Mitsunori Ikeguchi

The paper identifies functional differences in feline NTCPs that determine susceptibility to hepadnavirus infection, revealing evolutionary trade-offs between viral receptor activity and bile acid transport.

The paper develops a hydrogen-bond correction to improve RNA force fields' accuracy in modeling noncanonical motifs like the MAPT A-bulge.

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

The paper introduces CoMPLip, a method that improves membrane-protein structure prediction by co-folding proteins with lipid molecules during AlphaFold 3 predictions, enhancing ligand-pose prediction and conformational sampling.

The paper introduces intDesc-AbMut, a tool to automate the analysis of antibody mutations' effects on environmental interactions, achieving high accuracy in predicting crystal-like environments.

The paper identifies a leucine-rich motif in NTCP essential for KIF4-mediated trafficking and HBV/HDV infection, revealing a conserved cargo recognition mechanism shared with integrin β1.

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 study reveals the roles of Rad51's DNA binding motifs in the catalytic process of DNA strand exchange during homologous recombination.