药物发现
计算生物学
药理学
药品
化学
纳米技术
神经科学
药物靶点
医学
心理学
生物信息学
生物
材料科学
作者
Giulia Bianco,David S. Goodsell,Stefano Forli
标识
DOI:10.1016/j.tips.2020.10.005
摘要
Targeted covalent inhibitors are currently showing great promise for systems that are normally difficult to target with small molecule therapies. This renewed interest has spurred the refinement of existing computational methods as well as the designof new ones, expanding the toolbox for discovery and optimization of selectiveand effective covalent inhibitors. Commonly applied approaches are covalentdocking methods that predict the conformation of the covalent complex with known residues. More recently, a new predictive method, reactive docking, was developed, building on the growing corpus of data generated by large proteomics experiments. This method was successfully used in several 'inverse drug discovery' programs that use high-throughput techniques to isolate effective compounds based on screening of entire compound libraries based on desired phenotypes.
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