Abstract: We developed a systematic large-scale approach to identifying protein surface regions sharing shape and residue similarity. We used a new fast structural comparison algorithm (LSC: Local Structure Comparison) to exhaustively analyze a set of functionally annotated protein patches with a larger collection of protein cavities. From a dataset of about 10.000 protein surface patches extracted from a non redundant list of PDB proteins (p-value=10-7), we collected a grand total of 65910 matches among patch pairs that were stored in the SURFACE database. The functional meaning of most of the matches could be confirmed by other established methods: the presence of the same PROSITE and ELM motifs in the sequence, the presence of the same ligand in the PDB structure, similar GO terms, common SWISS-PROT keywords, sequence similarity, same SCOP superfamily and E.C. numbers. We noticed that the fraction of matches whose functional association can be confirmed by more methods sensibly decreases with the extension of the match.