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gWEGA: GPU‐accelerated WEGA for molecular superposition and shape comparison
Author(s) -
Yan Xin,
Li Jiabo,
Gu Qiong,
Xu Jun
Publication year - 2014
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.23603
Subject(s) - computer science , virtual screening , pharmacophore , feature (linguistics) , similarity (geometry) , graphics processing unit , cuda , identification (biology) , gaussian , parallel computing , computational science , pattern recognition (psychology) , artificial intelligence , chemistry , computational chemistry , image (mathematics) , philosophy , biochemistry , linguistics , botany , biology
Virtual screening of a large chemical library for drug lead identification requires searching/superimposing a large number of three‐dimensional (3D) chemical structures. This article reports a graphic processing unit (GPU)‐accelerated weighted Gaussian algorithm (gWEGA) that expedites shape or shape‐feature similarity score‐based virtual screening. With 86 GPU nodes (each node has one GPU card), gWEGA can screen 110 million conformations derived from an entire ZINC drug‐like database with diverse antidiabetic agents as query structures within 2 s (i.e., screening more than 55 million conformations per second). The rapid screening speed was accomplished through the massive parallelization on multiple GPU nodes and rapid prescreening of 3D structures (based on their shape descriptors and pharmacophore feature compositions). © 2014 Wiley Periodicals, Inc.