Stability and expression of SARS-CoV-2 spike-protein mutations

Area of Science:

• Virology
• Biophysics
• Computational Biology

Background:

• Protein fold stability is crucial for SARS-CoV-2 S-protein evolution, alongside ACE2 binding and antibody evasion.
• Limited thermodynamic stability data exist for S-protein mutants, but experimental expression data are abundant.

Purpose of the Study:

• To investigate the relationship between thermodynamic fold stability and experimental expression levels of SARS-CoV-2 S-protein mutants.
• To explore if computed stability changes correlate with experimental expression and ACE2 binding.

Main Methods:

• Computed SARS-CoV-2 S-protein fold stability using three distinct computational methods and eight protein structures.
• Analyzed correlations between computed stability changes and experimental yeast expression data from literature.
• Assessed correlations between computed stability and ACE2 binding effects.

Main Results:

• Significant positive correlations (99% confidence) were found between computed stability changes and experimental yeast expression across all methods and structures.
• Higher protein expression was consistently associated with relatively higher fold stability.
• Weaker, yet significant, correlations were observed between stability and ACE2 binding effects.

Conclusions:

• Thermodynamic fold stability is a significant factor influencing SARS-CoV-2 S-protein expression and potentially ACE2 binding.
• Simple features, possibly including solvent exposure, appear to largely determine functional properties of the S-protein mutant space.
• Computational tools show promise for understanding and predicting SARS-CoV-2 S-protein evolution.