| Accurate prediction of protein structures and interactions using a three-track neural network M Baek, F DiMaio, I Anishchenko, J Dauparas, S Ovchinnikov, GR Lee, ... Science 373 (6557), 871-876, 2021 | 5930 | 2021 |
| Generalized biomolecular modeling and design with RoseTTAFold All-Atom R Krishna, J Wang, W Ahern, P Sturmfels, P Venkatesh, I Kalvet, GR Lee, ... Science 384 (6693), eadl2528, 2024 | 935 | 2024 |
| De novo design of luciferases using deep learning AHW Yeh, C Norn, Y Kipnis, D Tischer, SJ Pellock, D Evans, P Ma, ... Nature 614 (7949), 774-780, 2023 | 443 | 2023 |
| Prediction of protein structure and interaction by GALAXY protein modeling programs WH Shin, GR Lee, L Heo, H Lee, C Seok Bio Design 2 (1), 1-11, 2014 | 232 | 2014 |
| De novo design of high-affinity binders of bioactive helical peptides S Vázquez Torres, PJY Leung, P Venkatesh, ID Lutz, F Hink, HH Huynh, ... Nature 626 (7998), 435-442, 2024 | 206 | 2024 |
| Atomic context-conditioned protein sequence design using LigandMPNN J Dauparas, GR Lee, R Pecoraro, L An, I Anishchenko, C Glasscock, ... Nature Methods, 1-7, 2025 | 193 | 2025 |
| Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: a CASP‐CAPRI experiment MF Lensink, S Velankar, A Kryshtafovych, SY Huang, ... Proteins: Structure, Function, and Bioinformatics 84, 323-348, 2016 | 176 | 2016 |
| GalaxyRefine2: simultaneous refinement of inaccurate local regions and overall protein structure GR Lee, J Won, L Heo, C Seok Nucleic acids research 47 (W1), W451-W455, 2019 | 153 | 2019 |
| Effective protein model structure refinement by loop modeling and overall relaxation GR Lee, L Heo, C Seok Proteins: Structure, Function, and Bioinformatics 84, 293-301, 2016 | 149 | 2016 |
| Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments H Park, GR Lee, L Heo, C Seok PloS one 9 (11), e113811, 2014 | 104 | 2014 |
| Accurate protein structure prediction: what comes next C Seok, M Baek, M Steinegger, H Park, GR Lee, J Won Biodesign 9 (3), 47-50, 2021 | 73 | 2021 |
| Binding and sensing diverse small molecules using shape-complementary pseudocycles L An, M Said, L Tran, S Majumder, I Goreshnik, GR Lee, D Juergens, ... Science 385 (6706), 276-282, 2024 | 63* | 2024 |
| Biophysical and functional characterization of Norrin signaling through Frizzled4 I Bang, HR Kim, AH Beaven, J Kim, SB Ko, GR Lee, W Kan, H Lee, W Im, ... Proceedings of the National Academy of Sciences 115 (35), 8787-8792, 2018 | 59 | 2018 |
| High‐accuracy refinement using Rosetta in CASP13 H Park, GR Lee, DE Kim, I Anishchenko, Q Cong, D Baker Proteins: Structure, Function, and Bioinformatics 87 (12), 1276-1282, 2019 | 54 | 2019 |
| Galaxy7TM: flexible GPCR–ligand docking by structure refinement GR Lee, C Seok Nucleic acids research 44 (W1), W502-W506, 2016 | 51 | 2016 |
| Protein ensemble generation through variational autoencoder latent space sampling S Mansoor, M Baek, H Park, GR Lee, D Baker Journal of Chemical Theory and Computation 20 (7), 2689-2695, 2024 | 47 | 2024 |
| Computational design of sequence-specific DNA-binding proteins CJ Glasscock, RJ Pecoraro, R McHugh, LA Doyle, W Chen, O Boivin, ... Nature Structural & Molecular Biology 32 (11), 2252-2261, 2025 | 39 | 2025 |
| Evaluating GPCR modeling and docking strategies in the era of deep learning-based protein structure prediction S Lee, S Kim, GR Lee, S Kwon, H Woo, C Seok, H Park Computational and Structural Biotechnology Journal 21, 158-167, 2023 | 38 | 2023 |
| An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12 C Keasar, LJ McGuffin, B Wallner, G Chopra, B Adhikari, D Bhattacharya, ... Scientific reports 8 (1), 9939, 2018 | 25 | 2018 |
| De novo design of high-affinity protein binders to bioactive helical peptides SV Torres, PJY Leung, ID Lutz, P Venkatesh, JL Watson, F Hink, ... Biorxiv, 2022.12. 10.519862, 2022 | 24 | 2022 |
