SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new pathogen from the family of Coronaviridae that caused a global pandemic of COVID-19 disease. In the absence of effective antiviral drugs, research of novel therapeutic targets such as SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) becomes essential. This viral protein is without a human counterpart and thus represents a unique prospective drug target. However, in vitro biological evaluation testing on RdRp remains difficult and is not widely available. Therefore, we prepared a database of commercial small-molecule compounds and performed an in silico high-throughput virtual screening on the active site of the SARS-CoV-2 RdRp using ensemble docking. We identified a novel thioether-amide or guanidine-linker class of potential RdRp inhibitors and calculated favorable binding free energies of representative hits by molecular dynamics simulations coupled with Linear Interaction Energy calculations. This innovative procedure maximized the respective phase-space sampling and yielded non-covalent inhibitors representing small optimizable molecules that are synthetically readily accessible, commercially available as well as suitable for further biological evaluation and mode of action studies.
【저자키워드】 COVID-19, SARS-CoV-2 virus, Virtual screening, molecular dynamics, RNA-dependent RNA polymerase, in silico drug design, Ensemble docking, binding site identification, non-covalent inhibitors, free-energy calculations, 【초록키워드】 SARS-CoV-2, coronavirus, antiviral drugs, docking, in vitro, in silico, binding free energy, database, Molecular dynamics simulation, COVID-19 disease, global pandemic, pathogen, Research, drug target, RdRP, inhibitor, Coronaviridae, therapeutic target, energy, acute respiratory syndrome, Viral protein, Compound, RdRp inhibitor, effective, performed, caused, calculated, absence, unique, representing, the SARS-CoV-2, 【제목키워드】 SARS-CoV-2, Screening, RNA, novel, class, calculation, Potential, Identified,