Zhang Chun-Hui, Stone Elizabeth A, Deshmukh Maya, Ippolito Joseph A, Ghahremanpour Mohammad M, Tirado-Rives Julian, Spasov Krasimir A, Zhang Shuo, Takeo Yuka, Kudalkar Shalley N, Liang Zhuobin, Isaacs Farren, Lindenbach Brett, Miller Scott J, Anderson Karen S, Jorgensen William L
Department of Chemistry, Yale University, New Haven, Connecticut 06520-8107, United States.
Department of Pharmacology, Yale University School of Medicine, New Haven, Connecticut 06520-8066, United States.
ACS Cent Sci. 2021 Mar 24;7(3):467-475. doi: 10.1021/acscentsci.1c00039. Epub 2021 Feb 22.
Starting from our previous finding of 14 known drugs as inhibitors of the main protease (M) of SARS-CoV-2, the virus responsible for COVID-19, we have redesigned the weak hit perampanel to yield multiple noncovalent, nonpeptidic inhibitors with ca. 20 nM IC values in a kinetic assay. Free-energy perturbation (FEP) calculations for M-ligand complexes provided valuable guidance on beneficial modifications that rapidly delivered the potent analogues. The design efforts were confirmed and augmented by determination of high-resolution X-ray crystal structures for five analogues bound to M. Results of cell-based antiviral assays further demonstrated the potential of the compounds for treatment of COVID-19. In addition to the possible therapeutic significance, the work clearly demonstrates the power of computational chemistry for drug discovery, especially FEP-guided lead optimization.
基于我们之前发现的14种已知药物可作为新型冠状病毒肺炎(COVID-19)病原体严重急性呼吸综合征冠状病毒2(SARS-CoV-2)主要蛋白酶(M)的抑制剂,我们对活性较弱的吡拉西坦进行了重新设计,以产生多种非共价、非肽类抑制剂,在动力学分析中其半数抑制浓度(IC)值约为20 nM。对M-配体复合物的自由能扰动(FEP)计算为有益修饰提供了有价值的指导,这些修饰迅速产生了强效类似物。通过测定与M结合的五种类似物的高分辨率X射线晶体结构,证实并加强了设计工作。基于细胞的抗病毒试验结果进一步证明了这些化合物治疗COVID-19的潜力。除了可能具有的治疗意义外,这项工作清楚地展示了计算化学在药物发现中的作用,尤其是FEP引导的先导化合物优化。