ABOUT_PROGRAM
image

The Mario Negri Institute for Pharmacological Research is a non-profit biomedical research organisation with major activities on drug research. It was established in Milan in 1961 and there are now research units in Bergamo, Ranica (near Bergamo) and Santa Maria Imbaro (near Chieti). The Institute’s main goal is to contribute to the defense of human health and life. The Institute’s research programs span from the molecular level to the whole human being.

Department of Environmental Health Science (Dipartimento:Ambiente e Salute)  
Laboratory of Environmental Chemistry and toxicology    is the place where the CORAL software has been developed.

The CHEMPREDICT (project 39036) project supported by Maria Curie incoming fellowship (Dr. Emilio Benfenati was the scientist-in-charge, and Dr. Andrey A. Toropov was the invited researcher) has been aimed to develop a software for the QSPR/QSAR analysis where the molecular structure should be represented by SMILES.

The Monte Carlo method is used as basis to design of the so-called optimal descriptors.
Thus, the CORAL software is result of the EU project CHEMPREDICT (2007-2009).

Dr. Alla P. Toropova had prepared the basic version of web-site to represent the CORAL software for interested users (2010).
At present Dr. Alla P. Toropova is permanently updating the contains of the web-site in accordance with new options related to the Monte Carlo optimization as well as in accordance with new publications where the CORAL is used as a tool for the QSPR/QSAR analysis.


The CORAL has been used to solve tasks of EU projects DEMETRA (2003-2006), CAESAR (2006-2009), CHEMPREDICT(2007-2009), ANTARES (2009-2011), NanoBRIDGES (2011-2013), CALEIDOS(2013-2015), NanoPUZZLES (2013-2015), PROSIL (2013-2015), PeptiCAPS (2015-2018), EU-ToxRisk (2016-2022), EFSA contract (NP//EFSA/AFSCO/2016/1) (2016-2017), LIFE-COMBASE (LIFE15 ENV/ES/000416) (2017-2019), Optitox (OC/EFSA/SCER/2018/01) (2018-2020), LIFE-VERMEER (LIFE16 ENV/ES/000167) (2017-2021), LIFE-CONCERT (LIFE17 GIE/IT/000461) (2018-2022) and some others.

CORAL for nanomaterials.

The EU projects NanoPUZZLES and PreNanoTox have been aimed to intensive studies of nanomaterials and their properties.
Thanks to the NanoPUZZLES and also the PreNanoTox a special approaches to computational predicting of endpoints related to nanomaterials have been developed.
It was so-called codification of phenomena by quasi-SMILES.
The quasi-SMILES can become a tool for the solving the above-mentioned tasks. In particular, the quasi-SMILES can become convenient basis for QSPR/QSAR analyses of nanomaterials.
More detailed information on quasi-SMILES is available in section "Quasi-SMILES".
More detailed information on Nano-QSPR/QSAR is available in section "NANO-QSPR/QSAR".

In fact, the CORAL software is one of few programs which is able to produce nano-descriptors for prediction of endpoints related to the nanomaterials. Description how to use the software for nanomaterials is available in section "PUBLICATIONS" as well as in the “REFERENCE MANUAL”.
Comparison of PreNanoTox and NanoPUZZLES .
Demo of model for NanoPUZZLES (Ecotoxicol. Environ. Saf. 108 (2014) 203–209).
Demo of model for PreNanoTox (Environ. Sci. Pollut. Res. 22 (2015)745–757).
Demo of model for PeptiCAPS (Journal of Theoretical Biology 416 (2017) 113–118).

A. A. Toropov; E. Benfenati, Optimisation of correlation weights of SMILES invariants for modelling oral quail toxicity . European Journal of Medicinal Chemistry (2007) 42( 5): 606-613.
A. A. Toropov; E. Benfenati, SMILES as an alternative to the graph in QSAR modelling of bee toxicity . Computational Biology and Chemistry (2007) 31(1): 57-60.

A. A. Toropov; A. P. Toropova ; E. Benfenati ; A. Manganaro, QSAR modelling of carcinogenicity by balance of correlations. Mol Divers. (2009) 13: 367–373.
A.A. Toropov; A. P. Toropova; E. Benfenati; D. Leszczynska; J. Leszczynski, Additive InChI-based optimal descriptors: QSPR modeling of fullerene C60 solubility in organic solvents. J Math Chem (2009) 46: 1232–1251.
A. A. Toropov; A. P. Toropova ; E. Benfenati, Additive SMILES-Based Carcinogenicity Models: Probabilistic Principles in the Search for Robust Predictions. Int. J. Mol. Sci. (2009) 10(7): 3106-3127.
A. A. Toropov; A. P. Toropova ; E. Benfenati, QSPR modeling bioconcentration factor (BCF) by balance of correlations . European Journal of Medicinal Chemistry (2009) 44( 6): 2544-2551.
A. A. Toropov; A. P. Toropova ; E. Benfenati, SMILES-based optimal descriptors: QSAR modeling of carcinogenicity by balance of correlations with ideal slopes. European Journal of Medicinal Chemistry (2010) 45: 3581-3587.

A. A. Toropov; A. P. Toropova ; E. Benfenati, QSPR modeling for enthalpies of formation of organometallic compounds by means of SMILES-based optimal descriptors . Chemical Physics Letters (2008) 461( 4-6): 343-347.
A. A. Toropov, B.F. Rasulev, D. Leszczynska, J. Leszczynski, Multiplicative SMILES-based optimal descriptors: QSPR modeling of fullerene C60 solubility in organic solvents . Chemical Physics Letters (2008) 457( 4-6): 332-336.
A. A. Toropov; E. Benfenati, Additive SMILES-based optimal descriptors in QSAR modelling bee toxicity: Using rare SMILES attributes to define the applicability domain. Bioorganic & Medicinal Chemistry (2008 )16( 9): 4801-4809.
A. A. Toropov; A. P. Toropova ; E. Benfenati, QSPR modelling of the octanol/water partition coefficient of organometallic substances by optimal SMILES-based descriptors. Cent. Eur. J. Chem. 2009 7(4): 846–856.
A. A. Toropov; A. P. Toropova ; E. Benfenati, QSPR modeling of octanol water partition coefficient of platinum complexes by InChI-based optimal descriptors. J Math Chem (2009) 46: 1060–1073.
A.A. Toropov; A. P. Toropova; E. Benfenati; D. Leszczynska; J. Leszczynski, Additive InChI-based optimal descriptors: QSPR modeling of fullerene C60 solubility in organic solvents. J Math Chem (2009) 46: 1232–1251.
A. A. Toropov; A. P. Toropova ; E. Benfenati, Additive SMILES-Based Carcinogenicity Models: Probabilistic Principles in the Search for Robust Predictions. Int. J. Mol. Sci. (2009) 10(7): 3106-3127.
A. A. Toropov; A. P. Toropova ; E. Benfenati, QSPR modeling bioconcentration factor (BCF) by balance of correlations . European Journal of Medicinal Chemistry (2009) 44( 6): 2544-2551.
A. A. Toropov; A. P. Toropova ; E. Benfenati, Simplified Molecular Input Line Entry System-Based Optimal Descriptors: Quantitative Structure–Activity Relationship Modeling Mutagenicity of Nitrated Polycyclic Aromatic Hydrocarbons. Chemical Biology & Drug Design ( 2009) 73(5): 515–525.
A. A. Toropov; A. P. Toropova ; E. Benfenati, QSAR Modelling for Mutagenic Potency of Heteroaromatic Amines by Optimal SMILES-based Descriptors. Chemical Biology & Drug Design ( 2009) 73(3): 301–312.
A. A. Toropov; A. P. Toropova ; E. Benfenati, Erratum: QSAR Modelling for Mutagenic Potency of Heteroaromatic Amines by Optimal SMILES-based Descriptors. Chemical Biology & Drug Design ( 2009) 73(4): 482.
A. A. Toropov; A. P. Toropova ; E. Benfenati ; A. Manganaro, QSAR modelling of carcinogenicity by balance of correlations. Mol Divers (2009) 13:367–373.
A. A. Toropov; A. P. Toropova ; E. Benfenati, QSPR modelling of normal boiling points and octanol/water partition coefficient for acyclic and cyclic hydrocarbons using SMILES-based optimal descriptors . Central European Journal Chemistry. (2010) 8: 1047-1062.
A. A. Toropov; A. P. Toropova ; E. Benfenati; D. Leszczynska; J. Leszczynski, SMILES-based optimal descriptors: QSAR analysis of fullerene-based HIV-1 PR inhibitors by means of balance of correlations. J Comput Chem. (2010) 31 : 381-392.
A. A. Toropov; A. P. Toropova ; E. Benfenati; D. Leszczynska; J. Leszczynski, QSAR analysis of 1,4-dihydro-4-oxo-1-(2-thiazolyl)-1,8-naphthyridines exhibiting anticancer activity by optimal SMILES-based descriptors. J Math Chem. (2010) 47 : 647-666.
A. A. Toropov; A. P. Toropova ; E. Benfenati ; A. Manganaro, QSAR modelling of the toxicity to Tetrahymena pyriformis by balance of correlations. Mol Divers. (2010) 14 : 821-827.
A. A. Toropov; A. P. Toropova ; E. Benfenati, QSAR-modeling of toxicity of organometallic compounds by means of the balance of correlations for InChI-based optimal descriptors. Mol Divers. (2010) 14 : 183-192.
A. A. Toropov; A. P. Toropova ; E. Benfenati; D. Leszczynska; J. Leszczynski, Use of the international chemical identifier for constructing QSPR-model of normal boiling points of acyclic carbonyl substances. J Math Chem. (2010) 47: 355-369.
A. A. Toropov; A. P. Toropova ; E. Benfenati; D. Leszczynska; J. Leszczynski, QSAR modeling of measured binding affinity for fullerene-based HIV-1 PR inhibitors by CORAL. J Math Chem. (2010) 48 : 959-987.
A. A. Toropov; A. P. Toropova ; E. Benfenati, SMILES-based optimal descriptors: QSAR modeling of carcinogenicity by balance of correlations with ideal slopes. European Journal of Medicinal Chemistry (2010) 45: 3581-3587.
A. A. Toropov; A. P. Toropova ; E. Benfenati; D. Leszczynska; J. Leszczynski, InChI-based optimal descriptors: QSAR analysis of fullerene [C60]-based HIV-1 PR inhibitors by correlation balance. Eur J Med Chem. (2010) 45 : 1387-1394.
A. A. Toropov; A. P. Toropova ; I.Jr.Raska; E. Benfenati, QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations. Eur J Med Chem. (2010) 45 : 1639-1647.
A. P. Toropova ; A. A. Toropov; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, CORAL: QSPR models for solubility of [C60] and [C70] fullerene derivatives Mol. Divers. (2011) 105: 249-256.
A. A. Toropov; A. P. Toropova ; E. Benfenati, QSPR modelling of the octanol/water partition coefficient of organometallic substances by optimal SMILES-based descriptors. Cent. Eur. J. Chem. 2009 7(4): 846–856.
A. A. Toropov; A. P. Toropova ; E. Benfenati, QSAR-modeling of toxicity of organometallic compounds by means of the balance of correlations for InChI-based optimal descriptors. Mol Divers. (2010) 14 : 183-192.
A. P. Toropova ; A. A. Toropov; E. Benfenati; G. Gini, QSAR modelling toxicity toward rats of inorganic substances by means of CORAL. Cent. Eur. J. Chem. (2011) 9(1): 75-85.

A. P. Toropova ; A. A. Toropov; A. Lombardo; A. Roncaglioni; E. Benfenati; G. Gini, A new bioconcentration factor model based on SMILES and indices of presence of atoms. Eur J Med Chem. (2010) 45 : 4399-4402.
A. P. Toropova ; A. A. Toropov; R. Gonella Diaza; E. Benfenati; G. Gini, Analysis of the co-evolutions of correlations as a tool for QSAR-modeling of carcinogenicity: an unexpected good prediction based on a model that seems untrustworthy. Central European Journal Chemistry (2011) 9 : 165-174.
A. P. Toropova ; A. A. Toropov; E. Benfenati; G. Gini, Co-evolutions of correlations for QSAR of toxicity of organometallic and inorganic substances: An unexpected good prediction based on a model that seems untrustworthy. Chemometr. Intell. Lab. (2011) 105: 215-219.
A.A. Toropov; A.P. Toropova; A. Lombardo; A. Roncaglioni; E. Benfenati; G. Gini, CORAL: building up the model for bioconcentration factor and defining it’s applicability domain Eur. J. Med. Chem. (2011) 46: 1400-1403.
A. A. Toropov ; A. P. Toropova; R. Gonella Diaza; E. Benfenati; G. Gini, SMILES-based optimal descriptors: QSAR modeling of estrogen receptor binding affinity by correlation balance. Struct Chem. (2012) 23: 529-544.
A.P. Toropova; A.A. Toropov; A. Lombardo; A. Roncaglioni; E. Benfenati; G. Gini, Coral: QSAR models for acute toxicity in fathead minnow (Pimephales promelas). J Comput Chem. (2012) 33 : 1218-1223.

A.P. Toropova; A.A. Toropov; S.E. Martyanov; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, CORAL: QSAR modeling of toxicity of organic chemicals to Daphnia magna. Chemometr. Intell. Lab. (2012) 110: 177-181.
A.P. Toropova; A.A. Toropov; A. Lombardo; A. Roncaglioni; E. Benfenati; G. Gini, Coral: QSAR models for acute toxicity in fathead minnow (Pimephales promelas). J Comput Chem. (2012) 33 : 1218-1223.
A.P. Toropova; A.A. Toropov; E. Benfenati; G. Gini, QSAR models for toxicity of organic substances to Daphnia magna built up by CORAL freeware. Chem Biol Drug Des. 2012; 79: 332–338.
A.A. Toropov, A.P. Toropov, S.E. Martyanov, E. Benfenati, G. Gini, D. Leszczynska, J. Leszczynski, CORAL: Predictions of Rate Constants of Hydroxyl Radical Reaction using representation of the molecular structure obtained by combination of SMILES and Graph approaches. Chemometr. Intell. Lab. (2012) 112: 65-70.
A.A. Toropov; A.P. Toropova; A. Lombardo; A. Roncaglioni; N. De Brita; G. Stella; E. Benfenati, CORAL: the prediction of biodegradation of organic compounds with optimal SMILES-based descriptors. Cent. Eur. J. Chem. (2012) 10: 1042-1048.
A.P. Toropova; A.A. Toropov; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, The average numbers of outliers over groups of various splits into training and test sets: a criterion of the reliability of a QSPR? A case of water solubility. Chem. Phys. Lett. (2012) 542: 134-137.
A. A. Toropov; A.P. Toropova; B.F. Rasulev; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, CORAL: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical. J. Comput. Chem. (2012) 33: 1902-1906.
A. A. Toropov; A.P. Toropova; B.F. Rasulev; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, Calculation of molecular features with apparent impact on both activity of mutagens and activity of anticancer agents. Anti-Cancer Agents in Med. Chem. (2012) 12: 807-817.
A. A. Toropov; A.P. Toropova; E. Benfenati; G. Gini; T. Puzyn; D. Leszczynska; J. Leszczynski, Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli. Chemosphere (2012) 89: 1098–1102.
A. P. Toropova; A.A. Toropov; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, CORAL: Quantitative Models for Estimatingbioconcentration Factor of Organic Compounds. Chemometr. Intell. Lab. (2012) 118: 70-73.
A. P. Toropova; A.A. Toropov; B.F. Rasulev; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, QSAR models for ACE-inhibitor activity of tri-peptides based on representation of the molecular structure by graph of atomic orbitals and SMILES. Struct Chem . (2012) 23: 1873-1878.
A. A. Toropov; A.P. Toropova; I. Raska Jr ; E. Benfenati; G. Gini, QSAR modeling of endpoints for peptides which is based on representation of the molecular structure by a sequence of amino acids. Struct Chem. (2012) 23: 1891-1904.
A. P. Toropova; A.A. Toropov; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, CORAL: QSAR models of toxicity of binary mixtures . Chemometr. Intell. Lab. (2012) 119: 39-43.
A. A. Toropov; A.P. Toropova; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, CORAL: Classification model for predictions of anti-sarcoma activity. Current Topics in Medicinal Chemistry (2012) 12: 2741-2744.
A. A. Toropov; A.P. Toropova; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, CORAL: QSPR model of water solubility based on local and global SMILES attributes. Chemosphere (2013) 90: 877–880.
A. P. Toropova; A.A. Toropov; S.E. Martyanov; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, CORAL: the Monte Carlo method as a tool for prediction of bioconcentration factor of industrial pollutants. Molecular Informatics (2013) 32: 145-154.
A. A. Toropov; A.P. Toropova; E. Benfenati; G. Gini; R. Fanelli, The definition of the molecular structure for potential anti-malaria agents by the Monte Carlo method. Struct Chem. (2013) 24: 1369-1381.

A. A. Toropov; A.P. Toropova ; I. Raska Jr ; E. Benfenati ; G. Gini , Development of QSAR models for predicting anti-HIV-1 activity using the Monte Carlo method. Cent. Eur. J. Chem. (2013) 11: 371-380.
A. P. Toropova; A.A. Toropov; T. Puzyn; E. Benfenati; D. Leszczynska; J. Leszczynski, Optimal descriptor as a translator of eclectic information into the prediction of thermal conductivity of Micro-Electro-Mechanical Systems. J. Math. Chem. (2013) 51: 2230-2237.

A. P. Toropova; A.A. Toropov; T. Puzyn; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, QSAR as a random event: Models for nanoparticles uptake in PaCa2 cancer cells. Chemosphere (2013) 92: 31–37.
A. P. Toropova; A.A. Toropov; T. Puzyn; E. Benfenati; D. Leszczynska; J. Leszczynski, Optimal descriptor as a translator of eclectic information into the prediction of thermal conductivity of Micro-Electro-Mechanical Systems. J. Math. Chem. (2013) 51: 2230-2237.
A. P. Toropova; A.A. Toropov, Optimal descriptor as a translator of eclectic information into the prediction of membrane damage by means of various TiO2 nanoparticles. Chemosphere (2013) 93: 2650–2655.
A. A. Toropov; A.P. Toropova, Optimal descriptor as a translator of eclectic data into endpoint prediction: Mutagenicity of fullerene as a mathematical function of conditions. Chemosphere (2014) 104: 262-264.
A. P. Toropova ; A.A. Toropov; E. Benfenati; T. Puzyn; D. Leszczynska; J. Leszczynski, Optimal descriptor as a translator of eclectic information into the prediction of membrane damage: The case of a group of ZnO and TiO2 nanoparticles. Ecotoxicology and Environmental Safety (2014) 108: 203-209.
A. Worachartcheewan ; P. Mandi ; V. Prachayasittikul ; A.P. Toropova ; A.A. Toropov ; C. Nantasenamat , Large-scale QSAR study of aromatase inhibitors using SMILES-based descriptors . Chemometrics and Intelligent Laboratory Systems (2014) 138: 120-126.
P.R. Duchowicz ; S.E. Fioressi; D.E. Bacelo; L.M. Saavedra; A.P. Toropova; A.A. Toropov, QSPR Studies on Refractive Indices of Structurally Heterogeneous Polymers. Chemom. Intell. Lab. Syst. (2015) 140: 86–91.
J. B. Veselinović A. A. Toropov; A.P. Toropova; G. M. Nikolić A. M. Veselinović, Monte Carlo Method-Based QSAR Modeling of Penicillins Binding to Human Serum Proteins. Arch. Pharm. (2015) 348(1): 62-67.
A. P. Toropova; A. A. Toropov; R. Rallo; D. Leszczynska; J. Leszczynski, Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions. Ecotoxicology and Environmental Safety (2015) 112: 39–45.
A. A. Toropov, A.P. Toropova. Quasi-QSAR for mutagenic potential of multi-walled carbon-nanotubes. Chemosphere (2015) 124 ; 40–46
A. P. Toropova and A. A. Toropov. Mutagenicity: QSAR - quasi-QSAR - nano-QSAR. Mini-Reviews in Medicinal Chemistry, (2015) Vol. 15, No. 2 , 608-621
A. P. Toropova, A. A. Toropov, J.B. Veselinović, A. M. Veselinović, E. Benfenati, D. Leszczynska, J. Leszczynski. Application of the Monte Carlo method to prediction of dispersibility of graphene in various solvents. Int. J. Environ. Res., 9(4):1211-1216, Autumn 2015
A. A. Toropov, A. P. Toropova, A. M. Veselinović, J. B. Veselinović, K. Nesměrák, I. Raska Jr, P. R. Duchowicz, E. A. Castro, V. O. Kudyshkin, D. Leszczynska, J. Leszczynski. The Monte Carlo method based on eclectic data as an efficient tool for predictions of endpoints for nanomaterials – two examples of application. Combinatorial Chemistry & High Throughput Screening. 2015, 18(4), 376-386
A. P. Toropova, A. A. Toropov, Quasi-SMILES and nano-QFAR: United model for mutagenicity of fullerene and MWCNT under different conditions. Chemosphere, 139 (2015) 18-22
Alla P. Toropova, Andrey A. Toropov, Valentin O. Kudyshkin, Robert Rallo, Prediction of the Q-e parameters from structures of transfer chain agents, Journal of Polymer Research, 22 (2015)128.
Manganelli, S., Leone, C., Toropov, A.A., Toropova, A.P., Benfenati, E. (2015): QSAR model for cytotoxicity of silica nanoparticles on human embryonic kidney cells. Materials Today: Proceedings , Volume 3, Issue 3, 2016, Pages 847-854.
S. Manganelli, C. Leone, A.A. Toropov, A.P. Toropova, E. Benfenati, QSAR model for predicting cell viability of human embryonic kidney cells exposed to SiO2 nanoparticles. Chemosphere,144 (2016) 995-1001.
Veselinovic A.M., Veselinovic J.B., Nikolic G.M., Toropova A.P., Toropov A.A., QSPR models for estimating retention in HPLC with the p solute polarity parameter based on the Monte Carlo method. Struct. Chem. (2016) 27: 821–828.
Toropov A.A., Toropova A.P., Nesměrák K., Veselinović A.M., Veselinović J.B., Leszczynska D., Leszczynski J.: Development of the latest tools for building up "nano-QSAR": Quantitative features-property/activity relationships (QFPRs/QFARs).  Chapter 12, In Book: Practical Aspects of Computational Chemistry IV. J. Leszczynski, M.K. Shukla (Eds.). Springer 2016. ISBN 78-1-4899-7699-4, p. 353-396. DOI: 10.1007/978-1-4899-7699-4_12 http://rd.springer.com/chapter/10.1007%2F978-1-4899-7699-4_12


A. P. Toropova; A.A. Toropov; T. Puzyn; E. Benfenati; D. Leszczynska; J. Leszczynski, Optimal descriptor as a translator of eclectic information into the prediction of thermal conductivity of Micro-Electro-Mechanical Systems. J. Math. Chem. (2013) 51: 2230-2237.
A.P. Toropova; A.A. Toropov; E. Benfenati ; R. Korenstein , QSAR model for cytotoxicity of SiO2 nanoparticles on human lung fibroblasts , (2014) Journal of Nanoparticle Research 16: 2282.
A. Worachartcheewan ; P. Mandi ; V. Prachayasittikul ; A.P. Toropova ; A.A. Toropov ; C. Nantasenamat , Large-scale QSAR study of aromatase inhibitors using SMILES-based descriptors. Chemometrics and Intelligent Laboratory Systems (2014) 138: 120-126.
A. P. Toropova; A.A. Toropov; R. Rallo; D. Leszczynska; J. Leszczynski, Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions. Ecotoxicology and Environmental Safety (2015) 112: 39–45.
A.P. Toropova; A.A. Toropov; E. Benfenati; R. Korenstein; D. Leszczynska; J. Leszczynski, 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. (2015) 22:745–757
A. A. Toropov, A.P. Toropova. Quasi-QSAR for mutagenic potential of multi-walled carbon-nanotubes. Chemosphere (2015) 124 ; 40–46
A. P. Toropova and A. A. Toropov. Mutagenicity: QSAR - quasi-QSAR - nano-QSAR. Mini-Reviews in Medicinal Chemistry, (2015) Vol. 15, No. 2, 608-621
A. A. Toropov, A. P. Toropova, A. M. Veselinovic´, J. B. Veselinovic´, K. Nesměrák, I. Raška Jr, P. R. Duchowicz, E. A. Castro, V. O. Kudyshkin, D. Leszczynska, J. Leszczynski. The Monte Carlo method based on eclectic data as an efficient tool for predictions of endpoints for nanomaterials – two examples of application. Combinatorial Chemistry & High Throughput Screening. 2015, 18(4), 376-386
A.P. Toropova, A. A. Toropov, E. Benfenati, A quasi-QSPR modeling for the photocatalytic decolorisation rate constants and cellular viability (CV%) of nanoparticles by CORAL. SAR and QSAR in Environmental Research. Jan 2015, 26(1); 29-40.
Alla P. Toropova, Andrey A. Toropov, Valentin O. Kudyshkin, Robert Rallo, Prediction of the Q-e parameters from structures of transfer chain agents, Journal of Polymer Research, 22 (2015)128.
A. P. Toropova, A. A. Toropov, Quasi-SMILES and nano-QFAR: United model for mutagenicity of fullerene and MWCNT under different conditions. Chemosphere, 139 (2015) 18-22
A. P. Toropova, A. A. Toropov, J.B. Veselinović, A. M. Veselinović, E. Benfenati, D. Leszczynska, J. Leszczynski. Application of the Monte Carlo method to prediction of dispersibility of graphene in various solvents. Int. J. Environ. Res., 9(4):1211-1216, Autumn 2015
Manganelli, S., Leone, C., Toropov, A.A., Toropova, A.P., Benfenati, E. QSAR model for cytotoxicity of silica nanoparticles on human embryonic kidney cells. Materials Today: Proceedings, Volume 3, Issue 3, 2016, Pages 847-854.
S. Manganelli, C. Leone, A.A. Toropov, A.P. Toropova, E. Benfenati, QSAR model for predicting cell viability of human embryonic kidney cells exposed to SiO2 nanoparticles. Chemosphere,144 (2016) 995-1001.
Veselinovic A.M., Veselinovic J.B., Nikolic G.M., Toropova A.P., Toropov A.A., QSPR models for estimating retention in HPLC with the p solute polarity parameter based on the Monte Carlo method. Struct. Chem. (2016) 27: 821–828.
Toropov A.A., Toropova A.P., Nesměrák K., Veselinović A.M., Veselinović J.B., Leszczynska D., Leszczynski J.: Development of the latest tools for building up "nano-QSAR": Quantitative features-property/activity relationships (QFPRs/QFARs).  Chapter 12, In Book: Practical Aspects of Computational Chemistry IV. J. Leszczynski, M.K. Shukla (Eds.). Springer 2016. ISBN 78-1-4899-7699-4, p. 353-396. DOI: 10.1007/978-1-4899-7699-4_12 http://rd.springer.com/chapter/10.1007%2F978-1-4899-7699-4_12


A. A. Toropov; A.P. Toropova ; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski; G.De Nucci , QSAR models for inhibitors of physiological impact of Escherichia coli that leads to diarrhea. Biochemical and Biophysical Research Communications (2013) 432: 214–225.
A. P. Toropova; A.A. Toropov; E. Benfenati; G. Gini; D. Leszczynska; J. Leszczynski, CORAL: QSPRs of enthalpies of formation of organometallic compounds. J Math Chem. (2013) 51: 1684-1693.
A. A. Toropov; A.P. Toropova ; E. Benfenati; G. Gini, OCWLGI Descriptors: Theory and Praxis. Curr Comput-Aid Drug Des. (2013) 9: 226-232.
A. Worachartcheewan ; P. Mandi ; V. Prachayasittikul ; A.P. Toropova ; A.A. Toropov ; C. Nantasenamat , Large-scale QSAR study of aromatase inhibitors using SMILES-based descriptors. Chemometrics and Intelligent Laboratory Systems (2014) 138: 120-126.
Veselinovic A.M., Veselinovic J.B., Nikolic G.M., Toropova A.P., Toropov A.A., QSPR models for estimating retention in HPLC with the p solute polarity parameter based on the Monte Carlo method. Struct. Chem. (2016) 27: 821–828.

A. P. Toropova; A.A.Toropov; R. Rallo; D. Leszczynska; J. Leszczynski, Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions. Ecotoxicology and Environmental Safety (2015) 112: 39–45.
A. A. Toropov, A.P. Toropova. Quasi-QSAR for mutagenic potential of multi-walled carbon-nanotubes. Chemosphere (2015) 124 ; 40–46
A.P. Toropova , A. A. Toropov , E.Benfenati , D. Leszczynska , J. Leszczynski. QSAR model as a random event: A case of rat toxicity. Bioorganic & Medicinal Chemistry 2015, 23(6), 1223-1230
Andrey A. Toropov, Alla P. Toropova, Claudia Ileana Cappelli, Emilio Benfenati. CORAL: model for octanol/water partition coefficient. Fluid Phase Equilibria, (2015); 397, 44-49
Andrey A. Toropov, Alla P. Toropova, Fabiola Pizzo, Anna Lombardo, Domenico Gadaleta, Emilio Benfenati. CORAL: Model for No Observed Adverse Effect Level (NOAEL). Molecular Diversity, 19(3) (2015) 563-575.
A. P. Toropova, A. A. Toropov, J. B. Veselinović, A. M. Veselinović, QSAR as a random event: a case of NOAEL. Environ. Sci. Poll. Res. (2015), 22(11), 8264-8271
A. A. Toropov, R. Rallo, A. P. Toropova. Use of quasi-SMILES and Monte Carlo optimization to develop quantitative feature property/activity relationships(QFPR/QFAR) for nanomaterials. Current Topics in Medicinal Chemistry, 2015, 15( 18 )1837-1844.
Alla P. Toropova, Andrey A. Toropov, Valentin O. Kudyshkin, Robert Rallo, Prediction of the Q-e parameters from structures of transfer chain agents, Journal of Polymer Research, J. Polym. Res. 22 (2015)128
M. A. Toropova, A. A. Toropov, I. Raška Jr, M. Rašková. Searching therapeutic agents for treatment of Alzheimer disease using the Monte Carlo method. Computers in Biology and Medicine,64 (1 September 2015 ) 148-154.
A. P. Toropova, A. A. Toropov, Quasi-SMILES and nano-QFAR: United model for mutagenicity of fullerene and MWCNT under different conditions. Chemosphere, 139 (2015) 18-22
Apilak Worachartcheewan, Virapong Prachayasittikul, Alla P. Toropova, Andrey A. Toropov, Chanin Nantasenamat, Large-scale structure-activity relationship study of hepatitis C virus NS5B polymerase inhibition using SMILES-based descriptors. Molecular Diversity, 2015; 19: 955-964.
A. P. Toropova, A. A. Toropov, J.B. Veselinović, A. M. Veselinović, E. Benfenati, D. Leszczynska, J. Leszczynski. Application of the Monte Carlo method to prediction of dispersibility of graphene in various solvents. Int. J. Environ. Res., 9(4): 1211-1216, Autumn 2015
A. P. Toropova, A.A. Toropov, and E. Benfenati, CORAL: Prediction of binding affinity and efficacy of thyroid hormone receptor ligands. Journal of Medicinal Chemistry, 101 (2015) 452-461.
Alla P. Toropova, Andrey A. Toropov, Aleksandar M. Veselinović, Jovana B. Veselinović, Emilio Benfenati, Danuta Leszczynska, Jerzy Leszczynski, Nano-QSAR: Model of mutagenicity of fullerene as a mathematical function of different conditions. Ecotoxicology and Environmental Safety, 124 (2016) 32-36.
Karel Nesměrák, Andrey A. Toropov, Alla P. Toropova, Ilkay Yildiz, Ismail Yalcin, Marketa Brozikova, Vera Klimešová, Karel Waisser, Prediction of Retention Characteristics of Heterocyclic Compounds. Analytical and Bioanalytical Chemistry,(2015) 407: 9185–9189.
Alla P. Toropova, Terry W. Schultz, Andrey A. Toropov, Building up a QSAR model for toxicity towards Tetrahymena Pyriformis by the Monte Carlo method: A case of benzene derivatives. Environmental Toxicology and Pharmacology, 42 (2016) 135-145.
Karel Nesměrák, Andrey A. Toropov, Alla P. Toropova, Model for electrochemical parameters for 4-(benzylsulfanyl)pyridines calculated from the molecular structure. Journal of Electroanalytical Chemistry. 766 (2016) 24-29.
Toropova, A.; Toropov, A. CORAL: The dispersion of SWNTs in different organic solvents. In Proceedings of the MOL2NET, 5-15 December 2015; Sciforum Electronic Conference Series, Vol. 1, 2015 , c007; doi:10.3390/MOL2NET-1-c007.
Toropova, A.P., Toropov, A.A., Rallo, R., Leszczynska, D., and Leszczynski, J.,Nano-QSAR: Genotoxicity of multi-walled carbon nanotubes. Int. J. Environ. Res., 10(1): 59-64, Winter 2016.
Alla P. Toropova, Andrey A. Toropov. QSPR model for dispersibility of graphene in various solvents, Letters in Drug Design & Discovery, 13( 6), 2016, 514-520.
Alla P. Toropova, P.Ganga Raju Achary, Andrey A. Toropov. Quasi-SMILES for Nano-QSAR prediction of toxic effect of Al2O3 nanoparticles. Journal of Nanotoxicology and Nanomedicine, 1(1), 2016, 17-28.
Andrey A. Toropov, Alla. P. Toropova, Emilio Benfenati, Roberto Fanelli, QSAR as a random event: selecting of the molecular structure for potential anti-tuberculosis agents, Anti-Infective Agents, 2016, 14(1): 3 - 10.
Alla P. Toropova, Andrey A. Toropov, Evolution of Optimal Descriptors: Solved, Unsolved, and Unsoluble Tasks, International Journal of Quantitative Structure-Property Relationships , 1 (2), 2016, 52-71.
Alla P. Toropova and Andrey A. Toropov, Assessment of nano-QSPR models of organic contaminant absorption by carbon nanotubes for ecological impact studies. Materials Discovery, 4 (2016) 22–28.
Toropov A.A., Toropova A.P., Nesměrák K., Veselinović A.M., Veselinović J.B., Leszczynska D., Leszczynski J.: Development of the latest tools for building up "nano-QSAR": Quantitative features-property/activity relationships (QFPRs/QFARs).  Chapter 12, In Book: Practical Aspects of Computational Chemistry IV. J. Leszczynski, M.K. Shukla (Eds.). Springer 2016. ISBN 78-1-4899-7699-4, p. 353-396. DOI: 10.1007/978-1-4899-7699-4_12 http://rd.springer.com/chapter/10.1007%2F978-1-4899-7699-4_12
Andrey A. Toropov, Alla P. Toropova, Francesca Como, Emilio Benfenati; Quantitative structure–activity relationship models for bee toxicity. Toxicological & Environmental Chemistry; 99: 7-8, 2017, 1117-1128. DOI: 10.1080/02772248.2016.1242006
Veda Prachayasittikula, Apilak Worachartcheewana, Alla P. Toropova, Andrey A. Toropov, Virapong Prachayasittikul, Chanin Nantasenamat. Large-scale classification of P -glycoprotein inhibitors using SMILES-based descriptors. SAR and QSAR in Environmental Research, 28(1), 2017, 1-16. DOI:10.1080/1062936X.2016.1264468


J. B. Veselinović, A. M. Veselinović, A. P. Toropova, A. A. Toropov, The Monte Carlo technique as a tool to predict LOAEL. European Journal of Medicinal Chemistry, 116 (2016) 71-75.
Andrey A. Toropov, Alla P. Toropova, Sanija Begum, P. Ganga Raju Achary, Towards predicting the solubility of CO2 and N2 in different polymers using a Quasi-SMILES based QSPR approach. SAR and QSAR in Environmental Research,Vol. 27, Iss. 4, 2016, pages 293-301.
M. Gobbi, M. Beeg, M. A. Toropova, A. A. Toropov, M. Salmona, Monte Carlo method for Predicting of Cardiac Toxicity: hERG blocker compounds. Toxicology Letters. 250 (2016) 42–46.
A. P. Toropova, A. A. Toropov, S. Manganelli, C.Leone, D. Baderna, E. Benfenati, R. Fanelli, Quasi-SMILES as a tool to utilize eclectic data for predicting the behavior of nanomaterials. NANOIMPACT, 1 (2016) 60-64.
A. P. Toropova, A. A. Toropov, A. M. Veselinović, J. B. Veselinović, D. Leszczynska, J. Leszczynski, Monte Carlo based QSAR models for toxicity of organic chemicals to Daphnia magna. Environmental Toxicology and Chemistry, Vol. 35, No. 11, pp. 2691–2697, 2016. DOI: 10.1002/etc.3466
Alla P. Toropova, P.Ganga Raju Achary, Andrey A. Toropov. Quasi-SMILES for Nano-QSAR prediction of toxic effect of Al2O3 nanoparticles. Journal of Nanotoxicology and Nanomedicine, 1(1), 2016, 17-28.
M. A. Toropova, I. Raška Jr, A.A. Toropov, M. Rašková, The utilization of the Monte Carlo technique for rational drug discovery. Combinatorial Chemistry & High Throughput Screening. 2016, 19 (8), 676-687.
P. Ganga Raju Achary, Sanija Begum, Alla P. Toropova, Andrey A. Toropov, A quasi-SMILES based QSPR Approach towards the prediction of adsorption energy of Ziegler - Natta catalysts for propylene polymerization. Materials Discovery, 5, August 2016, 22–28.
Andrey A. Toropov, P. Ganga Raju Achary, Alla P. Toropova. Quasi-SMILES and nano-QFPR: The predictive model for zeta potentials of metal oxide nanoparticles. Chemical Physics Letters 660 (2016) 107-110.
A.A. Toropov, A. P. Toropova, L. Cappellini, E. Benfenati, E. Davoli. Odor Threshold prediction by means of the Monte Carlo method. Ecotoxicology and Environmental Safety 133 (2016) 390-394.
Alla P. Toropova and Andrey A. Toropov, Assessment of nano-QSPR models of organic contaminant absorption by carbon nanotubes for ecological impact studies. Materials Discovery, 4 (2016) 22–28.
Alla P. Toropova, Andrey A. Toropov. Nano-QSAR in cell biology: Model of cell viability as a mathematical function of available eclectic data. Journal of Theoretical Biology 416 (2017) 113-118.
Alla P. Toropova, Andrey A. Toropov. CORAL: Binary classifications (active/inactive) for drug-induced liver injury. Toxicology Letters, 268, 15 February 2017, 51–57.
M. A. Toropova, I. Raska Jr, A. P. Toropova, M. Raskova. CORAL software: analysis of impacts of pharmaceutical agents upon metabolism via the optimal descriptors. Current Drug Metabolism, Vol. 18, No. 6, 500-510, 2017.
Alla P. Toropova, Andrey A. Toropov, Danuta Leszczynska, Jerzy Leszczynski. CORAL and Nano-QFAR: Quantitative feature – activity relationships (QFAR) for bioavailability of nanoparticles (ZnO, CuO, Co3O4, and TiO2). Ecotoxicology and Environmental Safety, 2017; 139: 404-407.
Toropova, A. P.; Toropov, A. A.; Veselinovic, A. M.; Veselinovic, J. B.; Leszczynska, D.; Leszczynski, J. Quasi-SMILES as a Novel Tool for Prediction of Nanomaterials' Endpoints. In Multi-Scale Approaches in Drug Discovery: From Empirical Knowledge to In Silico Experiments and Back, 1st ed.; Speck-Planche, A., Ed. Elsevier: Oxford, UK, 2017; pp 191-221. doi: http://dx.doi.org/10.1016/B978-0-08-101129-4.00008-4
Alla P. Toropova, Andrey A. Toropov, Marten Beeg, Marco Gobbi, Mario Salmona, Utilization of the Monte Carlo method to build up QSAR models for hemolysis and cytotoxicity of antimicrobial peptides. Current Drug Discovery Technologies,14(4), 2017, 229-243. DOI: 10.2174/1570163814666170525114128
Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, Robert Rallo, Danuta Leszczynska and Jerzy Leszczynski: Development of Monte Carlo Approaches in Support of Environmental Research. Chapter 12 (pages 453-469), In Book: Advances in QSAR modeling. Volume 24 of the series Challenges and Advances in Computational Chemistry and Physics. Edited: Roy, K. Springer International Publishing AG, 25 May 2017. DOI: 10.1007/978-3-319-56850-8_12


Alla P. Toropova, Andrey A. Toropov, Maria Raškova, Ivan Raška Jr, Improved building up a model of toxicity towards Pimephales promelas by the Monte Carlo method. Environmental Toxicology and Pharmacology 48 (2016) 278–285.
Alla P. Toropova, Andrey A. Toropov. CORAL: Binary classifications (active/inactive) for drug-induced liver injury. Toxicology Letters, 268, 15 February 2017, 51–57.
Alla P. Toropova, Andrey A. Toropov. The index of ideality of correlation: A criterion of predictability of QSAR models for skin permeability? Science of the Total Environment 586 (2017) 466–472.
Alla P. Toropova, Andrey A. Toropov, Danuta Leszczynska, Jerzy Leszczynski. CORAL and Nano-QFAR: Quantitative feature – activity relationships (QFAR) for bioavailability of nanoparticles (ZnO, CuO, Co3O4, and TiO2). Ecotoxicology and Environmental Safety, 2017; 139: 404-407.
Alla P. Toropova, Andrey A. Toropov. Hybrid Optimal Descriptors as a Tool to Predict Skin Sensitization in accordance to OECD principles. Toxicology Letters 275 (2017) 57-66.
Andrey A. Toropov, Alla P. Toropova. The index of ideality of correlation: a criterion of predictive potential of QSPR/QSAR models? Mutation Research - Genetic Toxicology and Environmental Mutagenesis, 819 (2017) 31–37.
Alla P. Toropova, Andrey A. Toropov, Marco Marzo, Sylvia E. Escher, Jean Lou Dorne, Nikolaos Georgiadis, Emilio Benfenati. The application of new HARD-descriptor available from the CORAL software to building up NOAEL models. Food and Chemical Toxicology 112 (2018) 544-550.

Cosimo Toma, Domenico Gadaleta, Alessandra Roncaglioni, Andrey Toropov, Alla Toropova, Marco Marzo, Emilio Benfenati, QSAR development for plasma protein binding: influence of the ionization state. Pharmaceutical Research,(2019) 36: 28.
Alla P. Toropova, Andrey A. Toropov, Marco Marzo, Sylvia E. Escher, Jean Lou Dorne, Nikolaos Georgiadis, Emilio Benfenati, Corrigendum to “The application of new HARD-descriptor available from the CORAL software to building up NOAEL models”[Food Chem. Toxicol.112 (2018) 544–550].Food and Chemical Toxicology 128 (2019) 146.
Gadaleta, D.; Marzo, M.; Toropov, A.A.; Toropova, A.P.; Lavado, G.; Escher, S.; Dorne, J.-L.; Benfenati, E. Integrated in silico models for the prediction of No-Observed-(Adverse)-Effect-Levels and Lowest-Observed-(Adverse)-Effect-Levels in rats for sub-chronic repeated dose toxicity. Chemical Research in Toxicology, Accepted for publication: July 15, 2020.

Alla P. Toropova, Andrey A. Toropov, Maria Raškova, Ivan Raška Jr, Improved building up a model of toxicity towards Pimephales promelas by the Monte Carlo method. Environmental Toxicology and Pharmacology 48 (2016) 278–285.
Alla P. Toropova, Andrey A. Toropov. The index of ideality of correlation: A criterion of predictability of QSAR models for skin permeability? Science of the Total Environment 586 (2017) 466–472.
Alla P. Toropova, Andrey A. Toropov, Danuta Leszczynska, Jerzy Leszczynski. CORAL and Nano-QFAR: Quantitative feature – activity relationships (QFAR) for bioavailability of nanoparticles (ZnO, CuO, Co3O4, and TiO2). Ecotoxicology and Environmental Safety, 2017; 139: 404-407.
A. A. Toropov, A. P. Toropova, M. Marzo, J.L. Dorne, N. Georgiadis, E. Benfenati, QSAR models for predicting acute toxicity of pesticides in rainbow trout using the CORAL software and EFSA’s OpenFoodTox database. Environmental Toxicology and Pharmacology 53 (2017) 158–163.
Alla P. Toropova, Andrey A. Toropov, Marco Marzo, Sylvia E. Escher, Jean Lou Dorne, Nikolaos Georgiadis, Emilio Benfenati. The application of new HARD-descriptor available from the CORAL software to building up NOAEL models. Food and Chemical Toxicology 112 (2018) 544-550.
Gadaleta, D.; Marzo, M.; Toropov, A.A.; Toropova, A.P.; Lavado, G.; Escher, S.; Dorne, J.-L.; Benfenati, E. Integrated in silico models for the prediction of No-Observed-(Adverse)-Effect-Levels and Lowest-Observed-(Adverse)-Effect-Levels in rats for sub-chronic repeated dose toxicity. Chemical Research in Toxicology, Accepted for publication: July 15, 2020. https://doi.org/10.1021/acs.chemrestox.0c00176



Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, Robert Rallo, Danuta Leszczynska and Jerzy Leszczynski: Development of Monte Carlo Approaches in Support of Environmental Research. Chapter 12 (pages ),In Book: Advances in QSAR modeling. Edited: Roy, K. Springer International Publishing AG, 2017.
Alla P. Toropova, Andrey A. Toropov. Hybrid Optimal Descriptors as a Tool to Predict Skin Sensitization in accordance to OECD principles. Toxicology Letters 275 (2017)57-66.
Andrey A. Toropov, Alla P. Toropova, Marten Beeg, Marco Gobbi, Mario Salmona, QSAR model for Blood-Brain Barrier Permeation. Journal of Pharmacological and Toxicological Methods 88 (2017) 7–18.
Andrey A. Toropov, Alla P. Toropova. The index of ideality of correlation: a criterion of predictive potential of QSPR/QSAR models? Mutation Research - Genetic Toxicology and Environmental Mutagenesis, 819 (2017) 31–37.
A. A. Toropov, A. P. Toropova, M. Marzo, J.L. Dorne, N. Georgiadis, E. Benfenati, QSAR models for predicting acute toxicity of pesticides in rainbow trout using the CORAL software and EFSA’s OpenFoodTox database. Environmental Toxicology and Pharmacology 53 (2017) 158–163.
Karel Nesmerák, Andrey A. Toropov, Alla P. Toropova, Tugba Ertan-Bolelli, Ilkay Yildiz. QSAR of antimycobacterial activity of benzoxazoles by optimal SMILES-based descriptors. Med. Chem. Res. (2017) 26: 3203-3208.
Alla P. Toropova, Andrey A. Toropov, CORAL: Monte Carlo method to predict endpoints for medical chemistry. Mini-Reviews in Medicinal Chemistry. 18(5), 2018, 382 - 391.
Alla P. Toropova, Andrey A. Toropov, S. Begum, P. G. R. Achary, Blood brain barrier and Alzheimer’s disease: Similarity and dissimilarity of molecular alerts. Current Neuropharmacology, 2018, 16, 769-785.
Andrey A. Toropov, Alla P. Toropova, Luigi Cappellini, Emilio Benfenati, Enrico Davoli, QSPR analysis of threshold of odor for the large number of heterogenic chemicals. Molecular Diversity, (2018) 22:397–403.
Andrey A. Toropov and Alla P. Toropova. Improved Model for Biodegradability of Organic Compounds: The Correlation Contributions of Rings. Chapter 8, In Book: Toxicity and Biodegradation Testing, Methods in Pharmacology and Toxicology. Edited: Ederio Dino Bidoia and Renato Nallin Montagnolli, Springer Science+Business Media LLC 2018. DOI 10.1007/978-1-4939-7425-2_8
Andrey A. Toropov, Ramon Carbó-Dorca, Alla P. Toropova, Index of Ideality of Correlation: new possibilities to validate QSAR: a case study. Structural Chemistry, (2018) 29: 33–38.
Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, Mario Salmona, Mutagenicity, Anticancer activity, and Blood brain barrier: Similarity and dissimilarity of molecular alerts. Toxicology Mechanisms and Methods, 28(5), 2018, 321-327.
Alla P. Toropova and Andrey A. Toropov, CORAL: QSAR Models for Carcinogenicity of Organic Compounds for Male and Female Rats. Computational Biology and Chemistry, Volume 72, February 2018, Pages 26–32.
A. Worachartcheewan, A. P. Toropova, A.A. Toropov, S. Siriwong, J. Prapojanasomboon, V. Prachayasittikul, C. Nanatasenamat, Quantitative Structure-activity Relationship Study of Betulinic Acid Derivatives Against HIV using SMILES-based Descriptors. Current Computer-Aided Drug Design, 2018;14(2):152-159.
Andrey A. Toropov, Alla P. Toropova, Application of the Monte Carlo method for building up models for octanol-water partition coefficient of platinum complexes. Chemical Physics Letters, 701 (2018) 137-146.
Andrey A. Toropov, Alla P. Toropova, Alessandra Roncaglioni, and Emilio Benfenati, Prediction of Biochemical Endpoints by the CORAL Software: Prejudices, Paradoxes, and Results. Chapter 27, In book: Orazio Nicolotti (ed.), Computational Toxicology: Methods and Protocols, Methods in Molecular Biology, vol. 1800, https://doi.org/10.1007/978-1-4939-7899-1_27, © Springer Science+Business Media, LLC, part of Springer Nature 2018.
A.A. Toropov, A.P. Toropova, E. Benfenati, L. Diomede, M. Salmona, Use of Quasi-SMILES to model biological activity of "micelle-polymer" samples. Structural Chemistry (2018) 29: 1213–1223.
Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, Jean Lou Dorne, SAR for gastro-intestinal absorption and blood-brain barrier permeation of pesticides. Chemico-Biological Interactions, 290 (2018) 1–5.
Andrey A. Toropov, Alla P. Toropova, Giuseppa Raitano, Emilio Benfenati,CORAL: building up QSAR models for the chromosome aberration test. Saudi Journal of Biological Sciences, 26 (2019) 1101-1106. https://doi.org/10.1016/j.sjbs.2018.05.013
Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, Danuta Leszczynska, Jerzy Leszczynski, Prediction of antimicrobial activity of large pool of peptides using quasi-SMILES. BioSystems,169-170 (2018) 5-12.
Alla P. Toropova, Andrey A. Toropov. The index of ideality of correlation: Improvement of models for toxicity to algae. Natural Product Research, 33(15), 2019, 2200-2207.
Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, Sara Castiglioni,Renzo Bagnati, Alice Passoni, Ettore Zuccato, Roberto Fanelli. Quasi-SMILES as a tool to predict removal rates of pharmaceuticals and dyes in sewage. Process Safety and Environmental Protection, 118 (2018) 227-233.
Andrey A. Toropov, Alla P. Toropova, Use of The Index of Ideality of Correlation to improve predictive potential for biochemical endpoints. Toxicology Mechanisms and Methods, 2019, 29(1), 43–52.
Alla P. Toropova, Andrey A. Toropov, Aleksandar M. Veselinović, Jovana B. Veselinović, Danuta Leszczynska, Jerzy Leszczynski, Semi-correlations combined with the index of ideality of correlation: A tool to build up model of mutagenic potential. Molecular and Cellular Biochemistry, 2019, Volume 452, Issue 1–2, pp. 133–140.
Alla P. Toropova, Andrey A. Toropov, Danuta Leszczynska, Jerzy Leszczynski, The Index of Ideality of Correlation: Hierarchy of Monte Carlo models for Glass Transition Temperatures of Polymers. Journal of Polymer Research, (2018) 25:221-227.
M.Marzo, G.J. Lavado, F. Como, A.A. Toropov, A.P. Toropova, D. Baderna, C. Cappelli, A. Lombardo, C. Toma, M. Blázquez Sánchez, E. Benfenati, QSAR models for Biocides. The example of the prediction of Daphnia Magna acute toxicity. SAR and QSAR in Environmental Research, 31:3, 227-243, 2020. https://doi.org/10.1080/1062936X.2019.1709221
Claudia Ileana Cappelli, Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, Ecosystem ecology: models for acute toxicity of pesticides towards Daphnia magna. Environmental Toxicology and Pharmacology 80 (2020) 103459.https://doi.org/10.1016/j.etap.2020.103459


A.A. Toropov, A.P. Toropova, E. Benfenati, The Index of Ideality of Correlation: QSAR model of acute toxicity for zebrafish (Danio rerio) embryo. International Journal of Environmental Research (2019) 13: 387–394.
Andrey A. Toropov, Alla P. Toropova, The Monte Carlo Method as a tool to build up predictive QSPR/QSAR. Curr. Comput. Aided Drug Des. 2020, 16(3), 197 – 206. DOI: 10.2174/1573409915666190328123112
Andrey A. Toropov, Alla P. Toropova, Danuta Leszczynska, Jerzy Leszczynski, "Ideal correlations" for biological activity of peptides. BioSystems, 181 (2019) 51-57. https://doi.org/10.1016/j.biosystems.2019.04.008
Andrey A. Toropov, Alla P. Toropova, Gianluca Selvestrel, Emilio Benfenati, Idealization of correlations between optimal SMILES-based descriptors and skin sensitization. SAR and QSAR in Environmental Research, 30(6), 2019, 447-455.
Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, QSPR as a random event: solubility of fullerenes C[60] and C[70]. Fullerenes, Nanotubes and Carbon Nanostructures, 2019, 27(10), 816-821. DOI: 10.1080/1536383X.2019.1649659
Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, QSAR-models, validation, and IIC-paradox for drug toxicity. International Journal of Quantitative Structure-Property Relationships (IJQSPR), 5(1), 2020, 22-43. DOI: 10.4018/IJQSPR.2020010102
E. Carnesecchi, A.A. Toropov, A.P. Toropova, N. Kramer, C.Svendsen, J.L. Dorne, E. Benfenati, Predicting acute contact toxicity of organic binary mixtures in honey bees (A. mellifera) through innovative QSAR models. Science of The Total Environment, 704 (2020) 135302.
Andrey A.Toropov, Alla P.Toropova, Marco Marzo, Emilio Benfenati, Use of the index of ideality of correlation to improve aquatic solubility model. Journal of Molecular Graphics and Modelling 96 (2020) 107525.
Alla P. Toropova, Pablo R. Duchowicz, Laura M. Saavedra, Eduardo A. Castro and Andrey A. Toropov, The use of the index of ideality of correlation to build up models for bioconcentration factor. Molecular Informatics, 2020, 39, 1900070. https://doi.org/10.1002/minf.201900070
Alla P. Toropova, Andrey A. Toropov, Edoardo Carnesecchi, Emilio Benfenati, Jean Lou Dorne,The using of the Index of Ideality of Correlation (IIC) to improve predictive potential of models of water solubility for pesticides. Environmental Science and Pollution Research, 27, pages 13339–13347 (2020).DOI: 10.1007/s11356-020-07820-6
Andrey A. Toropov, Alla P. Toropova, QSPR/QSAR: state-of-art, weirdness, the future. Molecules 2020, 25(6), 1292. https://doi.org/10.3390/molecules25061292
A.A. Toropov, A.P. Toropova, M. Marzo, E. Carnesecchi, G. Selvestrel, E. Benfenati, Pesticides, Cosmetics, Drugs: identical and opposite influences of various molecular features as measures of endpoints similarity and dissimilarity. Molecular Diversity, Accepted April 4, 2020. DOI: 10.1007/s11030-020-10085-3
G.J. Lavado, D. Gadaleta, C. Toma, A. Golbamaki, A.A. Toropov, A.P. Toropova, M. Marzo, D. Baderna, E. Benfenati, Zebrafish AC50 Modelling: (Q)SAR Models to Predict Developmental Toxicity in Zebrafish Embryo. Ecotoxicology and Environmental Safety 202 (2020) 110936.
Andrey A. Toropov and Alla P. Toropova, Correlation Intensity Index: building up models for mutagenicity of silver nanoparticles. Science of the Total Environment 737 (2020) 139720. https://doi.org/10.1016/j.scitotenv.2020.139720
K. Jafari, M.H. Fatemi, A.P. Toropova, A.A. Toropov, Correlation Intensity Index (CII) as a criterion of predictive potential: applying to model thermal conductivity of metal oxide-based ethylene glycol nanofluids. Chemical Physics Letters 754 (2020) 137614. DOI: 10.1016/j.cplett.2020.137614
Alla P. Toropova and Andrey A. Toropov, Fullerenes C60 and C70: a model for solubility by applying the correlation intensity index. Fullerenes, Nanotubes and Carbon Nanostructures, 2020; 28:11, 900-906. DOI:10.1080/1536383X.2020.1779705
Shahin Ahmadi, Alla P. Toropova, and Andrey A. Toropov, Correlation Intensity Index: Mathematical modelling of cytotoxicity of metal oxide nanoparticles. Nanotoxicology, 2020, 14:8, 1118-1126. DOI: 10.1080/17435390.2020.1808252
Andrey A. Toropov, Natalia Sizochenko, Alla P. Toropova, Danuta Leszczynska, Jerzy Leszczynski, Advancement of predictive modeling of zeta potentials in metal oxide nanoparticles with correlation intensity index (CII). Journal of Molecular Liquids, 317 (2020) 113929. https://doi.org/10.1016/j.molliq.2020.113929
Andrey A. Toropov, Alla P. Toropova, Aleksandar Veselinović, Danuta Leszczynska, Jerzy Leszczynski, SARS-CoV Mpro inhibitory activity of aromatic disulfide compounds: QSAR model. Journal of Biomolecular Structure and Dynamics, Accepted Aug 29, 2020. Published online: 09 Sep 2020 DOI: 10.1080/07391102.2020.1818627
Alla P. Toropova, Maria Raškova, Ivan Raška Jr., Andrey A. Toropov, The sequence of amino acids as the basis for the model of biological activity of peptides. Theoretical Chemistry Accounts, Accepted Dec 14, 2020.

Alla P. Toropova, Andrey A. Toropov, Use of the Index of Ideality of Correlation to improve models of Eco-toxicity. Environmental Science and Pollution Research, (2018) 25: 31771-31775.
A.P. Toropova, A.A. Toropov, E. Benfenati, D. Leszczynska, J. Leszczynski, Virtual Screening of Anti-Cancer Compounds: Application of Monte Carlo Technique. Anti-Cancer Agents in Medicinal Chemistry, 19(2), 2019, 148 – 153.
Alla P. Toropova, Andrey A. Toropov, Quasi-SMILES: Quantitative Structure - Activity Relationships to predict anti-cancer activity. Molecular Diversity (2019) 23: 403–412.
Andrey A. Toropov and Alla P. Toropova, Predicting Cytotoxicity of 2-Phenylindole Derivatives Against Breast Cancer Cells Using Index of Ideality of Correlation. Anticancer Research, 38: 6189-6194 (2018).
Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, Semi-correlations as a tool to build up categorical (active/inactive) model of GABAA receptor modulators activity. Struct. Chem.(2019) 30 (3): 853–861.
Alla Toropova; Andrey Toropov; Emilio Benfenati, Idealized correlations: prediction of solubility of fullerene in organic solvents , Published: 10 December 2018 by MDPI AG in MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition session WCUCW-02: West Coast University Capstone Workshop, WCU, Miami, USA, 2018 ( doi: 10.3390/mol2net-04-05898 )
Andrey A. Toropov, Ivan Raška Jr., Alla P. Toropova, Maria Raškova, Aleksandar M. Veselinović, Jovana B. Veselinović, The study of the Index of Ideality of Correlation As a new criterion of predictive potential of QSPR/QSAR-models. Science of the Total Environment 659 (2019) 1387–1394.
Alla P. Toropova, Andrey A. Toropov, QSPR and nano-QSPR: what is the difference? Journal of Molecular Structure, 1182 (2019) 141-149.
Alla P. Toropova, Andrey A. Toropov, Does the index of ideality of correlation detect the better model correctly? Molecular Informatics,2019, 38, 1800157. https://doi.org/10.1002/minf.201800157
Alla P. Toropova and Andrey A. Toropov, Applying of the Monte Carlo method for the prediction of behavior of peptides, Current Protein & Peptide Science (2019) 20(12): 1151 - 1157.
P.G.R. Achary, A.P. Toropova, A.A. Toropov, Combinations of graph invariants and attributes of simplified molecular input-line entry system (SMILES) to build up models for sweetness. Food Research International 122 (2019) 40–46.
Alla P. Toropova and Andrey A. Toropov, Whether the Validation of the Predictive Potential of Toxicity Models is Solved Task? Current Topics in Medicinal Chemistry, 2019; 19(29): 2643 - 2657.
Alla P. Toropova, Andrey A. Toropov, Edoardo Carnesecchi, Emilio Benfenati, Jean Lou Dorne. The index of ideality of correlation: models for flammability of binary liquid mixtures. Chemical Papers, 2020, 74(2): 601-609. https://doi.org/10.1007/s11696-019-00903-w
Alla P. Toropova, Andrey A. Toropov, Danuta Leszczynska, Jerzy Leszczynski, The index of ideality of correlation: models of flash points of ternary mixtures. New Journal of Chemistry, 2020, 44, 4858 - 4868. DOI: 10.1039/D0NJ00121J
Andrey A. Toropov, Alla P. Toropova, Edoardo Carnesecchi, Emilio Benfenati, Jean Lou Dorne, The Index of Ideality of Correlation and the variety of molecular rings as a base to improve model of HIV-1 protease inhibitors activity. Structural Chemistry, (2020) 31: 1441–1448.DOI: 10.1007/s11224-020-01525-9
A. A. Toropov, A. P. Toropova, V. O. Kudyshkin, N. I. Bozorov, S. Sh. Rashidova, Applying of the Monte Carlo technique to build up models of glass transition temperatures of diverse polymers. Structural Chemistry, (2020) 31: 1739-1743. DOI: 10.1007/s11224-020-01588-8
A.A. Toropov, A.P. Toropova, E. Benfenati, “Ideal correlations” for the predictive toxicity to Tetrahymena pyriformis. Toxicology Mechanisms and Methods, 30(8), 2020, 605-610. DOI: 10.1080/15376516.2020.1801928
P.G.R. Achary, A. P. Toropova, A.A. Toropov, Prediction of the self-accelerating decomposition temperature of organic peroxides. Process Safety Progress, 2020; e12189. DOI: 10.1002/prs.12189
Andrey A.Toropov, Alla P.Toropova, Emilio Benfenati, QSAR model for pesticides toxicity to Rainbow Trout based on “ideal correlations”. Aquatic Toxicology 227 (2020) 105589. https://doi.org/10.1016/j.aquatox.2020.105589
A. Worachartcheewan, A. P. Toropova, A. A. Toropov, R. Pratiwi, V. Prachayasittikul, C. Nantasenamat, Interpretable SMILES-based QSAR model of inhibitory activity of sirtuins 1 and 2. Combinatorial Chemistry & High Throughput Screening, Accepted Sep 1, 2020. DOI: 10.2174/1386207323666200902141907
A.P. Toropova, A.A. Toropov, D. Leszczynska, J. Leszczynski, How the CORAL software can be used to select compounds for treatment of neurodegenerative diseases? Toxicology and Applied Pharmacology 408 (2020) 115276. https://doi.org/10.1016/j.taap.2020.115276
A.A. Toropov, A.P. Toropova, G. Selvestrel, D. Baderna, E. Benfenati, Prediction of No Observed Adverse Effect Concentration for Inhalation toxicity: Monte Carlo approach. SAR and QSAR in Environmental Research, 31(12), 2020, 1-12. DOI: 10.1080/1062936X.2020.1841827


M. Marzo, G.J. Lavado, F. Como, A.A. Toropov, A.P. Toropova, D. Baderna, C. Cappelli, A. Lombardo, C. Toma, M. Blázquez Sánchez, E. Benfenati, QSAR models for Biocides. The example of the prediction of Daphnia Magna acute toxicity. SAR and QSAR in Environmental Research, 31:3, 227-243, 2020.
Alla P. Toropova, Andrey A. Toropov, Edoardo Carnesecchi, Emilio Benfenati, Jean Lou Dorne, The using of the Index of Ideality of Correlation (IIC) to improve predictive potential of models of water solubility for pesticides. Environmental Science and Pollution Research (2020) 27: 13339-13347.
Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, QSAR model for pesticides toxicity to Rainbow Trout based on "ideal correlations". Aquatic Toxicology 227 (2020) 105589.
Claudia Ileana Cappelli, Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, Ecosystem ecology: models for acute toxicity of pesticides towards Daphnia magna. Environmental Toxicology and Pharmacology, 80 (2020) 103459.
A.A. Toropov, A.P. Toropova, G. Selvestrel, D. Baderna, E. Benfenati, Prediction of No Observed Adverse Effect Concentration for Inhalation toxicity: Monte Carlo approach. SAR and QSAR in Environmental Research, 31(12), 2020, 1-12. DOI: 10.1080/1062936X.2020.1841827
J.L.C.M. Dorne, J. Richardson, A. Livaniou, E. Carnesecchi, L. Ceriani, R. Baldin, S. Kovarich, M. Pavan, E. Saouter, F. Biganzoli, L. Pasinato, M. Zare Jeddi, T. P. Robinson, G.E.N. Kass, A.K.D. Liem, A.A. Toropov, A.P. Toropova, C. Yang, A. Tarkhov, N. Georgiadis, M.R. Di Nicola, A. Mostrag, H. Verhagen, A. Roncaglioni, E. Benfenati, A. Bassan. EFSA’s OpenFoodTox: An open source toxicological database on chemicals in food and feed and its future developments. Environment International 146 (2021) 106293. https://doi.org/10.1016/j.envint.2020.106293


Dr. Andrey A. Toropov, PhD (CV)
ORCID iD iconorcid.org/0000-0001-6864-6340

Dr. Alla P. Toropova, PhD (CV)
ORCID iD iconorcid.org/0000-0002-4194-9963