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SARS-CoV-2 Omicron BA.2.75 Variant May Be Much More Infective than Preexisting Variants Based on In Silico Model.
Sugano, Aki; Takaoka, Yutaka; Kataguchi, Haruyuki; Ohta, Mika; Kimura, Shigemi; Araki, Masatake; Morinaga, Yoshitomo; Yamamoto, Yoshihiro.
  • Sugano A; Center for Clinical Research, Toyama University Hospital, Toyama 930-0194, Japan.
  • Takaoka Y; Department of Medical Systems, Kobe University Graduate School of Medicine, Kobe 650-0017, Hyogo, Japan.
  • Kataguchi H; Department of Medical Systems, Kobe University Graduate School of Medicine, Kobe 650-0017, Hyogo, Japan.
  • Ohta M; Department of Computational Drug Design and Mathematical Medicine, Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama 930-0194, Japan.
  • Kimura S; Data Science Center for Medicine and Hospital Management, Toyama University Hospital, Toyama 930-0194, Japan.
  • Araki M; Center for Advanced Antibody Drug Development, University of Toyama, Toyama 930-0194, Japan.
  • Morinaga Y; Life Science Institute, Kobe Tokiwa University, Kobe 653-0838, Hyogo, Japan.
  • Yamamoto Y; Division of Genomics, Institute of Resource Development and Analysis, Kumamoto University, Kumamoto 860-0811, Japan.
Microorganisms ; 10(10)2022 Oct 21.
Article in English | MEDLINE | ID: covidwho-2082271
ABSTRACT
Previously, we developed a mathematical model via molecular simulation analysis to predict the infectivity of six SARS-CoV-2 variants. In this report, we aimed to predict the relative risk of the recent new variants of SARS-CoV-2 based on our previous research. We subjected Omicron BA.4/5 and BA.2.75 variants of SARS-CoV-2 to the analysis to determine the evolutionary distance of the spike protein gene (S gene) of the variants from the Wuhan variant so as to appreciate the changes in the spike protein. We performed molecular docking simulation analyses of the spike proteins with human angiotensin-converting enzyme 2 (ACE2) to understand the docking affinities of these variants. We then compared the evolutionary distances and the docking affinities of these variants with those of the variants that we had analyzed in our previous research. As a result, BA.2.75 has both the highest docking affinity (ratio per Wuhan variant) and the longest evolutionary distance of the S gene from the Wuhan variant. These results suggest that BA.2.75 infection can spread farther than can infections of preexisting variants.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Variants Language: English Year: 2022 Document Type: Article Affiliation country: Microorganisms10102090

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Variants Language: English Year: 2022 Document Type: Article Affiliation country: Microorganisms10102090