タンパク質の試験管内と細胞内における構造の違いは、その働きや薬の効果に影響を与えることが知られています。このため、細胞内の環境がタンパク質の構造に与える影響を調べることが重要です。しかし、細胞内の複雑な環境を実験的に再現することは難しく、計算科学的なアプローチに期待が高まっています。そこで、本研究では細胞内部、とくに生体分子内部の環境を再現した構造モデルを生成するプログラム：BEMM-GEN (Biomolecular Environment Mimicking Model GENerator) を開発・公開しました(https://github.com/y4suda/BEMM-GEN)。BEMM-GENは、ユーザーが指定した任意の化学的組成を持つ筒状または球状の構造モデルを生成します。本プログラムにより、細胞内の環境におけるタンパク質の立体構造を解明する研究が加速することが期待されます。
研究内容と成果
近年の研究から、タンパク質の構造や機能が試験管内と実際の細胞内で異なることが明らかになってきました。とくに、細胞内に存在する「シャペロン」というタンパク質の折り畳みを補助する生体分子や、「リボソーム」と呼ばれるタンパク質を合成する生体分子の内で、タンパク質は特異的な構造を示し、それが機能に大きな影響を与えることがわかっています。そのため、それぞれの分子内部の環境がタンパク質の構造に与える影響を調べることが重要となります。しかし、複雑な生体分子内の環境を再現したり、その内部におけるタンパク質の構造を実験的に観測したりすることは依然として困難であるため、計算科学的手法が注目されています。このような背景を受けて、本研究では生体分子内部の環境を再現した構造モデルを自動的に生成するプログラムである：BEMM-GEN（Biomolecular Environment Mimicking Model GENerator）を開発しました。BEMM-GENは、ユーザーが指定した化学的な組成をもつ筒状または球状の構造モデルを生成でき、その内部に任意のタンパク質を配置することができます。そのため、BEMM-GENにより生成した構造を利用して分子動力学計算注1）を実行することで、注目したい生体分子内の環境がタンパク質の構造に与える影響を定量的に評価することが可能になります。
【題 名】 BEMM-GEN: A Toolkit for Generating a Biomolecular Environment-Mimicking Model for Molecular Dynamics Simulation. 【著者名】 Yasuda. T1,2., Morita .R3., Shigeta. Y3., Harada. R3,4.
理工情報生命学術院 生命地球科学研究群 生物学学位プログラム 博士後期課程
日本学術振興会特別研究員
計算科学研究センター
生命環境系
【掲載誌】 Journal of Chemical Information and Modeling 【掲載日】 2024年10月4日 【DOI】 10.1021/acs.jcim.4c01467
Tsukuba, Japan—Gas swirls around a black hole (BH) owing to the intense gravity of the BH, forming an accretion disk. These accretion disks, being among the most efficient energy conversion mechanisms in the universe, emit light and plasma jets. When a BH spins on its axis, the accretion disk wobbles like a spinning top. This precessional motion has been studied in less luminous accretion disks, but it is unclear if the same phenomenon occurs in ultraluminous accretion disks that emit strong radiation.
Researchers at University of Tsukuba conducted a large-scale radiation electromagnetic hydrodynamics simulation based on general relativity and demonstrated for the first time that the precessional motion of a tilted ultraluminous accretion disk is caused by the spin of the BH. Furthermore, this precessional motion periodically changes the direction of the jets and radiation emitted from the BH, which indicates that the periodic fluctuations in luminosity of ultraluminous accretion disks may be caused by the spin of the BH. The cause of such periodic fluctuations has previously been unknown.
In the future, the researchers intend to validate whether BHs are spinning by comparative analyses between extended-term simulations and observational data. This pioneering achievement is poised to deepen our understanding of how the spin of a BH influences cosmic phenomena, and make a substantial contribution to the authentication of the spacetime framework of BHs and general relativity.
### This work was supported by JSPS KAKENHI Grant Numbers 23K03445(Y.A.), 21H01132(R.T.), 21H04488, 18K03710(K.O.). This work was also supported by MEXT as “Program for Promoting Researches on the Supercomputer Fugaku” (Structure and Evolution of the Universe Unraveled by Fusion of Simulation and AI; Grant Number JPMXP1020230406) and used computational resources of supercomputer Fugaku (RIKEN Center for Computational Science, Project ID: hp230204, hp230116), ATERUI II (National Astronomical Observatory of Japan), Oakforest-PACS (the University of Tokyo, University of Tsukuba), and Wisteria/BDEC-01 Odyssey (the University of Tokyo).
Original Paper
Title of original paper: General relativistic radiation-MHD simulations of Precessing Tilted Super-Eddington Disks
The 22nd International Conference on Recent Progress in Many-Body Theories (RPMBT22) will be held in Tsukuba, Japan, September 23-27, 2024 (The reception and the registration are available on September 22). A series of conferences offer an ideal opportunity to recognize important achievements and to showcase significant new results in various aspects of many-body physics.
The conference is hosted by the Center for Computational Sciences, University of Tsukuba.
Today, computational science is an indispensable research methodology in the basic and applied sciences and contributes significantly to the progress of a wide variety of scientific research fields. For multidisciplinary computational science based on the fusion of computational and computer sciences, frequent/regular opportunities for communication and collaboration are essential. The Center for Computational Sciences (CCS) at the University of Tsukuba aims to improve such collaborations between different research fields. In this symposium, plenary speakers in various fields of computational sciences will give us talks on research frontiers, comprehensible to researchers and graduate students in other fields. In 2010, the CCS was recognized under the Advanced Interdisciplinary Computational Science Collaboration Initiative (AISCI) by MEXT, and has since provided the use of its computational facilities to researchers nationwide as part of the Multidisciplinary Cooperative Research Program (MCRP).
Date and Venue
Dates: 7 Oct. [Mon] 14:00 - 8 Oct. [Tue] 17:00 Venue: EpochalTsukuba International Congress Center “Hall 300” *Zoom streaming will also be available, but no questions will be accepted online.
Program
Oct. 7 (mon)
14:00 – 14:15
Welcome address
SHIGETA Yasuteru
University of Tsukuba (Vice President and Executive Director for Research)
Welcome address
BOKU Taisuke
University of Tsukuba (Director of CCS)
14:15 – 14:45
What global urban climate modeling teaches us
Dan Li
Boston University
14:45 – 15:15
Modern ab initio nuclear many-body theory
Alexandros Gezerlis
University of Guelph, Department of Physics
15:15 – 15:45
Coffee Break / Group photo
15:45 – 16:15
Dynamical nonequilibrium molecular dynamics (D-NEMD) reveals the structural basis for allostery and signal propagation in biomolecular systems (online)
Ana Sofia Fernandes Oliveira
School of Chemistry, University of Bristol, UK
16:15 – 16:45
Upcoming supercomputers in CCS and JCAHPC
TATEBE Osamu
University of Tsukuba
16:45 – 17:15
Scaling El Capitan
Ramesh Pankajakshan
LLNL, El Capitan Center of Excellence
17:30 – 19:30
Reception
Oct.8 (Tue)
9:30 – 10:00
Quantum computers to aid simulations of fundamental particles and interactions (online)
Zohreh Davoudi
University of Maryland, Department of Physics
10:00 – 10:30
Tensor network approaches for condensed matter physics
OKUBO Tsuyoshi
the University of Tokyo
10:30 – 10:50
Coffee Break
10:50 – 11:20
From Smart Services to Intelligent Services in Pervasive Computing
Philippe Lalanda
University Grenoble-Alpes (UGA), Computer Science
11:20 – 11:50
The genomes of unicellular holozoans elucidate the origin of multicellularity
SUGA Hiroshi
Prefectural University of Hiroshima
11:50 – 13:20
Lunch Break
13:20 – 14:50
Poster Session
14:50 – 15:20
Digital Brain Models and Their Applications
Dean Chou
National Cheng Kung University
15:20 – 15:50
Next-generation simulations of galaxy formation: coupling surrogate models with conventional simulations
FUJII Michiko
the University of Tokyo
15:50 – 16:00
Closing
TATEBE Osamu
University of Tsukuba (Deputy Director of CCS)
Registration
Please complete your participation registration via the link below. The registration deadline is September 24. https://forms.gle/7gdZ4VCwNR2Yw58U7 (Registration is free, and the reception fee will be 7,000 JPY. )
Title: AI for Personalized Education Speaker: Prof. Mukesh Mohania (IIIT Delhi, India) Date: 18 June 2024 Time:14:30-15:30 (updated) Venue:SB911-2 (updated) Language: English
Abstract: Online courses and learning systems have gained tremendous popularity over the last few years. While their ease of access and availability make them a very useful medium for knowledge sharing and learning, they do not keep the learners and their learning abilities in mind. The “one size fits all” approach to learning content and the question paper does not work in a large virtual classroom consisting of diverse students with different skill profiles, learning styles, aptitude and capabilities. In a traditional classroom, teachers who interact closely with students are in a position to evaluate the pace and depth of the curriculum being taught and can also suggest learning content to students not being able to cope with the general classroom teaching. Such suggestions and guidance are absent in current online learning systems. In this talk, we aim to address how AI can help in (1) making content smarter through learning content analytics and automatic content tagging, (2) generating the diverse, but semantically related, questions for evaluating the students’ knowledge, (3) assisting in short answers evaluation, and finally (4) understanding the students’ learning style/capacity through learning data analytics, thus enabling the adaptive and personalized education on Big Data platform.
![[ウェブリリース]生体内の特殊な環境を計算科学的に再現するプログラムを開発](https://www.ccs.tsukuba.ac.jp/wp-content/uploads/sites/14/2024/10/241004fig1-825x510.jpg)
