| QSAR modelling of rat acute toxicity on the basis of PASS prediction A Lagunin, A Zakharov, D Filimonov, V Poroikov Molecular informatics 30 (2‐3), 241-250, 2011 | 479 | 2011 |
| CERAPP: collaborative estrogen receptor activity prediction project K Mansouri, A Abdelaziz, A Rybacka, A Roncaglioni, A Tropsha, A Varnek, ... Environmental health perspectives 124 (7), 1023-1033, 2016 | 335 | 2016 |
| Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen MP Menden, D Wang, MJ Mason, B Szalai, KC Bulusu, Y Guan, T Yu, ... Nature communications 10 (1), 2674, 2019 | 313 | 2019 |
| 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 | 180 | 2021 |
| CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity Environmental Health Perspectives 128 (2), 2020 | 159 | 2020 |
| QNA-based ‘Star Track’QSAR approach DA Filimonov, AV Zakharov, AA Lagunin, VV Poroikov SAR and QSAR in Environmental Research 20 (7-8), 679-709, 2009 | 156 | 2009 |
| Alarms about structural alerts VM Alves, EN Muratov, SJ Capuzzi, R Politi, Y Low, RC Braga, ... Green Chemistry 18 (16), 4348-4360, 2016 | 138 | 2016 |
| Collaborative development of predictive toxicology applications B Hardy, N Douglas, C Helma, M Rautenberg, N Jeliazkova, V Jeliazkov, ... Journal of cheminformatics 2, 1-29, 2010 | 137 | 2010 |
| Deep learning identifies synergistic drug combinations for treating COVID-19 W Jin, JM Stokes, RT Eastman, Z Itkin, AV Zakharov, JJ Collins, ... Proceedings of the National Academy of Sciences 118 (39), e2105070118, 2021 | 132 | 2021 |
| Quantitative prediction of antitarget interaction profiles for chemical compounds AV Zakharov, AA Lagunin, DA Filimonov, VV Poroikov Chemical Research in Toxicology 25 (11), 2378-2385, 2012 | 129 | 2012 |
| Synergistic and antagonistic drug combinations against SARS-CoV-2 T Bobrowski, L Chen, RT Eastman, Z Itkin, P Shinn, CZ Chen, H Guo, ... Molecular Therapy 29 (2), 873-885, 2021 | 122* | 2021 |
| PASS: identification of probable targets and mechanisms of toxicity V Poroikov, D Filimonov, A Lagunin, T Gloriozova, A Zakharov SAR and QSAR in Environmental Research 18 (1-2), 101-110, 2007 | 122 | 2007 |
| QSAR modeling of imbalanced high-throughput screening data in PubChem AV Zakharov, ML Peach, M Sitzmann, MC Nicklaus Journal of chemical information and modeling 54 (3), 705-712, 2014 | 117 | 2014 |
| CATMoS: collaborative acute toxicity modeling suite K Mansouri, AL Karmaus, J Fitzpatrick, G Patlewicz, P Pradeep, D Alberga, ... Environmental health perspectives 129 (4), 047013, 2021 | 108 | 2021 |
| A widely-applicable high-throughput cellular thermal shift assay (CETSA) using split Nano Luciferase NJ Martinez, RR Asawa, MG Cyr, A Zakharov, DJ Urban, JS Roth, ... Scientific reports 8 (1), 9472, 2018 | 100 | 2018 |
| An OpenData portal to share COVID-19 drug repurposing data in real time KR Brimacombe, T Zhao, RT Eastman, X Hu, K Wang, M Backus, ... BioRxiv, 2020 | 81 | 2020 |
| Qsar modeling and prediction of drug–drug interactions AV Zakharov, EV Varlamova, AA Lagunin, AV Dmitriev, EN Muratov, ... Molecular pharmaceutics 13 (2), 545-556, 2016 | 78 | 2016 |
| Computer-aided prediction for medicinal chemistry via the Internet A Geronikaki, D Druzhilovsky, A Zakharov, V Poroikov SAR and QSAR in Environmental Research 19 (1-2), 27-38, 2008 | 73 | 2008 |
| Programmable nucleic acid based polygons with controlled neuroimmunomodulatory properties for predictive QSAR modeling MB Johnson, JR Halman, E Satterwhite, AV Zakharov, MN Bui, K Benkato, ... Therapeutic RNA Nanotechnology, 885-909, 2021 | 72 | 2021 |
| Chemical toxicity prediction for major classes of industrial chemicals: Is it possible to develop universal models covering cosmetics, drugs, and pesticides? VM Alves, EN Muratov, A Zakharov, NN Muratov, CH Andrade, A Tropsha Food and Chemical Toxicology 112, 526-534, 2018 | 72 | 2018 |
