Molecular dynamics simulation study on the binding mechanism between carbon nanotubes and RNA-dependent RNA polymerase

Abstract

Carbon nanotubes (CNTs) have potential prospects in disease treatment, so it is of great significance to study CNTs as the possible inhibitors of RNA-dependent RNA polymerase (RdRp). Through the way of using the RdRp of SARS-COV-2 as a model, five armchair single-walled carbon nanotubes (SWCNTs) (namely Dn, which stands for CNTs (n, m = n), n = 3–7) and RdRp have been selected to study the interactions by means of molecular docking and molecular dynamics simulation. After five SWCNT-RdRp complex systems have been subjected to the molecular dynamics simulations of 100 ns, and Molecular Mechanics Poisson − Boltzmann Surface Area (MMPBSA) has been used to calculate the binding free energy, it is found that the binding free energy of the D6 system (-189.541 kJ/mol) is significantly higher than that of the other four systems, and most of the amino acids with strong positive effects on binding are usually basic amino acids. What’s more, in the further investigation of the specific interaction mechanism between CNT (6,6) and RdRp, it is revealed that the three amino acid residues LYS545, ARG553 and ARG555 located in the nucleoside triphosphate (NTP) entry channel all have strong effects. In addition, it is also observed that when ARG555 has been inserted into SWCNT, a stable structure will be formed, which will break the original NTP entry channel structure and inhibit virus replication. Therefore, it can be concluded that certain specific types of SWCNT, such as CNT (6,6), could be potential small molecule inhibitors in the treatment of coronavirus.

Communicated by Ramaswamy H. Sarma

Keywords:

• RdRp
• carbon nanotube
• molecular docking
• molecular dynamics simulation
• binding free energy

Author contributions

Zhaopeng Ma performed all MD simulations and analysis under the supervision of Guanglai Zhu. Zhaopeng Ma wrote the manuscript and Guanglai Zhu improved it. All authors were involved in the conceptualization and discussion of the model.

Acknowledgments

We thank Prof. Jing Cai (Anhui Normal University) for linguistic assistance during the revision of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Anhui Provincial Natural Science Foundation of China [No. 2108085MA21] and the National Natural Science Foundation of China [No. 21173002].