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PubMedDate not supplied

Impact of scoring functions on enrichment in docking-based virtual screening: an application study on renin inhibitors.

The docking program LigandFit/Cerius(2) has been used to perform shape-based virtual screening of databases against the aspartic protease renin, a target of determined three-dimensional structure. The protein structure was used in the induced fit binding conformation that occurs when renin is bound to the highly active renin inhibitor 1 (IC(50) = 2 nM). The scoring was calculated using several different scoring functions in order to get insight into the predictability of the magnitude of binding interactions. A database of 1000 diverse and druglike compounds, comprised of 990 members of a virtual database generated by using the iLib diverse software and 10 known active renin inhibitors, was docked flexibly and scored to determine appropriate scoring functions. All seven scoring functions used (LigScore1, LigScore2, PLP1, PLP2, JAIN, PMF, LUDI) were able to retrieve at least 50% of the active compounds within the first 20% (200 molecules) of the entire test database. A hit rate of 90% in the top 1.4% resulted using the quadruple consensus scoring of LigScore2, PLP1, PLP2, and JAIN. Additionally, a focused database was created with the iLib diverse software and used for the same procedure as the test database. Docking and scoring of the 990 focused compounds and the 10 known actives were performed. A hit rate of 100% in the top 8.4% resulted with use of the triple consensus scoring of PLP1, PLP2, and PMF. As expected, a ranking of the known active compounds within the focused database compared to the test database was observed. Adequate virtual screening conditions were derived empirically. They can be used for proximate docking and scoring application of compounds with putative renin inhibiting potency.

Ligands↗
PubMedDate not supplied

Comparing ligand interactions with multiple receptors via serial docking.

Standard uses of ligand-receptor docking typically focus on the association of candidate ligands with a single targeted receptor, but actual applications increasingly require comparisons across multiple receptors. This study demonstrates that comparative docking to multiple receptors can help to select homology models for virtual compound screening and to discover ligands that bind to one set of receptors but not to another, potentially similar, set. A serial docking algorithm is furthermore described that reduces the computational costs of such calculations by testing compounds against a series of receptor structures and discarding a compound as soon as it fails to satisfy specified bind/no bind criteria for each receptor. The algorithm also realizes substantial efficiencies by taking advantage of the fact that a ligand typically binds in similar conformations to similar receptors. Thus, once detailed docking has been used to fit a ligand into the first of a series of similar receptors, much less extensive calculations can be used for the remaining structures.

Algorithms↗
PubMedDate not supplied

Improved FlexX docking using FlexS-determined base fragment placement.

We report on a novel hybrid FlexX/FlexS docking approach, whereby the base fragment of the test ligand is chosen by FlexS superposition onto a cocrystallized template ligand and then fed into FlexX for the incremental construction of the final solution. The new approach is tested on the diverse 200 protein-ligand complex dataset that has been previously described for FlexX validation. In total, 62.9% of the complexes can be reproduced at rank 1 by our approach, which compares favorably with 46.9% when using FlexX alone. In addition, we report "cross-docking" experiments in which several receptor structures of complexes with identical proteins have been used for docking all cocrystallized ligands of these complexes. The results show that, in almost all cases, the hybrid approach can acceptably dock a ligand into a foreign receptor structure using a different ligand template, can give solutions where FlexX alone fails, and tends to give solutions that are more accurately positioned.

Algorithms↗
PubMedDate not supplied

Retrospective docking study of PDE4B ligands and an analysis of the behavior of selected scoring functions.

Scoring forms a major obstacle to the success of any docking study. In general, fast scoring functions perform poorly when used to determine the relative affinity of ligands for their receptors. In this study, the objective was not to rank compounds with confidence but simply to identify a scoring method which could provide a 4-fold hit enrichment in a screening sample over random selection. To this end, LigandFit, a fast shape matching docking algorithm, was used to dock a variety of known inhibitors of type 4 phosphodiesterase (PDE4B) into its binding site determined crystallographically for a series of pyrazolopyridine inhibitors. The success of identifying good poses with this technique was explored through RMSD comparisons with 19 known inhibitors for which crystallographic structures were available. The effectiveness of five scoring functions (PMF, JAIN, PLP2, LigScore2, and DockScore) was then evaluated through consideration of the success in enriching the top ranked fractions of nine artificial databases, constructed by seeding 1980 inactive ligands (pIC50 < 5) with 20 randomly selected inhibitors (pIC50 > 6.5). PMF and JAIN showed high average enrichment factors (greater than 4 times) in the top 5-10% of the ranked databases. Rank-based consensus scoring was then investigated, and the rational combination of 3 scoring functions resulted in more robust scoring schemes with (cScore)-DPmJ (consensus score of DockScore, PMF, and JAIN) and (cScore)-PPmJ (PLP2, PMF, and JAIN) yielding particularly good results. These cScores are believed to be of greater general application. Finally, the analysis of the behavior of the scoring functions across different chemotypes uncovered the inherent bias of the docking and scoring toward compounds in the same structural family as that employed for the crystal structure, suggesting the need to use multiple versions of the binding site for more successful virtual screening strategies.

3',5'-Cyclic-AMP Phosphodiesterases↗
PubMedDate not supplied

A comparative study on the application of hierarchical-agglomerative clustering approaches to organize outputs of reiterated docking runs.

Reiterated runs of standard docking protocols usually provide a collection of possible binding modes rather than pinpoint a single solution. Usually, this ensemble is then ranked by means of an energy-based scoring function. However, since many degrees of approximation have to be introduced in the computation of the binding free energy, scoring functions cannot always rank the experimental pose among the top scorers. Cluster analysis might help to overcome this limit, provided that data clusterability has been earlier assessed. In this paper, first, we present a modified version of a test earlier developed by Hopkins to assess whether or not docking outputs show the natural tendency to be grouped in clusters. Then, we report the results of a comparative study on the application of different hierarchical-agglomerative cluster rules to partition docking outputs. The rule that was able to best manage the observed data was finally applied to the whole ensemble of poses collected from several docking tools. The combination of the average linkage rule with the cutting function developed by Sutcliffe and co-workers turned out to be an approach that meets all of the criteria required for a robust clustering protocol. Furthermore, a consensus clustering allowed us to identify the pose closest to the experimental one within a statistically significant cluster, whose number was always of few units.

Adenine↗
PubMed2002

Dynamic docking and electron transfer between Zn-myoglobin and cytochrome b(5).

We present a broad study of the effect of neutralizing the two negative charges of the Mb propionates on the interaction and electron transfer (ET) between horse Mb and bovine cyt b(5), through use of Zn-substituted Mb (ZnMb, 1) to study the photoinitiated reaction, ((3)ZnP)Mb + Fe(3+)cyt b(5) --> (ZnP)(+)Mb + Fe(2+)cyt b(5). The charge neutralization has been carried out both by replacing the Mb heme with zinc-deuteroporphyrin dimethylester (ZnMb(dme), 2), which replaces the charges by small neutral hydrophobic patches, and also by replacement with the newly prepared zinc-deuteroporphyrin diamide (ZnMb(diamide), 3), which converts the charged groups to neutral, hydrophilic ones. The effect of propionate neutralization on the conformation of the zinc-porphyrin in the Mb heme pocket has been studied by multinuclear NMR with an (15)N labeled zinc porphyrin derivative (ZnMb((15)N-diamide), 4). The rates of photoinitiated ET between the Mb's (1-3) and cyt b(5) have been measured over a range of pH values and ionic strengths. Isothermal titration calorimetry (ITC) and NMR methods have been used to independently investigate the effect of charge neutralization on Mb/b(5) binding. The neutralization of the two heme propionates of ZnMb by formation of the heme diester or, for the first time, the diamide increases the second-order rate constant of the ET reaction between ZnMb and cyt b(5) by as much as several 100-fold, depending on pH and ionic strength, while causing negligible changes in binding affinity. Brownian dynamic (BD) simulations and ET pathway calculations provide insight into the protein docking and ET process. The results support a new "dynamic docking" paradigm for protein-protein reactions in which numerous weakly bound conformations of the docked complex contribute to the binding of cyt b(5) to Mb and Hb, but only a very small subset of these are ET active, and this subset does not include the conformations most favorable for binding; the Mb surface is a large "target" with a small "bullseye" for the cyt b(5) "arrow". This paradigm differs sharply from the more familiar, "simple" docking within a single, or narrow range of conformations, where binding strength and ET reactivity increase in parallel. Likewise, it is distinct from, although complementary to, the well-known picture of conformational control of ET through "gating", or a related picture of "conformational coupling". The new model describes situations in which tight binding does not correlate with efficient ET reactivity, and explains how it is possible to modulate reactivity without changing affinity. Such "decoupling" of reactivity from binding clearly is of physiological relevance for the reduction of met-Mb in muscle and of met-Hb in a red cell, where tight binding of cyt b(5) to the high concentration of ferrous-Mb/Hb would prevent the cytochrome from finding and reducing the oxidized proteins; it likely is of physiological relevance in other situations, as well.

Animals↗
PubMed2005

Flexible docking in solution using metadynamics.

We apply our recently developed metadynamics method to the docking of ligands on flexible receptors in water solution. This method mimics the real dynamics of a ligand exiting or entering an enzyme and in so doing reconstructs the free energy surface. We apply it to four docking cases: beta-trypsin/benzamidine, beta-trypsin/chlorobenzamidine, immunoglobulin McPC-603/phosphocholine, and cyclin-dependent kinase 2/staurosporine. In every case studied, the method is able to predict the docked geometry and the free energy of docking. Its added value with respect to many other available methods is that it reconstructs the complete free energy surface, including all the relevant minima and the barriers between them.

Benzamidines↗
PubMed2006

Predicting substrates by docking high-energy intermediates to enzyme structures.

With the emergence of sequences and even structures for proteins of unknown function, structure-based prediction of enzyme activity has become a pragmatic as well as an interesting question. Here we investigate a method to predict substrates for enzymes of known structure by docking high-energy intermediate forms of the potential substrates. A database of such high-energy transition-state analogues was created from the KEGG metabolites. To reduce the number of possible reactions to consider, we restricted ourselves to enzymes of the amidohydrolase superfamily. We docked each metabolite into seven different amidohydrolases in both the ground-state and the high-energy intermediate forms. Docking the high-energy intermediates improved the discrimination between decoys and substrates significantly over the corresponding standard ground-state database, both by enrichment of the true substrates and by geometric fidelity. To test this method prospectively, we attempted to predict the enantioselectivity of a set of chiral substrates for phosphotriesterase, for both wild-type and mutant forms of this enzyme. The stereoselectivity ratios of the six enzymes considered for those four substrate enantiomer pairs differed over a range of 10- to 10,000-fold and underwent 20 switches in stereoselectivities for favored enantiomers, compared to the wild type. The docking of the high-energy intermediates correctly predicted the stereoselectivities for 18 of the 20 substrate/enzyme combinations when compared to subsequent experimental synthesis and testing. The possible applications of this approach to other enzymes are considered.

Algorithms↗
PubMed2004

Multiple active site corrections for docking and virtual screening.

Several docking programs are now available that can reproduce the bound conformation of a ligand in an active site, for a wide variety of experimentally determined complexes. However, these programs generally perform less well at ranking multiple possible ligands in one site. Since accurate identification of potential ligands is a prerequisite for many aspects of structure-based drug design, this is a serious limitation. We have tested the ability of two docking programs, FlexX and Gold, to match ligands and active sites for multiple complexes. We show that none of the docking scores from either program are able to match consistently ligands and active sites in our tests. We propose a simple statistical correction, the multiple active site correction (MASC), which greatly ameliorates this problem. We have also tested the correction method against an extended set of 63 cocrystals and in a virtual screening experiment. In all cases, MASC significantly improves the results of the docking experiments.

Binding Sites↗
PubMed2005

Binding mode prediction of cytochrome p450 and thymidine kinase protein-ligand complexes by consideration of water and rescoring in automated docking.

The popular docking programs AutoDock, FlexX, and GOLD were used to predict binding modes of ligands in crystallographic complexes including X-ray water molecules or computationally predicted water molecules. Isoenzymes of two different enzyme systems were used, namely cytochromes P450 (n = 19) and thymidine kinases (n = 19) and three different "water" scenarios: i.e., docking (i) into water-free active sites, (ii) into active sites containing crystallographic water molecules, and (iii) into active sites containing water molecules predicted by a novel approach based on the program GRID. Docking accuracies were determined in terms of the root-mean-square deviation (RMSD) accuracy and, newly defined, in terms of the ligand catalytic site prediction (CSP) accuracy. Consideration of both X-ray and predicted water molecules and the subsequent pooling and rescoring of all solutions (generated by all three docking programs) with the SCORE scoring function significantly improved the quality of prediction of the binding modes both in terms of RMSD and CSP accuracy.

Catalytic Domain↗
PubMed2005

Comparison of automated docking programs as virtual screening tools.

The performance of several commercially available docking programs is compared in the context of virtual screening. Five different protein targets are used, each with several known ligands. The simulated screening deck comprised 1000 molecules from a cleansed version of the MDL drug data report and 49 known ligands. For many of the known ligands, crystal structures of the relevant protein-ligand complexes were available. We attempted to run experiments with each docking method that were as similar as possible. For a given docking method, hit rates were improved versus what would be expected for random selection for most protein targets. However, the ability to prioritize known ligands on the basis of docking poses that resemble known crystal structures is both method- and target-dependent.

Binding Sites↗
PubMed2006

Benchmarking sets for molecular docking.

Ligand enrichment among top-ranking hits is a key metric of molecular docking. To avoid bias, decoys should resemble ligands physically, so that enrichment is not simply a separation of gross features, yet be chemically distinct from them, so that they are unlikely to be binders. We have assembled a directory of useful decoys (DUD), with 2950 ligands for 40 different targets. Every ligand has 36 decoy molecules that are physically similar but topologically distinct, leading to a database of 98,266 compounds. For most targets, enrichment was at least half a log better with uncorrected databases such as the MDDR than with DUD, evidence of bias in the former. These calculations also allowed 40x40 cross-docking, where the enrichments of each ligand set could be compared for all 40 targets, enabling a specificity metric for the docking screens. DUD is freely available online as a benchmarking set for docking at http://blaster.docking.org/dud/.

Adenosine Deaminase↗
PubMed2006

Automatic and efficient decomposition of two-dimensional structures of small molecules for fragment-based high-throughput docking.

The computer program DAIM (Decomposition and Identification of Molecules) has been developed to automatically break up compounds in small-molecule libraries for fragment-based docking as well as database analysis. Here, DAIM is evaluated on 130 ligands derived from known crystal structures of ligand-protein complexes. The decomposition and a new fingerprint-based identification technique are used to select anchor fragments for docking. The docking results show that the DAIM selection is superior to size-based or random selection of fragments. To evaluate the usefulness for analyzing the fragment composition of a large library, DAIM is applied to a collection of about 1.85 million commercially available compounds. Interestingly, it is found that the set of most frequent cyclic and acyclic fragments originating from the decomposition of the 1.85 million molecules shows a large overlap with the most frequent fragments in a library of 5120 known drugs. DAIM has been successfully used in the in silico screening for inhibitors of beta-secretase and EphB4 kinase by fragment-based high-throughput docking. Possible future applications for de novo ligand design are briefly discussed.

Amyloid Precursor Protein Secretases↗
PubMed1998

Conformational analysis and automated receptor docking of selective arylacetamide-based kappa-opioid agonists.

The three-dimensional structure, dynamics, and binding modes of representative kappa-opioid agonists of the arylacetamide class (U50, 488; U69,593; U62,066; CI-977; ICI199,441; ICI197,067; BRL52,537; and BRL52,656) have been investigated using molecular modeling techniques. Systematic exploration of the conformational space of the ligand combined with molecular dynamics (MD) simulations in water revealed consistent conformational preferences for all the kappa-agonists in this series. The results were further compared with available X-ray and 1D- and 2D-NMR data to identify potential "lead" conformers for molecular docking. Ligand binding modes were initially determined using automated docking of two of the ligands (U50,488 and BRL52,537) to the kappa-opioid receptor. Extrapolation of the predicted binding mode to other members in this ligand series revealed similar docking preferences, with each ligand docked along the receptor helical axis. The binding modes were further refined using MD simulations of the receptor-ligand complexes. The results show a that salt bridge is formed between the amino proton of the ligands and the carboxylate group of Asp138 in TM3. This interaction most likely serves as a key anchoring point for the agonist association. Additional ligand contacts were noted with kappa-specific residues Ile294, Leu295, and Ala298, which may, in part, explain the kappa-selectivity in this series. In comparing the arylacetamides with opiate-based ligands, no evidence was found to link these classes through a common binding motif (except for the ion pair). The binding site model was also applied to explain the enantiomeric preference of U50,488 and to provide insight to the mu/kappa-selectivity of representative ligands in this series. Overall, the results provide a structure-based rationale for ligand recognition that is consistent both with site-directed mutagenesis experiments and structure-function relationship data.

Acetamides↗
PubMed1999

The role of waters in docking strategies with incremental flexibility for carbohydrate derivatives: heat-labile enterotoxin, a multivalent test case.

Molecular docking studies of carbohydrate derivatives in protein binding sites are often challenging because of water-mediated interactions and the inherent flexibility of the many terminal hydroxyl groups. Using the recognition process between heat-labile enterotoxin from Escherichia coli and ganglioside GM1 as a paradigm, we developed a modeling protocol that includes incremental conformational flexibility of the ligand and predicted water interactions. The strategy employs a modified version of the Monte Carlo docking program AUTODOCK and water affinity potentials calculated with GRID. After calibration of the protocol on the basis of the known binding modes of galactose and lactose to the toxin, blind predictions were made for the binding modes of four galactose derivatives: lactulose, melibionic acid, thiodigalactoside, and m-nitrophenyl-alpha-galactoside. Subsequent crystal structure determinations have demonstrated that our docking strategy can predict the correct binding modes of carbohydrate derivatives within 1.0 A from experiment. In addition, it is shown that repeating the docking simulations in each of the seemingly identical binding sites of the multivalent toxin increases the chance of finding the correct binding mode.

Binding Sites↗
PubMed1999

Probing the binding of indolactam-V to protein kinase C through site-directed mutagenesis and computational docking simulations.

Protein kinase C (PKC) comprises a family of ubiquitous enzymes transducing signals by the lipophilic second messenger sn-1, 2-diacylglycerol (DAG). Teleocidin and its structurally simpler congener indolactam-V (ILV) bind to PKC with high affinity. In this paper, we report our computational docking studies on ILV binding to PKC using an automatic docking computer program, MCDOCK. In addition, we used site-directed mutagenesis to assess the quantitative contribution of crucial residues around the binding site of PKC to the binding affinity of ILV to PKC. On the basis of the docking studies, ILV binds to PKC in its cis-twist conformation and forms a number of optimal hydrogen bond interactions. In addition, the hydrophobic groups in ILV form "specific" hydrophobic interactions with side chains of a number of conserved hydrophobic residues in PKC. The predicted binding mode for ILV is entirely consistent with known structure-activity relationships and with our mutational analysis. Our mutational analysis establishes the quantitative contributions of a number of conserved residues to the binding of PKC to ILV. Taken together, our computational docking simulations and analysis by site-directed mutagenesis provide a clear understanding of the interaction between ILV and PKC and the structural basis for design of novel, high-affinity, and isozyme-selective PKC ligands.

Animals↗
PubMed1999

Automated docking of 82 N-benzylpiperidine derivatives to mouse acetylcholinesterase and comparative molecular field analysis with 'natural' alignment.

Automated docking and three-dimensional Quantitative Structure-Activity Relationship studies (3D QSAR) were performed for a series of 82 reversible, competitive and selective acetylcholinesterase (AChE) inhibitors. The suggested automated docking technique, making use of constraints taken from experimental crystallographic data, allowed to dock all the 82 substituted N-benzylpiperidines to the crystal structure of mouse AChE, because of short computational times. A 3D QSAR model was then established using the CoMFA method. In contrast to conventional CoMFA studies, the compounds were not fitted to a reference molecule but taken in their 'natural' alignment obtained by the docking study. The established and validated CoMFA model was then applied to another series of 29 N-benzylpiperidine derivatives whose AChE inhibitory activity data were measured under different experimental conditions. A good correlation between predicted and experimental activity data shows that the model can be extended to AChE inhibitory activity data measured on another acetylcholinesterase and/or at different incubation times and pH level.

Acetylcholinesterase↗
PubMed2000

Deciphering common failures in molecular docking of ligand-protein complexes.

Common failures in predicting crystal structures of ligand-protein complexes are investigated for three ligand-protein systems by a combined thermodynamic and kinetic analysis of the binding energy landscapes. Misdocked predictions in ligand-protein docking are classified as 'soft' and 'hard' failures. While a soft failure arises when the search algorithm is unable to find the global energy minimum corresponding to the crystal structure, a hard failure results from a flaw of the energy function to qualify the crystal structure as the predicted lowest energy conformation in docking simulations. We find that neither the determination of a single structure with the lowest energy nor finding the most common binding mode is sufficient to predict crystal structures of the complexes, which belong to the category of hard failures. In a proposed hierarchical approach, structural similarity clustering of the conformations, generated from equilibrium simulations with the simplified energy function, is followed by energy refinement with the AMBER force field. This protocol, that involves a hierarchy of energy functions, resolves some common failures in ligand-protein docking and detects crystallographic binding modes that were not found during docking simulations.

Crystallography↗