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Development of 3D model construction method using structure database and electron microscope images

Research Project

Project/Area Number 18K06101
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 43020:Structural biochemistry-related
Research InstitutionNational Institutes for Quantum Science and Technology

Principal Investigator

Matsumoto Atsushi  国立研究開発法人量子科学技術研究開発機構, 量子生命科学研究所, 主幹研究員 (10399420)

Project Period (FY) 2018-04-01 – 2023-03-31
Project Status Completed (Fiscal Year 2022)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2021: ¥390,000 (Direct Cost: ¥300,000、Indirect Cost: ¥90,000)
Fiscal Year 2020: ¥390,000 (Direct Cost: ¥300,000、Indirect Cost: ¥90,000)
Fiscal Year 2019: ¥260,000 (Direct Cost: ¥200,000、Indirect Cost: ¥60,000)
Fiscal Year 2018: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
Keywordsプログラム開発 / ニューラルネットワーク / 電子顕微鏡 / 生体分子 / 立体構造 / 電子顕微鏡画像 / 立体構造モデリング / 生体超分子 / データベース / モデリング / シミュレーション
Outline of Final Research Achievements

In this study, a computer method to select or find a matching or similar three-dimensional structure from a database of biomolecules when given an electron microscope image of a biomolecule was developed. The method used a combination of the microscopy image creation technique developed by the lead author and neural networks. For this purpose, a dataset of electron microscopy images was created for machine learning from approximately 20,000 large biomolecules selected from the current database consisting of approximately 200,000 biomolecules. The structures were classified by size and machine learning was performed in each class. In the largest structure class, the accuracy rate was about 70% (with the correct answer included in the top three answers about 90% of the time).

Academic Significance and Societal Importance of the Research Achievements

本研究で開発した計算機手法を用いることにより、立体構造が分かっていない生体分子であっても、それに類似する構造がデータベースに登録されていれば、その電子顕微鏡画像をもとに、立体構造を速やかに類推することができる。
電子顕微鏡による立体構造解析では、通常クライオ電子顕微鏡が用いられるが、非常に高価で、これを持つ施設も限られている。本手法を用いることで、従来の電子顕微鏡を活用して、立体構造解析を行うことができる。

Report

(6 results)
  • 2022 Annual Research Report   Final Research Report ( PDF )
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • 2018 Research-status Report
  • Research Products

    (3 results)

All 2022 2020 2019

All Journal Article (2 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 2 results,  Open Access: 2 results) Presentation (1 results)

  • [Journal Article] Structural Studies of Overlapping Dinucleosomes in Solution2020

    • Author(s)
      Matsumoto Atsushi、Sugiyama Masaaki、Li Zhenhai、Martel Anne、Porcar Lionel、Inoue Rintaro、Kato Daiki、Osakabe Akihisa、Kurumizaka Hitoshi、Kono Hidetoshi
    • Journal Title

      Biophysical Journal

      Volume: 118 Issue: 9 Pages: 2209-2219

    • DOI

      10.1016/j.bpj.2019.12.010

    • Related Report
      2019 Research-status Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Dynamic analysis of ribosome by a movie made from many three-dimensional electron-microscopy density maps2019

    • Author(s)
      Matsumoto Atsushi
    • Journal Title

      Biophysics and Physicobiology

      Volume: 16 Issue: 0 Pages: 108-113

    • DOI

      10.2142/biophysico.16.0_108

    • NAID

      130007623864

    • ISSN
      2189-4779
    • Related Report
      2018 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] Deep learning of computer-generated electron microscopy images to identify biomolecules2022

    • Author(s)
      松本淳
    • Organizer
      第60回日本生物物理学会年会
    • Related Report
      2022 Annual Research Report

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Published: 2018-04-23   Modified: 2024-01-30  

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