| Project/Area Number |
25650050
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Biophysics
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| Research Institution | Japan Advanced Institute of Science and Technology |
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Principal Investigator |
Mizukami Taku 北陸先端科学技術大学院大学, 先端科学技術研究科, 助教 (50270955)
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| Project Period (FY) |
2013-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2015: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2014: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2013: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
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| Keywords | タンパク質 / 水和 / 分子動力学計算 / データマイニング / 特徴空間 / 機械学習 / 蛋白質 / 分子動力学 / ドッキング / Lasso正則化 |
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| Outline of Final Research Achievements |
The motivation of the research is 1) visualization of hydration water defined by data-mining method, and 2) estimation of hydration effect by means of solvation free energy.
We founded a system for mining water behavior by means of the mixture model from MD simulation data. It detected a strong correlation between solvation free energy and hydration water behavior that enables a prediction of free energy.
The machine learning and prediction system was build with the combination of three methods, linear model, clustering and a new descriptor that was designed by accounting the multi-body interaction between atoms. Application of the machine for the small-scale solution / molecular systems resulted in a more detailed prediction for the energies.
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