Research article summary (published 29 Sep 2009):

Blind docking of 260 protein-ligand complexes with EADock 2.0.

Full Abstract

Molecular docking softwares are one of the important tools of modern drug development pipelines. The promising achievements of the last 10 years emphasize the need for further improvement, as reflected by several recent publications (Leach et al., J Med Chem 2006, 49, 5851; Warren et al., J Med Chem 2006, 49, 5912). Our initial approach, EADock, showed a good performance in reproducing the experimental binding modes for a set of 37 different ligand-protein complexes (Grosdidier et al., Proteins 2007, 67, 1010). This article presents recent improvements regarding the scoring and sampling aspects over the initial implementation, as well as a new seeding procedure based on the detection of cavities, opening the door to blind docking with EADock. These enhancements were validated on 260 complexes taken from the high quality Ligand Protein Database [LPDB, (Roche et al., J Med Chem 2001, 44, 3592)]. Two issues were identified: first, the quality of the initial structures cannot be assumed and a manual inspection and/or a search in the literature are likely to be required to achieve the best performance. Second the description of interactions involving metal ions still has to be improved. Nonetheless, a remarkable success rate of 65% was achieved for a large scale blind docking assay, when considering only the top ranked binding mode and a success threshold of 2 A RMSD to the crystal structure. When looking at the five-top ranked binding modes, the success rate increases up to 76%. In a standard local docking assay, success rates of 75 and 83% were obtained, considering only the top ranked binding mode, or the five top binding modes, respectively. Copyright 2009 Wiley Periodicals, Inc.

Author information

Author/s: Grosdidier, Aurélien (A); Zoete, Vincent (V); Michielin, Olivier (O);

Affiliation: Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne, Switzerland.

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Journal of computational chemistry (J Comput Chem), published in United States. (Language: eng)

Reference: 2009-Oct; vol 30 (issue 13) : pp 2021-30

Dates: Created 2009/08/03; Completed 2009/10/09;

PMID: 19130502, status: MEDLINE (last retrieval date: 10/9/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Algorithms Drug Design Ligands

Protein Binding Proteins - chemistry; metabolism Software

Associated Chemicals: Ligands (0) ; Proteins (0)

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