| Macromolecular modeling and design in Rosetta: recent methods and frameworks JK Leman, BD Weitzner, SM Lewis, J Adolf-Bryfogle, N Alam, RF Alford, ... Nature methods 17 (7), 665-680, 2020 | 565 | 2020 |
| De novo protein design by deep network hallucination I Anishchenko, SJ Pellock, TM Chidyausiku, TA Ramelot, S Ovchinnikov, ... Nature 600 (7889), 547-552, 2021 | 402 | 2021 |
| Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: meeting new challenges I Kufareva, V Katritch, RC Stevens, R Abagyan Structure 22 (8), 1120-1139, 2014 | 181 | 2014 |
| 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 | 159 | 2023 |
| Protein sequence design by conformational landscape optimization C Norn, BIM Wicky, D Juergens, S Liu, D Kim, D Tischer, B Koepnick, ... Proceedings of the National Academy of Sciences 118 (11), e2017228118, 2021 | 141 | 2021 |
| Principles for computational design of binding antibodies D Baran, MG Pszolla, GD Lapidoth, C Norn, O Dym, T Unger, S Albeck, ... Proceedings of the National Academy of Sciences 114 (41), 10900-10905, 2017 | 140 | 2017 |
| AbDesign: An algorithm for combinatorial backbone design guided by natural conformations and sequences GD Lapidoth, D Baran, GM Pszolla, C Norn, A Alon, MD Tyka, ... Proteins: Structure, Function, and Bioinformatics 83 (8), 1385-1406, 2015 | 109 | 2015 |
| An enumerative algorithm for de novo design of proteins with diverse pocket structures B Basanta, MJ Bick, AK Bera, C Norn, CM Chow, LP Carter, I Goreshnik, ... Proceedings of the National Academy of Sciences 117 (36), 22135-22145, 2020 | 64 | 2020 |
| Computational design of protein self-assembly CH Norn, I André Current opinion in structural biology 39, 39-45, 2016 | 62 | 2016 |
| Molecular characterization of oxysterol binding to the Epstein-Barr virus-induced gene 2 (GPR183) T Benned-Jensen, S Norn, Christoffer, Laurent, CM Madsen, HM Larsen, ... The Journal of Biological Chemistry 287, 35470-35483, 2012 | 50 | 2012 |
| Top-down design of protein architectures with reinforcement learning ID Lutz, S Wang, C Norn, A Courbet, AJ Borst, YT Zhao, A Dosey, L Cao, ... Science 380 (6642), 266-273, 2023 | 42 | 2023 |
| Mapping the Ca2+ induced structural change in calreticulin SG Boelt, C Norn, MI Rasmussen, I André, E Čiplys, R Slibinskas, ... Journal of Proteomics 142, 138-148, 2016 | 38 | 2016 |
| Assessment and challenges of ligand docking into comparative models of G-protein coupled receptors ED Nguyen, C Norn, T Frimurer, J Meiler PLoS One 8 (7), e67302, 2013 | 38 | 2013 |
| Structural basis for constitutive activity and agonist-induced activation of the enteroendocrine fat sensor GPR119 MS Engelstoft, C Norn, M Hauge, ... British Journal of Pharmacology, 2014 | 35 | 2014 |
| High-accuracy modeling of antibody structures by a search for minimum-energy recombination of backbone fragments CH Norn, G Lapidoth, SJ Fleishman Proteins 85 (1), 30-38, 2016 | 26 | 2016 |
| Protein sequence design by explicit energy landscape optimization C Norn, BIM Wicky, D Juergens, S Liu, D Kim, B Koepnick, I Anishchenko, ... BioRxiv, 2020.07. 23.218917, 2020 | 21 | 2020 |
| A combined computational-experimental approach to define the structural origin of antibody recognition of sialyl-Tn, a tumor-associated carbohydrate antigen R Amon, OC Grant, S Leviatan Ben-Arye, S Makeneni, AK Nivedha, ... Scientific reports 8 (1), 10786, 2018 | 15 | 2018 |
| A thermodynamic model of protein structure evolution explains empirical amino acid substitution matrices C Norn, I André, DL Theobald Protein science 30 (10), 2057-2068, 2021 | 13 | 2021 |
| Mutation-guided unbiased modeling of the fat sensor GPR119 for high-yield agonist screening C Norn, M Hauge, MS Engelstoft, SH Kim, J Lehmann, RM Jones, ... Structure 23 (12), 2377-2386, 2015 | 11 | 2015 |
| Computational design of sequence-specific DNA-binding proteins CJ Glasscock, R Pecoraro, R McHugh, LA Doyle, W Chen, O Boivin, ... bioRxiv, 2023 | 6 | 2023 |
