BEAR, a Novel Virtual Screening Methodology for Drug Discovery

被引:28
作者
Degliesposti, Gianluca [1 ]
Portioli, Corinne [1 ]
Parenti, Marco Daniele [1 ]
Rastelli, Giulio [1 ]
机构
[1] Univ Modena & Reggio Emilia, Dipartimento Sci Farmaceut, I-41125 Modena, Italy
关键词
virtual screening; computational chemistry; chemoinformatics; drug design; BEAR; BINDING FREE-ENERGIES; AUTOMATED PROCEDURE; MOLECULAR DOCKING; MM-GBSA; INHIBITORS; PREDICTION; INSIGHTS; PBSA;
D O I
10.1177/1087057110388276
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
BEAR (binding estimation after refinement) is a new virtual screening technology based on the conformational refinement of docking poses through molecular dynamics and prediction of binding free energies using accurate scoring functions. Here, the authors report the results of an extensive benchmark of the BEAR performance in identifying a smaller subset of known inhibitors seeded in a large (1.5 million) database of compounds. BEAR performance proved strikingly better if compared with standard docking screening methods. The validations performed so far showed that BEAR is a reliable tool for drug discovery. It is fast, modular, and automated, and it can be applied to virtual screenings against any biological target with known structure and any database of compounds. (Journal of Biomolecular Screening 2011:129-133)
引用
收藏
页码:129 / 133
页数:5
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