Structural feature extraction protocol for classifying reversible membrane binding protein domains

Machine learning based classification protocols for automated function annotation of protein structures have in many instances proven superior to simpler sequence based procedures. Here we present an automated method for extracting features from protein structures by construction of surface patches to be used in such protocols. The utility of the developed patch-growing procedure is exemplified by its ability to identify reversible membrane binding domains from the C1, C2, and PH families.