TY - JOUR T1 - Online biophysical predictions for SARS-CoV-2 proteins JF - bioRxiv DO - 10.1101/2020.12.04.411744 SP - 2020.12.04.411744 AU - Luciano Kagami AU - Joel Roca-Martínez AU - Jose Gavaldá-García AU - Pathmanaban Ramasamy AU - K. Anton Feenstra AU - Wim Vranken Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/12/05/2020.12.04.411744.abstract N2 - 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. ER -