In silico methods to address polypharmacology: current status, applications and future perspectives

被引:145
|
作者
Lavecchia, Antonio [1 ]
Cerchia, Carmen [1 ]
机构
[1] Univ Naples Federico II, Drug Discovery Lab, Dept Pharm, Via D Montesano 49, I-80131 Naples, Italy
关键词
DE-NOVO DESIGN; TARGET PREDICTION; DRUG DISCOVERY; MACROMOLECULAR TARGETS; NETWORK PHARMACOLOGY; BIOLOGICAL SPACE; SYSTEMS BIOLOGY; NEXT-GENERATION; BINDING-SITES; WEB SERVER;
D O I
10.1016/j.drudis.2015.12.007
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Polypharmacology, a new paradigm in drug discovery that focuses on multi-target drugs (MTDs), has potential application for drug repurposing, the process of finding new uses for existing approved drugs, prediction of off-target toxicities and rational design of MTDs. In this scenario, computational strategies have demonstrated great potential in predicting polypharmacology and in facilitating drug repurposing. Here, we provide a comprehensive overview of various computational approaches that enable the prediction and analysis of in vitro and in vivo drug-response phenotypes and outline their potential for drug discovery. We give an outlook on the latest advances in rational design of MTDs and discuss possible future directions of algorithm development in this field.
引用
收藏
页码:288 / 298
页数:11
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