Surflex:  Fully Automatic Flexible Molecular Docking Using a Molecular Similarity-Based Search Engine

Jain, Ajay N.

doi:10.1021/jm020406h

Cited by 1,253 publications

(1,134 citation statements)

References 16 publications

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“…Among these five methods, the accuracy of GEMDOCK-Pharma was the best for TK and both ER receptors and GOLD-Goldinter outperformed other methods for DHFR. Table 2 shows FP rates of GEMDOCK and four comparable approaches (Surflex, 32 DOCK, 18 FlexX, 19 and GOLD 20 ) for screening ER and TK. All of these methods were tested using the same reference protein and screening database with true positive rates ranging from 80 to 100%.…”

Section: Methods Of Data Fusionmentioning

confidence: 99%

Consensus Scoring Criteria for Improving Enrichment in Virtual Screening

Yang

Chen

Shen

et al. 2005

J. Chem. Inf. Model.

221

240

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Motivation: Virtual screening of molecular compound libraries is a potentially powerful and inexpensive method for the discovery of novel lead compounds for drug development. The major weakness of virtual screeningsthe inability to consistently identify true positives (leads)sis likely due to our incomplete understanding of the chemistry involved in ligand binding and the subsequently imprecise scoring algorithms. It has been demonstrated that combining multiple scoring functions (consensus scoring) improves the enrichment of true positives. Previous efforts at consensus scoring have largely focused on empirical results, but they have yet to provide a theoretical analysis that gives insight into real features of combinations and data fusion for virtual screening. Results: We demonstrate that combining multiple scoring functions improves the enrichment of true positives only if (a) each of the individual scoring functions has relatively high performance and (b) the individual scoring functions are distinctive. Notably, these two prediction variables are previously established criteria for the performance of data fusion approaches using either rank or score combinations. This work, thus, establishes a potential theoretical basis for the probable success of data fusion approaches to improve yields in in silico screening experiments. Furthermore, it is similarly established that the second criterion (b) can, in at least some cases, be functionally defined as the area between the rank versus score plots generated by the two (or more) algorithms. Because rank-score plots are independent of the performance of the individual scoring function, this establishes a second theoretically defined approach to determining the likely success of combining data from different predictive algorithms. This approach is, thus, useful in practical settings in the virtual screening process when the performance of at least two individual scoring functions (such as in criterion a) can be estimated as having a high likelihood of having high performance, even if no training sets are available. We provide initial validation of this theoretical approach using data from five scoring systems with two evolutionary docking algorithms on four targets, thymidine kinase, human dihydrofolate reductase, and estrogen receptors of antagonists and agonists. Our procedure is computationally efficient, able to adapt to different situations, and scalable to a large number of compounds as well as to a greater number of combinations. Results of the experiment show a fairly significant improvement (vs single algorithms) in several measures of scoring quality, specifically "goodness-of-hit" scores, false positive rates, and "enrichment". This approach (available online at http://gemdock.life. nctu.edu.tw/dock/download.php) has practical utility for cases where the basic tools are known or believed to be generally applicable, but where specific training sets are absent.

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Section: Methods Of Data Fusionmentioning

confidence: 99%

Consensus Scoring Criteria for Improving Enrichment in Virtual Screening

Yang

Chen

Shen

et al. 2005

J. Chem. Inf. Model.

221

240

View full text Add to dashboard Cite

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“…A proto_thresh value of 0.5 and a proto_bloat value of 0 were used to generate a compact protomol. A TRIPOS mol2file (TRIPOS Associates Inc., St. Louis, MO) of the antagonist, obtained from a two-dimensional sketch as previously reported (29) was docked into the TM cavity using standard parameters of Surflex used in the "whole" docking approach (27). The best 30 solutions were finally stored in mol2 format.…”

Section: Methodsmentioning

confidence: 99%

Positive and Negative Allosteric Modulators of the Ca2+-sensing Receptor Interact within Overlapping but Not Identical Binding Sites in the Transmembrane Domain

Pétrel

Kessler

Dauban

et al. 2004

Journal of Biological Chemistry

195

167

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A three-dimensional model of the human extracellular Ca 2؉ -sensing receptor (CaSR) has been used to identify specific residues implicated in the recognition of two negative allosteric located in transmembranes (TM) 6 and TM7, in the binding pocket for both calcimimetics and calcilytics, despite important differences observed between each family of compounds. The TMs involved in the recognition of both calcilytics include residues located in TM3 (Arg-680 3.28 , Phe-684 3.32 , and Phe-688 3.36 ). However, our study indicates subtle differences between the binding of these two compounds. Importantly, the observation that some mutations that have no effect on calcimimetics recognition but which affect the binding of calcilytics in TM3 and TM5, suggests that the binding pocket of positive and negative allosteric modulators is partially overlapping but not identical. Our CaSR model should facilitate the development of novel drugs of this important therapeutic target and the identification of the molecular determinants involved in the binding of allosteric modulators of class 3 G-protein-coupled receptors.

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“…All heteroatoms were removed from the file and hydrogen atoms were added using the QuacPac program from Openeye Scientific Software. The docking experiments of the different steroids were performed using the flexible docking program Surflex 26 . The binding site for docking experiments was defined around the co-crystallized Adamantane Sulfone inhibitor.…”

Section: Discussionmentioning

confidence: 99%