Drug Discovery Molecular Simulation Platform Unit | RIKEN BDR

Drug Discovery Molecular Simulation Platform Unit

Unit Leader

Makoto TaijiD.Sci.

Photo of principal investigator

  • Location:Osaka / Quantitative Biology Buildings
  • E-mail:taiji[at]riken.jpPlease replace [at] with @.

Research Summary

This unit aims to use leading computational technologies using large-scale, high-speed supercomputers for in silico drug discovery. In particular, we are focusing on molecular simulation technologies to predict high-precision binding affinity, taking into account the dynamics of complex structures consisting of proteins and other low molecular compounds while in aqueous solution for better estimations on binding affinities and other drug efficacy parameters. Such studies will help identify drug behavior at the molecular level and help predict what structural formulas make for highly effective and selective drug candidates.

Research Theme

  • Large-scale, high-speed super computing for in silico drug discovery
  • In silico screening of drug compounds for protein targets
  • Developing of high affinity compounds based on the simulations from (2)

Main Publications List

  • Okimoto N, Suenaga A, Taiji M.
    Evaluation of protein–ligand affinity prediction using steered molecular dynamics simulations.
    Journal of Biomolecular Structure and Dynamics 35(15). 1-11 (2016) doi: 10.1080/07391102.2016.1251851
  • Yamagishi J, Okimoto N, Morimoto G, Taiji M.
    A New Set of Atomic Radii for Accurate Estimation of Solvation Free Energy by Poisson-Boltzmann Solvent Model.
    Journal of Computational Chemistry 35(29). 2132-2139 (2014) doi: 10.1002/jcc.23728
  • Kondo HX, Okimoto N, Morimoto G, Taiji M.
    Free-Energy Landscapes of Protein Domain Movements upon Ligand Binding.
    Journal of Physical Chemistry B 115(23). 7629-7636 (2011) doi: 10.1021/jp111902t
  • Okimoto N, Futatsugi N, Fuji H, et al.
    High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations.
    Plos Computational Biology 5(10). e1000528 (2009) doi: 10.1371/journal.pcbi.1000528
  • Suenaga A, Takada N, Hatakeyama M, et al.
    Novel mechanism of interaction of p85 subunit of phosphatidylinositol 3-kinase and ErbB3 receptor-derived phosphotyrosyl peptides.
    Journal of Biological Chemistry 280(2). 1321-1326 (2005) doi: 10.1074/jbc.M410436200
  • Suenaga A, Hatakeyama M, Ichikawa M, et al.
    Molecular dynamics, free energy, and SPR analyses of the interactions between the SH2 domain of grb2 and ErbB phosphotyrosyl peptides.
    Biochemistry 42(18). 5195-5200 (2003) doi: 10.1021/bi034113h