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bioRxiv · 10.1101/514372

Feature Design for Protein Interface hotspots using KFC2 and Rosetta

Seeger, F.·Little, A.·Chen, Y.·Woolf, T.·Cheng, H.·Mitchell, J. C.
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Abstract

Protein-protein interactions regulate many essential biological processes and play an important role in health and disease. The process of experimentally charac-terizing protein residues that contribute the most to protein-protein interaction affin-ity and specificity is laborious. Thus, developing models that accurately characterize hotspots at protein-protein interfaces provides important information about how to inhibit therapeutically relevant protein-protein interactions. During the course of the ICERM WiSDM workshop 2017, we combined the KFC2a protein-protein interaction hotspot prediction features with Rosetta scoring function terms and interface filter metrics. A 2-way and 3-way forward selection strategy was employed to train support vector machine classifiers, as was a reverse feature elimination strategy. From these results, we identified subsets of KFC2a and Rosetta combined features that show improved performance over KFC2a features alone.

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Seeger, F., Little, A., Chen, Y., Woolf, T., Cheng, H., Mitchell, J. C.. 2019-01-16. Feature Design for Protein Interface hotspots using KFC2 and Rosetta. https://doi.org/10.1101/514372

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