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Differences between Omicron SARS-CoV-2 RBD and other variants in their ability to interact with cell receptors and monoclonal antibodies
Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil; Universidade Federal do Triângulo Mineiro, Hospital de Clínicas, Uberaba, MG, Brazil.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science. Department of Materials and Environmental Chemistry, Arrhenius Laboratory, Stockholm University, Stockholm, Sweden; State Key Laboratory of Materials-Oriented and Chemical Engineering, Nanjing Tech University, Nanjing, PR China; Centre of Advanced Research in Bionanoconjugates and Biopolymers, Petru Poni Institute of Macromolecular Chemistry, Iasi, Romania; Department of Chemical and Geological Sciences, University of Cagliari, Monserrato, Italy.ORCID iD: 0000-0001-9783-4535
Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil; Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, USA.
2023 (English)In: Journal of Biomolecular Structure and Dynamics, ISSN 0739-1102, E-ISSN 1538-0254, Vol. 41, no 12, p. 5707-5727Article in journal (Refereed) Published
Abstract [en]

SARS-CoV-2 remains a health threat with the continuous emergence of new variants. This work aims to expand the knowledge about the SARS-CoV-2 receptor-binding domain (RBD) interactions with cell receptors and monoclonal antibodies (mAbs). By using constant-pH Monte Carlo simulations, the free energy of interactions between the RBD from different variants and several partners (Angiotensin-Converting Enzyme-2 (ACE2) polymorphisms and various mAbs) were predicted. Computed RBD-ACE2-binding affinities were higher for two ACE2 polymorphisms (rs142984500 and rs4646116) typically found in Europeans which indicates a genetic susceptibility. This is amplified for Omicron (BA.1) and its sublineages BA.2 and BA.3. The antibody landscape was computationally investigated with the largest set of mAbs so far in the literature. From the 32 studied binders, groups of mAbs were identified from weak to strong binding affinities (e.g. S2K146). These mAbs with strong binding capacity and especially their combination are amenable to experimentation and clinical trials because of their high predicted binding affinities and possible neutralization potential for current known virus mutations and a universal coronavirus.

Place, publisher, year, edition, pages
Taylor & Francis, 2023. Vol. 41, no 12, p. 5707-5727
Keywords [en]
Protein-protein interactions, host-pathogen interaction, ACE2 polymorphism, molecular recognition, antibody, development, binding affinities, Covid-19, Monte Carlo
National Category
Biophysics Biochemistry and Molecular Biology Public Health, Global Health, Social Medicine and Epidemiology
Research subject
Energy Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-92153DOI: 10.1080/07391102.2022.2095305ISI: 000822640300001PubMedID: 35815535Scopus ID: 2-s2.0-85133669820OAI: oai:DiVA.org:ltu-92153DiVA, id: diva2:1683028
Funder
Swedish Research Council
Note

Validerad;2023;Nivå 2;2023-12-12 (marisr);

Funder: Fundação de Amparo à Pesquisa do Estado de São Paulo (Fapesp 2020/07158-2); Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq 305393/2020-0, PIBIC/CNPq 2020-1732); Ministry of Research and Innovation of Romania (PN-III-P4-ID-PCCF-2016-0050)

Available from: 2022-07-13 Created: 2022-07-13 Last updated: 2023-12-12Bibliographically approved

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