Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.11.11.378828v1?rss=1

Authors: Niemi, A. J., Peng, X.

Abstract:

The spike protein is a most promising target for the development of vaccines and therapeutic drugs against the SARS-CoV-2 infection. But the apparently high rate of mutations makes the development of antiviral inhibitors a challenge. Here a methodology is presented to try and predict mutation hot-spot sites, where a small local change in spike protein's structure can lead to a large scale conformational effect, and change the protein's biological function. The methodology starts with a systematic physics based investigation of the spike protein's C backbone in terms of its local topology. This topological investigation is then combined with a statistical examination of the pertinent backbone fragments; the statistical analysis builds on a comparison with high resolution Protein Data Bank (PDB) structures. Putative mutation hot-spot sites are identified as proximal sites to bifurcation points that can change the local topology of the C backbone in an essential manner. The likely outcome of a mutation, if it indeed occurs, is predicted by a comparison with residues in best-matching PDB fragments together with general stereochemical considerations. The detailed methodology is developed using the already observed D614G mutation as an example. This is a mutation that could have been correctly predicted by the present approach. Several additional examples of potential hot-spot residues are identified and analyzed in detail, some of them are found to be even better candidates for a mutation hot-spot than D614G.

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