Shigeyuki Matsumoto

The paper introduces aBCC, a machine learning-based metric for evaluating ligand coordinate-density consistency in crystallographic structures across different resolutions.

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.

The paper converts an agonistic anti-TNFR2 biparatopic antibody into an antagonist by inserting peptide linkers into the hinge region, altering its immunocomplex formation.

The paper introduces cryoMDM, a method that estimates 3D atomic models from single cryoEM particle images by matching them to simulated structural models, revealing intermediate structures of the SARS-CoV-2 spike protein.

This study uses molecular dynamics to analyze inhibitor binding to DHFR, showing that reduced activity correlates with multiple-bound states on the protein surface.

This paper introduces DEFMap, a deep learning method that extracts dynamics information from cryo-EM maps, achieving results comparable to molecular dynamics simulations and experimental approaches.