Elucidation of the molecular recognition mechanism of peptide receptors in ascidians using a feature extraction method

Research Project

Project/Area Number	18K14687
Research Category	Grant-in-Aid for Early-Career Scientists
Allocation Type	Multi-year Fund
Review Section	Basic Section 43060:System genome science-related
Research Institution	Suntory Foundation for Life Sciences
Principal Investigator	Shiraishi Akira 公益財団法人サントリー生命科学財団, 生物有機科学研究所・統合生体分子機能研究部, 研究員 (50710729)
Project Period (FY)	2018-04-01 – 2021-03-31
Project Status	Completed (Fiscal Year 2020)
Budget Amount *help	¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000) Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000) Fiscal Year 2019: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000) Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Keywords	機械学習 / SVM / Gタンパク共役型受容体 / GPCR / 神経ペプチド / 特徴抽出 / 線形SVM / Substance P / MRGX2 / Neurotensin / ペプチド / 相互作用 / 特長抽出 / カタユウレイボヤ
Outline of Final Research Achievements	We have constructed a PD-incorporated SVM that predicts the interaction between peptides and GPCRs. In this study, we developed and validated a method to extract molecular recognition factors from the machine learning model with the aim of clarifying "which mutations of ligand-receptor residues are involved in the activity and how the differences in the residues contribute to the diversification of ligand-receptors in each organism”. As a result, we obtained results suggesting that multiple GPCR-peptide pairs are involved in the interaction.
Academic Significance and Societal Importance of the Research Achievements	本研究はペプチドとGPCRの相互作用機序を明らかにすることが可能な手法を開発した。それにより、単純な配列相同性や分子系統樹解析では解釈できなかった複雑な分子認識因子に基づいた生物種の多様化の仕組みの解明という、新たな学術的分野を切り開くための解析手法を確立することが出来た。