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ABSTRACT: The root-mean-squared deviation (rmsd) is a widely used measure of distance between two aligned objects -- often chemical structures. However, rmsd has a number of known limitations including difficulty of interpretation, no limit on weighting for any portion of the alignment, and a lack of normalization. In this work, a Generally Applicable Replacement for rmsD (GARD) is proposed. In this implementation atomic contributions are weighted by their relative importance to binding, as determined statistically by Andrews et al. (1) , and as such this method is 'chemically aware'. This novel measure is normalized and does not have many of the failings of traditional rmsd. It is, thus, perfectly suited for a wide variety of uses, including the assessment of the quality of poses produced from molecular docking programs and the comparison of conformers. Rmsd and GARD are compared in their ability to assess docking software and multiple examples of the use of GARD to rescue essentially correct poses with a high rmsd are presented.
Journal of Chemical Information and Modeling 08/2009; 49(8):1889-900. · 4.68 Impact Factor
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ABSTRACT: Molecular docking programs are widely used modeling tools for predicting ligand binding modes and structure based virtual screening. In this study, six molecular docking programs (DOCK, FlexX, GLIDE, ICM, PhDOCK, and Surflex) were evaluated using metrics intended to assess docking pose and virtual screening accuracy. Cognate ligand docking to 68 diverse, high-resolution X-ray complexes revealed that ICM, GLIDE, and Surflex generated ligand poses close to the X-ray conformation more often than the other docking programs. GLIDE and Surflex also outperformed the other docking programs when used for virtual screening, based on mean ROC AUC and ROC enrichment values obtained for the 40 protein targets in the Directory of Useful Decoys (DUD). Further analysis uncovered general trends in accuracy that are specific for particular protein families. Modifying basic parameters in the software was shown to have a significant effect on docking and virtual screening results, suggesting that expert knowledge is critical for optimizing the accuracy of these methods.
Journal of Chemical Information and Modeling 07/2009; 49(6):1455-74. · 4.68 Impact Factor
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ABSTRACT: Target-based virtual screening is increasingly used to generate leads for targets for which high quality three-dimensional (3D) structures are available. To allow large molecular databases to be screened rapidly, a tiered scoring scheme is often employed whereby a simple scoring function is used as a fast filter of the entire database and a more rigorous and time-consuming scoring function is used to rescore the top hits to produce the final list of ranked compounds. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approaches are currently thought to be quite effective at incorporating implicit solvation into the estimation of ligand binding free energies. In this paper, the ability of a high-throughput MM-PBSA rescoring function to discriminate between correct and incorrect docking poses is investigated in detail. Various initial scoring functions are used to generate docked poses for a subset of the CCDC/Astex test set and to dock one set of actives/inactives from the DUD data set. The effectiveness of each of these initial scoring functions is discussed. Overall, the ability of the MM-PBSA rescoring function to (i) regenerate the set of X-ray complexes when docking the bound conformation of the ligand, (ii) regenerate the X-ray complexes when docking conformationally expanded databases for each ligand which include "conformation decoys" of the ligand, and (iii) enrich known actives in a virtual screen for the mineralocorticoid receptor in the presence of "ligand decoys" is assessed. While a pharmacophore-based molecular docking approach, PhDock, is used to carry out the docking, the results are expected to be general to use with any docking method.
Journal of Chemical Information and Modeling 06/2008; 48(5):1081-91. · 4.68 Impact Factor
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ABSTRACT: Structure-based lead optimization approaches are increasingly playing a role in the drug-discovery process. Recent advances in 'high-throughput' molecular docking methods and examples of their successful use in lead optimization are reviewed. Measures of docking accuracy, scoring function comparisons, and consensus approaches are discussed. Differences in docking protocols typically used for lead optimization versus lead generation are highlighted; this section includes a discussion of the latest methods for the incorporation of protein flexibility. New approaches developed specifically for the design of combinatorial libraries as well as those designed or used for 'fragment' versus lead optimization are presented. Finally, potential future improvements to the technology are outlined.
Current opinion in drug discovery & development 06/2007; 10(3):264-74. · 4.20 Impact Factor
