Wu Fengxu, Zhuo Linsheng, Wang Fan, Huang Wei, Hao Gefei, Yang Guangfu
Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan 430079, P. R. China; International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan 430079, China.
Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan 430079, P. R. China; International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan 430079, China.
iScience. 2020 Jun 26;23(6):101179. doi: 10.1016/j.isci.2020.101179. Epub 2020 May 18.
Motivated by the growing demand for reducing the chemical optimization burden of H2L, we developed auto in silico ligand directing evolution (AILDE, http://chemyang.ccnu.edu.cn/ccb/server/AILDE), an efficient and general approach for the rapid identification of drug leads in accessible chemical space. This computational strategy relies on minor chemical modifications on the scaffold of a hit compound, and it is primarily intended for identifying new lead compounds with minimal losses or, in some cases, even increases in ligand efficiency. We also described how AILDE greatly reduces the chemical optimization burden in the design of mesenchymal-epithelial transition factor (c-Met) kinase inhibitors. We only synthesized eight compounds and found highly efficient compound 5g, which showed an ∼1,000-fold improvement in in vitro activity compared with the hit compound. 5g also displayed excellent in vivo antitumor efficacy as a drug lead. We believe that AILDE may be applied to a large number of studies for rapid design and identification of drug leads.
受减轻H2L化学优化负担的需求不断增长的推动,我们开发了自动计算机辅助配体定向进化(AILDE,http://chemyang.ccnu.edu.cn/ccb/server/AILDE),这是一种在可及化学空间中快速识别药物先导物的高效通用方法。这种计算策略依赖于对命中化合物支架进行微小的化学修饰,其主要目的是识别新的先导化合物,使配体效率损失最小,在某些情况下甚至提高。我们还描述了AILDE如何在间充质上皮转化因子(c-Met)激酶抑制剂的设计中大大减轻化学优化负担。我们仅合成了8种化合物,就发现了高效化合物5g,其体外活性与命中化合物相比提高了约1000倍。5g作为药物先导物还显示出优异的体内抗肿瘤疗效。我们相信AILDE可应用于大量研究,以快速设计和识别药物先导物。