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• W2112632190 abstract "Identifying specific hot spot residues that contribute significantly to the affinity and specificity of protein interactions is a problem of the utmost importance. We present an interactive web server, PredHS, which is based on an effective structure-based hot spot prediction method. The PredHS prediction method integrates many novel structural and energetic features with two types of structural neighborhoods (Euclidian and Voronoi), and combines random forest and sequential backward elimination algorithms to select an optimal subset of features. PredHS achieved the highest performance identifying hot spots compared with other state-of-the-art methods, as benchmarked by using an independent experimentally verified dataset. The input to PredHS is protein structures in the PDB format with at least two chains that form interfaces. Users can visualize their predictions in an interactive 3D viewer and download the results as text files. PredHS is available at http://www.predhs.org." @default.
• W2112632190 created "2016-06-24" @default.
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• W2112632190 date "2014-05-22" @default.
• W2112632190 modified "2023-09-26" @default.
• W2112632190 title "PredHS: a web server for predicting protein–protein interaction hot spots by using structural neighborhood properties" @default.
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• W2112632190 doi "https://doi.org/10.1093/nar/gku437" @default.
• W2112632190 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4086081" @default.
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