ジャーナル論文 / Journal
  1. Tučs, A., Ito, T., Kurumida, Y., Kawada, S., Nakazawa, H., Saito, Y., Umetsu, M., and Tsuda, K., "Extensive antibody search with whole spectrum black-box optimization", Sci. Rep. 14(1), 552, (2024).
  2. Sumita, M., Takahashi, H., Sugita, T., and Tsuda, K., "Theoretical Insight into the Origin of Dielectric and Magnetoelectric FeCo Alloy–Metal Fluoride Insulators", The Journal of Physical Chemistry C 128(3), 1386–1392, (2024).
  3. Suleiman, M., Frere, G. A., Törner, R., Tabunar, L., Bhole, G. V., Taverner, K., Tsuchimura, N., Pichugin, D., Lichtenecker, R. J., Vozny, O., Gunning, P., Arthanari, H., Sljoka, A., and Prosser, R. S., "Characterization of conformational states of the homodimeric enzyme fluoroacetate dehalogenase by 19 F– 13 C two-dimensional NMR", RSC Chemical Biology 5(12), 1214–1218, (2024).
  4. Picard, L., Orazietti, A., Tran, D. P., Tucs, A., Hagimoto, S., Qi, Z., Huang, S. K., Tsuda, K., Kitao, A., Sljoka, A., and Prosser, R. S., "Balancing G protein selectivity and efficacy in the adenosine A2A receptor", Nat. Chem. Biol., 1–9, (2024).
  5. Kozome, D., Sljoka, A., and Laurino, P., "Remote loop evolution reveals a complex biological function for chitinase enzymes beyond the active site", Nat. Commun. 15(1), 3227, (2024).
  6. Yuan, W., Hibi, Y., Tamura, R., Sumita, M., Nakamura, Y., Naito, M., and Tsuda, K., "Revealing factors influencing polymer degradation with rank-based machine learning", Patterns 4(12), 100846, (2023).
  7. Yoshida, T., Hanada, H., Nakagawa, K., Taji, K., Tsuda, K., and Takeuchi, I., "Efficient model selection for predictive pattern mining model by safe pattern pruning", Patterns 4(12), 100890, (2023).
  8. Tučs, A., Berenger, F., Yumoto, A., Tamura, R., Uzawa, T., and Tsuda, K., "Quantum Annealing Designs Nonhemolytic Antimicrobial Peptides in a Discrete Latent Space", ACS Med. Chem. Lett. 14(5), 577–582, (2023).
  9. Terayama, K., Osaki, Y., Fujita, T., Tamura, R., Naito, M., Tsuda, K., Matsui, T., and Sumita, M., "Koopmans’ Theorem-Compliant Long-Range Corrected (KTLC) Density Functional Mediated by Black-Box Optimization and Data-Driven Prediction for Organic Molecules", J. Chem. Theory Comput. 19(19), 6770–6781, (2023).
  10. Tamura, R., Terayama, K., Sumita, M., and Tsuda, K., "Ranking Pareto optimal solutions based on projection free energy", Phys. Rev. Materials 7(9), 093804, (2023).
  11. Nguyen, D. H., and Tsuda, K., "On a linear fused Gromov-Wasserstein distance for graph structured data", Pattern Recognit. 138, 109351, (2023).
  12. Mao, Z., Matsuda, Y., Tamura, R., and Tsuda, K., "Chemical design with GPU-based Ising machines", Digital Discovery 2(4), 1098–1103, (2023).
  13. Li, J., Sumita, M., Tamura, R., and Tsuda, K., "Interpretable Fragment‐Based Molecule Design with Self‐Learning Entropic Population Annealing", Advanced Intelligent Systems 5(10), (2023).
  14. Ishida, S., Aasawat, T., Sumita, M., Katouda, M., Yoshizawa, T., Yoshizoe, K., Tsuda, K., and Terayama, K., "ChemTSv2: Functional molecular design using de novo molecule generator", Wiley Interdisciplinary Reviews Computational Molecular Science 13(6), (2023).
  15. Huang, S. K., Picard, L., Rahmatullah, R. S., Pandey, A., Van Eps, N., Sunahara, R. K., Ernst, O. P., Sljoka, A., and Prosser, R. S., "Mapping the conformational landscape of the stimulatory heterotrimeric G protein", Nat. Struct. Mol. Biol., 1–10, (2023).
  16. Tokuhisa, A., Akinaga, Y., Terayama, K., Okamoto, Y., and Okuno, Y., "Single-Image Super-Resolution Improvement of X‑ray Single-Particle Diffraction Images Using a Convolutional Neural Network", J. Chem. Inf. Model. 62(14), 3352–3364, (2022).
  17. Tamura, R., Sumita, M., Terayama, K., Tsuda, K., Izumi, F., and Matsushita, Y., "Automatic Rietveld refinement by robotic process automation with RIETAN-FP", Science and Technology of Advanced Materials Methods 2(1), 435–444, (2022).
  18. Sumita, M., Terayama, K., Tamura, R., and Tsuda, K., "QCforever: A Quantum Chemistry Wrapper for Everyone to Use in Black-Box Optimization", J. Chem. Inf. Model., (2022).
  19. Sumita, M., Terayama, K., Suzuki, N., Ishihara, S., Tamura, R., Chahal, M. K., Payne, D. T., Yoshizoe, K., and Tsuda, K., "De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning", Sci. Adv. 8, eabj3906, (2022).
  20. Kumawat, N., Tucs, A., Bera, S., Chuev, G. N., Valiev, M., Fedotova, M. V., Kruchinin, S. E., Tsuda, K., Sljoka, A., and Chakraborty, A., "Site Density Functional Theory and Structural Bioinformatics Analysis of the SARS-CoV Spike Protein and hACE2 Complex", Molecules 27(3), (2022).
  21. Huang, S. K., Almurad, O., Pejana, R. J., Morrison, Z. A., Pandey, A., Picard, L., Nitz, M., Sljoka, A., and Prosser, R. S., "Allosteric modulation of the adenosine A(2A) receptor by cholesterol", eLife 11, (2022).
  22. Fujita, T., Terayama, K., Sumita, M., Tamura, R., Nakamura, Y., Naito, M., and Tsuda, K., "Understanding the evolution of a de novo molecule generator via characteristic functional group monitoring", Sci. Technol. Adv. Mater. 23(1), 352–360, (2022).
  23. Besaw, J. E., Reichenwallner, J., De Guzman, P., Tucs, A., Kuo, A., Morizumi, T., Tsuda, K., Sljoka, A., Miller, R. J., and Ernst, O. P., "Low pH structure of heliorhodopsin reveals chloride binding site and intramolecular signaling pathway", Sci. Rep. 12(1), 13955, (2022).
  24. Baksh, K. A., Augustine, J., Sljoka, A., Prosser, R. S., and Zamble, D. B., "Mechanistic insights into the nickel-dependent allosteric response of the Helicobacter pylori NikR transcription factor", J. Biol. Chem. 299(1), 102785, (2022).
  25. Zhang, Y., Zhang, J., Suzuki, K., Sumita, M., Terayama, K., Li, J., Mao, Z., Tsuda, K., and Suzuki, Y., "Discovery of polymer electret material via de novo molecule generation and functional group enrichment analysis", Appl. Phys. Lett. 118, 223904, (2021).
  26. Tran, D. P., Tada, S., Yumoto, A., Kitao, A., Ito, Y., Uzawa, T., and Tsuda, K., "Using molecular dynamics simulations to prioritize and understand AI‑generated cell penetrating peptides", Sci. Rep. 11, 10630, (2021).
  27. Terayama, K., Sumita, M., Katouda, M., Tsuda, K., and Okuno, Y., "Efficient Search for Energetically Favorable Molecular Conformations against Metastable States via Gray-Box Optimization", J. Chem. Theory Comput. 17, 5419–5427, (2021).
  28. Sun, X., Tamura, R., Sumita, M., Mori, K., Terayama, K., and Tsuda, K., "Integrating Incompatible Assay Data Sets with Deep Preference Learning", ACS Med. Chem. Lett. 13, 70–75, (2021).
  29. Sumita, M., and Yoshikawa, N., "Augmented Lagrangian method for spin-coupled wave function", Int. J. Quantum Chem., (2021).
  30. Saito, Y., Oikawa, M., Sato, T., Nakazawa, H., Tomoyuki, I., Kameda, T., Tsuda, K., and Umetsu, M., "Machine-Learning-Guided Library Design Cycle for Directed Evolution of Enzymes: The Effects of Training Data Composition on Sequence Space Exploration", ACS Catal. 11, 14615–14624, (2021).
  31. Nojima, S., Terayama, K., Shimoura, S., Hijiki, S., Nonomura, N., Morii, E., Okuno, Y., and Fujita, K., "A deep learning system to diagnose the malignant potential of urothelial carcinoma cells in cytology specimens", Cancer Cytopathol 129(12), 984–995, (2021).
  32. Izawa, H., Yasufuku, F., Nokami, T., Ifuku, S., Saimoto, H., Matsui, T., Morihashi, K., and Sumita, M., "Unique Photophysical Properties of 1,8-Naphthalimide Derivatives: Generation of Semi-stable Radical Anion Species by Photo-Induced Electron Transfer from a Carboxy Group", ACS Omega 6(20), 13456–13465, (2021).
  33. Huang, S. K., Pandey, A., Duy Phuoc Tran, Villanueva, N. L., Kitao, A., Sunahara, R. K., Sljoka, A., and Prosser, R. S., "Delineating the conformational landscape of the adenosine A(2A) receptor during G protein coupling", Cell 184(7), 1884–+, (2021).
  34. Fowler, N. J., Sljoka, A., and Williamson, M. P., "The accuracy of NMR protein structures in the Protein Data Bank", Structure 29(12), 1430–+, (2021).
  35. Das, J. K., Thakuri, B., MohanKumar, K., Roy, S., Sljoka, A., Sun, G., and Chakraborty, A., "Mutation-Induced Long-Range Allosteric Interactions in the Spike Protein Determine the Infectivity of SARS-CoV-2 Emerging Variants", ACS Omega 6(46), 31305–31320, (2021).