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Potency Prediction of Covalent Inhibitors against SARS-CoV-2 3CL-like Protease and Multiple Mutants by Multiscale Simulations

文献类型：期刊论文

作者Xiong, Muya3,5; Nie, Tianqing1,2; Li, Zhewen3,4; Hu, Meiyi3; Su, Haixia3,4; Hu, Hangchen3,4; Xu, Yechun3,4,5; Shao, Qiang3,4
刊名JOURNAL OF CHEMICAL INFORMATION AND MODELING
出版日期2024-11-28
卷号64期号:24页码:9501-9516
ISSN号1549-9596
DOI10.1021/acs.jcim.4c01594
英文摘要3-Chymotrypsin-like protease (3CLpro) is a prominent target against pathogenic coronaviruses. Expert knowledge of the cysteine-targeted covalent reaction mechanism is crucial to predict the inhibitory potency of approved inhibitors against 3CLpros of SARS-CoV-2 variants and perform structure-based drug design against newly emerging coronaviruses. We carried out an extensive array of classical and hybrid QM/MM molecular dynamics simulations to explore covalent inhibition mechanisms of five well-characterized inhibitors toward SARS-CoV-2 3CLpro and its mutants. The calculated binding affinity and reactivity of the inhibitors are highly consistent with experimental data, and the predicted inhibitory potency of the inhibitors against 3CLpro with L167F, E166V, or T21I/E166V mutant is in full agreement with IC50s determined by the accompanying enzymatic assays. The explored mechanisms unveil the impact of residue mutagenesis on structural dynamics that communicates to change not only noncovalent binding strength but also covalent reaction free energy. Such a change is inhibitor dependent, corresponding to varied levels of drug resistance of these 3CLpro mutants against nirmatrelvir and simnotrelvir and no resistance to the 11a compound. These results together suggest that the present simulations with a suitable protocol can efficiently evaluate the reactivity and potency of covalent inhibitors along with the elucidated molecular mechanisms of covalent inhibition.
WOS关键词SCC-DFTB METHOD ; MOLECULAR-DYNAMICS ; 3CL PROTEASES ; CYSTEINE ; IMPLEMENTATION ; MECHANISM ; DISCOVERY
资助项目National Natural Science Foundation of China[32071248] ; National Natural Science Foundation of China[22277130] ; National Natural Science Foundation of China[22307133] ; National Natural Science Foundation of China[32301050] ; National Natural Science Foundation of China
WOS研究方向Pharmacology & Pharmacy ; Chemistry ; Computer Science
WOS记录号WOS:001366395100001
出版者AMER CHEMICAL SOC
源URL[http://119.78.100.183/handle/2S10ELR8/314801]  
专题新药研究国家重点实验室
通讯作者Xu, Yechun; Shao, Qiang
作者单位1.Lingang Lab, Shanghai 200031, Peoples R China
2.ShanghaiTech Univ, Sch Phys Sci & Technol, Shanghai 201210, Peoples R China
3.Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Shanghai 201203, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.Univ Chinese Acad Sci, Hangzhou Inst Adv Study, Sch Pharmaceut Sci & Technol, Hangzhou 310024, Peoples R China
推荐引用方式
GB/T 7714		 Xiong, Muya,Nie, Tianqing,Li, Zhewen,et al. Potency Prediction of Covalent Inhibitors against SARS-CoV-2 3CL-like Protease and Multiple Mutants by Multiscale Simulations[J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING,2024,64(24):9501-9516.
APA Xiong, Muya.,Nie, Tianqing.,Li, Zhewen.,Hu, Meiyi.,Su, Haixia.,...&Shao, Qiang.(2024).Potency Prediction of Covalent Inhibitors against SARS-CoV-2 3CL-like Protease and Multiple Mutants by Multiscale Simulations.JOURNAL OF CHEMICAL INFORMATION AND MODELING,64(24),9501-9516.
MLA Xiong, Muya,et al."Potency Prediction of Covalent Inhibitors against SARS-CoV-2 3CL-like Protease and Multiple Mutants by Multiscale Simulations".JOURNAL OF CHEMICAL INFORMATION AND MODELING 64.24(2024):9501-9516.

入库方式： OAI收割

来源：上海药物研究所

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