Chemical Genomics Language Model toward Reliable and Explainable Compound-Protein Interaction Exploration

Takuto Koyama, Hayato Tsumura, Ryunosuke Okita, Kimihiro Yamazaki, Aki Hasegawa, Keiko Imamura, Takashi Kato, Hiroaki Iwata, Ryosuke Kojima, Haruhisa Inoue, Shigeyuki Matsumoto, Yasushi Okuno. (2026). J. Cheminform.. [ARTICLE]

Empowering Federated Learning for Robust Compound-Protein Interaction Prediction across Heterogeneous Cross-Pharma Domains

Takuto Koyama, Hiroaki Iwata, Ryosuke Kojima, Takao Otsuka, Aki Hasegawa, Hiroshi Ueda, Toshiharu Morimoto, Ryoko Sasaki, Nao Torimoto, Sei Murakami, Manabu Tojo, Teruki Honma, Shigeyuki Matsumoto, Yasushi Okuno. (2026). J. Cheminform.. [ARTICLE]

Improving ADME Prediction with Multitask Graph Neural Networks and Assessing Explainability in Lead Optimization

Shoma Ito^*, Takuto Koyama^*, Shigeyuki Matsumoto, Ryosuke Kojima, Yuji Okamoto, Masataka Kuroda, Hitoshi Kawashima, Reiko Watanabe, Tomoki Yonezawa, Takaaki Sumiyoshi, Kazuyoshi Ikeda, Kenji Mizuguchi, Hiroaki Iwata, Ryosuke Kojima, and Yasushi Okuno. (2025). J. Chem. Inf. Model.. [ARTICLE] ^*Equal contribution

Improving Compound–Protein Interaction Prediction by Self-Training with Augmenting Negative Samples

Takuto Koyama, Shigeyuki Matsumoto, Hiroaki Iwata, Ryosuke Kojima, and Yasushi Okuno. (2023). J. Chem. Inf. Model.. [ARTICLE]

HELM-BERT: Topology-aware representations for chemically modified peptides

Seungeon Lee, Takuto Koyama, Itsuki Maeda, Shigeyuki Matsumoto, Yasushi Okuno (2025). J. Chem. Inf. Model.. [IN PRESS]

kMoL: an open-source machine and federated learning library for drug discovery

Romeo Cozac, Haris Hasic, Jun Jin Choong, Vincent Richard, Loic Beheshti, Cyrille Froehlich, Takuto Koyama, Shigeyuki Matsumoto, Ryosuke Kojima, Hiroaki Iwata, Aki Hasegawa, Takao Otsuka, and Yasushi Okuno. (2025). J. Cheminform.. [ARTICLE]

Synergistic involvement of the NZF domains of the LUBAC accessory subunits HOIL-1L and SHARPIN in the regulation of LUBAC function

Yusuke Toda, Hiroaki Fujita, Koshiki Mino, Takuto Koyama, Seiji Matsuoka, Toshie Kaizuka, Mari Agawa, Shigeyuki Matsumoto, Akiko Idei, Momoko Nishikori, Yasushi Okuno, Hiroyuki Osada, Minoru Yoshida, Akifumi Takaori-Kondo, and Kazuhiro Iwai (2024). Cell Death & Disease. [ARTICLE]

Feature extraction of particle morphologies of pharmaceutical excipients from scanning electron microscope images using convolutional neural networks

Hiroaki Iwata, Yoshihiro Hayashi, Takuto Koyama, Aki Hasegawa, Kosuke Ohgi, Ippei Kobayashi, and Yasushi Okuno. (2024). Int. J. Pharm. [ARTICLE]

VGAE-MCTS: a New Molecular Generative Model combining Variational Graph Auto-Encoder and Monte Carlo Tree Search

Hiroaki Iwata, Taichi Nakai, Takuto Koyama, Shigeyuki Matsumoto, Ryosuke Kojima, and Yasushi Okuno. (2023). J. Chem. Inf. Model.. [ARTICLE]