Masakazu Sekijima

2003-2008 Research Scientist, AIST
2008-2016 Assoc. Prof., GSIC, Tokyo Institute of Technology
2016- Unit Leader, Advanced Computational Drug Discovery Unit, Tokyo Institute of Technology

Field of Specialization
Bioinformatics / in silico Drug Discovery

Advanced Computational Drug Discovery Unit(IIR, Tokyo Tech)

Research Hub Group:Information and Artificial Intelligence Research International Hub Group

Research Highlights

  • Development of platform for efficiency of drug discovery by Machine learning, Augmented Reality, and Supercomputing and its application to search for therapeutic agents for tropical diseases.


  • Aug. 2017: Efficient combination of drug discovery and IT, Nikkei Shimbun
  • Apr. 2016: The next generation of leaders, Nikkei Sangyo Shimbun
  • Apr. 2016: Business and university seriously cooperate, Nikkan Kogyo Shimbun

Selected Awards

  • 2017 SIGBIO Achievement Award 2017 by SIGBIO, IPSJ
  • 2014 Young Researcher’s Award 2014 by IIBMP

Selected Publications

  • N. Wakui et al., “Exploring the selectivity of inhibitor complexes with Bcl-2 and Bcl-XL: a molecular dynamics simulation approach”, Journal of Molecular Graphics and Modelling,, 2018.
  • S. Chiba et al., “An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes”, Scientific Reports, 7, doi:10.1038/s41598-017-10275-4, 2017.
  • R. Yoshino et al., “In silico, in vitro, X-ray crystallography, and integrated strategies for discovering spermidine synthase inhibitors for Chagas disease”, Scientific Reports, 7, doi:10.1038/s41598-017-06411-9, 2017.
  • S. Chiba et al, “Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target”, Scientific Reports, 5, doi:10.1038/srep17209 ,2015.
  • R. Yoshino et al., ” Pharmacophore Modeling for Anti-Chagas Drug Design Using the Fragment Molecular Orbital Method “, PLoS ONE, 10(5):e0125829, doi:10.1371/journal.pone.0125829, 2015.