期刊
AAPS JOURNAL
卷 14, 期 1, 页码 133-141出版社
SPRINGER
DOI: 10.1208/s12248-012-9322-0
关键词
docking; machine learning; structure-based virtual scoring; target-biased scoring function
资金
- National Institutes of Health (NIH), National Library of Medicine (NLM)
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.
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