分子シミュレーションと深層学習の連携によるペプチドの高精度ドッキング予測と設計

• Project/Area Number: 21K12122
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 62010:Life, health and medical informatics-related
• Research Institution: The University of Tokyo
• Principal Investigator: 清水 謙多郎 東京大学, 農学生命科学研究科, 教授 (80178970)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Project Status: Adopted (Fiscal Year 2021)
• Budget Amount: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000); Fiscal Year 2023: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000); Fiscal Year 2022: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000); Fiscal Year 2021: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)