Refinement of protein structure prediction by using simulation and database analyses
| Project/Area Number |
16K16142
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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 |
Life / Health / Medical informatics
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| Research Institution | Tohoku University |
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Principal Investigator |
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| Project Period (FY) |
2016-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2016: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | 蛋白質構造 / 構造予測 / RNA-seq / 蛋白質立体構造 / アミノ酸配列 / 水素結合 / 二次構造 / シミュレーション / リファインメント / データベース解析 / 分子動力学シミュレーション / 経験的評価関数 / 立体構造予測 |
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| Outline of Final Research Achievements |
Improving the quality of protein models generated by protein structure prediction is a challenging task that can extend the applicability of the predicted models to function prediction and drug design. In this study, known protein structures are utilized for refinement of protein structure models by comprehensively processing all the available structures. The information from known structures are aligned to the human protein sequences by sequence alignment for improving the structure models of human proteins. As applications of the model refinement methods, two genomic analyses were performed. First, amino acid insertions of human protein structures by splicing-in microexons were analyzed by using public RNA-seq data. Second, amino acid variations within the transmembrane domains of G-protein coupled receptors were summarized. The results of these analyses provide g resource for appying model refinement methods.
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Report
(3 results)
Research Products
(7 results)
