Research field (2)：
Biological, health, and medical informatics
, Pharmaceuticals - chemistry and drug development
Research keywords (8)：
SBDD
, hERG
, cheminformatics
, in silico drug discovery
, cardiotoxicity
, support vector machine
, deep learning
, machine learning
Research theme for competitive and other funds (2)：
2023 - 2026 Construction of a predictive model for antigen-antibody interaction energies using the FMO database
2013 - 2015 Drug side effect prediction based on the machine learning of small molecule-protein interaction profiles
Papers (22)：
Yosuke Nishigaya, Shohei Takase, Tatsunobu Sumiya, Ko Kikuzato, Tomohiro Sato, Hideaki Niwa, Shin Sato, Akiko Nakata, Takeshi Sonoda, Noriaki Hashimoto, et al. Discovery of Novel Substrate-Competitive Lysine Methyltransferase G9a Inhibitors as Anticancer Agents. Journal of medicinal chemistry. 2023. 66. 6. 4059-4085
Tatsuya Yoshizawa, Shoichi Ishida, Tomohiro Sato, Masateru Ohta, Teruki Honma, Kei Terayama. Selective Inhibitor Design for Kinase Homologs Using Multiobjective Monte Carlo Tree Search. Journal of chemical information and modeling. 2022. 62. 22. 5351-5360
Masataka Kuroda, Reiko Watanabe, Tsuyoshi Esaki, Hitoshi Kawashima, Rikiya Ohashi, Tomohiro Sato, Teruki Honma, Hiroshi Komura, Kenji Mizuguchi. Utilizing public and private sector data to build better machine learning models for the prediction of pharmacokinetic parameters. Drug discovery today. 2022. 103339-103339
Yasuko Koda, Shin Sato, Hirofumi Yamamoto, Hideaki Niwa, Hisami Watanabe, Chiduru Watanabe, Tomohiro Sato, Kana Nakamura, Akiko Tanaka, Mikako Shirouzu, et al. Design and Synthesis of Tranylcypromine-Derived LSD1 Inhibitors with Improved hERG and Microsomal Stability Profiles. ACS Medicinal Chemistry Letters. 2022. 13. 5. 848-854
Preparation of 4-[3-(3-pyridyl)-4-pyrazolyl]pyrimidin-2-amine derivatives as BMP-signal pathway inhibitors
Books (1)：
in silico創薬におけるスクリーニングの高速化・高精度化技術
技術情報協会 2018 ISBN:4861046882
Lectures and oral presentations (4)：
Customizing applicability domain of a machine learning model using transfer learning
(MOE Forum 2021 2021)
Development of an informatics system for predicting cardiotoxicity: 5. Quantitative model for hERG blocking small molecules based on the integrated database
(CBI Annual meeting 2018 2018)
Adverse effect prediction by random forests model using polypharmacological profile of a small compound
(CBI Annual meeting 2015 2015)
