Conclusions
In conclusion, this study unraveled key molecular traits underlying the higher affinity of nCOV-2019 for ACE2 compared to SARS-COV and unveiled critical residues for the interaction by in silico alanine scanning mutations and binding free energy calculations. The higher affinity of nCOV-2019 to binding with ACE2 correlates with higher human-to-human transmissibility of nCOV-2019 compared to SARS-COV. Ala-scanning mutagenesis of the interface residues of nCOV-2019 RBM has shed light on the crucial interface residues and helped obtain an atomic-level understanding of the interaction between coronavirus and the receptor ACE2 on the host cell. MD simulations on RBD mutations found in strains of nCOV-2019 from different countries aid in the understanding of how these mutations can play an important role in viral infection with ACE2 attachment. In addition to previously reported residues, it was found that residue F486 locating in L3 plays a crucial role in the dynamic stability of the complex by a π-stacking interaction with ACE2. Per-residue free energy decomposition pinpoints the critical role of residues K417, Y505, Q498, and Q493 in binding ACE2. Alanine scanning of interface residues in nCOV-2019 RBD showed that alanine substitution at some residues such as G502, K417, and L455 can significantly decrease the binding affinity of the complex. Moreover, mutation T478I, which is one of the most probable mutations in RBD of nCOV-2019 is found to bind ACE2 with about 7 kcal/mol higher affinity than wild-type. It is also alerting that some of the alanine substitutions at residues G446, G447, and Y489 substantially increased the binding affinity that may lead to a strong RBD attachment to ACE2 and influence the infection virulence. However, details of interaction between these mutants and ACE2 should be carefully studied using experimental techniques. On the other hand, most mutations are found not to impact the binding affinity of RBD with ACE2 in nCOV-2019 which could have implications for vaccine design endeavors as these mutations could act as antibody escape mutants. Receptor recognition is the first line of attack for coronavirus and this study gives novel insights into key structural features of interface residues for the advancement of effective therapeutic strategies to stop the coronavirus pandemic.