Title:Virtual Screening Methods as Tools for Drug Lead Discovery from Large Chemical Libraries
VOLUME: 19 ISSUE: 32
Author(s):X. H. Ma, F. Zhu, X. Liu, Z. Shi, J. X. Zhang, S. Y. Yang, Y. Q. Wei and Y. Z. Chen
Affiliation:State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610064, P.R.China.
Keywords:Machine learning, molecular docking, pharmacophore, quantitative structure activity relationship, similarity searching, support
vector machines, Virtual screening, "cal libraries", "strategies"
Abstract:Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical
libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring
virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of
~ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these
methods.