| Project/Area Number |
26830142
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
System genome science
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| Research Institution | Suntory Foundation for Life Sciences |
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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)
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| Co-Investigator(Renkei-kenkyūsha) |
OKUNO Yasushi 京都大学, 大学院医学研究科, 教授 (20283666)
SATAKE Honoo 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, 主幹研究員 (20280688)
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| Research Collaborator |
OKUDA Toshimi 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, 協力研究員
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | 機械学習 / GPCR / ペプチド / カタユウレイボヤ / ホヤ / 相互作用 / 予測 / ＧＰＣＲ / 相互作用予測 / 遺伝的アルゴリズム / Gタンパク共役型受容体 |
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| Outline of Final Research Achievements |
Genomic and peptidomic analyses have identified huge amount of peptide hormones. However, due to the throughput of their receptors screening, the functions for most of these hormones have yet to be elucidated. Here, we developed the machine learning based-prediction model including selection of features plausibly attributed to peptide-receptor interactions. To verify this prediction model, we predicted the receptors for orphan neuropeptides of Ciona intestinalis and assessed its activity. The prediction and assays for the four orphan neuropeptides newly identified their receptors. Moreover, some of these receptors were far from known peptide receptors, indicating the prediction model availability for wide range of peptides and receptors.
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