Structural insight into the binding interactions of NTPs and nucleotide analogues to RNA dependent RNA polymerase of SARS-CoV-2

Abstract

RNA dependent RNA polymerase (RdRP) from positive-stranded RNA viruses has always been a hot target for designing of new drugs. Major class of drugs that are targeted against RdRP are nucleotide analogues. Extensive docking and molecular dynamics study describing the binding of natural nucleotides (NTPs) and its analogues leading to significant structural variation in the RdRP has been presented here. RdRP simulations in its apo, NTP-bound, and analogue-bound form have been performed. Nucleotide analogues included in this study were, favipiravir, galidesivir, lamivudine, ribavirin, remdesivir and sofosbuvir. The conformational flexibility of the RdRP molecule has been explored using principal component (PCA) and Markov state modeling (MSM) analysis. PCA inferred the presence of correlated motions among the conserved motifs of RdRP. Inter-domain distances between the finger and thumb subdomain flanking the nascent RNA template entry site sampled open and closed conformations. The ligand and template binding motifs F and G showed negatively correlated motions. K551, R553, and R555, a part of motif F appear to form strong interactions with the ligand molecules. R836, a primer binding residue was observed to strongly bind to the analogues. MSM analysis helped to extract statistically distinct conformations explored by the RdRP. Ensemble docking of the ligands on the Markov states also suggested the involvement of the above residues in ligand interactions. Markov states obtained clearly demarcated the open/closed conformations of the template entry site. These observations on residues from the conserved motifs involved in binding to the ligands may provide an insight into designing new inhibitors.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-CoV-2
• remdesivir
• favipiravir
• galidesivir
• sofosbuvir

Acknowledgements

The authors would like to acknowledge the National Supercomputing Mission, Ministry of Electronics and Information Technology (MeitY), Government of India for funding for this work. The authors would also like to thank the National PARAM Supercomputing Facility (NPSF) and Bioinformatics Resource and Applications Facility (BRAF) at Centre for Development of Advanced Computing (C-DAC), Pune for providing the computational infrastructure.

Disclosure statement

There are no conflicts of interest to declare.