C-3-07
PoSSuM Updates and Integration With ChEMBL
For Application of Drug Reuse
Kazuyoshi Ikeda 1,2,3
ikeda@level-five.jp	  	 Kenji Mizuguchi 2
kenji@nibio.go.jp
123	  	 Jun-Ichi Ito 2
junichi@nibio.go.jp

Kentaro Tomii 3
k-tomii@aist.go.jp

Drug Discovery Informatics Group, System Solution Division, LEVEL FIVE Co.,Ltd.,
Shiodome Shibarikyu Bldg., 1-2-3 Kaigan, Minato-ku, Tokyo 105-0022, Japan.
National Institute of Biomedical Innovation, 7-6-8 Saito Asagi, Ibaraki, Osaka, Japan.
Computational Biology Research Center (CBRC), National Institute of Advanced Industrial
Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan.

Keywords: Ligand binding site, Pocket similarity, Open drug discovery data, Drug reuse, Database
PoSSuM is a large-scale database for finding similar ligand-binding sites in proteins [1], which isfreely available via our web-interface (http://possum.cbrc.jp/PoSSuM). As of Aug. 2013, PoSSuM
stores over four millions of data points including both known small molecule-binding pockets andputative ones. Detection of structurally similar sites of known small-molecule drugs gives ususeful information for rational drug design such as drug-reuse and off-target prediction. For thepurpose, we have integrated PoSSuM pocket similarity data with ChEMBL open drug discovery
data [2], and have developed a new function for supporting the user to retrieve potential binding
pockets for a given small-molecule drug, in addition to a number of improved web interfaces.
First, we selected orally bioavailable small-molecule drugs from the release of ChEMBL16, andmatched the compound structures with the latest PDB ligand structures using IUPAC standard
InChIKey. In PoSSuM, 4,282 sites where 193 unique small-molecule drugs bound were found.
Second, we annotated 3D protein-structures in PDB using the ChEMBL target information fordrugs and drug candidates, and classified the protein structures based on its drug development
stage. For this purpose, we extracted 7,547 protein-targets from ChEMBL16 and joined those tothe FDA-approved drug targets from DrugBank [3]. The protein-targets were classified into thefollowing classes: A) Approved drug targets, B) Hit-to-lead stage, C) Bioactive targets and D)Unknown. Then, we combined the drug target classification with PoSSuM pocket similarity data,and built a pipeline for automatically identifying potential new drug targets having a pocket
similar to known small-molecule drug binding sites.
We identified in total 154,191 binding sites, from 10,255 protein structures, which arestructurally similar to the focused 4,282 binding sites, covering 182 unique small-molecule drugs
deposited in ChEMBL16. Users can retrieve all of the identified similar sites and can visualize 3Dsuperpositoin between them on our new web-interface which will be available soon. We also
conducted a preliminary study to compare between PDB-scale pocket similarity and genomic-scalebioactive data for surveying relations between the similarity score and binding affinities.
In this presentation, we will show new functions of the PoSSuM database, utility forstructure-based drug design, and discuss the possibility and limitation for application of drug
discovery purpose.
[1] Ito, J., et al., PoSSuM: a database of similar protein-ligand binding and putative pockets,
Nucleic Acids Res, 40(Database issue):D541-D548. 2012.
[2] Gaulton, A., et al., ChEMBL: a large-scale bioactivity database for drug discovery, Nucleic
Acids Res, 40(Database issue):D1100–D1107. 2012.
[3] Knox C., et al., DrugBank 3.0: a comprehensive resource for 'omics' research on drugs,
Nucleic Acids Res, 39(Database issue):D1035-D1041. 2011.