, Volume 14, Issue 1, pp 133-141
Date: 27 Jan 2012

Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review

Abstract

Structure-based virtual screening (SBVS) has been widely applied in early-stage drug discovery. From a problem-centric perspective, we reviewed the recent advances and applications in SBVS with a special focus on docking-based virtual screening. We emphasized the researchers’ practical efforts in real projects by understanding the ligand-target binding interactions as a premise. We also highlighted the recent progress in developing target-biased scoring functions by optimizing current generic scoring functions toward certain target classes, as well as in developing novel ones by means of machine learning techniques.

Guest Editor: Xiang-Qun Xie
Tiejun Cheng, Qingliang Li and Zhigang Zhou contributed equally to this work.