Prediction of Interacting Protein Residues Using Sequence and Structure Data
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Identifying hotspots responsible for protein interactions with other macromolecules or drugs provides insight into functional aspects of the protein network, and is a pivotal task in systems biology and drug discovery. Here, we present the protocol for the application of a machine-learning method – Random Forest – to prediction of interacting residues in proteins, based on either the structural parameters or the primary sequence alone.
