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

2020 Fiscal Year Final Research Report

• 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
• Keywords: 機械学習 / SVM / Gタンパク共役型受容体 / GPCR / 神経ペプチド

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.

Free Research Field

バイオインフォマティクス

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。