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DOI 10.12688/f1000research.26359.1

Медицинская библиотека · F1000Research · 2020

Targeting SARS-CoV-2 RNA-dependent RNA polymerase: An in silico drug repurposing for COVID-19.

Baby Krishnaprasad, Maity Swastika, Mehta Chetan H, Suresh Akhil, Nayak Usha Y, Nayak Yogendra

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Аннотация

Background

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), took more lives than combined epidemics of SARS, MERS, H1N1, and Ebola. Currently, the prevention and control of spread are the goals in COVID-19 management as there are no specific drugs to cure or vaccines available for prevention. Hence, the drug repurposing was explored by many research groups, and many target proteins have been examined. The major protease (M pro), and RNA-dependent RNA polymerase (RdRp) are two target proteins in SARS-CoV-2 that have been validated and extensively studied for drug development in COVID-19. The RdRp shares a high degree of homology between those of two previously known coronaviruses, SARS-CoV and MERS-CoV.

Methods

In this study, the FDA approved library of drugs were docked against the active site of RdRp using Schrodinger's computer-aided drug discovery tools for in silico drug-repurposing.

Results

We have shortlisted 14 drugs from the Standard Precision docking and interaction-wise study of drug-binding with the active site on the enzyme. These drugs are antibiotics, NSAIDs, hypolipidemic, coagulant, thrombolytic, and anti-allergics. In molecular dynamics simulations, pitavastatin, ridogrel and rosoxacin displayed superior binding with the active site through ARG555 and divalent magnesium.

Conclusion

Pitavastatin, ridogrel and rosoxacin can be further optimized in preclinical and clinical studies to determine their possible role in COVID-19 treatment.

Для цитирования: Baby Krishnaprasad, Maity Swastika, Mehta Chetan H, Suresh Akhil, Nayak Usha Y, Nayak Yogendra. Targeting SARS-CoV-2 RNA-dependent RNA polymerase: An in silico drug repurposing for COVID-19.. F1000Research. 2020. DOI: 10.12688/f1000research.26359.1.

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