Computational Insights into SARS-CoV-2 Main Protease Mutations and Nirmatrelvir Efficacy: The Effects of P132H and P132H-A173V

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-06-24 DOI:10.1021/acs.jcim.4c00334
Yuan-Ling Xia, Wen-Wen Du, Yong-Ping Li, Yan Tao, Zhi-Bi Zhang, Song-Ming Liu, Yun-Xin Fu, Ke-Qin Zhang and Shu-Qun Liu*, 
{"title":"Computational Insights into SARS-CoV-2 Main Protease Mutations and Nirmatrelvir Efficacy: The Effects of P132H and P132H-A173V","authors":"Yuan-Ling Xia,&nbsp;Wen-Wen Du,&nbsp;Yong-Ping Li,&nbsp;Yan Tao,&nbsp;Zhi-Bi Zhang,&nbsp;Song-Ming Liu,&nbsp;Yun-Xin Fu,&nbsp;Ke-Qin Zhang and Shu-Qun Liu*,&nbsp;","doi":"10.1021/acs.jcim.4c00334","DOIUrl":null,"url":null,"abstract":"<p >Nirmatrelvir, a pivotal component of the oral antiviral Paxlovid for COVID-19, targets the SARS-CoV-2 main protease (M<sup>pro</sup>) as a covalent inhibitor. Here, we employed combined computational methods to explore how the prevalent Omicron variant mutation P132H, alone and in combination with A173V (P132H-A173V), affects nirmatrelvir’s efficacy. Our findings suggest that P132H enhances the noncovalent binding affinity of M<sup>pro</sup> for nirmatrelvir, whereas P132H-A173V diminishes it. Although both mutants catalyze the rate-limiting step more efficiently than the wild-type (WT) M<sup>pro</sup>, P132H slows the overall rate of covalent bond formation, whereas P132H-A173V accelerates it. Comprehensive analysis of noncovalent and covalent contributions to the overall binding free energy of the covalent complex suggests that P132H likely enhances M<sup>pro</sup> sensitivity to nirmatrelvir, while P132H-A173V may confer resistance. Per-residue decompositions of the binding and activation free energies pinpoint key residues that significantly affect the binding affinity and reaction rates, revealing how the mutations modulate these effects. The mutation-induced conformational perturbations alter drug–protein local contact intensities and the electrostatic preorganization of the protein, affecting noncovalent binding affinity and the stability of key reaction states, respectively. Our findings inform the mechanisms of nirmatrelvir resistance and sensitivity, facilitating improved drug design and the detection of resistant strains.</p>","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":null,"pages":null},"PeriodicalIF":5.6000,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Information and Modeling ","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jcim.4c00334","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0

Abstract

Nirmatrelvir, a pivotal component of the oral antiviral Paxlovid for COVID-19, targets the SARS-CoV-2 main protease (Mpro) as a covalent inhibitor. Here, we employed combined computational methods to explore how the prevalent Omicron variant mutation P132H, alone and in combination with A173V (P132H-A173V), affects nirmatrelvir’s efficacy. Our findings suggest that P132H enhances the noncovalent binding affinity of Mpro for nirmatrelvir, whereas P132H-A173V diminishes it. Although both mutants catalyze the rate-limiting step more efficiently than the wild-type (WT) Mpro, P132H slows the overall rate of covalent bond formation, whereas P132H-A173V accelerates it. Comprehensive analysis of noncovalent and covalent contributions to the overall binding free energy of the covalent complex suggests that P132H likely enhances Mpro sensitivity to nirmatrelvir, while P132H-A173V may confer resistance. Per-residue decompositions of the binding and activation free energies pinpoint key residues that significantly affect the binding affinity and reaction rates, revealing how the mutations modulate these effects. The mutation-induced conformational perturbations alter drug–protein local contact intensities and the electrostatic preorganization of the protein, affecting noncovalent binding affinity and the stability of key reaction states, respectively. Our findings inform the mechanisms of nirmatrelvir resistance and sensitivity, facilitating improved drug design and the detection of resistant strains.

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
计算揭示 SARS-CoV-2 主要蛋白酶突变和 Nirmatrelvir 的疗效:P132H和P132H-A173V的影响。
Nirmatrelvir是COVID-19口服抗病毒药物Paxlovid的关键成分,它以SARS-CoV-2主蛋白酶(Mpro)为目标,是一种共价抑制剂。在这里,我们采用了综合计算方法来探讨普遍存在的 Omicron 变异突变 P132H 单独或与 A173V(P132H-A173V)结合如何影响 nirmatrelvir 的药效。我们的研究结果表明,P132H 增强了 Mpro 与 nirmatrelvir 的非共价结合亲和力,而 P132H-A173V 则降低了这种亲和力。虽然这两种突变体催化限速步骤的效率都高于野生型(WT)Mpro,但 P132H 减慢了共价键形成的总体速率,而 P132H-A173V 则加快了这一速率。对共价复合物整体结合自由能的非共价和共价贡献的综合分析表明,P132H 可能会增强 Mpro 对 nirmatrelvir 的敏感性,而 P132H-A173V 可能会赋予其抗性。结合自由能和活化自由能的每残基分解找出了对结合亲和力和反应速率有显著影响的关键残基,揭示了突变是如何调节这些效应的。突变引起的构象扰动改变了药物与蛋白质的局部接触强度和蛋白质的静电预组织,分别影响了非共价结合亲和力和关键反应状态的稳定性。我们的发现揭示了尼尔马特韦的耐药性和敏感性机制,有助于改进药物设计和检测耐药菌株。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
期刊最新文献
NetSci: A Library for High Performance Biomolecular Simulation Network Analysis Computation. Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery. AutoDesigner - Core Design, a De Novo Design Algorithm for Chemical Scaffolds: Application to the Design and Synthesis of Novel Selective Wee1 Inhibitors. Modeling Protein-Glycan Interactions with HADDOCK. Retrieval Augmented Docking Using Hierarchical Navigable Small Worlds.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1