Virtual screening of quinoline derived library for SARS-COV-2 targeting viral entry and replication

Abstract

The COVID-19 pandemic infection has claimed many lives and added to the social, economic, and psychological distress. The contagious disease has quickly spread to almost 218 countries and territories following the regional outbreak in China. As the number of infected populations increases exponentially, there is a pressing demand for anti-COVID drugs and vaccines. Virtual screening provides possible leads while extensively cutting down the time and resources required for ab-initio drug design. We report structure-based virtual screening of a hundred plus library of quinoline drugs with established antiviral, antimalarial, antibiotic or kinase inhibitor activity. In this study, targets having a role in viral entry, viral assembly, and viral replication have been selected. The targets include: 1) RBD of receptor-binding domain spike protein S 2) M^pro Chymotrypsin main protease 3) P^pro Papain protease 4) RNA binding domain of Nucleocapsid Protein, and 5) RNA Dependent RNA polymerase from SARS-COV-2. An in-depth analysis of the interactions and G-score compared to the controls like hydroxyquinoline and remdesivir has been presented. The salient results are (1) higher scoring of antivirals as potential drugs (2) potential of afatinib by scoring as better inhibitor, and (3) biological explanation of the potency of afatinib. Further MD simulations and MM-PBSA calculations showed that afatinib works best to interfere with the the activity of RNA dependent RNA polymerase of SARS-COV-2, thereby inhibiting replication process of single stranded RNA virus.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-COV-2
• RNA dependent RNA polymerase
• Bruton Tyrosine kinase inhibitors
• quinoline based FDA approved Drugs

Acknowledgements

The authors would like to thank Department of Chemistry, University of Delhi, New Delhi, India and Institute of Nuclear Medicine and Allied Sciences, Défense Research Development Organization, New Delhi, India for providing Schrodinger Software and other facilities to accomplish this work. The authors also would like to thank UGC for providing fellowship. The authors one and two have equal contribution.

Disclosure statement

The authors declare no conflict of interest.