Laboratory for Biomolecular Function Simulation
LocationKobe / Integrated Innovation Building
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In our laboratory, we carry out molecular dynamics simulations on Fugaku or other supercomputers to elucidate the relationships between structure, dynamics, and function in biomacromolecules, such as proteins, nucleic acids, glycans, and lipid molecules. We develop various free-energy calculation methods to evaluate free-energy differences between two thermodynamic states in biomacromolecules for understanding biomolecular functions more quantitatively. The developed methods are installed into GENESIS software, which is freeware and is available by everyone. We thus contribute not only to the basic life science but also to in-silico drug discovery.
- Effects of intracellular crowding on the dynamics of protein and water interactions
- Simulations and data analysis of large-scale protein structural changes
- Slow dynamics using Brownian dynamics simulations
Kasahara K, Re S, Nawrocki G, et al.
Reduced efficacy of a Src kinase inhibitor in crowded protein solution.
Nature Communications 12(1), 4099 (2021) doi: 10.1038/s41467-021-24349-5
Mori T, Jung J, Kobayashi C, et al.
Elucidation of interactions regulating conformational stability and dynamics of SARS-CoV-2 S-protein.
Biophysical Journal 120(6), 1060-1071 (2021) doi: 10.1016/j.bpj.2021.01.012
Oshima H, Re S, Sugita Y.
Prediction of Protein-Ligand Binding Pose and Affinity Using the gREST+FEP Method.
Journal of Chemical information and Modeling 60(11), 5382-5394 (2020) doi: 10.1021/acs.jcim.0c00338
Kim S, Oshima H, Zhang H, et al.
CHARMM-GUI Free Energy Calculator for Absolute and Relative Ligand Solvation and Binding Free Energy Simulations.
Journal of Chemical Theory and Computation 16(11), 7207-7218 (2020) doi: 10.1021/acs.jctc.0c00884
Re S, Oshima H, Kasahara K, et al.
Encounter Complexes and Hidden Poses of Kinase-Inhibitor Binding on the Free-Energy Landscape.
Proceedings of the National Academy of Sciences of the United States of America 116, 18404-18409 (2019) doi: 10.1073/pnas.1904707116
Oshima H, Re S, Sugita Y.
Replica-Exchange Umbrella Sampling Combined with Gaussian Accelerated Molecular Dynamics for Free-Energy Calculation of Biomolecules.
Journal of Chemical Theory and Computation 15(10), 5199-5208 (2019) doi: 10.1021/acs.jctc.9b00761
Niitsu A, Re S, Oshima H, et al.
De Novo Prediction of Binders and Nonbinders for T4 Lysozyme by gREST Simulations.
Journal of Chemical information and Modeling 59(9), 3879-3888 (2019) doi: 10.1021/acs.jcim.9b00416
Oshima H, Re S, Sakakura M, et al.
Population Shift Mechanism for Partial Agonism of AMPA Receptor.
Biophysical Journal 116(1), 57-68 (2019) doi: 10.1016/j.bpj.2018.11.3122
Re S, Watabe S, Nishima W, et al.
Characterization of Conformational Ensembles of Protonated N-glycans in the Gas-Phase.
Scientific Reports 8(1), 1644 (2018) doi: 10.1038/s41598-018-20012-0
Feig M, Yu I, Wang PH, et al.
Crowding in Cellular Environments at an Atomistic Level from Computer Simulations.
The Journal of Physical Chemistry. B 121(34), 8009-8025 (2017) doi: 10.1021/acs.jpcb.7b03570
Yu I, Mori T, Ando T, et al.
Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm.
Elife 5, e19274 (2016) doi: 10.7554/eLife.19274
Mar. 27, 2023 Research
How an early mutation in the COVID-19 virus helped it spread so fast
Apr. 28, 2022 BDR News
Four BDR scientists awarded MEXT prizes
Oct. 21, 2021 Research
Supercomputer simulations reveal how protein crowding in cells impacts interactions
Jul. 30, 2021 BDR News
RIKEN BDR signs MOU with Shinshu University for research and educational collaborations
Nov. 29, 2019 Research
Faster modeling of interactions between ligands and proteins