Open Access Highly Accessed Research article

An integrative in silico approach for discovering candidates for drug-targetable protein-protein interactions in interactome data

Nobuyoshi Sugaya1*, Kazuyoshi Ikeda1, Toshiyuki Tashiro1, Shizu Takeda2, Jun Otomo2, Yoshiko Ishida2, Akiko Shiratori2, Atsushi Toyoda3, Hideki Noguchi3, Tadayuki Takeda3, Satoru Kuhara4, Yoshiyuki Sakaki3 and Takao Iwayanagi5

Author Affiliations

1 PharmaDesign, Inc., 2-19-8 Hatchobori, Chuo-ku, Tokyo, 104-0032, Japan

2 Central Research Laboratory, Hitachi, Ltd., 1-280 Higashi-koigakubo, Kokubunji-shi, Tokyo, 185-8601, Japan

3 Genomic Sciences Center, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan

4 Graduate School of Genetic Resources Technology, Kyushu University, 6-10-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581, Japan

5 Research & Development Group, Hitachi, Ltd., 1-6-1 Marunouchi, Chiyoda-ku, Tokyo, 100-8220, Japan

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BMC Pharmacology 2007, 7:10  doi:10.1186/1471-2210-7-10

Published: 20 August 2007



Protein-protein interactions (PPIs) are challenging but attractive targets for small chemical drugs. Whole PPIs, called the 'interactome', have been emerged in several organisms, including human, based on the recent development of high-throughput screening (HTS) technologies. Individual PPIs have been targeted by small drug-like chemicals (SDCs), however, interactome data have not been fully utilized for exploring drug targets due to the lack of comprehensive methodology for utilizing these data. Here we propose an integrative in silico approach for discovering candidates for drug-targetable PPIs in interactome data.


Our novel in silico screening system comprises three independent assessment procedures: i) detection of protein domains responsible for PPIs, ii) finding SDC-binding pockets on protein surfaces, and iii) evaluating similarities in the assignment of Gene Ontology (GO) terms between specific partner proteins. We discovered six candidates for drug-targetable PPIs by applying our in silico approach to original human PPI data composed of 770 binary interactions produced by our HTS yeast two-hybrid (HTS-Y2H) assays. Among them, we further examined two candidates, RXRA/NRIP1 and CDK2/CDKN1A, with respect to their biological roles, PPI network around each candidate, and tertiary structures of the interacting domains.


An integrative in silico approach for discovering candidates for drug-targetable PPIs was applied to original human PPIs data. The system excludes false positive interactions and selects reliable PPIs as drug targets. Its effectiveness was demonstrated by the discovery of the six promising candidate target PPIs. Inhibition or stabilization of the two interactions may have potential therapeutic effects against human diseases.