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Mutations Strengthened SARS-CoV-2 Infectivity.
J Mol Biol. 2020 09 04; 432(19):5212-5226.JM

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity is a major concern in coronavirus disease 2019 (COVID-19) prevention and economic reopening. However, rigorous determination of SARS-CoV-2 infectivity is very difficult owing to its continuous evolution with over 10,000 single nucleotide polymorphisms (SNP) variants in many subtypes. We employ an algebraic topology-based machine learning model to quantitatively evaluate the binding free energy changes of SARS-CoV-2 spike glycoprotein (S protein) and host angiotensin-converting enzyme 2 receptor following mutations. We reveal that the SARS-CoV-2 virus becomes more infectious. Three out of six SARS-CoV-2 subtypes have become slightly more infectious, while the other three subtypes have significantly strengthened their infectivity. We also find that SARS-CoV-2 is slightly more infectious than SARS-CoV according to computed S protein-angiotensin-converting enzyme 2 binding free energy changes. Based on a systematic evaluation of all possible 3686 future mutations on the S protein receptor-binding domain, we show that most likely future mutations will make SARS-CoV-2 more infectious. Combining sequence alignment, probability analysis, and binding free energy calculation, we predict that a few residues on the receptor-binding motif, i.e., 452, 489, 500, 501, and 505, have high chances to mutate into significantly more infectious COVID-19 strains.

Authors+Show Affiliations

Department of Mathematics, Michigan State University, MI 48824, USA.Department of Mathematics, Michigan State University, MI 48824, USA.Department of Mathematics, Michigan State University, MI 48824, USA.Department of Mathematics, Michigan State University, MI 48824, USA; Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA; Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA. Electronic address: wei@math.msu.edu.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.

Language

eng

PubMed ID

32710986

Citation

Chen, Jiahui, et al. "Mutations Strengthened SARS-CoV-2 Infectivity." Journal of Molecular Biology, vol. 432, no. 19, 2020, pp. 5212-5226.
Chen J, Wang R, Wang M, et al. Mutations Strengthened SARS-CoV-2 Infectivity. J Mol Biol. 2020;432(19):5212-5226.
Chen, J., Wang, R., Wang, M., & Wei, G. W. (2020). Mutations Strengthened SARS-CoV-2 Infectivity. Journal of Molecular Biology, 432(19), 5212-5226. https://doi.org/10.1016/j.jmb.2020.07.009
Chen J, et al. Mutations Strengthened SARS-CoV-2 Infectivity. J Mol Biol. 2020 09 4;432(19):5212-5226. PubMed PMID: 32710986.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Mutations Strengthened SARS-CoV-2 Infectivity. AU - Chen,Jiahui, AU - Wang,Rui, AU - Wang,Menglun, AU - Wei,Guo-Wei, Y1 - 2020/07/23/ PY - 2020/06/04/received PY - 2020/07/09/revised PY - 2020/07/17/accepted PY - 2020/7/28/pubmed PY - 2020/9/26/medline PY - 2020/7/26/entrez KW - COVID-19 KW - mutation KW - protein-protein interaction KW - spike protein KW - viral infectivity SP - 5212 EP - 5226 JF - Journal of molecular biology JO - J Mol Biol VL - 432 IS - 19 N2 - Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity is a major concern in coronavirus disease 2019 (COVID-19) prevention and economic reopening. However, rigorous determination of SARS-CoV-2 infectivity is very difficult owing to its continuous evolution with over 10,000 single nucleotide polymorphisms (SNP) variants in many subtypes. We employ an algebraic topology-based machine learning model to quantitatively evaluate the binding free energy changes of SARS-CoV-2 spike glycoprotein (S protein) and host angiotensin-converting enzyme 2 receptor following mutations. We reveal that the SARS-CoV-2 virus becomes more infectious. Three out of six SARS-CoV-2 subtypes have become slightly more infectious, while the other three subtypes have significantly strengthened their infectivity. We also find that SARS-CoV-2 is slightly more infectious than SARS-CoV according to computed S protein-angiotensin-converting enzyme 2 binding free energy changes. Based on a systematic evaluation of all possible 3686 future mutations on the S protein receptor-binding domain, we show that most likely future mutations will make SARS-CoV-2 more infectious. Combining sequence alignment, probability analysis, and binding free energy calculation, we predict that a few residues on the receptor-binding motif, i.e., 452, 489, 500, 501, and 505, have high chances to mutate into significantly more infectious COVID-19 strains. SN - 1089-8638 UR - https://www.unboundmedicine.com/medline/citation/32710986/Mutations_Strengthened_SARS_CoV_2_Infectivity_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0022-2836(20)30456-3 DB - PRIME DP - Unbound Medicine ER -