| A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation M Brylinski, J Skolnick Proceedings of the National Academy of sciences 105 (1), 129-134, 2008 | 382 | 2008 |
| Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets WP Feinstein, M Brylinski Journal of cheminformatics 7, 1-10, 2015 | 219 | 2015 |
| eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates L Pu, M Naderi, T Liu, HC Wu, S Mukhopadhyay, M Brylinski BMC Pharmacology and Toxicology 20, 1-15, 2019 | 126 | 2019 |
| FINDSITE: a combined evolution/structure-based approach to protein function prediction J Skolnick, M Brylinski Briefings in bioinformatics 10 (4), 378-391, 2009 | 120 | 2009 |
| Gauss-function-based model of hydrophobicity density in proteins L Konieczny, M Brylinski, I Roterman In silico biology 6 (1-2), 15-22, 2006 | 111 | 2006 |
| DeepDrug3D: classification of ligand-binding pockets in proteins with a convolutional neural network L Pu, RG Govindaraj, JM Lemoine, HC Wu, M Brylinski PLoS computational biology 15 (2), e1006718, 2019 | 108 | 2019 |
| Aromatic interactions at the ligand–protein interface: Implications for the development of docking scoring functions M Brylinski Chemical biology & drug design 91 (2), 380-390, 2018 | 108 | 2018 |
| FINDSITE‐metal: integrating evolutionary information and machine learning for structure‐based metal‐binding site prediction at the proteome level M Brylinski, J Skolnick Proteins: Structure, Function, and Bioinformatics 79 (3), 735-751, 2011 | 101 | 2011 |
| The continuity of protein structure space is an intrinsic property of proteins J Skolnick, AK Arakaki, SY Lee, M Brylinski Proceedings of the National Academy of Sciences 106 (37), 15690-15695, 2009 | 95 | 2009 |
| FINDSITELHM: A Threading-Based Approach to Ligand Homology Modeling M Brylinski, J Skolnick PLoS computational biology 5 (6), e1000405, 2009 | 87 | 2009 |
| What is the relationship between the global structures of apo and holo proteins? M Brylinski, J Skolnick Proteins: Structure, Function, and Bioinformatics 70 (2), 363-377, 2008 | 80 | 2008 |
| eFindSite: Improved prediction of ligand binding sites in protein models using meta-threading, machine learning and auxiliary ligands M Brylinski, WP Feinstein Journal of computer-aided molecular design 27, 551-567, 2013 | 74 | 2013 |
| Prediction of functional sites based on the fuzzy oil drop model M Bryliński, K Prymula, W Jurkowski, M Kochańczyk, E Stawowczyk, ... PLoS computational biology 3 (5), e94, 2007 | 67 | 2007 |
| Break Down in Order To Build Up: Decomposing Small Molecules for Fragment-Based Drug Design with eMolFrag T Liu, M Naderi, C Alvin, S Mukhopadhyay, M Brylinski Journal of chemical information and modeling 57 (4), 627-631, 2017 | 65 | 2017 |
| Q‐Dock: Low‐resolution flexible ligand docking with pocket‐specific threading restraints M Brylinski, J Skolnick Journal of computational chemistry 29 (10), 1574-1588, 2008 | 61 | 2008 |
| Hydrophobic collapse in (in silico) protein folding M Brylinski, L Konieczny, I Roterman Computational biology and chemistry 30 (4), 255-267, 2006 | 61 | 2006 |
| Assessing the similarity of ligand binding conformations with the Contact Mode Score Y Ding, Y Fang, J Moreno, J Ramanujam, M Jarrell, M Brylinski Computational biology and chemistry 64, 403-413, 2016 | 57 | 2016 |
| Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction M Brylinski Journal of chemical information and modeling 53 (11), 3097-3112, 2013 | 51 | 2013 |
| Conformational subspace in simulation of early‐stage protein folding W Jurkowski, M Brylinski, L Konieczny, Z Wiíniowski, I Roterman Proteins: Structure, Function, and Bioinformatics 55 (1), 115-127, 2004 | 49 | 2004 |
| Comparative assessment of strategies to identify similar ligand-binding pockets in proteins RG Govindaraj, M Brylinski BMC bioinformatics 19, 1-17, 2018 | 47 | 2018 |
