Abstract
We show that a Fourier-based sequence distance function is able to identify structural homologs of target sequences with high accuracy. It is shown that Fourier distances correlate very strongly with independently determined structural distances between molecules, a property of the method that is not attainable using conventional representations. It is further shown that the ability of the Fourier approach to identify protein folds is statistically far in excess of random expectation. It is then shown that, in actual searches for structural homologs of selected target sequences, the Fourier approach gives excellent results. On the basis of these results, we suggest that the global information detected by the Fourier representation is an essential feature of structure encoding in protein sequences and a key to structural homology detection.
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Scheraga, H. A., & Rackovsky, S. (2014). Homolog detection using global sequence properties suggests an alternate view of structural encoding in protein sequences. Proceedings of the National Academy of Sciences of the United States of America, 111(14), 5225–5229. https://doi.org/10.1073/pnas.1403599111
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