Computational Biophysics Research Team

Research summary

Main research results

The first molecular dynamics simulations of an atomistic model of the bacteria cytoplasm

Conformational dynamics of a protein or nucleic acid is often investigated with conventional MD simulations. In such an analysis, a single biomolecule is solvated in solvent water and is simulated as long as possible to examine the structure-dynamics-function relationship. As well as molecular interaction between biomolecules in cellular environments such as the cytoplasm, investigation of the biological membrane and cellular nuclei are also essential for understanding biological cellular functions. However, due to the limitations in computational resources and power of MD software, these studies have not been performed until now.

We have optimized and parallelized our MD software GENESIS for simulating large biological systems that contain more than 10 million atoms. Mycoplasma genitalium is one of the smallest bacteria whose genetic and proteomic information is abundant. Based on this information, an atomistic model of the bacteria cytoplasm with its many proteins, RNAs, ribosomes, ions, metabolites like ATP, and water molecules was built, and was then simulated using GENESIS on the K computer. The detailed trajectory analysis produced new insights into protein stability, diffusion, and specific and nonspecific interactions in the cytoplasmic environments. Biomolecular simulations in cellular environments are expected to contribute not only to the life sciences but also to new drug discoveries.

Computer simulation of an atomistic model of the bacteria cytoplasm

Representative papers

• Yu, I., Mori, T., Ando, T., Harada, R., Jung, J., Sugita, Y., and Feig, M.:
  "Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm"
  eLife, 5, e19274 (2016).
• Jung, J., Naruse, A., Kobayashi, C., and Sugita, Y.:
  "Graphics Processing Unit Acceleration and Parallelization of GENESIS for Large-Scale Molecular Dynamics Simulations"
  J. Chem. Theory Comput. 12, 4947-4958 (2016).
• Matsunaga, Y., Komuro, Y., Kobayashi, C., Jung, J., Mori, T., and Sugita, Y.:
  "Dimensionality of Collective Variables for Describing Conformational Changes of a Multi-Domain Protein"
  J. Phys. Chem. Lett. 7, 1446-1451 (2016).
• Kobayashi, C., Matsunaga, Y., Koike R., Ota M., and Sugita Y.:
  "Domain Motion Enhanced (DoME) Model for Efficient Conformational Sampling of Multidomain Proteins"
  J. Phys. Chem. B 119, 14584-14593 (2015).
• Jung J., Kobayashi C., Imamura T., and Sugita Y.:
  "Parallel implementation of 3D FFT with volumetric decomposition schemes for efficient molecular dynamics simulations"
  Comp. Phys. Comm 200, 57-65 (2015).
• Fujisaki H., Moritsugu K., Matsunaga Y., Morishita T., and Maragliano L.:
  "Extended phase-space methods for enhanced sampling in molecular simulations: a review"
  Front. Bioeng. Biotechnol. (2015). doi: 10.3389/fbioe.2015.00125
• Matsunaga Y., Kidera A., and Sugita Y.:
  "Sequential data assimilation for single-molecule FRET photon-counting data"
  J. Chem. Phys. 142, 214115 (2015).
• Galvelis R., and Sugita Y.:
  "Replica State Exchange Metadynamics for Improving the Convergence of Free Energy Estimates"
  J. Comp. Chem. 36, 1446-1455 (2015).
• Jung J., Mori T., Kobayashi C., Matsunaga Y., Yoda T., Feig M., and Sugita Y.:
  "GENESIS: A hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations"
  WIREs Comp. Mol. Sci. 5, 310-323 (2015).
• Feig M., Harada R., Mori T., Yu I., Takahashi K., and Sugita Y.:
  "Complete Atomistic Model of a Bacterial Cytoplasm for Integrating Physics Biochemistry, and Systems Biology"
  J. Mol. Graph. Modeling 58, 1-9 (2015).

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