Examining sialic acid derivatives as potential inhibitors of SARS-CoV-2 spike protein receptor binding domain

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) has been the primary reason behind the COVID-19 global pandemic which has affected millions of lives worldwide. The fundamental cause of the infection is the molecular binding of the viral spike protein receptor binding domain (SP-RBD) with the human cell angiotensin-converting enzyme 2 (ACE2) receptor. The infection can be prevented if the binding of RBD-ACE2 is resisted by utilizing certain inhibitors or drugs that demonstrate strong binding affinity towards the SP RBD. Sialic acid based glycans found widely in human cells and tissues have notable propensity of binding to viral proteins of the coronaviridae family. Recent experimental literature have used N-acetyl neuraminic acid (Sialic acid) to create diagnostic sensors for SARS-CoV-2, but a detailed interrogation of the underlying molecular mechanisms is warranted. Here, we perform all atom molecular dynamics (MD) simulations for the complexes of certain Sialic acid-based molecules with that of SP RBD of SARS CoV-2. Our results indicate that Sialic acid not only reproduces a binding affinity comparable to the RBD-ACE2 interactions, it also assumes the longest time to dissociate completely from the protein binding pocket of SP RBD. Our predictions corroborate that a combination of electrostatic and van der Waals energies as well the polar hydrogen bond interactions between the RBD residues and the inhibitors influence free energy of binding.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-CoV-2
• molecular docking
• potential of mean force
• molecular dynamics
• protein-ligand

Acknowledgements

The simulations were performed on the Lehigh University LTS computing cluster, Hawk, acquired through the National Science Foundation (NSF) award OAC-2019035. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors’ and do not necessarily reflect the views of the NSF.

Author contributions

T.B. carried out all computational work described in the paper. T. B. and A. G. conducted the evaluation of the literature. T.B., A.G. and G.B wrote and edited the manuscript extensively. All authors reviewed and approved the final version of the manuscript.

Disclosure statement

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

Additional information

Funding

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