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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 Cα 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 Cα 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. Significance statement A novel approach to predict mutation hot-spots in SARS-CoV-2 spike protein is presented. The approach introduces new topology based techniques to biophysical protein research. For a proof-of-concept the approach is described with the notorious D614G mutation of the spike protein as an example. It is shown that this mutation could have been correctly predicted by the present methods. Several additional mutation hot-spots are then identified and a number of them are shown to be topologically similar to the observed D614G mutation. The methodology can be used to design effective drugs and antibodies against the spike protein. It can also be employed more generally, whenever one needs to search for and identify mutation hot-spots in a protein.
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?:doi
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10.1101/2020.11.11.378828
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document_parses/pdf_json/7f6cd6a202d8d63ec645747c284ba871a0f3fd8b.json
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Bifurcations and mutation hot-spots in SARS-CoV-2 spike protein
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