Literature DB >> 15715466

Comparison of automated docking programs as virtual screening tools.

Maxwell D Cummings1, Renee L DesJarlais, Alan C Gibbs, Venkatraman Mohan, Edward P Jaeger.   

Abstract

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.

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Year:  2005        PMID: 15715466     DOI: 10.1021/jm049798d

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  56 in total

1.  FRED and HYBRID docking performance on standardized datasets.

Authors:  Mark McGann
Journal:  J Comput Aided Mol Des       Date:  2012-06-05       Impact factor: 3.686

2.  Chemical space sampling by different scoring functions and crystal structures.

Authors:  Natasja Brooijmans; Christine Humblet
Journal:  J Comput Aided Mol Des       Date:  2010-04-18       Impact factor: 3.686

3.  Biased retrieval of chemical series in receptor-based virtual screening.

Authors:  Natasja Brooijmans; Jason B Cross; Christine Humblet
Journal:  J Comput Aided Mol Des       Date:  2010-10-30       Impact factor: 3.686

4.  Benchmarking sets for molecular docking.

Authors:  Niu Huang; Brian K Shoichet; John J Irwin
Journal:  J Med Chem       Date:  2006-11-16       Impact factor: 7.446

Review 5.  Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach.

Authors:  I M Kapetanovic
Journal:  Chem Biol Interact       Date:  2006-12-16       Impact factor: 5.192

Review 6.  Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

Authors:  N Moitessier; P Englebienne; D Lee; J Lawandi; C R Corbeil
Journal:  Br J Pharmacol       Date:  2007-11-26       Impact factor: 8.739

Review 7.  In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling.

Authors:  S Ekins; J Mestres; B Testa
Journal:  Br J Pharmacol       Date:  2007-06-04       Impact factor: 8.739

8.  Comparative performance of several flexible docking programs and scoring functions: enrichment studies for a diverse set of pharmaceutically relevant targets.

Authors:  Zhiyong Zhou; Anthony K Felts; Richard A Friesner; Ronald M Levy
Journal:  J Chem Inf Model       Date:  2007-06-23       Impact factor: 4.956

9.  Optimization of CAMD techniques 3. Virtual screening enrichment studies: a help or hindrance in tool selection?

Authors:  Andrew C Good; Tudor I Oprea
Journal:  J Comput Aided Mol Des       Date:  2008-01-09       Impact factor: 3.686

10.  Can we use docking and scoring for hit-to-lead optimization?

Authors:  Istvan J Enyedy; William J Egan
Journal:  J Comput Aided Mol Des       Date:  2008-01-09       Impact factor: 3.686

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