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Shum MHH, Lee Y, Tam L, Xia H, Chung OLW, Guo Z, Lam TTY. Binding affinity between coronavirus spike protein and human ACE2 receptor. Comput Struct Biotechnol J 2024; 23:759-770. [PMID: 38304547 PMCID: PMC10831124 DOI: 10.1016/j.csbj.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 01/14/2024] [Accepted: 01/15/2024] [Indexed: 02/03/2024] Open
Abstract
Coronaviruses (CoVs) pose a major risk to global public health due to their ability to infect diverse animal species and potential for emergence in humans. The CoV spike protein mediates viral entry into the cell and plays a crucial role in determining the binding affinity to host cell receptors. With particular emphasis on α- and β-coronaviruses that infect humans and domestic animals, current research on CoV receptor use suggests that the exploitation of the angiotensin-converting enzyme 2 (ACE2) receptor poses a significant threat for viral emergence with pandemic potential. This review summarizes the approaches used to study binding interactions between CoV spike proteins and the human ACE2 (hACE2) receptor. Solid-phase enzyme immunoassays and cell binding assays allow qualitative assessment of binding but lack quantitative evaluation of affinity. Surface plasmon resonance, Bio-layer interferometry, and Microscale Thermophoresis on the other hand, provide accurate affinity measurement through equilibrium dissociation constants (KD). In silico modeling predicts affinity through binding structure modeling, protein-protein docking simulations, and binding energy calculations but reveals inconsistent results due to the lack of a standardized approach. Machine learning and deep learning models utilize simulated and experimental protein-protein interaction data to elucidate the critical residues associated with CoV binding affinity to hACE2. Further optimization and standardization of existing approaches for studying binding affinity could aid pandemic preparedness. Specifically, prioritizing surveillance of CoVs that can bind to human receptors stands to mitigate the risk of zoonotic spillover.
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Affiliation(s)
- Marcus Ho-Hin Shum
- State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Hong Kong, China
- School of Public Health, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong, China
| | - Yang Lee
- School of Public Health, The University of Hong Kong, Hong Kong, China
- Centre for Immunology and Infection (C2i), Hong Kong Science Park, Hong Kong, China
| | - Leighton Tam
- School of Public Health, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong, China
| | - Hui Xia
- Department of Chemistry, South University of Science and Technology of China, China
- Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Oscar Lung-Wa Chung
- Department of Chemistry, South University of Science and Technology of China, China
| | - Zhihong Guo
- Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Tommy Tsan-Yuk Lam
- State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Hong Kong, China
- School of Public Health, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong, China
- Centre for Immunology and Infection (C2i), Hong Kong Science Park, Hong Kong, China
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