Consensus Scoring Criteria for Improving Enrichment in Virtual Screening
Author(s) -
JinnMoon Yang,
YenFu Chen,
Tsai-Wei Shen,
Bruce S. Kristal,
D. Frank Hsu
Publication year - 2005
Publication title -
journal of chemical information and modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 160
eISSN - 1549-960X
pISSN - 1549-9596
DOI - 10.1021/ci050034w
Subject(s) - virtual screening , computer science , drug discovery , bioinformatics , biology
Virtual screening of molecular compound libraries is a potentially powerful and inexpensive method for the discovery of novel lead compounds for drug development. The major weakness of virtual screening-the inability to consistently identify true positives (leads)-is likely due to our incomplete understanding of the chemistry involved in ligand binding and the subsequently imprecise scoring algorithms. It has been demonstrated that combining multiple scoring functions (consensus scoring) improves the enrichment of true positives. Previous efforts at consensus scoring have largely focused on empirical results, but they have yet to provide a theoretical analysis that gives insight into real features of combinations and data fusion for virtual screening.
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