{"title":"利用计算机分析开发治疗COVID-19的新药物:鉴定抑制SARS-Cov-2链霉菌的化合物","authors":"J. Kumar, Prachi Gholap, T. Pillai","doi":"10.33696/signaling.4.092","DOIUrl":null,"url":null,"abstract":"In accordance with the present epidemiological paradigm, viral mutations of the virus are on the rise, and their natural effects are being selected for at a higher rate than normal. According to the World Health Organization (WHO), the global COVID-19 pandemic induced by the Delta and Omicron strain of the SARS-CoV-2 virus could propagate and disseminate more rapidly than other viruses thanks to its many mutations, and these also caused some very significant health problems. The established medications would eventually start to lose their efficacy since the variation mutated more quickly than the original stain. As protein spikes are the point of origin or epitome for the mutations to take place, it would be most effective to target the remaining vital enzymes by binding the proteins with the largest pocket sizes. The objective of the current work is to employ in-silico analysis to discover the streptomyces chemicals that suppress the SARS-CoV-2 virus as well as its mutated strains thus promoting a healthy body. Based on the drug likeness property of compounds when subjected to molecular docking, a total of 14 compounds were identified and selected from the PUBCHEM database that showed highest binding energy with the targeted Receptor Binding Domain. The compounds namely - Streptomyces tanashiensis; Thaxtomin A; Bafilomycin A1 from Streptomyces griseus and few others as mentioned further on more research would support and confirm the utilizing of these to create new medications to treat the novel SARS-CoV-2 infectious strains.","PeriodicalId":73645,"journal":{"name":"Journal of cellular signaling","volume":"30 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel Drug Development for Treatment of COVID-19 by In Silico Analysis: Identification of SARS-Cov-2 Inhibiting Streptomyces Compounds\",\"authors\":\"J. Kumar, Prachi Gholap, T. Pillai\",\"doi\":\"10.33696/signaling.4.092\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In accordance with the present epidemiological paradigm, viral mutations of the virus are on the rise, and their natural effects are being selected for at a higher rate than normal. According to the World Health Organization (WHO), the global COVID-19 pandemic induced by the Delta and Omicron strain of the SARS-CoV-2 virus could propagate and disseminate more rapidly than other viruses thanks to its many mutations, and these also caused some very significant health problems. The established medications would eventually start to lose their efficacy since the variation mutated more quickly than the original stain. As protein spikes are the point of origin or epitome for the mutations to take place, it would be most effective to target the remaining vital enzymes by binding the proteins with the largest pocket sizes. The objective of the current work is to employ in-silico analysis to discover the streptomyces chemicals that suppress the SARS-CoV-2 virus as well as its mutated strains thus promoting a healthy body. Based on the drug likeness property of compounds when subjected to molecular docking, a total of 14 compounds were identified and selected from the PUBCHEM database that showed highest binding energy with the targeted Receptor Binding Domain. The compounds namely - Streptomyces tanashiensis; Thaxtomin A; Bafilomycin A1 from Streptomyces griseus and few others as mentioned further on more research would support and confirm the utilizing of these to create new medications to treat the novel SARS-CoV-2 infectious strains.\",\"PeriodicalId\":73645,\"journal\":{\"name\":\"Journal of cellular signaling\",\"volume\":\"30 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of cellular signaling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33696/signaling.4.092\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of cellular signaling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33696/signaling.4.092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Novel Drug Development for Treatment of COVID-19 by In Silico Analysis: Identification of SARS-Cov-2 Inhibiting Streptomyces Compounds
In accordance with the present epidemiological paradigm, viral mutations of the virus are on the rise, and their natural effects are being selected for at a higher rate than normal. According to the World Health Organization (WHO), the global COVID-19 pandemic induced by the Delta and Omicron strain of the SARS-CoV-2 virus could propagate and disseminate more rapidly than other viruses thanks to its many mutations, and these also caused some very significant health problems. The established medications would eventually start to lose their efficacy since the variation mutated more quickly than the original stain. As protein spikes are the point of origin or epitome for the mutations to take place, it would be most effective to target the remaining vital enzymes by binding the proteins with the largest pocket sizes. The objective of the current work is to employ in-silico analysis to discover the streptomyces chemicals that suppress the SARS-CoV-2 virus as well as its mutated strains thus promoting a healthy body. Based on the drug likeness property of compounds when subjected to molecular docking, a total of 14 compounds were identified and selected from the PUBCHEM database that showed highest binding energy with the targeted Receptor Binding Domain. The compounds namely - Streptomyces tanashiensis; Thaxtomin A; Bafilomycin A1 from Streptomyces griseus and few others as mentioned further on more research would support and confirm the utilizing of these to create new medications to treat the novel SARS-CoV-2 infectious strains.