E. I. Prokhorov, A. V. Bekker, A. V. Perevoznikov, M. Kumskov, I. Svitanko, “Combining 3D-QSAR and molecular docking for the virtual screening of PARP inhibitors”, Mendeleev Commun., 25:3 (2015), 214

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Mendeleev Communications, 2015, Volume 25, Issue 3, Pages 214–215
DOI: https://doi.org/10.1016/j.mencom.2015.05.019 (Mi mendc2355)

This article is cited in 5 scientific papers (total in 5 papers)

Communications

Combining 3D-QSAR and molecular docking for the virtual screening of PARP inhibitors

E. I. Prokhorov^a, A. V. Bekker^a, A. V. Perevoznikov^a, M. Kumskov^a, I. Svitanko^bcd

^a Department of Mechanics and Mathematics, M.V. Lomonosov Moscow State University, Moscow, Russian Federation
^b N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Moscow, Russian Federation
^c Department of Chemistry, M.V. Lomonosov Moscow State University, Moscow, Russian Federation
^d Higher Chemical College of the Russian Academy of Sciences, D.I. Mendeleev University of Chemical Technology of Russia, Moscow, Russian Federation

Full-text PDF (333 kB) Citations (5)

DOI: https://doi.org/10.1016/j.mencom.2015.05.019

Graphic abstract: Combining 3D-QSAR and molecular docking for the virtual screening of PARP inhibitors

Abstract: 3D-QSAR and molecular docking were applied to predict the inhibitory activity of 196 compounds towards poly(ADP-riboso) polymerase-1 (PARP). A proportion of experimentally active ligands was higher among compounds with good rankings from both methods (57%) compared to compounds scored as inactive by at least one method (40% for docking-active, QSAR-inactive compounds).

Document Type: Article

Language: English

Citation: E. I. Prokhorov, A. V. Bekker, A. V. Perevoznikov, M. Kumskov, I. Svitanko, “Combining 3D-QSAR and molecular docking for the virtual screening of PARP inhibitors”, Mendeleev Commun., 25:3 (2015), 214–215

Linking options:

https://www.mathnet.ru/eng/mendc2355

https://www.mathnet.ru/eng/mendc/v25/i3/p214

This publication is cited in the following 5 articles:

M. P. Egorov, V. P. Ananikov, E. G. Baskir, S. E. Boganov, V. I. Bogdan, A. N. Vereshchagin, V. A. Vil', I. L. Dalinger, A. D. Dilman, O. L. Eliseev, S. G. Zlotin, E. A. Knyazeva, V. M. Kogan, L. O. Kononov, M. M. Krayushkin, V. B. Krylov, L. M. Kustov, V. V. Levin, B. V. Lichitsky, M. G. Medvedev, N. E. Nifantiev, O. A. Rakitin, A. M. Sakharov, I. V. Svitanko, G. A. Smirnov, A. Yu. Stakheev, M. A. Syroeshkin, A. O. Terent'ev, Yu. V. Tomilov, E. V. Tretyakov, I. V. Trushkov, L. L. Fershtat, V. A. Chaliy, V. Z. Shirinian, “Current trends in organic chemistry: contribution of the N. D. Zelinsky Institute of Organic Chemistry of the Russian Academy of Sciences”, Russ Chem Bull, 73:9 (2024), 2423
I. V. Svitanko, T. S. Pivina, “Molecular modeling in synthesis: from statistical methods to quantum chemistry and practical applications”, Russ Chem Bull, 73:5 (2024), 1093
I. Yu. Titov, V. S. Stroylov, P. V. Rusina, I. Svitanko, “Preliminary modelling as the first stage of targeted organic synthesis”, Russian Chem. Reviews, 90:7 (2021), 831–867
Nafiseh Vahedi, Majid Mohammadhosseini, Mehdi Nekoei, “QSAR Study of PARP Inhibitors by GA-MLR, GA-SVM and GA-ANN Approaches”, CAC, 16:8 (2020), 1088
V. S. Stroylov, D. V. Katkov, I. Yu. Titov, O. V. Stroganov, F. N. Novikov, G. G. Chilov, I. Svitanko, “Modeling comparative selectivity profiles of kinase inhibitors using FEP/MD protocol”, Mendeleev Commun., 27:4 (2017), 349–351

Citing articles in Google Scholar: Russian citations, English citations
Related articles in Google Scholar: Russian articles, English articles

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