Blind docking of 260 protein-ligand complexes with EADock 2.0.
Details
Serval ID
serval:BIB_FCB3986DE97F
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Blind docking of 260 protein-ligand complexes with EADock 2.0.
Journal
Journal of Computational Chemistry
ISSN
1096-987X[electronic]
Publication state
Published
Issued date
2009
Volume
30
Number
13
Pages
2021-2030
Language
english
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.
Keywords
Algorithms, Drug Design, Ligands, Protein Binding, Proteins/chemistry, Proteins/metabolism, Software
Pubmed
Web of science
Create date
11/03/2009 14:56
Last modification date
20/08/2019 17:27