Abstract
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.
Funder
H2020 European Research Council
Fonds Wetenschappelijk Onderzoek
Publisher
Springer Science and Business Media LLC
Subject
Cell Biology,Molecular Biology
Reference24 articles.
1. Waman VP, Sen N, Varadi M, Daina A, Wodak SJ, Zoete V, et al. The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies. Brief Bioinformatics. 2020;5:536.
2. Bio2Byte group. Bio2Byte SARS-CoV-2 [Internet]. [cited 2020 Dec 29]. Available from: http://sars2.bio2byte.be/
3. Cilia E, Pancsa R, Tompa P, Lenaerts T, Vranken WF. From protein sequence to dynamics and disorder with DynaMine. Nat Commun. 2013;4(1):2741. https://doi.org/10.1038/ncomms3741.
4. Cilia E, Pancsa R, Tompa P, Lenaerts T, Vranken WF. The DynaMine webserver: predicting protein dynamics from sequence. Nucleic Acids Res. 2014;42(W1):W264–70. https://doi.org/10.1093/nar/gku270.
5. Raimondi D, Orlando G, Pancsa R, Khan T, Vranken WF. Exploring the sequence-based prediction of folding initiation sites in proteins. Sci Rep. 2017;7(1):8826. https://doi.org/10.1038/s41598-017-08366-3.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献