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Article: Binding affinity between coronavirus spike protein and human ACE2 receptor

TitleBinding affinity between coronavirus spike protein and human ACE2 receptor
Authors
KeywordsBinding affinity
Coronavirus
Human ACE2
Receptor use
Spike protein
Issue Date16-Jan-2024
PublisherElsevier
Citation
Computational and Structural Biotechnology Journal, 2024, v. 23, p. 759-770 How to Cite?
AbstractCoronaviruses (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.
Persistent Identifierhttp://hdl.handle.net/10722/364185

 

DC FieldValueLanguage
dc.contributor.authorShum, Marcus Ho Hin-
dc.contributor.authorLee, Yang-
dc.contributor.authorTam, Leighton-
dc.contributor.authorXia, Hui-
dc.contributor.authorChung, Oscar Lung Wa-
dc.contributor.authorGuo, Zhihong-
dc.contributor.authorLam, Tommy Tsan Yuk-
dc.date.accessioned2025-10-25T00:35:21Z-
dc.date.available2025-10-25T00:35:21Z-
dc.date.issued2024-01-16-
dc.identifier.citationComputational and Structural Biotechnology Journal, 2024, v. 23, p. 759-770-
dc.identifier.urihttp://hdl.handle.net/10722/364185-
dc.description.abstractCoronaviruses (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.-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofComputational and Structural Biotechnology Journal-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectBinding affinity-
dc.subjectCoronavirus-
dc.subjectHuman ACE2-
dc.subjectReceptor use-
dc.subjectSpike protein-
dc.titleBinding affinity between coronavirus spike protein and human ACE2 receptor-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1016/j.csbj.2024.01.009-
dc.identifier.scopuseid_2-s2.0-85184780903-
dc.identifier.volume23-
dc.identifier.spage759-
dc.identifier.epage770-
dc.identifier.eissn2001-0370-
dc.identifier.issnl2001-0370-

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