Jerzy Leszczynski to Quantitative Structure-Activity Relationship
This is a "connection" page, showing publications Jerzy Leszczynski has written about Quantitative Structure-Activity Relationship.
Connection Strength
17.823
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Toropova AP, Toropov AA, Leszczynska D, Leszczynski J. Application of quasi-SMILES to the model of gold-nanoparticles uptake in A549?cells. Comput Biol Med. 2021 09; 136:104720.
Score: 0.745
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Kar S, Leszczynski J. Is intraspecies QSTR model answer to toxicity data gap filling: Ecotoxicity modeling of chemicals to avian species. Sci Total Environ. 2020 Oct 10; 738:139858.
Score: 0.687
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Khan K, Kar S, Sanderson H, Roy K, Leszczynski J. Ecotoxicological Modeling, Ranking and Prioritization of Pharmaceuticals Using QSTR and i-QSTTR Approaches: Application of 2D and Fragment Based Descriptors. Mol Inform. 2019 08; 38(8-9):e1800078.
Score: 0.619
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Kar S, Roy K, Leszczynski J. Applicability Domain: A Step Toward Confident Predictions and Decidability for QSAR Modeling. Methods Mol Biol. 2018; 1800:141-169.
Score: 0.581
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Kar S, Roy K, Leszczynski J. Impact of Pharmaceuticals on the Environment: Risk Assessment Using QSAR Modeling Approach. Methods Mol Biol. 2018; 1800:395-443.
Score: 0.581
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Kar S, Sep?lveda MS, Roy K, Leszczynski J. Endocrine-disrupting activity of per- and polyfluoroalkyl substances: Exploring combined approaches of ligand and structure based modeling. Chemosphere. 2017 Oct; 184:514-523.
Score: 0.559
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Karabulut S, Sizochenko N, Orhan A, Leszczynski J. A DFT-based QSAR study on inhibition of human dihydrofolate reductase. J Mol Graph Model. 2016 11; 70:23-29.
Score: 0.531
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Toropova AP, Toropov AA, Veselinovic AM, Veselinovic JB, Leszczynska D, Leszczynski J. Monte Carlo-based quantitative structure-activity relationship models for toxicity of organic chemicals to Daphnia magna. Environ Toxicol Chem. 2016 11; 35(11):2691-2697.
Score: 0.525
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Watkins M, Sizochenko N, Rasulev B, Leszczynski J. Estimation of melting points of large set of persistent organic pollutants utilizing QSPR approach. J Mol Model. 2016 Mar; 22(3):55.
Score: 0.510
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Toropova AP, Toropov AA, Benfenati E, Leszczynska D, Leszczynski J. QSAR model as a random event: A case of rat toxicity. Bioorg Med Chem. 2015 Mar 15; 23(6):1223-30.
Score: 0.476
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Toropova AP, Toropov AA, Benfenati E, Korenstein R, Leszczynska D, Leszczynski J. Optimal nano-descriptors as translators of eclectic data into prediction of the cell membrane damage by means of nano metal-oxides. Environ Sci Pollut Res Int. 2015 Jan; 22(1):745-57.
Score: 0.463
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Toropova AP, Toropov AA, Benfenati E, Puzyn T, Leszczynska D, Leszczynski J. Optimal descriptor as a translator of eclectic information into the prediction of membrane damage: the case of a group of ZnO and TiO2 nanoparticles. Ecotoxicol Environ Saf. 2014 Oct; 108:203-9.
Score: 0.459
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Kar S, Gajewicz A, Puzyn T, Roy K, Leszczynski J. Periodic table-based descriptors to encode cytotoxicity profile of metal oxide nanoparticles: a mechanistic QSTR approach. Ecotoxicol Environ Saf. 2014 Sep; 107:162-9.
Score: 0.455
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Toropov AA, Toropova AP, Raska I, Leszczynska D, Leszczynski J. Comprehension of drug toxicity: software and databases. Comput Biol Med. 2014 Feb; 45:20-5.
Score: 0.438
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Toropov AA, Toropova AP, Puzyn T, Benfenati E, Gini G, Leszczynska D, Leszczynski J. QSAR as a random event: modeling of nanoparticles uptake in PaCa2 cancer cells. Chemosphere. 2013 Jun; 92(1):31-7.
Score: 0.419
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Toropov AA, Toropova AP, Benfenati E, Gini G, Leszczynska D, Leszczynski J. Calculation of molecular features with apparent impact on both activity of mutagens and activity of anticancer agents. Anticancer Agents Med Chem. 2012 Sep; 12(7):807-17.
Score: 0.402
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Toropov AA, Toropova AP, Benfenati E, Gini G, Leszczynska D, Leszczynski J. CORAL: QSPR model of water solubility based on local and global SMILES attributes. Chemosphere. 2013 Jan; 90(2):877-80.
Score: 0.401
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Toropov AA, Toropova AP, Rasulev BF, Benfenati E, Gini G, Leszczynska D, Leszczynski J. CORAL: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical. J Comput Chem. 2012 Sep 05; 33(23):1902-6.
Score: 0.395
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Toropov AA, Toropova AP, Benfenati E, Gini G, Leszczynska D, Leszczynski J. SMILES-based QSAR approaches for carcinogenicity and anticancer activity: comparison of correlation weights for identical SMILES attributes. Anticancer Agents Med Chem. 2011 Dec; 11(10):974-82.
Score: 0.381
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Toropova AP, Toropov AA, Benfenati E, Gini G, Leszczynska D, Leszczynski J. CORAL: quantitative structure-activity relationship models for estimating toxicity of organic compounds in rats. J Comput Chem. 2011 Sep; 32(12):2727-33.
Score: 0.369
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Puzyn T, Rasulev B, Gajewicz A, Hu X, Dasari TP, Michalkova A, Hwang HM, Toropov A, Leszczynska D, Leszczynski J. Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles. Nat Nanotechnol. 2011 Mar; 6(3):175-8.
Score: 0.361
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Turabekova MA, Rasulev BF, Dzhakhangirov FN, Leszczynska D, Leszczynski J. Aconitum and Delphinium alkaloids of curare-like activity. QSAR analysis and molecular docking of alkaloids into AChBP. Eur J Med Chem. 2010 Sep; 45(9):3885-94.
Score: 0.343
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Toropova AP, Toropov AA, Benfenati E, Gini G, Leszczynska D, Leszczynski J. CORAL: QSPR models for solubility of [C60] and [C70] fullerene derivatives. Mol Divers. 2011 Feb; 15(1):249-56.
Score: 0.339
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Muratov EN, Kuz'min VE, Artemenko AG, Kovdienko NA, Gorb L, Hill F, Leszczynski J. New QSPR equations for prediction of aqueous solubility for military compounds. Chemosphere. 2010 May; 79(8):887-90.
Score: 0.339
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Toropov AA, Toropova AP, Benfenati E, Leszczynska D, Leszczynski J. SMILES-based optimal descriptors: QSAR analysis of fullerene-based HIV-1 PR inhibitors by means of balance of correlations. J Comput Chem. 2010 Jan 30; 31(2):381-92.
Score: 0.336
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Puzyn T, Leszczynska D, Leszczynski J. Toward the development of "nano-QSARs": advances and challenges. Small. 2009 Nov; 5(22):2494-509.
Score: 0.330
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Toropov AA, Rasulev BF, Leszczynski J. QSAR modeling of acute toxicity by balance of correlations. Bioorg Med Chem. 2008 Jun 01; 16(11):5999-6008.
Score: 0.297
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Turabekova MA, Rasulev BF, Levkovich MG, Abdullaev ND, Leszczynski J. Aconitum and Delphinium sp. alkaloids as antagonist modulators of voltage-gated Na+ channels. AM1/DFT electronic structure investigations and QSAR studies. Comput Biol Chem. 2008 Apr; 32(2):88-101.
Score: 0.287
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Isayev O, Rasulev B, Gorb L, Leszczynski J. Structure-toxicity relationships of nitroaromatic compounds. Mol Divers. 2006 May; 10(2):233-45.
Score: 0.260
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Kar S, Pathakoti K, Leszczynska D, Tchounwou PB, Leszczynski J. In vitro and in silico study of mixtures cytotoxicity of metal oxide nanoparticles to Escherichia coli: a mechanistic approach. Nanotoxicology. 2022 06; 16(5):566-579.
Score: 0.202
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Kumar V, Kar S, De P, Roy K, Leszczynski J. Identification of potential antivirals against 3CLpro enzyme for the treatment of SARS-CoV-2: A multi-step virtual screening study. SAR QSAR Environ Res. 2022 May; 33(5):357-386.
Score: 0.195
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Toropova AP, Toropov AA, Leszczynska D, Leszczynski J. How the CORAL software can be used to select compounds for efficient treatment of neurodegenerative diseases? Toxicol Appl Pharmacol. 2020 12 01; 408:115276.
Score: 0.176
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Toropov AA, Toropova AP, Veselinovic AM, Leszczynska D, Leszczynski J. SARS-CoV Mpro inhibitory activity of aromatic disulfide compounds: QSAR model. J Biomol Struct Dyn. 2022 02; 40(2):780-786.
Score: 0.175
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Sizochenko N, Syzochenko M, Fjodorova N, Rasulev B, Leszczynski J. Evaluating genotoxicity of metal oxide nanoparticles: Application of advanced supervised and unsupervised machine learning techniques. Ecotoxicol Environ Saf. 2019 Dec 15; 185:109733.
Score: 0.164
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Toropov AA, Toropova AP, Leszczynska D, Leszczynski J. "Ideal correlations" for biological activity of peptides. Biosystems. 2019 Jul; 181:51-57.
Score: 0.159
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Petrosyan LS, Sizochenko N, Leszczynski J, Rasulev B. Modeling of Glass Transition Temperatures for Polymeric Coating Materials: Application of QSPR Mixture-based Approach. Mol Inform. 2019 08; 38(8-9):e1800150.
Score: 0.159
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Toropova AP, Toropov AA, Benfenati E, Leszczynska D, Leszczynski J. Virtual Screening of Anti-Cancer Compounds: Application of Monte Carlo Technique. Anticancer Agents Med Chem. 2019; 19(2):148-153.
Score: 0.156
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Samanta PN, Kar S, Leszczynski J. Recent Advances of In-Silico Modeling of Potent Antagonists for the Adenosine Receptors. Curr Pharm Des. 2019; 25(7):750-773.
Score: 0.156
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Jean J, Kar S, Leszczynski J. QSAR modeling of adipose/blood partition coefficients of Alcohols, PCBs, PBDEs, PCDDs and PAHs: A data gap filling approach. Environ Int. 2018 12; 121(Pt 2):1193-1203.
Score: 0.154
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Ojha PK, Kar S, Roy K, Leszczynski J. Toward comprehension of multiple human cells uptake of engineered nano metal oxides: quantitative inter cell line uptake specificity (QICLUS) modeling. Nanotoxicology. 2019 02; 13(1):14-34.
Score: 0.154
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Kar S, Ghosh S, Leszczynski J. Single or mixture halogenated chemicals? Risk assessment and developmental toxicity prediction on zebrafish embryos based on weighted descriptors approach. Chemosphere. 2018 Nov; 210:588-596.
Score: 0.151
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Kapusta K, Sizochenko N, Karabulut S, Okovytyy S, Voronkov E, Leszczynski J. QSPR modeling of optical rotation of amino acids using specific quantum chemical descriptors. J Mol Model. 2018 Feb 17; 24(3):59.
Score: 0.147
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Gooch A, Sizochenko N, Rasulev B, Gorb L, Leszczynski J. In vivo toxicity of nitroaromatics: A comprehensive quantitative structure-activity relationship study. Environ Toxicol Chem. 2017 08; 36(8):2227-2233.
Score: 0.138
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Toropova AP, Toropov AA, Leszczynska D, Leszczynski J. CORAL and Nano-QFAR: Quantitative feature - Activity relationships (QFAR) for bioavailability of nanoparticles (ZnO, CuO, Co3O4, and TiO2). Ecotoxicol Environ Saf. 2017 May; 139:404-407.
Score: 0.137
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Gooch A, Sizochenko N, Sviatenko L, Gorb L, Leszczynski J. A quantum chemical based toxicity study of estimated reduction potential and hydrophobicity in series of nitroaromatic compounds. SAR QSAR Environ Res. 2017 Feb; 28(2):133-150.
Score: 0.137
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Sizochenko N, Gajewicz A, Leszczynski J, Puzyn T. Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models. Nanoscale. 2016 Apr 07; 8(13):7203-8.
Score: 0.129
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Toropova AP, Toropov AA, Veselinovic AM, Veselinovic JB, Benfenati E, Leszczynska D, Leszczynski J. Nano-QSAR: Model of mutagenicity of fullerene as a mathematical function of different conditions. Ecotoxicol Environ Saf. 2016 Feb; 124:32-36.
Score: 0.125
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Toropov AA, Toropova AP, Veselinovic AM, Veselinovic JB, Nesmerak K, Raska I, Duchowicz PR, Castro EA, Kudyshkin VO, Leszczynska D, Leszczynski J. The Monte Carlo method based on eclectic data as an efficient tool for predictions of endpoints for nanomaterials - two examples of application. Comb Chem High Throughput Screen. 2015; 18(4):376-86.
Score: 0.118
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Gajewicz A, Cronin MT, Rasulev B, Leszczynski J, Puzyn T. Novel approach for efficient predictions properties of large pool of nanomaterials based on limited set of species: nano-read-across. Nanotechnology. 2015 Jan 09; 26(1):015701.
Score: 0.117
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Sizochenko N, Rasulev B, Gajewicz A, Kuz'min V, Puzyn T, Leszczynski J. From basic physics to mechanisms of toxicity: the "liquid drop" approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles. Nanoscale. 2014 Nov 21; 6(22):13986-93.
Score: 0.117
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Toropova AP, Toropov AA, Rallo R, Leszczynska D, Leszczynski J. Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions. Ecotoxicol Environ Saf. 2015 Feb; 112:39-45.
Score: 0.117
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Gajewicz A, Schaeublin N, Rasulev B, Hussain S, Leszczynska D, Puzyn T, Leszczynski J. Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: hints from nano-QSAR studies. Nanotoxicology. 2015 May; 9(3):313-25.
Score: 0.114
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Turabekova MA, Rasulev BF, Dzhakhangirov FN, Toropov AA, Leszczynska D, Leszczynski J. Aconitum and delphinium diterpenoid alkaloids of local anesthetic activity: comparative QSAR analysis based on GA-MLRA/PLS and optimal descriptors approach. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2014; 32(3):213-38.
Score: 0.110
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Ahmed L, Rasulev B, Turabekova M, Leszczynska D, Leszczynski J. Receptor- and ligand-based study of fullerene analogues: comprehensive computational approach including quantum-chemical, QSAR and molecular docking simulations. Org Biomol Chem. 2013 Sep 21; 11(35):5798-808.
Score: 0.108
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Toropov AA, Toropova AP, Benfenati E, Gini G, Leszczynska D, Leszczynski J, De Nucci G. QSAR models for inhibitors of physiological impact of Escherichia coli that leads to diarrhea. Biochem Biophys Res Commun. 2013 Mar 08; 432(2):214-25.
Score: 0.104
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Lubinski L, Urbaszek P, Gajewicz A, Cronin MT, Enoch SJ, Madden JC, Leszczynska D, Leszczynski J, Puzyn T. Evaluation criteria for the quality of published experimental data on nanomaterials and their usefulness for QSAR modelling. SAR QSAR Environ Res. 2013; 24(12):995-1008.
Score: 0.103
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Toropov AA, Toropova AP, Rasulev BF, Benfenati E, Gini G, Leszczynska D, Leszczynski J. CORAL: binary classifications (active/inactive) for Liver-Related Adverse Effects of Drugs. Curr Drug Saf. 2012 Sep; 7(4):257-61.
Score: 0.100
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Toropov AA, Toropova AP, Benfenati E, Gini G, Puzyn T, Leszczynska D, Leszczynski J. Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli. Chemosphere. 2012 Nov; 89(9):1098-102.
Score: 0.099
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Gajewicz A, Rasulev B, Dinadayalane TC, Urbaszek P, Puzyn T, Leszczynska D, Leszczynski J. Advancing risk assessment of engineered nanomaterials: application of computational approaches. Adv Drug Deliv Rev. 2012 Dec; 64(15):1663-93.
Score: 0.099
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Rasulev B, Turabekova M, Gorska M, Kulig K, Bielejewska A, Lipkowski J, Leszczynski J. Use of quantitative structure-enantioselective retention relationship for the liquid chromatography chiral separation prediction of the series of pyrrolidin-2-one compounds. Chirality. 2012 Jan; 24(1):72-7.
Score: 0.095
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Artemenko AG, Muratov EN, Kuz'min VE, Muratov NN, Varlamova EV, Kuz'mina AV, Gorb LG, Golius A, Hill FC, Leszczynski J, Tropsha A. QSAR analysis of the toxicity of nitroaromatics in Tetrahymena pyriformis: structural factors and possible modes of action. SAR QSAR Environ Res. 2011 Jul-Sep; 22(5-6):575-601.
Score: 0.093
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Rasulev B, Kusic H, Leszczynska D, Leszczynski J, Koprivanac N. QSAR modeling of acute toxicity on mammals caused by aromatic compounds: the case study using oral LD50 for rats. J Environ Monit. 2010 May; 12(5):1037-44.
Score: 0.085
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Toropov AA, Toropova AP, Benfenati E, Leszczynska D, Leszczynski J. InChI-based optimal descriptors: QSAR analysis of fullerene[C60]-based HIV-1 PR inhibitors by correlation balance. Eur J Med Chem. 2010 Apr; 45(4):1387-94.
Score: 0.084
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Puzyn T, Mostrag A, Falandysz J, Kholod Y, Leszczynski J. Predicting water solubility of congeners: chloronaphthalenes--a case study. J Hazard Mater. 2009 Oct 30; 170(2-3):1014-22.
Score: 0.080
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Kuz'min VE, Muratov EN, Artemenko AG, Gorb L, Qasim M, Leszczynski J. The effect of nitroaromatics' composition on their toxicity in vivo: novel, efficient non-additive 1D QSAR analysis. Chemosphere. 2008 Jul; 72(9):1373-80.
Score: 0.075
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Kuz'min VE, Muratov EN, Artemenko AG, Gorb L, Qasim M, Leszczynski J. The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study. J Comput Aided Mol Des. 2008 Oct; 22(10):747-59.
Score: 0.074
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Rasulev BF, Saidkhodzhaev AI, Nazrullaev SS, Akhmedkhodzhaeva KS, Khushbaktova ZA, Leszczynski J. Molecular modelling and QSAR analysis of the estrogenic activity of terpenoids isolated from Ferula plants. SAR QSAR Environ Res. 2007 Oct-Dec; 18(7-8):663-73.
Score: 0.071
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Toropova AP, Toropov AA, Leszczynski J, Sizochenko N. Using quasi-SMILES for the predictive modeling of the safety of 574 metal oxide nanoparticles measured in different experimental conditions. Environ Toxicol Pharmacol. 2021 Aug; 86:103665.
Score: 0.046
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Golbamaki A, Golbamaki N, Sizochenko N, Rasulev B, Leszczynski J, Benfenati E. Genotoxicity induced by metal oxide nanoparticles: a weight of evidence study and effect of particle surface and electronic properties. Nanotoxicology. 2018 12; 12(10):1113-1129.
Score: 0.037
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C P A, Subhramanian S, Sizochenko N, Melge AR, Leszczynski J, Mohan CG. Multiple e-Pharmacophore modeling to identify a single molecule that could target both streptomycin and paromomycin binding sites for 30S ribosomal subunit inhibition. J Biomol Struct Dyn. 2019 Apr; 37(6):1582-1596.
Score: 0.037
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Cook SM, Aker WG, Rasulev BF, Hwang HM, Leszczynski J, Jenkins JJ, Shockley V. Choosing safe dispersing media for C60 fullerenes by using cytotoxicity tests on the bacterium Escherichia coli. J Hazard Mater. 2010 Apr 15; 176(1-3):367-73.
Score: 0.021
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Kusic H, Rasulev B, Leszczynska D, Leszczynski J, Koprivanac N. Prediction of rate constants for radical degradation of aromatic pollutants in water matrix: a QSAR study. Chemosphere. 2009 May; 75(8):1128-34.
Score: 0.020