RT Journal Article
SR Electronic
T1 Online biophysical predictions for SARS-CoV-2 proteins
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.12.04.411744
DO 10.1101/2020.12.04.411744
A1 Kagami, Luciano
A1 Roca-Martínez, Joel
A1 Gavaldá-García, Jose
A1 Ramasamy, Pathmanaban
A1 Feenstra, K. Anton
A1 Vranken, Wim
YR 2020
UL http://biorxiv.org/content/early/2020/12/07/2020.12.04.411744.abstract
AB 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. We here present a website (http://sars2.bio2byte.be/) 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 and protein-protein interaction propensities. These predictions attempt to capture the ‘emergent’ properties of the proteins, so the inherent biophysical propensities encoded in the sequence, rather than context-dependent behaviour such as the final folded state. In addition, we provide an indication of the biophysical variation that is observed in homologous proteins, which give an indication of the limits of the functionally relevant biophysical behaviour of these proteins. With this website, we therefore hope to provide researchers with further clues on the behaviour of SARS-CoV-2 proteins.Competing Interest StatementThe authors have declared no competing interest.