Binding affinity between coronavirus spike protein and human ACE2 receptor.

Area of Science:

• Virology
• Biochemistry
• Computational Biology

Background:

• Coronaviruses (CoVs) present a significant public health threat due to zoonotic spillover potential.
• The CoV spike protein is critical for viral entry, mediating binding to host cell receptors like human ACE2 (hACE2).
• Understanding CoV spike protein and hACE2 interactions is vital for pandemic preparedness.

Purpose of the Study:

• To review and compare methods for studying binding interactions between CoV spike proteins and the hACE2 receptor.
• To evaluate the strengths and limitations of various quantitative and qualitative binding affinity assessment techniques.
• To highlight the role of computational and machine learning approaches in predicting CoV-hACE2 binding.

Main Methods:

• Qualitative assessment using solid-phase enzyme immunoassays and cell binding assays.
• Quantitative affinity measurement via Surface Plasmon Resonance (SPR), Bio-layer Interferometry (BLI), and Microscale Thermophoresis (MST) to determine dissociation constants (K_D).
• In silico methods including structural modeling, protein-protein docking, and binding energy calculations, alongside machine learning and deep learning models utilizing interaction data.

Main Results:

• Qualitative assays provide binding assessment but lack precise affinity quantification.
• SPR, BLI, and MST offer accurate equilibrium dissociation constant (K_D) measurements.
• In silico modeling yields variable results due to standardization issues, while ML/DL models identify key binding residues.

Conclusions:

• Standardization and optimization of binding affinity measurement techniques are crucial for enhancing pandemic preparedness.
• Prioritizing surveillance of CoVs capable of binding to human receptors can mitigate zoonotic spillover risks.
• Accurate characterization of CoV-hACE2 interactions is essential for developing countermeasures against potential pandemic threats.