{"title":"FDA批准的可能干扰SARS-CoV-2刺突蛋白激活、病毒RNA复制和翻译后修饰的真菌源药物的计算筛选:多靶点方法","authors":"Rajveer Singh, Anupam Gautam, Shivani Chandel, Vipul Sharma, Arijit Ghosh, Dhritiman Dey, Syamal Roy, V Ravichandiran, Dipanjan Ghosh","doi":"10.1007/s40203-021-00089-8","DOIUrl":null,"url":null,"abstract":"<p><p>Coronavirus spread is an emergency reported globally, and a specific treatment strategy for this significant health issue is not yet identified. COVID-19 is a highly contagious disease and needs to be controlled promptly as millions of deaths have been reported. Due to the absence of proficient restorative alternatives and preliminary clinical restrictions, FDA-approved medications can be a decent alternative to deal with the coronavirus malady (COVID-19). The present study aims to meet the imperative necessity of effective COVID-19 drug treatment with a computational multi-target drug repurposing approach. This study focused on screening the FDA-approved drugs derived from the fungal source and its derivatives against the SARS-CoV-2 targets. All the selected drugs showed good binding affinity towards these targets, and out of them, bromocriptine was found to be the best candidate after the screening on the COVID-19 targets. Further, bromocriptine is analyzed by molecular simulation and MM-PBSA study. These studies suggested that bromocriptine can be the best candidate for TMPRSS2, Main protease, and RdRp protein.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-021-00089-8.</p>","PeriodicalId":13380,"journal":{"name":"In Silico Pharmacology","volume":" ","pages":"27"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40203-021-00089-8","citationCount":"6","resultStr":"{\"title\":\"Computational screening of FDA approved drugs of fungal origin that may interfere with SARS-CoV-2 spike protein activation, viral RNA replication, and post-translational modification: a multiple target approach.\",\"authors\":\"Rajveer Singh, Anupam Gautam, Shivani Chandel, Vipul Sharma, Arijit Ghosh, Dhritiman Dey, Syamal Roy, V Ravichandiran, Dipanjan Ghosh\",\"doi\":\"10.1007/s40203-021-00089-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Coronavirus spread is an emergency reported globally, and a specific treatment strategy for this significant health issue is not yet identified. COVID-19 is a highly contagious disease and needs to be controlled promptly as millions of deaths have been reported. Due to the absence of proficient restorative alternatives and preliminary clinical restrictions, FDA-approved medications can be a decent alternative to deal with the coronavirus malady (COVID-19). The present study aims to meet the imperative necessity of effective COVID-19 drug treatment with a computational multi-target drug repurposing approach. This study focused on screening the FDA-approved drugs derived from the fungal source and its derivatives against the SARS-CoV-2 targets. All the selected drugs showed good binding affinity towards these targets, and out of them, bromocriptine was found to be the best candidate after the screening on the COVID-19 targets. Further, bromocriptine is analyzed by molecular simulation and MM-PBSA study. These studies suggested that bromocriptine can be the best candidate for TMPRSS2, Main protease, and RdRp protein.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-021-00089-8.</p>\",\"PeriodicalId\":13380,\"journal\":{\"name\":\"In Silico Pharmacology\",\"volume\":\" \",\"pages\":\"27\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/s40203-021-00089-8\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"In Silico Pharmacology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40203-021-00089-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"In Silico Pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40203-021-00089-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Computational screening of FDA approved drugs of fungal origin that may interfere with SARS-CoV-2 spike protein activation, viral RNA replication, and post-translational modification: a multiple target approach.
Coronavirus spread is an emergency reported globally, and a specific treatment strategy for this significant health issue is not yet identified. COVID-19 is a highly contagious disease and needs to be controlled promptly as millions of deaths have been reported. Due to the absence of proficient restorative alternatives and preliminary clinical restrictions, FDA-approved medications can be a decent alternative to deal with the coronavirus malady (COVID-19). The present study aims to meet the imperative necessity of effective COVID-19 drug treatment with a computational multi-target drug repurposing approach. This study focused on screening the FDA-approved drugs derived from the fungal source and its derivatives against the SARS-CoV-2 targets. All the selected drugs showed good binding affinity towards these targets, and out of them, bromocriptine was found to be the best candidate after the screening on the COVID-19 targets. Further, bromocriptine is analyzed by molecular simulation and MM-PBSA study. These studies suggested that bromocriptine can be the best candidate for TMPRSS2, Main protease, and RdRp protein.
Supplementary information: The online version contains supplementary material available at 10.1007/s40203-021-00089-8.