We report development of in-silico approaches for the identification of anti-coronaviral drugs against SARS-CoV-2. The prevalence of respiratory illness caused by the novel SARS-CoV-2 virus associated with multiple organ failures is spreading rapidly because of its contagious human-to-human transmission and inadequate globalhealth care systems. Pharmaceutical repurposing, an effective drug development technique using existing drugs, could shorten development time and reduce costs compared to those of de novo drug discovery. We carried out virtual screening of antiviral compounds targeting the spike glycoprotein (S), main protease (M pro ), and the SARS-CoV-2 receptor binding domain (RBD)–angiotensin-converting enzyme 2 (ACE2) complex of SARS-CoV-2. PC786, an antiviral polymerase inhibitor, showed enhanced binding affinity to all the targets. Furthermore, the postfusion conformation of the trimeric S protein RBD with ACE2 revealed conformational changes associated with PC786 drug binding. Exploiting immunoinformatics to identify T cell and B cell epitopes could guide future experimental studies with a higher probability of discovering appropriate vaccine candidates with fewer experiments and higher reliability.
【초록키워드】 SARS-CoV-2, ACE2, Drug discovery, Antiviral, reliability, spike glycoprotein, drugs, Respiratory illness, Virtual screening, drug, protease, binding affinity, Receptor binding domain, Prevalence, Probability, T cell, RBD, vaccine candidate, immunoinformatics, targets, experiment, multiple organ failure, in-silico, inhibitor, Care, binding, conformational change, B cell epitope, enzyme, complex, M pro, novel SARS-CoV-2 virus, human-to-human transmission, pharmaceutical, contagious, de novo, polymerase, trimeric S protein, Antiviral compound, postfusion, effective, identify, caused, approach, carried, PC786, reduce cost, the SARS-CoV-2, 【제목키워드】 SARS-CoV-2, immunoinformatics, approach,