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Feature Design for Protein Interface hotspots using KFC2 and Rosetta
- Publication Year :
- 2019
- Publisher :
- Cold Spring Harbor Laboratory, 2019.
-
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.
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....2798a40b4faeba18eef9ddf19fe28e53
- Full Text :
- https://doi.org/10.1101/514372