Publications
Notes: * corresponding author
Journal Articles
24. The consolidation of open-source computer-assisted chemical synthesis data into a comprehensive database. Haris Hasic, Takashi Ishida*. Journal of Cheminformatics 18, 4 (2026). doi: 10.1186/s13321-025-01130-0
23. Helix encoder: a compound-protein interaction prediction model specifically designed for class A GPCRs. Haruki Yamane, Takashi Ishida*. Frontiers in Bioinformatics 3, 1193025 (2023). doi: 10.3389/fbinf.2023.1193025
22. Comparing supervised learning and rigorous approach for predicting protein stability upon point mutations in difficult targets. Jason Kurniawan, Takashi Ishida*. Journal of Chemical Information and Modeling 63, 6778–6788 (2023). doi: 10.1021/acs.jcim.3c00750
21. Discovery of a hidden Trypanosoma cruzi spermidine synthase binding site and inhibitors through in silico, in vitro, and X-ray crystallography. Ryunosuke Yoshino, Nobuaki Yasuo, Yohsuke Hagiwara, Takashi Ishida, Daniel Ken Inaoka, Yasushi Amano, Yukihiro Tateishi, Kazuki Ohno, Ichiji Namatame, Tatsuya Niimi, Masaya Orita, Kiyoshi Kita, Yutaka Akiyama, Masakazu Sekijima*. ACS Omega 8, 25850–25860 (2023). doi: 10.1021/acsomega.3c01314
20. A benchmark dataset for evaluating practical performance of model quality assessment of homology models. Yuma Takei, Takashi Ishida*. Bioengineering 9, 118 (2022). doi: 10.3390/bioengineering9030118
19. Protein model quality estimation using molecular dynamics simulation. Jason Kurniawan, Takashi Ishida*. ACS Omega 7, 24274–24281 (2022). doi: 10.1021/acsomega.2c01475
18. Single-step retrosynthesis prediction based on the identification of potential disconnection sites using molecular substructure fingerprints. Haris Hasic, Takashi Ishida*. Journal of Chemical Information and Modeling 61, 641–652 (2021). doi: 10.1021/acs.jcim.0c01100
17. Modeling SARS-CoV-2 proteins in the CASP-commons experiment. Andriy Kryshtafovych, John Moult, Wendy M. Billings, Dennis Della Corte, Krzysztof Fidelis, Sohee Kwon, Kliment Olechnovič, Chaok Seok, Česlovas Venclovas, Jonghun Won, et al. (Takashi Ishida included). Proteins: Structure, Function, and Bioinformatics 89, 1987–1996 (2021). doi: 10.1002/prot.26231
16. Taxonomic and gene category analyses of subgingival plaques from a group of Japanese individuals with and without periodontitis. Kazuki Izawa, Kazuko Okamoto-Shibayama, Daichi Kita, Sachiyo Tomita, Atsushi Saito, Takashi Ishida, Masahito Ohue, Yutaka Akiyama, Kazuyuki Ishihara. International Journal of Molecular Sciences 22, 5298 (2021). doi: 10.3390/ijms22105298
15. P3CMQA: single-model quality assessment using 3DCNN with profile-based features. Yuma Takei, Takashi Ishida*. Bioengineering 8, 40 (2021). doi: 10.3390/bioengineering8030040
14. Computer aided drug discovery review for infectious diseases with case study of anti-Chagas project. Nobuaki Yasuo, Takashi Ishida, Masakazu Sekijima*. Parasitology International 83, 102366 (2021). doi: 10.1016/j.parint.2021.102366
13. End-to-end learning for compound activity prediction based on binding pocket information. Toshitaka Tanebe, Takashi Ishida*. BMC Bioinformatics 22 (Suppl 3), 529 (2021). doi: 10.1186/s12859-021-04440-w
12. Development of computational pipeline software for genome/exome analysis on the K computer. Kento Aoyama, Masanori Kakuta, Yuri Matsuzaki, Takashi Ishida, Masahito Ohue, Yutaka Akiyama. Supercomputing Frontiers and Innovations 7, 37–54 (2020). doi: 10.14529/jsfi200102
11. Sequence alignment generation using intermediate sequence search for homology modeling. Shuichiro Makigaki, Takashi Ishida*. Computational and Structural Biotechnology Journal 18, 2043–2050 (2020). doi: 10.1016/j.csbj.2020.07.012
10. Mathematical proof of the third order accuracy of the speedy double bootstrap method. Aizhen Ren, Takashi Ishida, Yutaka Akiyama. Communications in Statistics—Theory and Methods 49, 3950–3964 (2020). doi: 10.1080/03610926.2019.1594295
9. Sequence alignment using machine learning for accurate template-based protein structure prediction. Shuichiro Makigaki, Takashi Ishida*. Bioinformatics 36, 104–111 (2020). doi: 10.1093/bioinformatics/btz483
8. Protein model accuracy estimation based on local structure quality assessment using 3D convolutional neural network. Rin Sato, Takashi Ishida*. PLoS ONE 14, e0221347 (2019). doi: 10.1371/journal.pone.0221347
7. In silico prediction of major clearance pathways of drugs among 9 routes with two-step support vector machines. Naomi Wakayama, Kota Toshimoto, Kazuya Maeda, Shun Hotta, Takashi Ishida, Yutaka Akiyama, Yuichi Sugiyama*. Pharmaceutical Research 35, 197 (2018). doi: 10.1007/s11095-018-2479-1
6. Spresso: an ultrafast compound pre-screening method based on compound decomposition. Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama*. Bioinformatics 33, 3836–3843 (2017). doi: 10.1093/bioinformatics/btx178
5. An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes. 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*. Scientific Reports 7, 12038 (2017). doi: 10.1038/s41598-017-10275-4
4. In silico, in vitro, X-ray crystallography, and integrated strategies for discovering spermidine synthase inhibitors for Chagas disease. Ryunosuke Yoshino, Nobuaki Yasuo, Yohsuke Hagiwara, Takashi Ishida, Daniel Ken Inaoka, Yasushi Amano, Yukihiro Tateishi, Kazuki Ohno, Ichiji Namatame, Tatsuya Niimi, Masaya Orita, Kiyoshi Kita, Yutaka Akiyama, Masakazu Sekijima*. Scientific Reports 7, 6666 (2017). doi: 10.1038/s41598-017-06411-9
3. A massively parallel sequence similarity search for metagenomic sequencing data. Masanori Kakuta, Shuji Suzuki, Kazuki Izawa, Takashi Ishida, Yutaka Akiyama*. International Journal of Molecular Sciences 18, 2124 (2017). doi: 10.3390/ijms18102124
2. GPU-acceleration of sequence homology searches with database subsequence clustering. Shuji Suzuki, Masanori Kakuta, Takashi Ishida, Yutaka Akiyama*. PLoS ONE 11, e0157338 (2016). doi: 10.1371/journal.pone.0157338
1. Development of a support vector machine-based system to predict whether a compound is a substrate of a given drug transporter using its chemical structure. Atsushi Ose, Kota Toshimoto, Kazushi Ikeda, Kazuya Maeda, Shuya Yoshida, Fumiyoshi Yamashita, Mitsuru Hashida, Takashi Ishida, Yutaka Akiyama*. Journal of Pharmaceutical Sciences (2016). doi: 10.1016/j.xphs.2016.04.023
Conference Papers
5. Fair dataset splitting for protein-ligand complex binding affinity prediction. Nozomu Yamazaki, Takashi Ishida*. 13th International Conference on Bioinformatics and Computational Biology (ICBCB), pp. 97–102. IEEE (2025). doi: 10.1109/ICBCB64873.2025.11198062
4. Acceleration of machine learning-based sequence alignment generation for homology modeling. M. Narui, Shuichiro Makigaki, Takashi Ishida*. Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA), pp. 129–134 (2019).
3. End-to-end learning based compound activity prediction using binding pocket information. Toshitaka Tanebe, Takashi Ishida*. International Conference on Intelligent Computing (ICIC), pp. 226–234. Springer (2019).
2. Stacking multiple molecular fingerprints for improving ligand-based virtual screening. Yusuke Matsuyama, Takashi Ishida*. International Conference on Intelligent Computing (ICIC), pp. 279–288. Springer (2018).
1. Improvement of template-based protein structure prediction by using chimera alignment. Shuichiro Makigaki, Takashi Ishida*. 8th International Conference on Bioscience, Biochemistry and Bioinformatics (ICBBB), pp. 32–37. ACM (2018). doi: 10.1145/3180382.3180405
Book Chapters
1. GHOSTX: a fast sequence homology search tool for functional annotation of metagenomic data. Shuji Suzuki, Takashi Ishida, Masahito Ohue, Masanori Kakuta, Yutaka Akiyama*. In Protein Function Prediction: Methods and Protocols, pp. 15–25. Springer New York (2017). doi: 10.1007/978-1-4939-7015-5_2