Published online 1 December 2011 Nucleic Acids Research, 2012, Vol. 40, Database issue D541–D548 doi:10.1093/nar/gkr1130 PoSSuM: a database of similar protein–ligand binding and putative pockets Jun-Ichi Ito1,2, Yasuo Tabei3, Kana Shimizu 2 , Koji Tsuda2,3 and Kentaro Tomii1,2,* 1Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, 2Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064 and 3Minato Discrete Structure Manipulation System Project, ERATO, Japan Science and Technology Agency, Sapporo 060-0814, Japan Received August 22, 2011; Revised October 31, 2011; Accepted November 8, 2011 ABSTRACT Numerous potential ligand-binding sites are avail- able today, along with hundreds of thousands of known binding sites observed in the PDB. Exhaustive similarity search for such vastly numerous binding site pairs is useful to predict protein functions and to enable rapid screening of target proteins for drug design. Existing databases of ligand-binding sites offer databases of limited scale. For example, SitesBase covers only 33 000 known binding sites. Inferring protein function and drug discovery purposes, however, demands a much more comprehensive database including known and putative-binding sites. Using a novel al- gorithm, we conducted a large-scale all-pairs simi- larity search for 1.8 million known and potential binding sites in the PDB, and discovered over 14 million similar pairs of binding sites. Here, we present the results as a relational database Pocket Similarity Search using Multiple-sketches (PoSSuM) including all the discovered pairs with an- notations of various types. PoSSuM enables rapid exploration of similar binding sites among struc- tures with different global folds as well as similar ones. Moreover, PoSSuM is useful for predicting the binding ligand for unbound structures, which provides important clues for characterizing protein structures with unclear functions. The PoSSuM database is freely available at http://possum.cbrc .jp/PoSSuM/. INTRODUCTION With the rapid growth in the number of solved protein structures, mainly as a result of structural genomics projects, the need for automated methods to predict protein functions from structures has become increasingly important. In many cases, proteins exhibit their biological functions by interacting with other molecules: so-called ligands. Therefore, ligand-binding sites can be regarded as functional units of the proteins. Their comparison is an important approach for elucidating protein functions. For that purpose, many methods have been developed during the last decade (1–6). To date, more than 70 000 protein structures have been available in the Protein Data Bank (PDB) (7), which contains hundreds of thousands of local regions binding to molecules of many kinds such as metal ions, nucleic acids, peptides and other small mol- ecules. In addition to these known binding sites, numerous potential ligand-binding sites are available through various methods of ligand-binding site prediction (8–13). Performing an exhaustive similarity search for such vast quantities of protein-binding sites provides the basis for automatic classiﬁcation of protein functions. Moreover, such a systematic understanding of protein–ligand inter- actions can be exploited for structure-based drug design. Nevertheless, existing binding site comparison methods are applicable only to small data sets such as representa- tive entries in the PDB, mainly because the time complex- ity for obtaining 3D alignment is too expensive. In many cases, the protein structure has been solved in multiple forms with a wide variety of ligands, e.g. inhibitors of different kinds. Therefore, using a representative data set results requires that the user miss such valuable samples. A reasonable strategy to retrieve similar binding sites in the PDB scale is that of employing a fast alignment-free method to detect candidates of similar binding sites ﬁrst, with subsequent application of the time-consuming 3D alignment to the candidates. To achieve that objective, ﬁngerprint-based fast similarity search approaches have been proposed recently (14–17). We have also developed an ultrafast ﬁngerprint-based method (24) that can enu- merate similar pairs from millions of binding sites in a *To whom correspondence should be addressed. Tel: +81 3 3599 8080; Fax: +81 3 3599 8081; Email: k-tomii@aist.go.jp The Author(s) 2011. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.