Publications
- ‘Molecular Optimization Using Conditional Transformer for Reaction-Aware Compound Exploration with Reinforcement Learning’ Shogo Nakamura, Nobuaki Yasuo and Masakazu Sekijima* Commun. Chem. 2025, 8, 40. Link
- ‘IEV2Mol: Molecular Generative Model Considering Protein–Ligand Interaction Energy Vectors’ Mami Ozawa, Shogo Nakamura, Nobuaki Yasuo, Masakazu Sekijima* J. Chem. Inf. Model. 2024, 64, 6969. Link
- ‘LLM Drug Discovery Challenge: A Contest as a Feasibility Study on the Utilization of Large Language Models in Medicinal Chemistry’ Kusuri Murakumo, Naruki Yoshikawa, Kentaro Rikimaru, Shogo Nakamura, Kairi Furui, Takamasa Suzuki, Hiroyuki Yamasaki, Yuki Nishigaya, Yuzo Takagi, Masahito Ohue NeurIPS 2023 AI for Accelerated Materials Design (AI4Mat) Workshop 2023. Link
- ‘Gargoyles: An Open Source Graph-Based Molecular Optimization Method Based on Deep Reinforcement Learning’ Daiki Erikawa, Nobuaki Yasuo, Takamasa Suzuki, Shogo Nakamura, and Masakazu Sekijima* ACS Omega 2023, 8, 37431–37441. Link
- ‘Transition-Metal-Free Aziridination of Alkenes with Sulfamate Esters Using tert-Butyl Hypoiodite’ Kensuke Kiyokawa*, Shogo Nakamura, and Satoshi Minakata* Heterocycles 2021, 103, 190–197. Link
- ‘Transition-Metal-Free Intramolecular C−H Amination of Sulfamate Esters and N-Alkylsulfamides’ Kensuke Kiyokawa*, Shogo Nakamura, Keisuke Jou, Kohji Iwaida, and Satoshi Minakata* Chem. Commun. 2019, 55, 11782–11785. Link
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