Computational prediction of binding affinity and structural impact of three Pakistani SARS-CoV-2 spike RBD variants on human ACE2 interaction

Abstract

Despite the current development and progress in vaccine synthesis, the transmission and infection rate of new variants of SARS-CoV-2 is still challenging in developing countries like Pakistan. Previous studies reported the transmission of new virus variants associated with the mutation in spike protein particularly in the receptor binding domain (RBD) of SARS-CoV-2 making RBD a promising target to control the infection rate. Any change in the spike RBD affects the interaction with host angiotensin-converting enzyme 2 (hACE2) receptor. These mutations in RBD assist SARS-CoV-2 entry in the host and enhance virulence and transmission rate. In the current study, we retrieved all substitution mutations in RBD of spike protein in three Pakistani SARS-CoV-2 variants from the GISAID database. Their structures were predicted via ColabFold2 and protein-protein docking was performed using HADDOCK. Interactions between docked complexes were checked by PyMOL and binding affinity (ΔG) (kcal/mol) was calculated via Prodigy server. The results of protein-protein interaction showed that the mutated hCoV-12471804 variant exhibited a higher number of interactions (202), low Z-score (−2.1), increased buried surface area (4066.4 ± 55.9), and high binding affinity (−21.3 kcal/mol) with hACE2 compared to hCoV-Wild variant. Moreover, the current study provides insights into the effects of mutations in RBD with hACE2 interaction providing deeper structural insight to understand the molecular mechanism responsible for the increased transmissibility of newly emerged SARS-CoV-2 variants. The exclusively in silico nature of this study necessitates experimental validation to definitively quantify the kinetic and thermodynamic parameters of the hACE2-RBD interaction.