Abstract
The pandemic prevalence of COVID-19 has become a very serious global health issue. Scientists all over the world have been seriously attempting in the discovery of a drug to combat SARS-CoV-2. It has been found that RNA-dependent RNA polymerase (RdRp) plays a crucial role in SARS-CoV-2 replication, and thus could be a potential drug target. Here, comprehensive computational approaches including drug repurposing and molecular docking were employed to predict an effective drug candidate targeting RdRp of SARS-CoV-2. This study revealed that Rifabutin, Rifapentine, Fidaxomicin, 7-methyl-guanosine-5′-triphosphate-5′-guanosine and Ivermectin have a potential inhibitory interaction with RdRp of SARS-CoV-2 and could be effective drugs for COVID-19. In addition, virtual screening of the compounds from ZINC database also allowed the prediction of two compounds (ZINC09128258 and ZINC09883305) with pharmacophore features that interact effectively with RdRp of SARS-CoV-2, indicating their potentiality as effective inhibitors of the enzyme. Furthermore, ADME analysis along with analysis of toxicity was also undertaken to check the pharmacokinetics and drug-likeness properties of the two compounds. Comparative structural analysis of protein-inhibitor complexes revealed that the amino acids Y32, K47, Y122, Y129, H133, N138, D140, T141, S709 and N781 are crucial for drug surface hotspot in the RdRp of SARS-CoV-2.
【저자키워드】 COVID-19, SARS-CoV-2, drug, RNA-dependent RNA polymerase, 【초록키워드】 pandemic, molecular docking, Toxicity, Virtual screening, ZINC database, ADME, drug-likeness, Health, drug target, RdRP, predict, SARS-CoV-2 replication, compounds, Amino acid, fidaxomicin, Interaction, Analysis, Structural analysis, Comparative, enzyme, Compound, scientist, drug candidate, effective inhibitor, hotspot, inhibitory, feature, effective, rifabutin, addition, complexes, computational approach, effective drug, prevalence of COVID-19, Rifapentine, 【제목키워드】 molecular docking, prediction, inhibitor, approach,