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
This paper introduces ChemGLaM, a chemical genomics language model for reliable and explainable compound-protein interaction predictions, achieving state-of-the-art performance and enabling drug/target exploration for ALS.
Journal of Cheminformatics · Jan 30, 2026Peer-reviewedBioinformatics