Information/AI
Masakazu Sekijima
Associate Professor
Bioinformaticsin silico Drug Discovery
Research Projects
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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.
Topics
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METI Minister’s Awards under the FY2020 Awards Program Promoting Informatization
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Efficient combination of drug discovery and IT, Nikkei Shimbun
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The next generation of leaders, Nikkei Sangyo Shimbun
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Business and university seriously cooperate, Nikkan Kogyo Shimbun
2020- | Associate Professor, School of Computing, Tokyo Institute of Technology |
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2016-2020 | Unit Leader/Associate Professor, Advanced Computational Drug Discovery Unit, Tokyo Institute of Technology |
2008-2016 | Associate Professor, GSIC, Tokyo Institute of Technology |
2003-2008 | Research Scientist, AIST |
2020 | METI Minister’s Awards under the FY2020 Awards Program Promoting Informatization |
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2017 | 2017 SIGBIO Achievement Award 2017 by SIGBIO, IPSJ |
2014 | 2014 Young Researcher’s Award 2014 by IIBMP |
2019 | Ramakrishnan C, Nagarajan R, Sekijima M, Gromiha MM., “Molecular dynamics simulations of cognate and non-cognate AspRS-tRNAAsp complexes.”, J Biomol Struct Dyn. 2020 Jan 3:1-12. |
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2019 | Chiba S, et al., “A prospective compound screening contest identified broader inhibitors for Sirtuin 1.”, Sci Rep. 2019 Dec 20;9(1):19585. |
2019 | S Jemimah, M Sekijima, MM Gromiha, “ProAffiMuSeq: Sequence-based method to predict the binding free energy change of protein-protein complexes upon mutation using functional classification”, Bioinformatics, Volume 36, Issue 6, 15 |
2018 | Ramakrishnan C, Mary Thangakani A, Velmurugan D, Anantha Krishnan D, Sekijima M, Akiyama Y, Gromiha MM, “Identification of type I and type II inhibitors of c-Yes kinase using in silico and experimental techniques”, J Biomol Struct Dyn. 2018 May;36(6):1566-1576 |
2018 | 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, doi.org/10.1016/j.jmgm.2017.11.011, 2018. |
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. |
2017 | 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. |
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. |
2015 | 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. |