Online biophysical predictions for SARS-CoV-2 proteins

Luciano Kagami, Joel Roca-Martínez, Jose Gavaldá-García, Pathmanaban Ramasamy, K. Anton Feenstra, Wim F. Vranken*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

BACKGROUND: The SARS-CoV-2 virus, the causative agent of COVID-19, consists of an assembly of proteins that determine its infectious and immunological behavior, as well as its response to therapeutics. Major structural biology efforts on these proteins have already provided essential insights into the mode of action of the virus, as well as avenues for structure-based drug design. However, not all of the SARS-CoV-2 proteins, or regions thereof, have a well-defined three-dimensional structure, and as such might exhibit ambiguous, dynamic behaviour that is not evident from static structure representations, nor from molecular dynamics simulations using these structures. MAIN: We present a website ( https://bio2byte.be/sars2/ ) that provides protein sequence-based predictions of the backbone and side-chain dynamics and conformational propensities of these proteins, as well as derived early folding, disorder, β-sheet aggregation, protein-protein interaction and epitope propensities. These predictions attempt to capture the inherent biophysical propensities encoded in the sequence, rather than context-dependent behaviour such as the final folded state. In addition, we provide the biophysical variation that is observed in homologous proteins, which gives an indication of the limits of their functionally relevant biophysical behaviour.

CONCLUSION: The https://bio2byte.be/sars2/ website provides a range of protein sequence-based predictions for 27 SARS-CoV-2 proteins, enabling researchers to form hypotheses about their possible functional modes of action.

Original languageEnglish
Article number23
Pages (from-to)1-7
Number of pages7
JournalBMC Molecular and Cell Biology
Volume22
Issue number1
DOIs
Publication statusPublished - 23 Apr 2021

Bibliographical note

Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813239, for funding of JR-M and JG-G. WV acknowledges funding by the Research Foundation Flanders (FWO) - project nr. G.0328.16 N for the development of the methodology underlying the provided predictions.

Publisher Copyright:
© 2021, The Author(s).

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Funding

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813239, for funding of JR-M and JG-G. WV acknowledges funding by the Research Foundation Flanders (FWO) - project nr. G.0328.16 N for the development of the methodology underlying the provided predictions.

FundersFunder number
Marie Skłodowska-Curie
Horizon 2020 Framework Programme813239
H2020 European Research CouncilMarie Sklodowska-Curie 813239
Fonds Wetenschappelijk OnderzoekG.0328.16N

    Keywords

    • Biophysical features
    • COVID-19
    • Proteins
    • SARS-CoV-2
    • Single sequence based predictions

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