Identification of SARS-CoV-2 RNA dependent RNA polymerase inhibitors using pharmacophore modelling, molecular docking and molecular dynamics simulation approaches

Abstract

The RNA-dependent RNA polymerase (RdRp) is one of the crucial enzymes in severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) catalysing the replication of RNA, therefore acts as a potential target for antiviral drug design. The fixation of a ligand in the active site of RdRp may alter the SARS-CoV-2 life cycle. Present work aimed at identifying novel inhibitors of the SARS-CoV-2 RdRp enzyme by performing pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation (MDS). Initially, the pharmacophore model of SARS-CoV-2 RdRp was constructed and the resulting model was used to screen compounds from ChEMBL, ZINC and PubChem databases. During the investigation, 180 compounds were screened using the above model and subjected to molecular docking with RdRp. Two compounds viz. ChEMBL1276156 and PubChem135548348 showed a strong binding affinity with RdRp than its standard inhibitor, Remdesivir. Toxicity prediction of these two compounds reveals their non-toxic nature. These compounds were further subjected to MDS for 100 ns to check their stability after binding with RdRp. The MDS of RdRp-ChEMBL1276156 and RdRp-PubChem135548348 complexes show enhanced stability in comparison to the RdRp-Remdesivir complex. The average interaction energy calculated after 100 ns of MDS was −146.56 and −172.68 KJ mol⁻¹ for RdRp-CHEMBL1276156 complex and RdRp-PubChem135548348 complex, respectively, while −59.90 KJ mol⁻¹ for RdRp-Remdesivir complex. The current investigation reveals that these two compounds are potent inhibitors of SARS-CoV-2 RdRp and they could be tested in the experimental condition to evaluate their efficacy against SARS-CoV-2.

Communicated by Ramaswamy H. Sarma

Graphical Abstract

Keywords:

• SARS-CoV-2
• RdRp
• pharmacophore
• molecular docking
• CHEMBL
• zinc
• PubChem libraries

Acknowledgements

The authors are thankful to Head Department of Botany, Kumaun University, Nainital for providing the facility, space and resources for this work. The authors also acknowledge the Kumaun University, Nainital for providing high-speed internet facilities. We also extend our acknowledge to the Rashtriya Uchchattar Shiksha Abhiyan (RUSA), Ministry of Human Resource Development, Government of India to provide computational infrastructure for the establishment of Bioinformatics Centre in Kumaun University, S.S.J. Campus, Almora.

Disclosure statement

The authors declare that they have no conflict of interest.

Funding

The author(s) reported there is no funding associated with the work featured in this article.