How do we respond to the next SARS CoV epidemic/pandemic? A bioinformatics approach with the promise of preventing or reducing the severity of future SARS CoV related pandemics
Abstract In this work, we develop a Bayesian weighted scheme to generate evolutionary lineages of a particular viral protein sequence of interest and through a process of clustering and choosing representative lineages from the different clusters according to an evolutionary fitness objective function, we demonstrate it is possible to have anticipated the emergence of the SARS-CoV 2 (2019) strain from the SARS-CoV 1(2004) strain and having shown this retrospectively, we discuss the possibility of applying this approach along with continuous genomic surveillance of SARS-CoVs to prevent or reduce severity of future SARS-CoV related pandemics by being prepared with broad neutralization strategies for anticipated future lineages of SARS-CoVs identified through bioinformatics approaches such as that reported in this work..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 27. März Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Geoffrey A S, Ben [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2024.03.22.586249 |
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| PPN (Katalog-ID): |
XBI043057748 |
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| 520 | |a Abstract In this work, we develop a Bayesian weighted scheme to generate evolutionary lineages of a particular viral protein sequence of interest and through a process of clustering and choosing representative lineages from the different clusters according to an evolutionary fitness objective function, we demonstrate it is possible to have anticipated the emergence of the SARS-CoV 2 (2019) strain from the SARS-CoV 1(2004) strain and having shown this retrospectively, we discuss the possibility of applying this approach along with continuous genomic surveillance of SARS-CoVs to prevent or reduce severity of future SARS-CoV related pandemics by being prepared with broad neutralization strategies for anticipated future lineages of SARS-CoVs identified through bioinformatics approaches such as that reported in this work. | ||
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