bacterium Vibrio cholerae, the causative agent of cholera. Binding preferences were investigated for N-acetylneuraminic acid (Neu5Ac, 1), the product of the sialidase catalytic reaction, for the known sialidase inhibitor 5-acetamido-2,6-anhydro-3,5-dideoxy-D-glycero-D-galacto-non-2-enoic acid (Neu5Ac2en, 2), and for the uronic acid-based Neu5Ac2en mimetic iso-propyl 2-acetamido-2,4-dideoxy-alpha-L-threo-hex-4-enopyranosiduronic acid (3), in which the native glycerol side-chain of Neu5Ac2en is replaced with an O-iso-propyl ether. The STD experiments provided evidence, supporting previous studies, that Neu5Ac (1) binds to the sialidase as the alpha-anomer. Docking experiments using DOCK (version 4.0.1) revealed further information regarding the binding characteristics of the enzyme active site in complex with Neu5Ac2en (2) and the Neu5Ac2en mimetic (3), indicating an expected dominant interaction of the acetamide moiety with the protein.

Acetamides↗
PubMed2004

Towards a MIP-based alignment and docking in computer-aided drug design.

Structural alignment of ligands in their biological conformation is a crucial step in the building of pharmacophoric models in structure-based drug design. In addition, docking algorithms are limited in some cases by the quality of the scoring functions and the limited flexibility of the environment that the different programs allow. On the other hand, GRID molecular interaction potentials (MIPs) have been used for a long time in 3D-QSAR studies. However, in most of these studies the alignment of the molecules is performed on the basis of geometrical or physico-chemical criteria that differ from the MIPs used in the partial least squares statistical analysis. We have previously developed a method to use the same scoring function for the molecular alignment and for 3D-QSAR studies. This methodology, based on the use of GRID potentials, consists in the weighted averaging of similarities of the relevant MIPs of the molecules to be aligned. Here we present a method to obtain the weights for the different GRID probes in the average based on the structural information on protein-ligand complexes for relevant systems. The method, implemented in MIPSIM, is shown to yield good accuracy in the prediction of the alignments for two systems: a set of three inhibitors of dihydrofolate reductase and a set of fifteen non-nucleoside HIV-1 reverse transcriptase inhibitors (NNRTIs). The smooth GRID potentials are shown to capture the flexible character of the active site, as opposed to traditional docking scoring energy functions.

Binding Sites↗
PubMed2005

How does nitrous oxide reductase interact with its electron donors?--A docking study.

Electron transfer reactions are crucial for respiration and denitrification. In this article, we analyze the interaction of nitrous oxide reductase with its electron donors cytochrome c550 and pseudoazurin. Our docking protocol comprises generation of candidate complexes followed by a selection step based on the distance of the donor and acceptor groups in each partner protein. Finally, the structures of the candidate complexes were optimized using a force field calculation, together with a second distance filtering step. The prediction power of this protocol was studied using the crystal structure of the cytochrome c2/photosynthetic reaction center of Rhodobacter sphaeroides as a reference. The results suggest that both cytochrome c550 and pseudoazurin bind at the same hydrophobic surface patch residing near the CuA center of nitrous oxide reductase. The central, well-conserved interaction surface of the donors is hydrophobic, but it is surrounded by numerous lysine side-chains, which interact electrostatically with analogously positioned side-chain carboxylates of the acceptor. The prediction output is an ensemble of energetically similar structures that are rotationally related to each other. While such an ensemble may reflect incomplete prediction power of the docking protocol, it may also manifest a biological situation where there are multiple ways of forming a productive electron transfer complex. Analyses of the predicted structures and the conservation pattern of the amino acid residues suggest the existence of specific electron transfer pathways to and from the CuA center of nitrous oxide reductase.

Azurin↗
PubMed2005

Virtual screening to enrich a compound collection with CDK2 inhibitors using docking, scoring, and composite scoring models.

Docking programs can generate subsets of a compound collection with an increased percentage of actives against a target (enrichment) by predicting their binding mode (pose) and affinity (score), and retrieving those with the highest scores. Using the QXP and GOLD programs, we compared the ability of six single scoring functions (PLP, Ligscore, Ludi, Jain, ChemScore, PMF) and four composite scoring models (Mean Rank: MR, Rank-by-Vote: Vt, Bayesian Statistics: BS and PLS Discriminant Analysis: DA) to separate compounds that are active against CDK2 from inactives. We determined the enrichment for the entire set of actives (IC50 < 10 microM) and for three activity subsets. In all cases, the enrichment for each subset was lower than for the entire set of actives. QXP outperformed GOLD at pose prediction, but yielded only moderately better enrichments. Five to six scoring functions yielded good enrichments with GOLD poses, while typically only two worked well with QXP poses. For each program, two scoring functions generally performed better than the others (Ligscore2 and Ludi for GOLD; QXP and Jain for QXP). Composite scoring functions yielded better results than single scoring functions. The consensus approaches MR and Vt worked best when separating micromolar inhibitors from inactives. The statistical approaches BS and DA, which require training data, performed best when distinguishing between low and high nanomolar inhibitors. The key observation that all hit rate profiles for all four activity intervals for all scoring schemes for both programs are significantly better than random, is evidence that docking can be successfully applied to enrich compound collections.

Adenosine Triphosphate↗
PubMed2005

Protein-Protein Docking Benchmark 2.0: an update.

We present a new version of the Protein-Protein Docking Benchmark, reconstructed from the bottom up to include more complexes, particularly focusing on more unbound-unbound test cases. SCOP (Structural Classification of Proteins) was used to assess redundancy between the complexes in this version. The new benchmark consists of 72 unbound-unbound cases, with 52 rigid-body cases, 13 medium-difficulty cases, and 7 high-difficulty cases with substantial conformational change. In addition, we retained 12 antibody-antigen test cases with the antibody structure in the bound form. The new benchmark provides a platform for evaluating the progress of docking methods on a wide variety of targets. The new version of the benchmark is available to the public at http://zlab.bu.edu/benchmark2.

Algorithms↗
PubMed2005

Scoring docking models with evolutionary information.

We have developed methods for the extraction of evolutionary information from multiple sequence alignments for use in the study of the evolution of protein interaction networks and in the prediction of protein interaction. For Rounds 3, 4, and 5 of the CAPRI experiment, we used scores derived from the analysis of multiple sequence alignments to submit predictions for 7 of the 12 targets. Our docking models were generated with Hex and GRAMM, but all our predictions were selected using methods based on multiple sequence alignments and on the available experimental evidence. With this approach, we were able to predict acceptable level models for 4 of the targets, and for a fifth target, we located the residues involved in the binding surface. Here we detail our successes and highlight several of the limitations and problems that we faced while dealing with particular docking cases.

Algorithms↗