the PDB. We tried to provide a simple user interface to observe the ‘real’ binding sites, by simultaneously consid- ering multiple binding states of individual proteins at the residue level, and not just for protein domains but for entire protein chains. PiSite also provides a list of ‘sociable proteins’, proteins with multiple binding states and multi- ple binding partners, which are considered as the key molecules in protein interaction networks. It should be noted that the sociable proteins are somewhat diﬀerent from the so-called hub proteins, because the so-called hub proteins, which are usually deﬁned as proteins with multiple binding partners in a protein interaction network obtained by large-scale experiments (20–23), are some- times the subunits of a supermolecule (6). Furthermore, PiSite provides up-to-date statistics of protein interfaces. PiSite will be periodically updated every 3 months, using the most recent version of the PDB. CONSTRUCTION METHOD Data set The current version of PiSite was constructed from the PDB entries as of July 2008. We did not use the asymmetric unit of the coordinates, but employed the bio- logical units distributed by RCSB, to eliminate the crys- tallographic interfaces (ftp://ftp.rcsb.org/pub/pdb/data/ biounit/coordinates). All protein chains with more than 30 residues were considered as proteins and we excluded the entries with >5.0 A˚ resolution and the models with only Ca coordinates. As a result, we selected 110 325 pro- tein chains from the 51 482 PDB entries in our data set. Nucleic Acids Research, 2009, Vol. 37, Database issue D361 Mapping The binding sites that appeared in the PDB were gathered by mapping from all complexes to each protein chain (Fig. 1). For this purpose, at ﬁrst, a similarity search by BLAST (24) against all protein chains in the data set was carried out for each protein chain. Ideally, the exact match of the amino acid sequence may be suﬃcient to ﬁnd other complex structures in the PDB, but to enlarge the complex information and to avoid minor errors in sequence records due to missing residues and/or modiﬁcations, the proteins with sequence identity >90% and with coverage of the smaller protein >80% were used to select the entries for mapping. Then, mapping of the binding sites from one complex to a query chain was performed according to the BLAST alignment. The identiﬁcation of the binding site residues was achieved by the distance criteria: when the minimum distance between the atoms in a residue pair was <4.0 A˚, then the pair of residues was deﬁned as con- tact residues. If the number of contacting residues between a pair of proteins was less than two, then the pair of protein chains was not used for mapping. It should be noted that we sometimes refer to the similar proteins used for the mapping as similar proteins for simplicity, but our focus is not to analyze the interfaces among the family members, in contrast to other protein–protein databases. Definition of the binding state By selecting similar entries, as mentioned, we can enumer- ate all complexes containing the protein chain being con- sidered, and can identify all of the binding partners that interact with the considering protein chain. The binding Figure 1. An explanation of residue mapping. The upper panel shows a schematic representation of residue mapping, and the lower panel shows an example of the mapping by using 3D models. In the example, the GTP binding protein RAN (PDB: 1byu, chain A) was used. The gray, light blue, purple, green, blue and red chains were taken from 1byuB, 1a2kD, 1ibrB, 1k5gKL and 1l1mB, respectively (the four letter code indicates the PDB ID and the ﬁfth letter means the chain ID).