xgBoost based Interface Prediction of Specific Partner Interactions (BIPSPI) is a method for the prediction of partner-specific protein interfaces from pdb files or input sequences. BIPSPI employs Extreme Gradient Boosting (XGBoost) models trained on residue pairs of the protein complexes and a scoring function that converts pair prediction to interface residue predictions.
BIPSPI+ has been trained on two different datasets. One dataset for hetero-oligomeric interactions and another one for homo-oligomeric interactions. The rational behind is that, althouhgh the physics behind all types of interactions is the same, statistically speaking, the interfaces of homo-complexes tend to be different from the ones of hetero-complexes. Compared to version 1, that was trained only on the complexes included in the Protein-Protein Docking Benchmark version 5, our new training sets have grown one order of magnitude, offering better performace, especially for the case of homo-oligomeric interactions.
Datasets and precomputed results used for training and evaluation are available in our download section.
BIPSPI v1 is available at: https://biocomp.cnb.csic.es/bipspi1/
