Osawa, Masanori

写真a

Affiliation

Faculty of Pharmacy, Department of Pharmaceutical Sciences Division of Physics for Life Functions （Shiba-Kyoritsu）

Position

Professor

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Research Areas 【 Display / hide 】

  • Life Science / Structural biochemistry

  • Life Science / Structural biochemistry

  • Life Science / Biophysics

  • Life Science / Biophysics

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Research Keywords 【 Display / hide 】

  • ion channel

  • ion channel

  • Signal transduction

  • Signal transduction

  • nuclear magnetic resonance

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Books 【 Display / hide 】

  • Peptide Toxins Targeting KV Channels

    Matsumura K, Yokogawa M, Osawa M, Springer Nature, 2021

    　View Summary

    A number of peptide toxins isolated from animals target potassium ion (K+) channels. Many of them are particularly known to inhibit voltage-gated K+ (KV) channels and are mainly classified into pore-blocking toxins or gating-modifier toxins. Pore-blocking toxins directly bind to the ion permeation pores of KV channels, thereby physically occluding them. In contrast, gating-modifier toxins bind to the voltage-sensor domains of KV channels, modulating their voltage-dependent conformational changes. These peptide toxins are useful molecular tools in revealing the structure-function relationship of KV channels and have potential for novel treatments for diseases related to KV channels. This review focuses on the inhibition mechanism of pore-blocking and gating-modifier toxins that target KV channels.

  • Nuclear magnetic resonance approaches for characterizing protein-protein interactions

    Toyama Y, Mase Y, Kano H, Yokogawa M, Osawa M, Shimada I, Methods in Molecular Biology, 2018

    　View Summary

    The gating of potassium ion (K+) channels is regulated by various kinds of protein-protein interactions (PPIs). Structural investigations of these PPIs provide useful information not only for understanding the gating mechanisms of K+ channels, but also for developing the pharmaceutical compounds targeting K+ channels. Here, we describe a nuclear magnetic resonance spectroscopic method, termed the cross saturation (CS) method, to accurately determine the binding surfaces of protein complexes, and its application to the investigation of the interaction between a G protein-coupled inwardly rectifying K+ channel and a G protein α subunit.

  • 【試料分析講座】「蛋白質の分析」

    OSAWA MASANORI, 分析化学会（丸善）, 2012

    Scope: NMR・CDスペクトル

  • 分子細胞生物学辞典 (第２版)

    OSAWA MASANORI, 東京化学同人, 2008

    Scope: 「等温滴定型カロリメトリー」,「滴定曲線」

  • 実験医学別冊「生命科学のための機器分析実験ハンドブック」

    OSAWA MASANORI, 羊土社, 2007

    Scope: 「等温滴定型カロリメトリー(ITC) ～熱量測定による相互作用の定量的解析～」

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Papers 【 Display / hide 】

  • AI-driven molecular generation of not-patented pharmaceutical compounds using world open patent data

    Shimizu Y., Ohta M., Ishida S., Terayama K., Osawa M., Honma T., Ikeda K.

    Journal of Cheminformatics （BioMed Central Ltd)  15 （ 1 ） 120 2023.12

    Research paper (scientific journal), Joint Work, Accepted

    　View Summary

    Developing compounds with novel structures is important for the production of new drugs. From an intellectual perspective, confirming the patent status of newly developed compounds is essential, particularly for pharmaceutical companies. The generation of a large number of compounds has been made possible because of the recent advances in artificial intelligence (AI). However, confirming the patent status of these generated molecules has been a challenge because there are no free and easy-to-use tools that can be used to determine the novelty of the generated compounds in terms of patents in a timely manner; additionally, there are no appropriate reference databases for pharmaceutical patents in the world. In this study, two public databases, SureChEMBL and Google Patents Public Datasets, were used to create a reference database of drug-related patented compounds using international patent classification. An exact structure search system was constructed using InChIKey and a relational database system to rapidly search for compounds in the reference database. Because drug-related patented compounds are a good source for generative AI to learn useful chemical structures, they were used as the training data. Furthermore, molecule generation was successfully directed by increasing and decreasing the number of generated patented compounds through incorporation of patent status (i.e., patented or not) into learning. The use of patent status enabled generation of novel molecules with high drug-likeness. The generation using generative AI with patent information would help efficiently propose novel compounds in terms of pharmaceutical patents. Scientific contribution: In this study, a new molecule-generation method that takes into account the patent status of molecules, which has rarely been considered but is an important feature in drug discovery, was developed. The method enables the generation of novel molecules based on pharmaceutical patents with high drug-likeness and will help in the efficient development of effective drug compounds.

  • PoSSuM v.3: A Major Expansion of the PoSSuM Database for Finding Similar Binding Sites of Proteins

    Tsuchiya Y, Yonezawa T, Yamamori Y, Inoura H, Osawa M, Ikeda K, and Tomii K.

    Journal of Chemical Information and Modeling （ACS Publications)  63 （ 23 ） 7578 - 7587 2023.11

    Research paper (scientific journal), Joint Work, Accepted

    　View Summary

    Information on structures of protein–ligand complexes, including comparisons of known and putative protein–ligand-binding pockets, is valuable for protein annotation and drug discovery and development. To facilitate biomedical and pharmaceutical research, we developed PoSSuM (https://possum.cbrc.pj.aist.go.jp/PoSSuM/), a database for identifying similar binding pockets in proteins. The current PoSSuM database includes 191 million similar pairs among almost 10 million identified pockets. PoSSuM drug search (PoSSuMds) is a resource for investigating ligand and receptor diversity among a set of pockets that can bind to an approved drug compound. The enhanced PoSSuMds covers pockets associated with both approved drugs and drug candidates in clinical trials from the latest release of ChEMBL. Additionally, we developed two new databases: PoSSuMAg for investigating antibody–antigen interactions and PoSSuMAF to simplify exploring putative pockets in AlphaFold human protein models.

  • TDP-43 N-terminal domain dimerisation or spatial separation by RNA binding decreases its propensity to aggregate

    Miura M, Sakaue F, Matsuno H, Morita K, Yoshida A, Hara RI, Nishimura R, Nishida Y, Yokogawa M, Osawa M, and Yokota T.

    FEBS Letters （FEBS PRESS)  597 （ 12 ） 1667 - 1676 2023.05

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  00145793

    　View Summary

    Aggregation of the 43 kDa TAR DNA-binding protein (TDP-43) is a pathological hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). RNA binding and TDP-43 N-terminal domain dimerisation has been suggested to ameliorate TDP-43 aggregation. However, the relationship between these factors and the solubility of TDP-43 is largely unknown. Therefore, we developed new oligonucleotides that can recruit two TDP-43 molecules and interfere with their intermolecular interactions via spatial separation. Using these oligonucleotides and TDP-43-preferable UG-repeats, we uncovered two distinct mechanisms for modulating TDP-43 solubility by RNA binding: One is N-terminal domain dimerisation, and the other is the spatial separation of two TDP-43 molecules. This study provides new molecular insights into the regulation of TDP-43 solubility.

  • Applying deep learning to iterative screening of medium-sized molecules for protein–protein interaction-targeted drug discovery

    Shimizu Y, Yonezawa T, Bao Y, Sakamoto J, Yokogawa M, Furuya T, Osawa M, and Ikeda K.

    Chemical Communications （The Royal Society of Chemistry)  Issue 44 （ 59 ） 6722 - 6725 2023.05

    Research paper (scientific journal), Accepted,  ISSN  13597345

    　View Summary

    We combined a library of medium-sized molecules with iterative screening using multiple machine learning algorithms that were ligand-based, which resulted in a large increase of the hit rate against a protein-protein interaction target. This was demonstrated by inhibition assays using a PPI target, Kelch-like ECH-associated protein 1/nuclear factor erythroid 2-related factor 2 (Keap1/Nrf2), and a deep neural network model based on the first-round assay data showed a highest hit rate of 27.3%. Using the models, we identified novel active and non-flat compounds far from public datasets, expanding the chemical space.

  • DLiP-PPI library: An integrated chemical database of small-to-medium-sized molecules targeting protein–protein interactions

    Ikeda K, Maezawa Y, Yonezawa T, Shimizu Y, Tashiro T, Kanai S, Sugaya N, Masuda Y, Inoue N, Niimi T, Masuya K, Mizuguchi K, Furuya T and Osawa M.

    Frontiers in Chemistry （Frontiers)  10 （ Volume 10 ）  2023.01

    Research paper (scientific journal), Joint Work, Last author, Accepted

    　View Summary

    Protein–protein interactions (PPIs) are recognized as important targets in drug discovery. The characteristics of molecules that inhibit PPIs differ from those of small-molecule compounds. We developed a novel chemical library database system (DLiP) to design PPI inhibitors. A total of 32,647 PPI-related compounds are registered in the DLiP. It contains 15,214 newly synthesized compounds, with molecular weight ranging from 450 to 650, and 17,433 active and inactive compounds registered by extracting and integrating known compound data related to 105 PPI targets from public databases and published literature. Our analysis revealed that the compounds in this database contain unique chemical structures and have physicochemical properties suitable for binding to the protein–protein interface. In addition, advanced functions have been integrated with the web interface, which allows users to search for potential PPI inhibitor compounds based on types of protein–protein interfaces, filter results by drug-likeness indicators important for PPI targeting such as rule-of-4, and display known active and inactive compounds for each PPI target. The DLiP aids the search for new candidate molecules for PPI drug discovery and is available online (https://skb-insilico.com/dlip).

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Papers, etc., Registered in KOARA 【 Display / hide 】

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Reviews, Commentaries, etc. 【 Display / hide 】

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Presentations 【 Display / hide 】

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Research Projects of Competitive Funds, etc. 【 Display / hide 】

  • Elucidation of the mechanism of hepatitis B virus entry and control of infection by entry inhibitors

    2022.04
    -
    2025.03

    Grants-in-Aid for Scientific Research, 伊藤 清顕, 宇根 瑞穂, 大澤 匡範, 梅澤 一夫, Grant-in-Aid for Scientific Research (B), No Setting

    　View Summary

    我々は、胆汁酸誘導体の一つであるINT-767がHBVのエンベロープ蛋白質の疎水性領域に結合してHBVの感染を強力に阻害することを発見した（Ito K et al. Hepatology. 2021）。本研究によりHBVの肝細胞内への侵入機構を分子レベルで解明し、胆汁酸誘導体や低分子化合物を利用して、より有効性および安全性が高い新たな感染阻害剤を開発する。HBVと同様に新型コロナウイルスやヒト免疫不全ウイルスなどのエンベロープウイルスもエンベロープ蛋白質の疎水性領域を利用して細胞膜やエンドソーム膜と融合して感染が成立するため、本研究成果は他のエンベロープウイルスに対する治療薬開発にも繋がる。

  • B型肝炎ウイルスの肝細胞侵入・増殖機構の構造基盤と立体構造に基づく創薬

    2021.04
    -
    2024.03

    Keio University, Grants-in-Aid for Scientific Research, 横川 真梨子, 大澤 匡範, Grant-in-Aid for Scientific Research (C), No Setting

    　View Summary

    B型肝炎ウイルス(HBV) 外殻膜の表面抗原タンパク質（LHBs）は、肝細胞への感染時には肝細胞膜上のタンパク質であるNTCPと結合し、宿主内での増殖時にはHBVのキャプシドを形成するタンパク質であるCpと結合する。そこで本研究は、LHBs―NTCPおよびLHBs―Cpの相互作用様式を原子分解能で明らかにすることで、HBVの肝細胞侵入・増殖メカニズムを解明する。明らかにした立体構造に基づくin silicoスクリーニング、および得られた候補化合物のin vitroアッセイを行うことで、これらのタンパク質－タンパク質相互作用を阻害する中分子合成化合物を探索し、新規作用機序の抗HBV薬を創製する。

  • 電位依存性イオンチャネルの機能構造と構造間遷移機構の解析による動作機構解明

    2021.04
    -
    2024.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, 大澤 匡範, 横川 真梨子, Grant-in-Aid for Scientific Research (B), Principal investigator

    　View Summary

    電位依存性イオンチャネル(VGIC)は、神経伝達や心臓の拍動を担う膜タンパク質であり、創薬の標的としても重要である。VGICは一般に、膜電位に応じた構造変化によりイオン透過ゲートを開閉し、特定のイオンを膜透過させることで膜電位を制御する。しかしながら、これまではその構造遷移メカニズムは不明であった。
    そこで本研究では、リガンドの結合や化学修飾により未解明である機能構造を安定化して構造解析を実現可能とする手法を確立し、その立体構造をX線結晶構造解析あるいは電子顕微鏡により原子レベルで明らかにするとともに、NMRによりそれらの間の構造遷移を解析することにより、VGICの動作メカニズムを解明する。

  • 14-3-3タンパク質によるリン酸化シグナル経路の熱力学的・構造生物学的基盤

    2019.04
    -
    2021.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, 大澤 匡範, Grant-in-Aid for Scientific Research on Innovative Areas, Principal investigator

    　View Summary

    多くのがん細胞においては、Ras タンパク質の活性化を起源として、その下流にあるキナーゼを活性化し、そのキナーゼは連鎖的に別のキナーゼをリン酸化・活性化する、というリン酸化シグナルが亢進している。そのシグナルを持続させる機能をもつタンパク質が14-3-3タンパク質である。本研究では、この14-3-3タンパク質がいかにしてリン酸化シグナルを持続させるのかを定量的に、かつ、タンパク質の立体構造の観点より解明することにより、この過程を数理モデル化して理解することを目的としている。このメカニズムが解明できれば、リン酸化シグナルを抑制する革新的な制がん剤の創製につながると考えている。
    多くのがん細胞においては、遺伝子変異によるRas タンパク質の活性化を起源として、その下流にあるキナーゼを活性化し、そのキナーゼは連鎖的に別のキナーゼをリン酸化・活性化する。このようなリン酸化シグナルの連鎖と増幅が、がん細胞の増殖能や浸潤能を高める。 Ser/Thr のリン酸化によるキナーゼの活性化は、14-3-3ζ の結合により持続・亢進し、14-3-3ζ の結合阻害により抑制されることが分かってきた。したがって、がんにおけるリン酸化シグナルの数理モデルを確立するためには、14-3-3ζ と各キナーゼの結合親和性や、その基盤となる複合体の立体構造を明らかにする必要がある。そこで本研究は、14-3-3ζの結合により活性化されるキナーゼや転写因子など（14-3-3ζのclientタンパク質）の全長、あるいは、14-3-3ζとの相互作用部位全体を用いた結合親和性の定量的解析、両者の複合体のX線結晶構造解析を行うことにより、リン酸化シグナルの数理モデルを構築する上での熱力学的・構造生物学的基盤を確立することを目的とする。
    本年度は、14-3-3ζのclientタンパク質のうち、キナーゼ3種類、転写因子2種類の大量発現系を構築し、大腸菌をホストとした大量発現・精製を試みた。これまでに、キナーゼおよび転写因子の各1種類について、大量発現・精製法確立に成功した。キナーゼについてはサイズ排除クロマトグラフィーにより多量体状態の解析を行い、単量体～2量体で存在することが分かった。現在、酵素処理によるリン酸化条件を検討している。転写因子については、これを基質とする別のリン酸化酵素によるリン酸化に成功した。GST融合14-3-3ζを用いたグルタチオンセファロースによるプルダウンアッセイにより、14-3-3ζとリン酸化した転写因子の高親和性結合を確認した。
    当初の計画は、以下の通りであった。
    (1) 14-3-3ζのclient タンパク質の大量調製法の確立、性状解析・活性確認 (2) 14-3-3ζとclient タンパク質全長（相互作用部位全体）の結合親和性の定量解析 (3) 14-3-3ζとclient タンパク質全長（相互作用部位全体）の複合体の結晶化 (4) 14-3-3ζと阻害剤BA およびUTKO1 との相互作用解析、複合体の立体構造解析
    <BR>
    これまでに、(1)については、転写因子およびタンパク質キナーゼの大量調製に成功し、特に転写因子についてはリン酸化方法を確立し、プルダウンアッセイによりリン酸化の有無による14-3-3ζとの結合親和性の変化の検出に成功した。(2)、(3)への取り組みを開始したところである。(4)については、未着手である。
    当初の計画の(2)、(3)については、結晶化に成功し次第、X線結晶構造解析を行う。
    また、大量調製法が確立できていない転写因子とタンパク質リン酸化酵素については、発現条件の検討を行う。

  • Structural analysis of hepatocyte specific entry and replication mechanism of hepatitis B virus

    2018.04
    -
    2021.03

    Keio University, Grants-in-Aid for Scientific Research, Yokogawa Mariko, Grant-in-Aid for Scientific Research (C), No Setting

    　View Summary

    Aim of this study was to obtain structural basis for hepatocyte specific entry and replication mechanism of hepatitis B virus (HBV), for the treatment of HBV infection.
    NTCP, an HBV receptor specifically expressed in hepatocyte, was prepared using cell-free protein synthesis system and the preS1-binding activity was successfully confirmed. We also exhibited that preS2 region of HBV large surface protein is important for binding to capsid, which might be important for enveloping of HBV during replication.

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Awards 【 Display / hide 】

  • Best Poster Award

    Masanori Osawa, 2016.07, The organizing committee of International and Interdisciplinary Symposium 2016, Structural Basis for the Inhibition of Voltage-dependent K+ Channel by Gating Modifier Toxin

    Type of Award： Other

  • 長瀬研究振興賞

    2016.04, NAGASE Science Technology Foundation, Development of novel nanodisc that enables solution NMR analyses of membrane protein interactions in the lipid bilayer

    Type of Award： Other

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Courses Taught 【 Display / hide 】

  • STUDY OF MAJOR FIELD:(PHYSICS FOR LIFE FUNCTIONS)

    2024

  • SEMINAR:(PHYSICS FOR LIFE FUNCTIONS)

    2024

  • RESEARCH FOR BACHELOR'S THESIS 1

    2024

  • PHYSICAL CHEMISTRY

    2024

  • PHARMACEUTICAL-ENGLISH SEMINAR

    2024

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Courses Previously Taught 【 Display / hide 】

  • RESEARCH FOR BACHELOR'S THESIS A

    Keio University

    2019.04
    -
    2020.03

  • Analytical Chemistry

    Keio University

    2018.04
    -
    2019.03
    , 

    Spring Semester, Lecture, Within own ｆaculty, 1h, 240people

  • 物理分析学

    Keio University

    2018.04
    -
    2019.03
    , 

    Autumn Semester, Lecture, 220people

  • Basic pharmaceutical sciences laboratory course

    Keio University

    2018.04
    -
    2019.03
    , 

    Autumn Semester, Laboratory work/practical work/exercise, 240people

  • Physical chemistry (3)B

    Keio University

    2015.04
    -
    2016.03
    , 

    Autumn Semester, Lecture, 240people

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