Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review
National Center for Biotechnology Information · National Institutes of Health
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.
Citation impact
- FWCI
- 36.10
- Percentile
- 100%
- References
- 100
Authors
5- TCTiejun ChengCorresponding
National Center for Biotechnology Information, National Institutes of Health
- QLQingliang Li
National Institutes of Health, National Center for Biotechnology Information
- ZZZhigang Zhou
National Institutes of Health, National Center for Biotechnology Information
- YWYanli Wang
National Institutes of Health, National Center for Biotechnology Information
- SHStephen H. Bryant
National Institutes of Health, National Center for Biotechnology Information
Topics & keywords
- Virtual screening
- Computer science
- Premise
- Drug discovery
- Data science
- Perspective (graphical)
- Machine learning
- Artificial intelligence