| Large-scale membrane permeability prediction of cyclic peptides crossing a lipid bilayer based on enhanced sampling molecular dynamics simulations M Sugita, S Sugiyama, T Fujie, Y Yoshikawa, K Yanagisawa, M Ohue, ... Journal of chemical information and modeling 61 (7), 3681-3695, 2021 | 51 | 2021 |
| Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target S Chiba, K Ikeda, T Ishida, MM Gromiha, YH Taguchi, M Iwadate, ... Scientific reports 5 (1), 17209, 2015 | 45 | 2015 |
| An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes S Chiba, T Ishida, K Ikeda, M Mochizuki, R Teramoto, YH Taguchi, ... Scientific Reports 7 (1), 12038, 2017 | 32 | 2017 |
| MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions T Hayashi, Y Matsuzaki, K Yanagisawa, M Ohue, Y Akiyama BMC bioinformatics 19, 61-72, 2018 | 30 | 2018 |
| QEX: target-specific druglikeness filter enhances ligand-based virtual screening M Mochizuki, SD Suzuki, K Yanagisawa, M Ohue, Y Akiyama Molecular Diversity 23, 11-18, 2019 | 16 | 2019 |
| Spresso: an ultrafast compound pre-screening method based on compound decomposition K Yanagisawa, S Komine, SD Suzuki, M Ohue, T Ishida, Y Akiyama Bioinformatics 33 (23), 3836-3843, 2017 | 14 | 2017 |
| Solving generalized polyomino puzzles using the ising model K Takabatake, K Yanagisawa, Y Akiyama Entropy 24 (3), 354, 2022 | 11 | 2022 |
| Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques T Tajimi, N Wakui, K Yanagisawa, Y Yoshikawa, M Ohue, Y Akiyama BMC bioinformatics 19, 157-170, 2018 | 11 | 2018 |
| Lipid composition is critical for accurate membrane permeability prediction of cyclic peptides by molecular dynamics simulations M Sugita, T Fujie, K Yanagisawa, M Ohue, Y Akiyama Journal of Chemical Information and Modeling 62 (18), 4549-4560, 2022 | 10 | 2022 |
| EXPRORER: Rational cosolvent set construction method for cosolvent molecular dynamics using large-scale computation K Yanagisawa, Y Moriwaki, T Terada, K Shimizu Journal of Chemical Information and Modeling 61 (6), 2744-2753, 2021 | 10 | 2021 |
| CycPeptMPDB: A comprehensive database of membrane permeability of cyclic peptides J Li, K Yanagisawa, M Sugita, T Fujie, M Ohue, Y Akiyama Journal of Chemical Information and Modeling 63 (7), 2240-2250, 2023 | 7 | 2023 |
| Molecular activity prediction using graph convolutional deep neural network considering distance on a molecular graph M Ohue, R Ii, K Yanagisawa, Y Akiyama arXiv preprint arXiv:1907.01103, 2019 | 7 | 2019 |
| Plasma protein binding prediction focusing on residue-level features and circularity of cyclic peptides by deep learning J Li, K Yanagisawa, Y Yoshikawa, M Ohue, Y Akiyama Bioinformatics 38 (4), 1110-1117, 2022 | 5 | 2022 |
| Optimization of memory use of fragment extension-based protein–ligand docking with an original fast minimum cost flow algorithm K Yanagisawa, S Komine, R Kubota, M Ohue, Y Akiyama Computational Biology and Chemistry 74, 399-406, 2018 | 4 | 2018 |
| Effective Protein–Ligand Docking Strategy via Fragment Reuse and a Proof-of-Concept Implementation K Yanagisawa, R Kubota, Y Yoshikawa, M Ohue, Y Akiyama ACS omega 7 (34), 30265-30274, 2022 | 2 | 2022 |
| Prediction device, trained model generation device, prediction method, and trained model generation method Y Akiyama, O Masahito, K Yanagisawa, Y Yoshikawa, J Li US Patent App. 17/577,527, 2022 | 1 | 2022 |
| Improved Large-Scale Homology Search by Two-Step Seed Search Using Multiple Reduced Amino Acid Alphabets K Takabatake, K Izawa, M Akikawa, K Yanagisawa, M Ohue, Y Akiyama Genes 12 (9), 1455, 2021 | 1 | 2021 |
| QUBO Problem Formulation of Fragment-Based Protein–Ligand Flexible Docking K Yanagisawa, T Fujie, K Takabatake, Y Akiyama Entropy 26 (5), 397, 2024 | | 2024 |
| AAp-MSMD: Amino Acid Preference Mapping on Protein–Protein Interaction Surfaces Using Mixed-Solvent Molecular Dynamics G Kudo, K Yanagisawa, R Yoshino, T Hirokawa Journal of Chemical Information and Modeling 63 (24), 7768-7777, 2023 | | 2023 |
| 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 T SAITO, K YANAGISAWA, Y AKIYAMA 情報処理学会研究報告 (Web) 2023 (MPS-143), 2023 | | 2023 |
