Online biophysical predictions for SARS-CoV-2 proteins

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

doi:10.1186/s12860-021-00362-w

Abstract

BackgroundThe 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.MainWe 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.ConclusionThe 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.

Highlights

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
We here present a website [2] that provides extensive protein sequence-based predictions for the SARS-CoV-2 proteins, which can help to pinpoint previously unidentified behavior or features of these proteins that might not be captured by structural biology or molecular dynamics approaches
This approach has already shown promise in, for example, detecting remote homologues by biophysical similarity, which gives more accurate results than directly using amino acid information [10]. We apply this concept on the SARS-CoV-2 proteins by incorporating evolutionary information, so enabling us to display the biophysical variation observed in homologous proteins, which indicates likely limits of their functionally relevant biophysical behaviour (Fig. 1)

Summary

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.

Background

Utility and discussion

Conclusions