| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2013: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2012: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Outline of Final Research Achievements |
This study presents a high performance virtual screening method for drug design based on machine learning. In drug discovery with computers, drug designer often use docking software and decide the docking between the compound and the protein with the result of docking software, structure of the compound, and any information of compound. Currently, the performance of docking software is not high. The present method exploits the experiential knowledge of pharmaceutical researchers and allows to screen compounds with high performance based on the result of the docking software and chemical information of compounds. The experiment shows our method have high-accuracy as 98.4 % and excellent ROC curve.
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