Well-Tempered Metadynamic Simulations Provide Insights and Leads for Designing Effective Allosteric Inhibitors against SARS-CoV-2 RNA-Dependent RNA Polymerase

精心设计的元动力学模拟为设计针对SARS-CoV-2 RNA依赖性RNA聚合酶的有效变构抑制剂提供了见解和线索

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Abstract

Drug development against RNA viruses is challenging due to continuously emerging mutational variants. RNA-dependent RNA polymerases (RdRp) of most RNA viruses are conserved in their catalytic and allosteric sites, making them a promising target for drug development and repurposing. Some RdRp allosteric inhibitors of Hepatitis C Virus (HCV) have undergone Phase I and II clinical trials. Aiming to rationally design RdRp inhibitors to combat emerging and life-threatening RNA viruses, we explored the binding modes and mechanisms of HCV RdRp allosteric inhibitors against HCV and SARS-CoV-2 RdRps through molecular docking, molecular dynamics (MD), and well-tempered metadynamic (WT-MD) simulations. Twelve allosteric inhibitors of HCV were screened based on their binding free energy profile through WT-MD simulations to understand the binding modes and their inhibitory mechanisms. Our results suggest that these inhibitors have a higher binding affinity toward HCV RdRp and a weaker binding affinity toward different allosteric sites of SARS-CoV-2 RdRp. WT-MD simulations provided details about the binding modes of these inhibitors in HCV and SARS-CoV-2 RdRp. The preliminary functional group modifications of lead molecules identified through WT-MD showed improved binding energy toward SARS-CoV-2 RdRp. WT-MD simulations provide insights into the binding modes of these inhibitors in HCV and SARS-CoV-2 RdRp and also provide structural insights, leads, and principles for designing effective allosteric inhibitors to combat future SARS-CoV-2 and other RNA virus outbreaks.

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