| Structural insight into allosteric modulation of protease-activated receptor 2 RKY Cheng, C Fiez-Vandal, O Schlenker, K Edman, B Aggeler, DG Brown, ... Nature 545 (7652), 112-115, 2017 | 247 | 2017 |
| Molecular rift: virtual reality for drug designers M Norrby, C Grebner, J Eriksson, J Bostrom Journal of chemical information and modeling 55 (11), 2475-2484, 2015 | 134 | 2015 |
| Ligand Binding Mechanism in Steroid Receptors: From Conserved Plasticity to Differential Evolutionary Constraints K Edman, A Hosseini, MK Bjursell, A Aagaard, L Wissler, A Gunnarsson, ... Structure 23 (12), 2280-2290, 2015 | 107 | 2015 |
| Topics in Current Chemistry TC Schmidt, A Paasche, C Grebner, K Ansorg, J Becker, W Lee, B Engels, ... Springer, 2012 | 72* | 2012 |
| Virtual screening in the cloud: how big is big enough? C Grebner, E Malmerberg, A Shewmaker, J Batista, A Nicholls, ... Journal of chemical information and modeling 60 (9), 4274-4282, 2019 | 64 | 2019 |
| Automated de novo design in medicinal chemistry: which types of chemistry does a generative neural network learn? C Grebner, H Matter, AT Plowright, G Hessler Journal of medicinal chemistry 63 (16), 8809-8823, 2020 | 43 | 2020 |
| Interpretation of structure–activity relationships in real-world drug design data sets using explainable artificial intelligence T Harren, H Matter, G Hessler, M Rarey, C Grebner Journal of Chemical Information and Modeling 62 (3), 447-462, 2022 | 40 | 2022 |
| Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design C Grebner, J Iegre, J Ulander, K Edman, A Hogner, C Tyrchan Journal of chemical information and modeling 56 (4), 774-787, 2016 | 35 | 2016 |
| Efficiency of tabu‐search‐based conformational search algorithms C Grebner, J Becker, S Stepanenko, B Engels Journal of computational chemistry 32 (10), 2245-2253, 2011 | 32 | 2011 |
| Application of deep neural network models in drug discovery programs C Grebner, H Matter, D Kofink, J Wenzel, F Schmidt, G Hessler ChemMedChem 16 (24), 3772-3786, 2021 | 26 | 2021 |
| 3D-Lab: a collaborative web-based platform for molecular modeling C Grebner, M Norrby, J Enström, I Nilsson, A Hogner, J Henriksson, ... Future Medicinal Chemistry 8 (14), 1739-1752, 2016 | 22 | 2016 |
| Exploring Binding Mechanisms in Nuclear Hormone Receptors by Monte Carlo and X-ray-derived Motions C Grebner, D Lecina, V Gil, J Ulander, P Hansson, A Dellsen, C Tyrchan, ... Biophysical Journal 112 (6), 1147-1156, 2017 | 21 | 2017 |
| A new tabu-search-based algorithm for solvation of proteins C Grebner, J Kästner, W Thiel, B Engels Journal of chemical theory and computation 9 (1), 814-821, 2013 | 16 | 2013 |
| PELE-MSM: a Monte Carlo based protocol for the estimation of absolute binding free energies JF Gilabert, C Grebner, D Soler, D Lecina, M Municoy, O Gracia Carmona, ... Journal of chemical theory and computation 15 (11), 6243-6253, 2019 | 15 | 2019 |
| CAST: A new program package for the accurate characterization of large and flexible molecular systems C Grebner, J Becker, D Weber, D Bellinger, M Tafipolski, C Brückner, ... Journal of computational chemistry 35 (24), 1801-1807, 2014 | 12 | 2014 |
| Impact of applicability domains to generative artificial intelligence M Langevin, C Grebner, S Güssregen, S Sauer, Y Li, H Matter, ... ACS omega 8 (25), 23148-23167, 2023 | 11 | 2023 |
| PathOpt—A global transition state search approach: Outline of algorithm C Grebner, LP Pason, B Engels Journal of computational chemistry 34 (21), 1810-1818, 2013 | 9 | 2013 |
| Artificial Intelligence in Compound Design C Grebner, H Matter, G Hessler Artificial Intelligence in Drug Design, 349-382, 2022 | 7 | 2022 |
| QM/MM investigations of organic chemistry oriented questions TC Schmidt, A Paasche, C Grebner, K Ansorg, J Becker, W Lee, B Engels Electronic Effects in Organic Chemistry, 25-101, 2012 | 6 | 2012 |
| Optimizing interactions to protein binding sites by integrating docking-scoring strategies into generative AI methods S Sauer, H Matter, G Hessler, C Grebner Frontiers in Chemistry 10, 1012507, 2022 | 4 | 2022 |
