Computational Hot-Spot Analysis of the SARS-CoV-2 Receptor Binding Domain/ACE2 Complex*

Area of Science:

• Molecular biology
• Virology
• Computational chemistry

Background:

• SARS-CoV-2 entry into host cells relies on the interaction between its receptor-binding domain (RBD) and the ACE2 enzyme.
• Inhibiting this SARS-CoV-2 RBD/ACE2 interaction is a therapeutic target for COVID-19.
• The molecular details of this critical protein-protein interaction (PPI) are not fully understood.

Purpose of the Study:

• To computationally identify critical
• hot-spot
• residues at the SARS-CoV-2 RBD/ACE2 binding interface.
• To compare these residues with those of SARS-CoV.
• To guide the development of therapeutics that disrupt viral entry.

Main Methods:

• Utilized multiple computational platforms for predicting hot-spot residues.
• Performed computational alanine scanning mutagenesis to assess binding energy changes.
• Employed the Adaptive Poisson-Boltzmann Solver to analyze electrostatic surfaces at the PPI interface.

Main Results:

• Identified and mapped predicted hot-spot residues and clusters at the SARS-CoV-2 RBD/ACE2 interface.
• Provided a comparative analysis of hot-spot residues between SARS-CoV and SARS-CoV-2.
• Predicted significant changes in Gibbs' free energy upon mutation of key residues.

Conclusions:

• The study illuminates critical residues at the SARS-CoV-2 RBD/ACE2 binding interface.
• These findings can guide the design of novel antiviral strategies.
• Disrupting the RBD/ACE2 complex offers a potential pathway to halt COVID-19 progression.