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  • 标题:Computational modelling supports that dengue virus envelope antibodies can bind to SARS-CoV-2 receptor binding sites: Is pre-exposure to dengue virus protective against COVID-19 severity?
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  • 作者:Himadri Nath ; Abinash Mallick ; Subrata Roy
  • 期刊名称:Computational and Structural Biotechnology Journal
  • 印刷版ISSN:2001-0370
  • 出版年度:2021
  • 卷号:19
  • 页码:459-466
  • DOI:10.1016/j.csbj.2020.12.037
  • 出版社:Computational and Structural Biotechnology Journal
  • 摘要:The world is going through the scourge of the COVID-19 pandemic since January 2020. However, the pandemic appears to be less severe in highly dengue endemic countries. In this connection, several studies reported that sero-diagnostic tests for dengue virus (DV) yielded considerable false-positive results for SARS-CoV-2 and vice versa in dengue endemic regions, thereby indicating towards potential cross-reactivity between these two viruses. We anticipated that SARS-CoV-2 and DV might share antigenic similarity and performed computational docking studies to test this hypothesis. Our results predicted with high confidence that human DV antibodies can indeed, bind to RBD of SARS-CoV-2 Spike protein. Some of these interactions can also potentially intercept human ACE2 receptor binding to RBM. Dengue serum samples predating the COVID-19, had been found to cross-react with SARS-CoV-2 Spike and this provides direct experimental validation of our predictions. Our analysis also showed that m396 and 80R antibodies (against SARS-CoV-1) did not dock with RBM of SARS-CoV-2, a fact already proven experimentally. This confirmed reliability and robustness of our approach. So, it is highly probable that immunological memory/antibodies to DV in endemic countries may reduce the severity and spread of COVID-19. It is not known whether SARS-CoV-2 antibodies will hinder DV infections by binding to DV particles and reduce dengue incidences in the future or, augment DV infection and severity by deploying antibody-dependent enhancement.
  • 关键词:SARS-CoV-2 ; Dengue ; Serodiagnosis ; Cross-reactivity ; Computational docking
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