Modelling SARS-CoV-2 spike-protein mutation effects on ACE2 binding.

Area of Science:

• Computational biology
• Virology
• Structural biology

Background:

• The SARS-CoV-2 spike (S)-protein's binding affinity to human ACE2 is crucial for viral infectivity.
• Understanding mutations in the S-protein is key to tracking and predicting concerning SARS-CoV-2 variants.

Purpose of the Study:

• To computationally screen SARS-CoV-2 S-protein mutations for their impact on ACE2 binding affinity.
• To assess if mutations in major variants maintain or alter viral binding compared to random mutations.

Main Methods:

• Utilized a computational protocol based on cryo-electron microscopy structures.
• Estimated binding affinity changes (ΔΔGbind) for all possible S-protein mutations across 21 complexes.
• Employed mutation group comparisons to minimize systematic errors in predictions.

Main Results:

• The study found that mutations in major SARS-CoV-2 variants, as a group, significantly maintain ACE2 binding affinity more than random mutations.
• Omicron variant mutations showed a modest change in binding affinity compared to other major variants.
• Single-mutation effects suggest Omicron's ACE2 binding is maintained despite other evolutionary pressures.

Conclusions:

• Computational prediction of SARS-CoV-2 evolution is challenging but feasible using large-scale data and group comparisons.
• The findings provide insights into viral evolution and offer a pathway to improve computational models for variant assessment.
• Further research should consider epistasis, glycosylation, and in vivo conditions for more accurate predictions.