Access

TOP    Research    AI for Science Platform Division    Past Research Units    Life and Medical Science Application Interface Platform Development Unit (Sugita)

Life and Medical Science Application Interface Platform Development Unit (Sugita)

Japanese

Unit Leader  Yuji SUGITA

2024
Unit Leader, Life and Medical Science Application Interface Platform Development Unit, AI for Science Platform Division, R-CCS, RIKEN (-present)
2024
Deputy Director, R-CCS, RIKEN (-present)
2012
Chief Scientist, RIKEN Theoretical Molecular Science Laboratory (-present)
2011
Team Leader, Laboratory of Biomolecular Function Simulation, RIKEN QBiC (-present)
2010
Team Leader, Computational Biophysics Research Team, AICS (renamed R-CCS in 2018), RIKEN (-present)
2007
Associate Chief Scientist, RIKEN Theoretical Biochemistry Laboratory
2002
Lecturer, Institute of Molecular and Cellular Biosciences, The University of Tokyo
1998
Research Associate, Institute for Molecular Science
1998
Ph. D (Chemistry), Graduate School of Science, Kyoto University

Research summary

The structure and dynamics of biomacromolecules are not only crucial for maintaining life activities but are also related to diseases, making their detailed observation important. We are developing AI-based technologies to combine image data obtained from advanced experimental methods such as High-Speed AFM, Cryo-EM/ET, and state-of-the-art microscopy techniques with the three-dimensional structures of biomacromolecules. Additionally, we are developing application interfaces and workflow technologies to integrate measurement data with molecular structures and dynamics. Furthermore, we are developing an application interface platform to connect software developed for scientific research using high-performance computing with AI.

Representative papers

  • J. Jung, K. Yagi, C. Tan, H. Oshima, T. Mori, I.Yu, Y. Matsunaga,C. Kobayashi, S. Ito, D. Ugarte La Torre, Y. Sugita
    "GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and QM/MM models",
    J. Phys. Chem. B. (2024) in press.
  • J. Jung, C. Tan, Y. Sugita
    "GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems",
    Nature Comm. 15, 3370 (2024)
  • C. Tan, J. Jung, C. Kobayashi, D. Ugarte, S. Takada, Y. Sugita
    "Implementation of residue-level coarse-grained models I GENESIS for large-scale molecular dynamics simulations",
    PLoS Comp. Biol. 18, e1009578 (2022)
  • Y. Matsunaga, M. Kamiya, H. Oshima, J. Jung, S. Ito, and Y. Sugia*
    “Use of multistate Bennett acceptance ratio method for free-energy calculations from enhanced sampling and free-energy perturbation”,
    Biophysical Reviews 14, 1503-1512 (2022).
  • Y. Matsunaga, and Y. Sugita*
    “Use of single-molecule time-series data for refining conformational dynamics in molecular simulations”,
    Current Opinion in Structural Biology 61, 153-159 (2020).
  • Y. Matsunaga, and Y. Sugita*,
    “Linking time-series of single-molecule experiments with molecular dynamics simulations by machine learning”,
    eLife 7, e32668 (2018).
  • Y. Matsunaga, and Y. Sugita*,
    “Refining Markov State Models for conformational dynamics using ensemble-averaged data and time-series trajectories”,
    The Journal of Chemical Physics 148, 241731 (2018).

Related Websites

Computational Biophysics Research Team