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Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants

View ORCID ProfileNatália Teruel, View ORCID ProfileOlivier Mailhot, View ORCID ProfileRafael Josef Najmanovich
doi: https://doi.org/10.1101/2020.12.16.423118
Natália Teruel
1Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal
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Olivier Mailhot
1Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal
2Institute for Research in Immunology and Cancer (IRIC), Faculty of Medicine, Université de Montréal
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Rafael Josef Najmanovich
1Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal
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  • ORCID record for Rafael Josef Najmanovich
  • For correspondence: rafael.najmanovich@umontreal.ca
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Abstract

The SARS-CoV-2 Spike protein needs to be in an open-state conformation to interact with ACE2 and facilitate viral entry. We utilise coarse-grained normal-mode analyses to model the dynamics of Spike and calculate transition probabilities between states for 17081 variants including experimentally observed variants. Our results correctly model an increase in open-state occupancy for the more infectious D614G via an increase in flexibility of the closed-state and decrease of flexibility of the open-state. We predict the same effect for several mutations on Glycine residues (404, 416, 504, 252) as well as residues K417, D467 and N501, including the N501Y mutation recently observed. This is, to our knowledge, the first use of normal-mode analysis to model conformational state transitions and the effect of mutations thereon. The specific mutations of Spike identified here may guide future studies to increase our understanding of SARS-CoV-2 infection mechanisms and guide public health in their surveillance efforts.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • 1. We placed figures within the text. 2. We fixed a typo on the name of one of the authors in the manuscript file. 3. We split Table 1 into Table 1 and Table S3 4. Added missing information to the acknowledgment section

  • https://github.com/nataliateruel/data_Spike

  • https://github.com/gregorpatof/nrgten_package

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 21, 2020.
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Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants
Natália Teruel, Olivier Mailhot, Rafael Josef Najmanovich
bioRxiv 2020.12.16.423118; doi: https://doi.org/10.1101/2020.12.16.423118
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Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants
Natália Teruel, Olivier Mailhot, Rafael Josef Najmanovich
bioRxiv 2020.12.16.423118; doi: https://doi.org/10.1101/2020.12.16.423118

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