| ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules A Leaver-Fay, M Tyka, SM Lewis, OF Lange, J Thompson, R Jacak, ... Methods in enzymology 487, 545-574, 2011 | 2084 | 2011 |
| MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology M Feig, J Karanicolas, CL Brooks III Journal of Molecular Graphics and Modelling 22 (5), 377-395, 2004 | 976 | 2004 |
| 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 | 735 | 2020 |
| Structure-based design of non-natural amino-acid inhibitors of amyloid fibril formation SA Sievers, J Karanicolas, HW Chang, A Zhao, L Jiang, O Zirafi, ... Nature 475 (7354), 96-100, 2011 | 540 | 2011 |
| The 3D profile method for identifying fibril-forming segments of proteins MJ Thompson, SA Sievers, J Karanicolas, MI Ivanova, D Baker, ... Proceedings of the National Academy of Sciences 103 (11), 4074-4078, 2006 | 476 | 2006 |
| The origins of asymmetry in the folding transition states of protein L and protein G J Karanicolas, CL Brooks III Protein Science 11 (10), 2351-2361, 2002 | 448 | 2002 |
| Atomic accuracy in predicting and designing noncanonical RNA structure R Das, J Karanicolas, D Baker Nature methods 7 (4), 291-294, 2010 | 417 | 2010 |
| Allostery in its many disguises: from theory to applications SJ Wodak, E Paci, NV Dokholyan, IN Berezovsky, A Horovitz, J Li, ... Structure 27 (4), 566-578, 2019 | 340 | 2019 |
| Musashi RNA-binding proteins as cancer drivers and novel therapeutic targets AE Kudinov, J Karanicolas, EA Golemis, Y Boumber Clinical Cancer Research 23 (9), 2143-2153, 2017 | 272 | 2017 |
| Improved Gō-like models demonstrate the robustness of protein folding mechanisms towards non-native interactions J Karanicolas, CL Brooks III Journal of molecular biology 334 (2), 309-325, 2003 | 261 | 2003 |
| Targeting CDK9 reactivates epigenetically silenced genes in cancer H Zhang, S Pandey, M Travers, H Sun, G Morton, J Madzo, W Chung, ... Cell 175 (5), 1244-1258. e26, 2018 | 215 | 2018 |
| A de novo protein binding pair by computational design and directed evolution J Karanicolas, JE Corn, I Chen, LA Joachimiak, O Dym, SH Peck, ... Molecular cell 42 (2), 250-260, 2011 | 201 | 2011 |
| Machine learning classification can reduce false positives in structure-based virtual screening YO Adeshina, EJ Deeds, J Karanicolas Proceedings of the National Academy of Sciences 117 (31), 18477-18488, 2020 | 171 | 2020 |
| Computational design of affinity and specificity at protein–protein interfaces J Karanicolas, B Kuhlman Current opinion in structural biology 19 (4), 458-463, 2009 | 155 | 2009 |
| Isothermal analysis of ThermoFluor data can readily provide quantitative binding affinities N Bai, H Roder, A Dickson, J Karanicolas Scientific reports 9 (1), 2650, 2019 | 154 | 2019 |
| The structural basis for biphasic kinetics in the folding of the WW domain from a formin-binding protein: lessons for protein design? J Karanicolas, CL Brooks III Proceedings of the National Academy of Sciences 100 (7), 3954-3959, 2003 | 153 | 2003 |
| Natural product (−)-gossypol inhibits colon cancer cell growth by targeting RNA-binding protein Musashi-1 L Lan, C Appelman, AR Smith, J Yu, S Larsen, RT Marquez, H Liu, X Wu, ... Molecular oncology 9 (7), 1406-1420, 2015 | 142 | 2015 |
| Rationalizing PROTAC-mediated ternary complex formation using Rosetta N Bai, SA Miller, GV Andrianov, M Yates, P Kirubakaran, J Karanicolas Journal of chemical information and modeling 61 (3), 1368-1382, 2021 | 109 | 2021 |
| Druggable protein interaction sites are more predisposed to surface pocket formation than the rest of the protein surface DK Johnson, J Karanicolas PLoS computational biology 9 (3), e1002951, 2013 | 99 | 2013 |
| Targeting the interaction between RNA-binding protein HuR and FOXQ1 suppresses breast cancer invasion and metastasis X Wu, G Gardashova, L Lan, S Han, C Zhong, RT Marquez, L Wei, ... Communications biology 3 (1), 193, 2020 | 95 | 2020 |
