| Improvements to the APBS biomolecular solvation software suite E Jurrus, D Engel, K Star, K Monson, J Brandi, LE Felberg, DH Brookes, ... Protein Science 27 (1), 112-128, 2018 | 1935 | 2018 |
| Lessons learned in empirical scoring with smina from the CSAR 2011 benchmarking exercise DR Koes, MP Baumgartner, CJ Camacho Journal of chemical information and modeling 53 (8), 1893-1904, 2013 | 1002 | 2013 |
| Protein–ligand scoring with convolutional neural networks M Ragoza, J Hochuli, E Idrobo, J Sunseri, DR Koes Journal of chemical information and modeling 57 (4), 942-957, 2017 | 863 | 2017 |
| GNINA 1.0: molecular docking with deep learning AT McNutt, P Francoeur, R Aggarwal, T Masuda, R Meli, M Ragoza, ... Journal of cheminformatics 13 (1), 43, 2021 | 491 | 2021 |
| ZINCPharmer: pharmacophore search of the ZINC database DR Koes, CJ Camacho Nucleic acids research 40 (W1), W409-W414, 2012 | 476 | 2012 |
| Pharmit: interactive exploration of chemical space J Sunseri, DR Koes Nucleic acids research 44 (W1), W442-W448, 2016 | 354 | 2016 |
| 3Dmol. js: molecular visualization with WebGL N Rego, D Koes Bioinformatics 31 (8), 1322-1324, 2015 | 338 | 2015 |
| Three-dimensional convolutional neural networks and a cross-docked data set for structure-based drug design PG Francoeur, T Masuda, J Sunseri, A Jia, RB Iovanisci, I Snyder, ... Journal of chemical information and modeling 60 (9), 4200-4215, 2020 | 270 | 2020 |
| Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening L Chen, A Cruz, S Ramsey, CJ Dickson, JS Duca, V Hornak, DR Koes, ... PloS one 14 (8), e0220113, 2019 | 250 | 2019 |
| Pharmer: efficient and exact pharmacophore search DR Koes, CJ Camacho Journal of chemical information and modeling 51 (6), 1307-1314, 2011 | 197 | 2011 |
| Generating 3D molecules conditional on receptor binding sites with deep generative models M Ragoza, T Masuda, DR Koes Chemical science 13 (9), 2701-2713, 2022 | 167 | 2022 |
| Enabling large-scale design, synthesis and validation of small molecule protein-protein antagonists D Koes, K Khoury, Y Huang, W Wang, M Bista, GM Popowicz, S Wolf, ... PloS one 7 (3), e32839, 2012 | 123 | 2012 |
| Open source molecular modeling S Pirhadi, J Sunseri, DR Koes Journal of Molecular Graphics and Modelling 69, 127-143, 2016 | 118 | 2016 |
| PocketQuery: protein–protein interaction inhibitor starting points from protein–protein interaction structure DR Koes, CJ Camacho Nucleic acids research 40 (W1), W387-W392, 2012 | 110 | 2012 |
| Visualizing convolutional neural network protein-ligand scoring J Hochuli, A Helbling, T Skaist, M Ragoza, DR Koes Journal of Molecular Graphics and Modelling 84, 96-108, 2018 | 104 | 2018 |
| DeepFrag: a deep convolutional neural network for fragment-based lead optimization H Green, DR Koes, JD Durrant Chemical Science 12 (23), 8036-8047, 2021 | 81 | 2021 |
| Small-molecule inhibitor starting points learned from protein–protein interaction inhibitor structure DR Koes, CJ Camacho Bioinformatics 28 (6), 784-791, 2012 | 81 | 2012 |
| SolTranNet–A machine learning tool for fast aqueous solubility prediction PG Francoeur, DR Koes Journal of chemical information and modeling 61 (6), 2530-2536, 2021 | 77 | 2021 |
| Precise omnidirectional camera calibration D Strelow, J Mishler, D Koes, S Singh Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision …, 2001 | 73 | 2001 |
| Exhaustive fluorine scanning towards potent p53-Mdm2 antagonists Y Huang, S Wolf, D Koes, GM Popowicz, CJ Camacho, TA Holak, ... ChemMedChem 7 (1), 49, 2011 | 64 | 2011 |
Jocelyn SunseriD. E. Shaw ResearchПодтвержден адрес электронной почты в домене deshawresearch.com
