Uika Koshimizu, Junichi Ono, Y. Fukunishi, Hiromi Nakai
{"title":"面向新型冠状病毒口服抗病毒药物开发的硅杂化药物发现研究","authors":"Uika Koshimizu, Junichi Ono, Y. Fukunishi, Hiromi Nakai","doi":"10.2477/jccj.2022-0029","DOIUrl":null,"url":null,"abstract":"Hybrid in silico drug discovery was performed by combining large-scale quantum molecular dynamics (QMD) simulations with the conventional in silico drug discovery, focusing on developing covalent inhibitors against the main protease (M-pro) of SARS-CoV-2, the virus responsible for ongoing COVID-19 pandemic. The crystal structures and instantaneous structures obtained from the large-scale QMD simulations for M-pro were used as receptors in ensemble docking to estimate the binding affinities of the four ligands: the natural substrate recognized by M-pro, that recognized by the other enzyme of SARS-CoV-2, approved covalent inhibitor (PF-07321332), and the new candidate compound X determined from virtual screening. The present result shows that the binding affinity of X was comparable to that of PF-07321332, demonstrating the potency of our drug discovery.","PeriodicalId":41909,"journal":{"name":"Journal of Computer Chemistry-Japan","volume":"1 1","pages":""},"PeriodicalIF":0.1000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hybrid in Silico Drug Discovery Study toward the Development of Oral Antivirals for COVID-19\",\"authors\":\"Uika Koshimizu, Junichi Ono, Y. Fukunishi, Hiromi Nakai\",\"doi\":\"10.2477/jccj.2022-0029\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hybrid in silico drug discovery was performed by combining large-scale quantum molecular dynamics (QMD) simulations with the conventional in silico drug discovery, focusing on developing covalent inhibitors against the main protease (M-pro) of SARS-CoV-2, the virus responsible for ongoing COVID-19 pandemic. The crystal structures and instantaneous structures obtained from the large-scale QMD simulations for M-pro were used as receptors in ensemble docking to estimate the binding affinities of the four ligands: the natural substrate recognized by M-pro, that recognized by the other enzyme of SARS-CoV-2, approved covalent inhibitor (PF-07321332), and the new candidate compound X determined from virtual screening. The present result shows that the binding affinity of X was comparable to that of PF-07321332, demonstrating the potency of our drug discovery.\",\"PeriodicalId\":41909,\"journal\":{\"name\":\"Journal of Computer Chemistry-Japan\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.1000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer Chemistry-Japan\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2477/jccj.2022-0029\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Chemistry-Japan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2477/jccj.2022-0029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Hybrid in Silico Drug Discovery Study toward the Development of Oral Antivirals for COVID-19
Hybrid in silico drug discovery was performed by combining large-scale quantum molecular dynamics (QMD) simulations with the conventional in silico drug discovery, focusing on developing covalent inhibitors against the main protease (M-pro) of SARS-CoV-2, the virus responsible for ongoing COVID-19 pandemic. The crystal structures and instantaneous structures obtained from the large-scale QMD simulations for M-pro were used as receptors in ensemble docking to estimate the binding affinities of the four ligands: the natural substrate recognized by M-pro, that recognized by the other enzyme of SARS-CoV-2, approved covalent inhibitor (PF-07321332), and the new candidate compound X determined from virtual screening. The present result shows that the binding affinity of X was comparable to that of PF-07321332, demonstrating the potency of our drug discovery.