| QSAR modeling: where have you been? Where are you going to? A Cherkasov, EN Muratov, D Fourches, A Varnek, II Baskin, M Cronin, ... Journal of medicinal chemistry 57 (12), 4977-5010, 2014 | 2446 | 2014 |
| The value of antimicrobial peptides in the age of resistance M Magana, M Pushpanathan, AL Santos, L Leanse, M Fernandez, ... The lancet infectious diseases 20 (9), e216-e230, 2020 | 1190 | 2020 |
| QSAR without borders EN Muratov, J Bajorath, RP Sheridan, IV Tetko, D Filimonov, V Poroikov, ... Chemical Society Reviews 49 (11), 3525-3564, 2020 | 970 | 2020 |
| Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information I Sushko, S Novotarskyi, R Körner, AK Pandey, M Rupp, W Teetz, ... Journal of computer-aided molecular design 25 (6), 533-554, 2011 | 788 | 2011 |
| Rapid identification of potential inhibitors of SARS‐CoV‐2 main protease by deep docking of 1.3 billion compounds AT Ton, F Gentile, M Hsing, F Ban, A Cherkasov Molecular informatics 39 (8), 2000028, 2020 | 554 | 2020 |
| SimBoost: a read-across approach for predicting drug–target binding affinities using gradient boosting machines T He, M Heidemeyer, F Ban, A Cherkasov, M Ester Journal of cheminformatics 9 (1), 24, 2017 | 509 | 2017 |
| Use of artificial intelligence in the design of small peptide antibiotics effective against a broad spectrum of highly antibiotic-resistant superbugs A Cherkasov, K Hilpert, H Jenssen, CD Fjell, M Waldbrook, SC Mullaly, ... ACS chemical biology 4 (1), 65-74, 2009 | 473 | 2009 |
| Deep docking: a deep learning platform for augmentation of structure based drug discovery F Gentile, V Agrawal, M Hsing, AT Ton, F Ban, U Norinder, ME Gleave, ... ACS central science 6 (6), 939-949, 2020 | 403 | 2020 |
| Artificial intelligence–enabled virtual screening of ultra-large chemical libraries with deep docking F Gentile, JC Yaacoub, J Gleave, M Fernandez, AT Ton, F Ban, A Stern, ... Nature Protocols 17 (3), 672-697, 2022 | 399 | 2022 |
| Identification of novel antibacterial peptides by chemoinformatics and machine learning CD Fjell, H Jenssen, K Hilpert, WA Cheung, N Panté, REW Hancock, ... Journal of medicinal chemistry 52 (7), 2006-2015, 2009 | 369 | 2009 |
| Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis H Zhu, A Tropsha, D Fourches, A Varnek, E Papa, P Gramatica, T Oberg, ... Journal of chemical information and modeling 48 (4), 766-784, 2008 | 355 | 2008 |
| Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR A Tropsha, O Isayev, A Varnek, G Schneider, A Cherkasov Nature Reviews Drug Discovery 23 (2), 141-155, 2024 | 308 | 2024 |
| AMPer: a database and an automated discovery tool for antimicrobial peptides CD Fjell, REW Hancock, A Cherkasov Bioinformatics 23 (9), 1148-1155, 2007 | 303 | 2007 |
| The transformational role of GPU computing and deep learning in drug discovery M Pandey, M Fernandez, F Gentile, O Isayev, A Tropsha, AC Stern, ... Nature Machine Intelligence 4 (3), 211-221, 2022 | 302 | 2022 |
| Applicability domains for classification problems: benchmarking of distance to models for Ames mutagenicity set I Sushko, S Novotarskyi, R Körner, AK Pandey, A Cherkasov, J Li, ... Journal of chemical information and modeling 50 (12), 2094-2111, 2010 | 302 | 2010 |
| Functional analysis of androgen receptor mutations that confer anti-androgen resistance identified in circulating cell-free DNA from prostate cancer patients N Lallous, SV Volik, S Awrey, E Leblanc, R Tse, J Murillo, K Singh, ... Genome biology 17 (1), 10, 2016 | 274 | 2016 |
| Therapeutic inhibition of Myc in cancer. Structural bases and computer-aided drug discovery approaches LA Carabet, PS Rennie, A Cherkasov International journal of molecular sciences 20 (1), 120, 2018 | 229 | 2018 |
| A critical overview of computational approaches employed for COVID-19 drug discovery EN Muratov, R Amaro, CH Andrade, N Brown, S Ekins, D Fourches, ... Chemical Society Reviews 50 (16), 9121-9151, 2021 | 223 | 2021 |
| Crystallographic structure of wild-type SARS-CoV-2 main protease acyl-enzyme intermediate with physiological C-terminal autoprocessing site J Lee, LJ Worrall, M Vuckovic, FI Rosell, F Gentile, AT Ton, NA Caveney, ... Nature communications 11 (1), 5877, 2020 | 219 | 2020 |
| Targeting the binding function 3 (BF3) site of the human androgen receptor through virtual screening. NA Lack, P Axerio-Cilies, P Tavassoli, FQ Han, KH Chan, C Feau, ... Journal of medicinal chemistry 54 (24), 8563-8573, 2011 | 196 | 2011 |
Robert E. W. HancockUniversity of British ColumbiaVerified email at hancocklab.com
