Development of a sustainable database for middle molecules using AI-driven data curation
Category
- In progress
- Database Integration Coordination Program (DICP)
- Projects funded in FY 2024-Fostering
Name and affiliation of Research Director
IKEDA Kazuyoshi
Senior Scientist, The Institute of Physical and Chemical Research, RIKEN
Outline of R&D
We will construct MIIDB-AI, an interaction database of middle molecules (peptides, non-peptides, and nucleic acids) for the purpose of accumulating information on target molecules that are difficult to discover for drug discovery. In this database, target interaction sites of middle molecules can be identified based on ligand binding site similarity data, and interactions between targets and ligands can be predicted with high accuracy using AI technology. The knowledge-based database of mid-molecules will enable efficient discovery of new mid-molecular drug candidates, and is expected to contribute to next-generation drug discovery research.
Main database(s) subject to research and development
MIIDB-AI
Period of research and development
Apr 2024 to Mar 2027
Grant Number
JPMJND2401
