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詳細
開催日 2024年7月17日(水)
開催時間 14:10 - 14:50
開催都市 オンライン
場所

Zoomによる遠隔セミナー

使用言語 発表・スライド共に英語
登壇者

德久 淳師

R-CCS HPC/AI駆動型医薬プラットフォーム部門 バイオメディカル計算知能ユニット 上級研究員

講演題目・要旨

1st Speaker: Atsushi Tokuhisa


Title:
Fusion of Experimental, AI and Simulation Technologies for Promoting Molecular Biomedical Science
Abstract:
Molecular Biomedical Science is an new field that develops innovative new technologies from a molecular perspectives and translates the results to human health. We aim to construct a next-generation molecular biomedical platform for promoting genomic drug discovery and genomic medicine utilizing the super computer “Fugaku”. The next-generation molecular biomedical platform aim to realize new modality drug discovery support technologies and new genomic diagnostic and treatment technologies based on structure and dynamics of biomolecules. My scientific goal is to understand and control living systems by observing the behavior of biomolecules, one atom at a time, inside/inter cells. However, several challenges remain in achieving this goal. For example, there is no universal method for experimentally observing biomolecules as a time-series data at the atomic level. Furthermore, when considering simulation assistance, there is a gap in the space-time scales that can be observed in experiments and simulations. It is also important to consider that there are many protein members involved in maintaining living system. To overcome these difficulties, I am promoting my research by fusion of experimental data on biomolecules and HPC/AI-driven technologies. In this seminar, I will review fundamental technologies for molecular biomedical science that I have developed. In particular, I will focus on the template matching (TM) method to elucidate multi conformational states of biomolecules with high resolutions based on single particle experimental data using scientific workflow constructing on the “Fugaku”. I will also report a translational research of the TM-method for rational drug design of SARS-CoV-2 focused on the spike-protein that is a target protein of antibody. Furthermore, I will discuss future development plans aiming for structure based proteome-wide analysis and the great potential these technologies offer for biomedical translational researches.

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(2024年7月8日)