Keisuke Yanagisawa

Assistant Professor, Tokyo Institute of Technology

Peer-reviewed Journal Papers

  1. Genki Kudo†, Keisuke Yanagisawa†, Ryunosuke Yoshino, Takatsugu Hirokawa. “AAp-MSMD: Amino Acid Preference Mapping on Protein-Protein Interaction Surfaces Using Mixed-Solvent Molecular Dynamics”, Journal of Chemical Information and Modeling, 63: 7768-7777, 2023/12. DOI: 10.1021/acs.jcim.3c01677
    * †: co-first authors
  2. Jianan Li, Keisuke Yanagisawa, Masatake Sugita, Takuya Fujie, Masahito Ohue, Yutaka Akiyama. “CycPeptMPDB: A Comprehensive Database of Membrane Permeability of Cyclic Peptides”, Journal of Chemical Information and Modeling, Journal of Chemical Information and Modeling, 63: 2240-2250, 2023/03. DOI: 10.1021/acs.jcim.2c01573
    * The CycPeptMPDB database is available at http://cycpeptmpdb.com/.
  3. Masatake Sugita, Takuya Fujie, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Lipid composition is critical for accurate membrane permeability prediction of cyclic peptides by molecular dynamics simulations”, Journal of Chemical Information and Modeling, 62: 4549-4560, 2022/09. DOI: 10.1021/acs.jcim.2c00931
  4. Keisuke Yanagisawa, Rikuto Kubota, Yasushi Yoshikawa, Masahito Ohue, Yutaka Akiyama. “Effective protein-ligand docking strategy via fragment reuse and a proof-of-concept implementation”, ACS Omega, 7: 30265-30274, 2022/08. DOI: 10.1021/acsomega.2c03470
  5. Keisuke Yanagisawa, Ryunosuke Yoshino, Genki Kudo, Takatsugu Hirokawa. “Inverse Mixed-Solvent Molecular Dynamics for Visualization of the Residue Interaction Profile of Molecular Probes”, International Journal of Molecular Sciences, 23: 4749, 2022/04. DOI: 10.3390/ijms23094749
  6. Kazuki Takabatake, Keisuke Yanagisawa, Yutaka Akiyama. “Solving Generalized Polyomino Puzzles Using the Ising Model”, Entropy, 24: 354, 2022/02. DOI: 10.3390/e24030354
  7. Jianan Li, Keisuke Yanagisawa, Yasushi Yoshikawa, Masahito Ohue, Yutaka Akiyama. “Plasma protein binding prediction focusing on residue-level features and circularity of cyclic peptides by deep learning”, Bioinformatics, 38: 1110-1117, 2022/02. DOI: 10.1093/bioinformatics/btab726
  8. Keisuke Yanagisawa. “Virtual Screening Methods with a Protein Tertiary Structure for Drug Discovery”, JSBi Bioinformatics Review, 2: 76-86, 2021/10. DOI: 10.11234/jsbibr.2021.9 (in Japanese)
  9. Kazuki Takabatake, Kazuki Izawa, Motohiro Akikawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Improved Large-Scale Homology Search by Two-step Seed Search Using Multiple Reduced Amino Acid Alphabets”, Genes, 12: 1455, 2021/09. DOI: 10.3390/genes12091455
  10. Masatake Sugita, Satoshi Sugiyama, Takuya Fujie, Yasushi Yoshikawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Large-scale membrane permeability prediction of cyclic peptides crossing a lipid bilayer based on enhanced sampling molecular dynamics simulations”, Journal of Chemical Information and Modeling, 61: 3681-3695, 2021/7. DOI: 10.1021/acs.jcim.1c00380
  11. Keisuke Yanagisawa, Yoshitaka Moriwaki, Tohru Terada, Kentaro Shimizu. “EXPRORER: Rational Cosolvent Set Construction Method for Cosolvent Molecular Dynamics Using Large-Scale Computation”, Journal of Chemical Information and Modeling, 61: 2744-2753, 2021/06. DOI: 10.1021/acs.jcim.1c00134
  12. Masahiro Mochizuki, Shogo D. Suzuki, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “QEX: Target-specific druglikeness filter enhances ligand-based virtual screening”, Molecular Diversity, 23(1): 11-18, 2019/02. DOI: 10.1007/s11030-018-9842-3
  13. Takashi Tajimi, Naoki Wakui, Keisuke Yanagisawa, Yasushi Yoshikawa, Masahito Ohue, Yutaka Akiyama. “Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques”, BMC Bioinformatics, 19(Suppl 19): 527, 2018/12. DOI: 10.1186/s12859-018-2529-z (14 pages)
  14. Keisuke Yanagisawa, Shunta Komine, Rikuto Kubota, Masahito Ohue, Yutaka Akiyama. “Optimization of memory use of fragment extension-based protein-ligand docking with an original fast minimum cost flow algorithm”, Computational Biology and Chemistry, 74: 399-406, 2018/06. DOI: 10.1016/j.compbiolchem.2018.03.013
  15. Takanori Hayashi, Yuri Matsuzaki, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions”, BMC Bioinformatics, 19(Suppl 4): 62, 2018/05. DOI: 10.1186/s12859-018-2073-x (12 pages)
  16. Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “Spresso: An ultrafast compound pre-screening method based on compound decomposition”, Bioinformatics, 33(23): 3836-3843, 2017/12. DOI: 10.1093/bioinformatics/btx178
  17. Shuntaro Chiba, Takashi Ishida, Kazuyoshi Ikeda, Masahiro Mochizuki, Reiji Teramoto, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Chandrasekaran Ramakrishnan, A. Mary Thangakani, D. Velmurugan, M. Michael Gromiha, Tatsuya Okuno, Koya Kato, Shintaro Minami, George Chikenji, Shogo D. Suzuki, Keisuke Yanagisawa, Woong-Hee Shin, Daisuke Kihara, Kazuki Z. Yamamoto, Yoshitaka Moriwaki, Nobuaki Yasuo, Ryunosuke Yoshino, Sergey Zozulya, Petro Borysko, Roman Stavniichuk, Teruki Honma, Takatsugu Hirokawa, Yutaka Akiyama, Masakazu Sekijima. “An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes”, Scientific Reports, 7: 12038, 2017/09. DOI: 10.1038/s41598-017-10275-4 (13 pages)
  18. Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, M. Michael Gromiha, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Kun-Yi Hsin, Hiroaki Kitano, Kazuki Yamamoto, Nobuyoshi Sugaya, Koya Kato, Tatsuya Okuno, George Chikenji, Masahiro Mochizuki, Nobuaki Yasuo, Ryunosuke Yoshino, Keisuke Yanagisawa, Tomohiro Ban, Reiji Teramoto, Chandrasekaran Ramakrishnan, A. Mary Thangakani, D. Velmurugan, Philip Prathipati, Junichi Ito, Yuko Tsuchiya, Kenji Mizuguchi, Teruki Honma, Takatsugu Hirokawa, Yutaka Akiyama, Masakazu Sekijima. “Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target”, Scientific Reports, 5: 17209, 2015/11. DOI: 10.1038/srep17209 (13 pages)
  19. Keisuke Yanagisawa, Takashi Ishida, Yutaka Akiyama. “Drug clearance pathway prediction based on semi-supervised learning”, IPSJ Transactions on Bioinformatics, 8: 21-27, 2015/08. DOI: 10.2197/ipsjtbio.8.21

Peer-reviewed International Conferences

  1. Kazuki Takabatake, Kazuki Izawa, Motohiro Akikawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Improved Homology Search for Metagenomic Analysis by Two-Step Seed Search with Reduced Amino Acid Alphabets”, The 10th International Conference on Bioinformatics and Biomedical Science (ICBBS2021), 2021/10/29-31. (Oral Presentation)
  2. Kazuya Isawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Antisense oligonucleotide activity analysis based on opening and binding energies to targets”, In Proceedings of the 27th International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’21), 2021/07/27. (14 pages, Oral Presentation)
  3. Masahito Ohue, Ryota Ii, Keisuke Yanagisawa, Yutaka Akiyama. “Molecular activity prediction using graph convolutional deep neural network considering distance on a molecular graph”, In Proceedings of the 25th International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’19), 2019/07/29. (7 pages, Oral Presentation)
    * The paper is published at arXiv.
  4. Takashi Tajimi, Naoki Wakui, Keisuke Yanagisawa, Yasushi Yoshikawa, Masahito Ohue, Yutaka Akiyama. “Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques”, The 29th International Conference on Genome Informatics (GIW 2018), 2018/12/04. (14 pages, Oral Presentation)
  5. Keisuke Yanagisawa, Shunta Komine, Rikuto Kubota, Masahito Ohue, Yutaka Akiyama. “Optimization of memory use of fragment extension-based protein-ligand docking with an original fast minimum cost flow algorithm”, The 16th Asia Pacific Bioinformatics Conference (APBC2018), O5, 2018/01/15. (8 pages, Oral Presentation)
  6. Takanori Hayashi, Yuri Matsuzaki, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions”, The 16th Asia Pacific Bioinformatics Conference (APBC2018), O20, 2018/01/15. (12 pages, Oral Presentation)
  7. Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “ESPRESSO: An ultrafast compound pre-screening method based on compound decomposition”, The 27th International Conference on Genome Informatics (GIW 2016), 2016/10/04. (8 pages, Oral Presentation)

International Conferences (without peer review)

Oral Presentation

  1. Keisuke Yanagisawa, Yoshitaka Moriwaki, Tohru Terada, Kentaro Shimizu. “Systematic construction of the cosolvents sets for cosolvent MD (CMD) with the large-scale simulation”, AHeDD2019/IPAB2019 Joint Symposium, 2019/11/29.

Poster Presentation

  1. Keisuke Yanagisawa, Ryunosuke Yoshino, Genki Kudo, Takatsugu Hirokawa. “Quantitative Evaluation of Protein-Compound Substructure Interaction with Inverse Mixed-Solvent Molecular Dynamics Simulation”, 21st IUPAB and 62nd BSJ joint congress 2024, 2024/6/24-28.
  2. Masahito Ohue, Takanori Hayashi, Yuri Matsuzaki, Keisuke Yanagisawa, Yutaka Akiyama. “Megadock-Web: An Integrated Database of High-Throughput Structure-Based Protein-Protein Interaction Predictions”, Biophysical Society 63rd Annual Meeting, 2792-Pos, 2019/03/02-06.
  3. Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “Spresso: An ultrafast compound pre-screening method based on compound fragmentation”, Biophysical Society 62nd Annual Meeting, 2018/02/17-21.
  4. Rikuto Kubota, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Toward efficient protein-ligand docking for virtual screening by reuse of fragments”, The 16th Asia Pacific Bioinformatics Conference (APBC2018), Poster C5, 2018/01/15-17.
  5. Keisuke Yanagisawa, Shunta Komine, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “Fast pre-filtering for virtual screening based on compound fragmentation”, 3rd IIT Madras – Tokyo Tech Joint Symposium on Algorithms and Applications of Bioinformatics, P34, 2015/11/05-06.

Domestic Conferences (without peer review)

Oral Presentation

  1. Keisuke Yanagisawa, Ryunosuke Yoshino, Genki Kudo, Takatsugu Hirokawa. “Quantitative Estimation of Protein-Compound Substructure Interaction with Inverse Mixed-Solvent Molecular Dynamics Simulation”, The 24th Annual Meeting of the Protein Science Society of Japan: [WS-14] バイオインフォマティクスと農芸化学の出会うところ, 2024/06/13.
  2. Ayako Nunobe, Keisuke Yanagisawa, Yutaka Akiyama. “フラグメントに基づくバーチャルスクリーニングへの利用などを目指したフラグメント集合の選定”, IPSJ SIG Technical Report, 2022-BIO-77(31): 1-7, 2024/03/08.
  3. Yudai Noso, Keisuke Yanagisawa, Yutaka Akiyama. “分子動力学シミュレーション軌跡データから抽出した位置依存特徴量を活用した環状ペプチドの膜透過性予測”, IPSJ SIG Technical Report, 2022-BIO-77(16): 1-8, 2024/03/07.
  4. Jianan Li, Keisuke Yanagisawa, Yutaka Akiyama. “CycPeptMP: Development of Membrane Permeability Prediction of Cyclic Peptides with Multi-Level Molecular Features and Data Augmentation”, IPSJ SIG Technical Report, 2022-BIO-77(15): 1-8, 2024/03/07.
  5. Keisuke Yanagisawa. “Further and Drastic Improvement of AlphaFold is Needed: Insights from Drug Design”, Informatics in Biology, Medicine, and Pharmacology 2023 (IIBMP2023): [WS-2] バイオインフォマティクスの8の問題, 2023/09/05.
    * Presentation slide (Japanese slide)
  6. Jianan Li, Keisuke Yanagisawa, Masatake Sugita, Takuya Fujie, Masahito Ohue, Yutaka Akiyama. “CycPeptMPDB：包括的な環状ペプチド膜透過率データベースの開発”, IPSJ SIG Technical Report, 2022-BIO-74(38): 1-8, 2023/07/01.
  7. Tomoya Saito, Keisuke Yanagisawa, Yutaka Akiyama. “フラグメント対の相対位置から検索可能な化合物立体配座データベースの構築”, IPSJ SIG Technical Report, 2022-BIO-74(37): 1-8, 2023/07/01.
  8. Ginga Watanabe, Keisuke Yanagisawa, Yutaka Akiyama. “標的RNAの高次構造予測に基づく低活性ASO候補配列の推測”, IPSJ SIG Technical Report, 2022-BIO-74(36): 1-8, 2023/07/01.
  9. Masatake Sugita, Takuya Fujie, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Lipid composition is critical for accurate membrane permeability prediction of cyclic peptides by molecular dynamics simulations”, Chem-Bio Informatics Society(CBI) Annual Meeting 2022, O3-2, 2022/10/25.
  10. Keisuke Yanagisawa, Rikuto Kubota, Yasushi Yoshikawa, Masahito Ohue, Yutaka Akiyama. “REstretto: An efficient protein-ligand docking tool based on a fragment reuse strategy”, Chem-Bio Informatics Society(CBI) Annual Meeting 2022, O2-1, 2022/10/25.
    * Presentation slide
  11. Yudai Noso, Masatake Sugita, Takuya Fujie, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “分子動力学シミュレーション軌跡データからの環状ペプチドの膜透過性と相関が高い特徴量の抽出”, IPSJ SIG Technical Report, 2022-BIO-70(51): 1-8, 2022/06/29.
  12. Keisuke Yanagisawa, Ryunosuke Yoshino, Genki Kudo, Takatsugu Hirokawa. “Inverse Mixed-Solvent Molecular Dynamics for Visualization of Residue Interaction Profile of Molecular Probes”, The 22nd Annual Meeting of the Protein Science Society of Japan, O7-12, 2022/06/07.
    * Presentation slide
  13. Yuki Tsushima, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “新たなデータセットによる長距離フラグメントリンキング手法の再評価”, IPSJ SIG Technical Report, 2021-BIO-69(16): 1-8, 2022/03/11.
  14. Masaya Inagaki, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Database of Drug Candidates Represented by 3D Positional Relationships between Fragments”, IPSJ SIG Technical Report, 2021-BIO-69(15): 1-8, 2022/03/11.
  15. Mahiro Yamazaki, Kazuki Izawa, Ryo Hirata, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Development of a Genome-wide Fast Short Nucleotide Sequence Search Method Considering Binding Energy”, IPSJ SIG Technical Report, 2021-BIO-69(8): 1-8, 2022/03/10.
  16. Shu Tamano, Kazuki Izawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Proposal of Evaluation Off-target Effects Method in Gapmer ASO”, IPSJ SIG Technical Report, 2021-BIO-69(7): 1-7, 2022/03/10.
  17. Masatake Sugita, Satoshi Sugiyama, Takuya Fujie, Yasushi Yoshikawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Large-scale membrane permeability prediction of cyclic peptides crossing a lipid bilayer based on enhanced sampling molecular dynamics simulations”, The 58th Annual Meeting of the Biophysical Society of Japan, 2-03-1712, 2021/11/25.
  18. Masatake Sugita, Satoshi Sugiyama, Takuya Fujie, Yasushi Yoshikawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Large-scale membrane permeability prediction of cyclic peptides crossing a lipid bilayer based on enhanced sampling molecular dynamics simulations”, Chem-Bio Informatics Society(CBI) Annual Meeting 2021, O2-1, 2021/10/26.
  19. Yuki Tsushima, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “タンパク質表面との結合親和性を考慮した長距離フラグメントリンキング手法の開発”, IPSJ SIG Technical Report, 2021-BIO-67(1): 1-8, 2021/09/30.
  20. Kazuya Isawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Inhibitory Activity Model of Antisense Oligonucleotide Based on Estimation of Binding and Opening Energies to Target Seuquences”, IPSJ SIG Technical Report, 2020-BIO-65(7): 1-7, 2021/03/11.
  21. Keisuke Yanagisawa. “Rational probe set construction for mixed-solvent molecular dynamics”, The 43rd Annual Meeting of the Molecular Biology Socienty of Japan (MBSJ2020): [2F-11] forum “State-of-the-art researches of in silico drug discovery”, online, 2020/12/03.
  22. Rikuto Kubota, Keisuke Yanagisawa, Yasushi Yoshikawa, Masahito Ohue, Yutaka Akiyama. “Development of an efficient protein-ligand docking method by reuse of fragments”, IPSJ SIG Technical Report, 2019-BIO-61(3): 1-8, 2020/03/12.
  23. Masahito Ohue, Ryota Ii, Keisuke Yanagisawa, Yutaka Akiyama. “Molecular activity prediction using graph convolutional deep neural network considering distance on a molecular graph”, IPSJ SIG Technical Report, 2019-MPS-124(3): 1-4, 2019/07/29.
  24. Ryota Ii, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Graph convolutional neural networks considering distanceon molecular graph for compound activity prediction”, IPSJ SIG Technical Report, 2018-BIO-57(11): 1-8, 2019/03/09.
  25. Rikuto Kubota, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Development of efficient protein-ligand docking method for virtual screening by reuse of fragments”, IPSJ SIG Technical Report, 2018-BIO-54(42): 1-7, 2018/06/15.
  26. Keisuke Yanagisawa, Shunta Komine, Rikuto Kubota, Masahito Ohue, Yutaka Akiyama. “An exact algorithm for the weighted offline cache problem in protein-ligand docking based on fragment extension”, IPSJ SIG Technical Report, 2017-BIO-50(38): 1-8, 2017/06/25.
    * [download] The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the IPSJ.
  27. Keisuke Yanagisawa, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “Compound filtering by estimation of the candidate compound’s upper limit size using target protein structure”, IPSJ SIG Technical Report, 2016-BIO-49(6): 1-7, 2017/03/24.
    * [download] The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the IPSJ.
  28. Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “ESPRESSO: An ultrafast compound pre-screening method based on compound decomposition”, IPSJ SIG Technical Report, 2016-BIO-46(18): 1-7, 2016/07/05.
    * [download] The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the IPSJ.
  29. Shogo D. Suzuki, Keisuke Yanagisawa, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “Prediction of Human c-Yes Kinase Inhibitors by SVM and Deep Learning”, IPSJ SIG Technical Report, 2015-BIO-42(36): 1-7, 2015/06/24.
  30. Keisuke Yanagisawa, Takashi Ishida, Yuichi Sugiyama, Yutaka Akiyama. “Drug clearance pathway prediction based on semi-supervised learning”, IPSJ SIG Technical Report, 2014-BIO-41(11): 1-6, 2015/03/20.
    * [download] The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the IPSJ.
  31. Keisuke Yanagisawa, Takashi Ishida, Yutaka Akiyama. “Drug clearance pathway prediction using semi-supervised learning”, IPSJ SIG Technical Report, 2014-BIO-38(10): 1-6, 2014/06/26.
    * [download] The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the IPSJ.

Poster Presentation

  1. Chie Motono, Keisuke Yanagisawa, Genki Kudo, Takatsugu Hirokawa, Kenichiro Imai. “Cryptic site prediction using mixed-solvent molecular dynamics simulation”, The 24th Annual Meeting of the Protein Science Society of Japan, 2024/06/11-13.
  2. Keisuke Yanagisawa, Ryunosuke Yoshino, Genki Kudo, Takatsugu Hirokawa. “Quantitative Evaluation of Protein-Chemical Substructure Interaction with Inverse Mixed-Solvent Molecular Dynamics Simulation”, The 61st Annual Meeting of The Biophysical Society of Japan, 2Pos013, 2023/11/14-16.
    * Presentation poster
  3. Masatake Sugita, Takuya Fujie, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Development of a Protocol for Predicting Membrane Permeability of Cyclic Peptides Based on Molecular Dynamics Simulations”, The 61st Annual Meeting of The Biophysical Society of Japan, 2Pos183, 2023/11/14-16.
  4. Keisuke Yanagisawa, Ryunosuke Yoshino, Genki Kudo, Takatsugu Hirokawa. “Quantitative Estimation of Protein-Chemical Substructure Interaction with Inverse Mixed-Solvent Molecular Dynamics Simulation”, Chem-Bio Informatics Society(CBI) Annual Meeting 2023, 2023/10/23-26.
    * Presentation poster
  5. Genki Kudo, Keisuke Yanagisawa, Ryunosuke Yoshino, Takatsugu Hirokawa. “Amino Acid Preference Mapping on Protein-Protein Interaction Surface using Mixed-Solvent Molecular Dynamics”, Chem-Bio Informatics Society(CBI) Annual Meeting 2022, P02-04, 2022/10/25-27.
  6. Keisuke Yanagisawa, Ryunosuke Yoshino, Genki Kudo, Takatsugu Hirokawa. “Inverse Mixed-Solvent Molecular Dynamics for Visualization of Amino Acid Residue Interaction Profile of Molecular Probes”, The 60th Annual Meeting of The Biophysical Society of Japan, 1Pos031, 2022/09/28.
    * Presentation Poster
  7. Masatake Sugita, Satoshi Sugiyama, Takuya Fujie, Yasushi Yoshikawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Large-scale membrane permeability prediction of cyclic peptides crossing a lipid bilayer based on enhanced sampling molecular dynamics simulations”, 43rd Symposium on Solution Chemistry of Japan, P38, 2021/10/29.
  8. Keisuke Yanagisawa, Yoshitaka Moriwaki, Tohru Terada, Kentaro Shimizu. “Systematic construction of the cosolvents sets for cosolvent MD (CMD) with the large-scale computation”, Chem-Bio Informatics Society(CBI) Annual Meeting 2019, P1-24, 2019/10/22-24.
  9. Keisuke Yanagisawa, Yoshitaka Moriwaki, Tohru Terada, Kentaro Shimizu. “Estimation of the probability map (Pmap) similarity of cosolvent MD (CMD) from structural similarities of cosolvents”, The 57th Annual Meeting of The Biophysical Society of Japan, 1Pos012, 2019/09/24.
  10. Juanjuan Lu, Keisuke Yanagisawa, Takashi Ishida. “Development of a novel linear notation of chemical compounds for deep learning”, Chem-Bio Informatics Society(CBI) Annual Meeting 2018, P5-17, 2018/10/09-11.
  11. Ryota Ii, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “大域的化合物特徴を表現するグラフ畳み込みネットワーク”, Informatics in Biology, Medicine and Pharmacology 2018 (IIBMP2018), P-76, 2018/09/19-21.
  12. Rikuto Kubota, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama. “Development of efficient protein-ligand docking method for virtual screening by reuse of fragments”, 1st RWBC-OIL Workshop, Poster no. 18, 2018/05/08.
  13. Masahito Ohue, Takanori Hayashi, Yuri Matsuzaki, Keisuke Yanagisawa, Yutaka Akiyama. “MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions”, Informatics in Biology, Medicine and Pharmacology 2017 (IIBMP2017), P57, 2017/09/27-29.
  14. Masahito Ohue, Takanori Hayashi, Yuri Matsuzaki, Keisuke Yanagisawa, Yutaka Akiyama. “MEGADOCK-WEB: an integrated database of structure-based protein-protein interaction predictions”, The 55th Annual Meeting of The Biophysical Society of Japan, 3Pos174, 2017/09/21.
  15. Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “ESPRESSO: An ultrafast compound pre-screening method with segmented compounds”, Chem-Bio Informatics Society(CBI) Annual Meeting 2016, P2-19, 2016/10/25-27.
  16. Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “ESPRESSO: An ultrafast compound pre-screening method based on compound segmentation”, Informatics in Biology, Medicine and Pharmacology 2016 (IIBMP2016), P65, 2016/09/29-10/01.
  17. Keisuke Yanagisawa, Shunta Komine, Masahito Ohue, Takashi Ishida, Yutaka Akiyama; “Fast pre-filtering for virtual screening based on ligand decomposition”, 第21回 創剤フォーラム若手研究会, P-6, 2015/11/28.
  18. Keisuke Yanagisawa, Shunta Komine, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “Fast pre-filtering for virtual screening based on compound decomposition”, Informatics in Biology, Medicine and Pharmacology 2015 (IIBMP2015), 2015/10/29-31.

Books

  1. 金森 敬文 監訳, データサイエンスと機械学習 理論からPythonによる実装まで, 東京化学同人, 2022
    * Japanese translation of: Kroese DP, et al., Data Science and Machine Learning: Mathematical and Statistical Methods, CRC Press, 2019.

Patents

Grants

  1. “Designing cyclic peptide with target protein selection based on mixed-solvent molecular dynamics simulation”, JSPS KAKENHI (Grant-in-Aid for Scientific Research (B)) 23H03495, PI, 18 590 000 yen, 2023/04-2027/03.
  2. “Recognition of protein surface where suitable for ligand binding with Inverse-MSMD simulations”, Grant for young researcher, School of Computing, Tokyo Institute of Technology, PI, 500 000 yen, 2022/06-2023/03.
  3. “Development of chemical substructure-based virtual screening method for huge compound library”, JSPS KAKENHI (Grant-in-Aid for Scientific Research (B)) 22H03684, Co-investigator (PI: Yutaka Akiyama), 17 030 000 yen (in total), 2022/04-2025/03.
  4. “Computer-aided lead optimization with cosolvent molecular dynamics (CMD)”, Grant for young researcher, School of Computing, Tokyo Institute of Technology, PI, 496 000 yen, 2020/10-2021/03.
  5. “Comprehensive prediction of cryptic binding sites by multi-task deep learning”, JSPS KAKENHI (grant-in-aid for young reseachers) 20K19917, PI, 4 290 000 yen, 2020/04-2023/03.
  6. “Improvement of cosolvent MD which enables the systematic search of binding sites and the novel screening way of drug candidates”, JSPS KAKENHI (grant-in-aid for JSPS fellows) 19J00878, PI, 1 820 000 yen, 2019/04-2020/03.
  7. “Development of divide-and-conquer based docking method using common partial structures of hundreds of millions of compounds”, JSPS KAKENHI (grant-in-aid for JSPS fellows) 17J06897, PI, 2 100 000 yen, 2017/04-2019/03.

Computation resources, etc.

  1. Yutaka Akiyama, Masahito Ohue, Keisuke Yanagisawa, Masatake Sugita, Takuya Fujie, Yudai Noso, “Detailed analysis of membrane permeation mechanisms of difficult-to-predict membrane permeability peptides based on large-scale simulations using a two-dimensional replica exchange method”, TSUBAME Grand Challenge Program, 2023/05.
  2. Yutaka Akiyama, Masahito Ohue, Keisuke Yanagisawa, Masatake Sugita, Takuya Fujie, Yudai Noso, “Development of a method to accelerate convergence of large-scale simulations of membrane permeation processes of cyclic peptides based on a two-dimensional replica exchange method”, TSUBAME Grand Challenge Program, 2022/05.
  3. Yutaka Akiyama, Keisuke Yanagisawa, Ohue Masahito, Yasushi Yoshikawa, Masatake Sugita, Takuya Fujie, Kento Aoyama, Satoshi Sugiyama, “Membrane permeability prediction of more than 100 cyclic peptides by REUS simulations and machine learning”, “ABCI Grand Challenge” Program, National Institute of Advanced Industrial Science and Technology (AIST), 2020/08/26-2020/08/27.
  4. Keisuke Yanagisawa, “Construction of the optimal cosolvents sets for cosolvent MD (CMD) with the large-scale computation”, Initiative on Promotion of Supercomputing for Young or Women Researchers, Information Technology Center, The University of Tokyo, $950, 2019/10-2020/03.

Awards

  1. 2019 Education Award of Excellence, Tokyo Institute of Technology (2021/03/02)
    * Yoshihiro Miyake, Naoaki Okazaki, Takefumi Kanamori, Tsuyoshi Murata, Shin-ya Nishizaki, Kazuyuki Shudo, Kenji Kise, Masamichi Shimosaka, Masakazu Sekijima, Keisuke Yanagisawa, Masahiro Kuze, Mitsuji Sampei, Ichiro Yamanaka, Takehiko Itoh, Toru Takeuchi, Takeo Yamaguchi, Kei Sakaguchi. “Progressive Graduate Minor in Data Science and Artificial Intelligence”
  2. Seiichi Tejima Doctoral Dissertation Award (2020/02/27)
  3. Grand Prize (Schrödinger K.K. Prize), 4th Computer-Aided Drug Discovery Contest (2017/12/15)
    * Team “DD-friends” (Yusuke Matsuyama, Takanori Hayashi, Ryota Ii, Toshitaka Tanebe, Takashi Tajimi, Rin Sato, Hikaru Ikeda, Keisuke Yanagisawa) : “Compound virtual screening by hybridization of structure- and ligand-based methods”
  4. Student Encouragement Prize, 2nd Computer-Aided Drug Discovery Contest (2015/07/17) [link]
    * Team “DEDENNE” (Shogo D. Suzuki, Keisuke Yanagisawa) : “c-Yes kinase inhibitor prediction with DEDENNE: Druggability Estimator by Deep Neural Network”
  5. 2014 SIGBIO Best Student Presentation Award, IPSJ SIGBIO (2015/06/25) [link]
    * Keisuke Yanagisawa, Takashi Ishida, Yutaka Akiyama. “Drug clearance pathway prediction based on semi-supervised learning”, IPSJ Transactions on Bioinformatics, 8: 21-27, 2015/08. DOI: 10.2197/ipsjtbio.8.21
  6. Student Encouragement Prize, 1st Computer-Aided Drug Discovery Contest (2014/07/17) [link]
    * Team “Tokyo Tech TSUBAME” (Nobuaki Yasuo, Ryunosuke Yoshino, Keisuke Yanagisawa, Tomohiro Ban) : “Compound screening with constraint docking”
  7. 2013 Tokyo Institute of Technology Academic Excellence Awards, Tokyo Institute of Technology (2014/03/26)
  8. Bronze Prize, 2009 High School Chemistry Grand Prix (2009/09/26)

Others

  1. 柳澤 渓甫. “共溶媒分子動力学における薬剤設計向け共溶媒セットの構築”, スーパーコンピューティングニュース, 23: 46-49, 2021/07. (in Japanese)
  2. 柳澤 渓甫, “「なんで、私が留学に！？」から始まる留学”, JSBi news letter 38, 4-5, 2020/08. (in Japanese)
  3. Keisuke Yanagisawa: “情報工学から考える創薬”, 2nd Tokyo Bioinformatics Meeting, 2018/08/07. (Oral presentation, in Japanese)
  4. Keisuke Yanagisawa: “Spresso - 高速なタンパク質立体構造ベース創薬を目指して”, 1st Tokyo Bioinformatics Meeting, 2017/08/09. (Oral presentation, in Japanese)
  5. Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “フラグメント分割による超高速化合物プレスクリーニング手法 ESPRESSO”, 第56回 生物物理若手の会 夏の学校, 2016/09/02-05. (poster session, in Japanese)
  6. Keisuke Yanagisawa, Shunta Komine, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. “Fast pre-docking method based on compound structure fragmentation”, ACLS International Summer School 2015, 2015/08/30-09/06. (poster session)
  7. Keisuke Yanagisawa, Takashi Ishida, Yutaka Akiyama. “Drug clearance pathway prediction using semi-supervised learning”, ACLS International Summer School 2014, 2014/08/13-19. (poster session)

Theses