International Mammalian Genome Society

The 14th International Mouse Genome Conference (2000)

C18. Construction of the Riken Mouse Protein-Protein Interaction Database

Rintaro Saito1, Kiyoshi Yoshida1, Harukazu Suzuki1, Yoshihide Hayashizaki1,2
1Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center and Genome Science Laboratory, RIKEN Tsukuba Institute,3-1-1 Koyadai, Tsukuba 305-0074, Japan

Protein-protein interactions play important roles in many phenomena such as DNA replication, transcription, metabolism, signal transduction or cell cycle control. Thus, a systematic analysis of protein-protein interaction is important approach for not only understanding cellular processes but also drug development.

Riken has developed a rapid in vivo detection system for producing protein-protein interaction panel which enables us to examine more than 1,000,000 combinations per day(Suzuki, H. et al. submitting). To store and administrate large amount of assay data and interaction data, we are currently developing Riken Mouse Protein-Protein Interaction Database.

The database is implemented as a relational database and it is composed of 3 main tables which describes protein information, protein-protein interactions, and the assay information respectively. We have deposited all the association data from our assay system. Because it is linked to Riken mouse cDNA database that consist of more than 120,000 clusters of cDNA sequences, the integrated information system is very useful to explore global genetic networks. User can search and extract interaction information by invoking SQL commands. Further, user interfaces for searching and visualization of the information is currently under development.

We are also conducting data analysis concerning to the characteristics of interacting proteins and their genes from various points of view, such as amino acid composition or base composition of their genes. We will present current interesting results. We also give some perspective on drawing signal transduction pathway using the PPI database.

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