QSPR/QSAR analyses by means of the CORAL software: Results, challenges, perspectives
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Jerzy Leszczynski | Andrey A. Toropov | Alla P. Toropova | Angelo Carotti | Pablo R. Duchowicz | Orazio Nicolotti | Danuta Leszczynska | Emilio Benfenati | Karel Nesmerak | Eduardo A. Castro | Bakhtiyor Rasulev | Aleksandar M. Veselinović | Jovana B. Veselinović | Daniel E. Bacelo | E. Castro | E. Benfenati | J. Leszczynski | D. Leszczyńska | O. Nicolotti | A. Toropova | A. Toropov | P. Duchowicz | B. Rasulev | A. Veselinović | J. Veselinovic | A. Carotti | K. Nesměrák | D. E. Bacelo
[1] Jerzy Leszczynski,et al. CORAL: QSPR model of water solubility based on local and global SMILES attributes. , 2013, Chemosphere.
[2] Andrey A Toropov,et al. Optimal descriptor as a translator of eclectic information into the prediction of membrane damage by means of various TiO(2) nanoparticles. , 2013, Chemosphere.
[3] Jerzy Leszczynski,et al. QSAR modeling of measured binding affinity for fullerene-based HIV-1 PR inhibitors by CORAL , 2010 .
[4] Kunal Roy,et al. QSAR modeling of toxicity of diverse organic chemicals to Daphnia magna using 2D and 3D descriptors. , 2010, Journal of hazardous materials.
[5] Emilio Benfenati,et al. QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations. , 2010, European journal of medicinal chemistry.
[6] Jerzy Leszczynski,et al. CORAL: QSPR models for solubility of [C60] and [C70] fullerene derivatives , 2011, Molecular Diversity.
[7] A. Monge,et al. New 3-[4-(aryl)piperazin-1-yl]-1-(benzo[b]thiophen-3-yl)propane derivatives with dual action at 5-HT1A serotonin receptors and serotonin transporter as a new class of antidepressants. , 2001, European journal of medicinal chemistry.
[8] Peter C. Jurs,et al. Prediction of Aqueous Solubility of Organic Compounds , 1994 .
[9] Mihai V. Putz,et al. Alert-QSAR. Implications for Electrophilic Theory of Chemical Carcinogenesis , 2011, International journal of molecular sciences.
[10] Paul J Hergenrother,et al. The complex role of the triphenylmethyl motif in anticancer compounds. , 2008, Journal of the American Chemical Society.
[11] Ivan Gutman. Topological analysis of Eigenvalues of the adjacency matrices in graph theory: A difficulty with the concept of internal connectivity , 1988 .
[12] Ovidiu Ivanciuc,et al. Quantitative Structure—Property Relationship Study of Normal Boiling Points for Halogen-/ Oxygen-/ Sulfur-Containing Organic Compounds Using the CODESSA Program , 1998 .
[13] N. Trinajstic,et al. The Zagreb Indices 30 Years After , 2003 .
[14] T. Öberg. A QSAR for the hydroxyl radical reaction rate constant: validation, domain of application, and prediction , 2005 .
[15] Andrey A. Toropov,et al. QSAR modeling of toxicity on optimization of correlation weights of Morgan extended connectivity , 2002 .
[16] Jerzy Leszczynski,et al. Comprehension of drug toxicity: Software and databases , 2014, Comput. Biol. Medicine.
[17] G. Melagraki,et al. QSAR study on para-substituted aromatic sulfonamides as carbonic anhydrase II inhibitors using topological information indices. , 2006, Bioorganic & medicinal chemistry.
[18] T. Puzyn,et al. Computational Techniques Application in Environmental Exposure Assessment , 2015 .
[19] Jerzy Leszczynski,et al. QSAR analysis of 1,4-dihydro-4-oxo-1-(2-thiazolyl)-1,8-naphthyridines exhibiting anticancer activity by optimal SMILES-based descriptors , 2010 .
[20] K R Scott,et al. Enhancing the permeation of marker compounds and enaminone anticonvulsants across Caco-2 monolayers by modulating tight junctions using zonula occludens toxin. , 2001, European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V.
[21] Kunal Roy,et al. Comparative QSARs for antimalarial endochins: Importance of descriptor-thinning and noise reduction prior to feature selection , 2011 .
[22] Hagai Ginsburg,et al. Arylpiperazines displaying preferential potency against chloroquine-resistant strains of the malaria parasite Plasmodium falciparum. , 2005, Biochemical pharmacology.
[23] Emilio Benfenati,et al. The definition of the molecular structure for potential anti-malaria agents by the Monte Carlo method , 2013, Structural Chemistry.
[24] A. Balaban. Highly discriminating distance-based topological index , 1982 .
[25] Emin Sarıpınar,et al. Application of electron conformational–genetic algorithm approach to 1,4-dihydropyridines as calcium channel antagonists: pharmacophore identification and bioactivity prediction , 2011, Journal of Molecular Modeling.
[26] M. Teijeira,et al. GETAWAY descriptors to predicting A(2A) adenosine receptors agonists. , 2005, European journal of medicinal chemistry.
[27] Milan Randic,et al. Optimal Molecular Descriptors Based on Weighted Path Numbers , 1999, J. Chem. Inf. Comput. Sci..
[28] Pablo R Duchowicz,et al. QSAR study for carcinogenicity in a large set of organic compounds. , 2012, Current drug safety.
[29] Milan Randic,et al. A New Descriptor for Structure-Property and Structure-Activity Correlations , 2001, J. Chem. Inf. Comput. Sci..
[30] Emilio Benfenati,et al. QSAR modeling of endpoints for peptides which is based on representation of the molecular structure by a sequence of amino acids , 2012, Structural Chemistry.
[31] Jouko Yliruusi,et al. Prediction of physicochemical properties based on neural network modelling. , 2003, Advanced drug delivery reviews.
[32] Albert J. Leo,et al. Quantitative Structure-Activity Relationships in Drug-Design , 1975 .
[33] A A Toropov,et al. Aconitum and Delphinium Diterpenoid Alkaloids of Local Anesthetic Activity: Comparative QSAR Analysis Based on GA-MLRA/PLS and Optimal Descriptors Approach , 2014, Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews.
[34] J. Poupaert,et al. Anticonvulsant activity and interactions with neuronal voltage-dependent sodium channel of analogues of ameltolide. , 1998, Journal of medicinal chemistry.
[35] P. Achary,et al. Simplified molecular input line entry system-based optimal descriptors: QSAR modelling for voltage-gated potassium channel subunit Kv7.2 , 2014, SAR and QSAR in environmental research.
[36] David Weininger,et al. SMILES. 2. Algorithm for generation of unique SMILES notation , 1989, J. Chem. Inf. Comput. Sci..
[37] M. Randic. Characterization of molecular branching , 1975 .
[38] Giuseppina C. Gini,et al. CORAL: Quantitative structure–activity relationship models for estimating toxicity of organic compounds in rats , 2011, J. Comput. Chem..
[39] Vilma Edite Fonseca Heinzen,et al. Semi-empirical topological index: development of QSPR/QSRR and optimization for alkylbenzenes. , 2008, Talanta.
[40] Kunal Roy,et al. Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment , 2015 .
[41] H. Wiener. Structural determination of paraffin boiling points. , 1947, Journal of the American Chemical Society.
[42] Apilak Worachartcheewan,et al. QSAR Study of H1N1 Neuraminidase Inhibitors from Influenza a Virus , 2014 .
[43] Marjan Vracko,et al. A Study of Structure-Carcinogenic Potency Relationship with Artificial Neural Networks. The Using of Descriptors Related to Geometrical and Electronic Structures , 1997, J. Chem. Inf. Comput. Sci..
[44] K R Scott,et al. Synthesis and anticonvulsant activity of enaminones. Part 7. Synthesis and anticonvulsant evaluation of ethyl 4-[(substituted phenyl)amino]-6-methyl-2-oxocyclohex-3-ene-1-carboxylates and their corresponding 5-methylcyclohex-2-enone derivatives. , 2003, European journal of medicinal chemistry.
[45] Komal Sharma,et al. Quantitative structure pharmacokinetic relationship modeling of Cephalosporins : Elimination half-life , 2016 .
[46] Jerzy Leszczynski,et al. CORAL: Models of toxicity of binary mixtures , 2012 .
[47] Bahram Hemmateenejad,et al. Optimal QSAR analysis of the carcinogenic activity of drugs by correlation ranking and genetic algorithm‐based PCR , 2004 .
[48] A. Toropova,et al. Prediction of heteroaromatic amine mutagenicity by means of correlation weighting of atomic orbital graphs of local invariants , 2001 .
[49] Martin Egginger,et al. Material Solubility‐Photovoltaic Performance Relationship in the Design of Novel Fullerene Derivatives for Bulk Heterojunction Solar Cells , 2009 .
[50] M. Natália D. S. Cordeiro,et al. QSAR-Based Studies of Nanomaterials in the Environment , 2017 .
[51] Andrey A Toropov,et al. SMILES-based QSAR model for arylpiperazines as high-affinity 5-HT(1A) receptor ligands using CORAL. , 2013, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.
[52] Karel Nesmerak,et al. Quantitative structure–property relationships of new benzoxazines and their electrooxidation as a model of metabolic degradation , 2005 .
[53] N. Trinajstic,et al. Information theory, distance matrix, and molecular branching , 1977 .
[54] Karel Nesmerak,et al. SMILES-based quantitative structure–retention relationships for RP HPLC of 1-phenyl-5-benzylsulfanyltetrazoles , 2013, Structural Chemistry.
[55] S. Kombian,et al. Anticonvulsant evaluation and mechanism of action of benzylamino enaminones. , 2006, Bioorganic & medicinal chemistry.
[56] Haralambos Sarimveis,et al. Prediction of intrinsic viscosity in polymer-solvent combinations using a QSPR model , 2006 .
[57] Mark T D Cronin,et al. Comparative assessment of methods to develop QSARs for the prediction of the toxicity of phenols to Tetrahymena pyriformis. , 2002, Chemosphere.
[58] K R Scott,et al. Influence of multidrug resistance (MDR) proteins at the blood-brain barrier on the transport and brain distribution of enaminone anticonvulsants. , 2001, Journal of pharmaceutical sciences.
[59] Maykel Pérez González,et al. QSAR modeling of the rodent carcinogenicity of nitrocompounds. , 2008, Bioorganic & medicinal chemistry.
[60] Andrey A Toropov,et al. SMILES‐Based QSAR Models for the Calcium Channel‐Antagonistic Effect of 1,4‐Dihydropyridines , 2013, Archiv der Pharmazie.
[61] E Benfenati,et al. SMILES-based optimal descriptors: QSAR modeling of carcinogenicity by balance of correlations with ideal slopes. , 2010, European journal of medicinal chemistry.
[62] Vilma Edite Fonseca Heinzen,et al. Semi-empirical topological index: a tool for QSPR/QSAR studies , 2005, Journal of molecular modeling.
[63] L. Hammett,et al. Some Relations between Reaction Rates and Equilibrium Constants. , 1935 .
[64] Serdar Durdagi,et al. 3D QSAR CoMFA/CoMSIA, molecular docking and molecular dynamics studies of fullerene-based HIV-1 PR inhibitors. , 2008, Bioorganic & medicinal chemistry letters.
[65] K R Scott,et al. Synthesis and anticonvulsant activity of enaminones. 4. Investigations on isoxazole derivatives. , 2002, European journal of medicinal chemistry.
[66] Danail Bonchev,et al. Topological order in molecules 1. Molecular branching revisited , 1995 .
[67] Jerzy Leszczynski,et al. Prediction of rate constants for radical degradation of aromatic pollutants in water matrix: a QSAR study. , 2009, Chemosphere.
[68] E. B. Melo,et al. A new quantitative structure-property relationship model to predict bioconcentration factors of polychlorinated biphenyls (PCBs) in fishes using E-state index and topological descriptors. , 2012 .
[69] Kunal Roy,et al. On Selection of Training and Test Sets for the Development of Predictive QSAR models , 2006 .
[70] H. Wiener. Vapor pressure-temperature relationships among the branched paraffin hydrocarbons. , 1948, The Journal of physical and colloid chemistry.
[71] Andrey A. Toropov,et al. Maximum Topological Distances Based Indices As Molecular Descriptors for QSPR: 2 - Application to Aromatic Hydrocarbons , 2000, Comput. Chem..
[72] Roberto Todeschini,et al. Comparison of Different Approaches to Define the Applicability Domain of QSAR Models , 2012, Molecules.
[73] Jerzy Leszczynski,et al. CORAL: QSAR modeling of toxicity of organic chemicals towards Daphnia magna , 2012 .
[74] Zhirong Wang,et al. Quantitative structure-property relationship studies for predicting flash points of alkanes using group bond contribution method with back-propagation neural network. , 2007, Journal of hazardous materials.
[75] Jerzy Leszczynski,et al. SMILES‐based optimal descriptors: QSAR analysis of fullerene‐based HIV‐1 PR inhibitors by means of balance of correlations , 2009, J. Comput. Chem..
[76] Alexander Golbraikh,et al. Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection , 2002, J. Comput. Aided Mol. Des..
[77] Alan Talevi,et al. An integrated drug development approach applying topological descriptors. , 2012, Current computer-aided drug design.
[78] David Weininger,et al. SMILES, 3. DEPICT. Graphical depiction of chemical structures , 1990, J. Chem. Inf. Comput. Sci..
[79] Naomi L Kruhlak,et al. Progress in QSAR toxicity screening of pharmaceutical impurities and other FDA regulated products. , 2007, Advanced drug delivery reviews.
[80] Boris Galabov,et al. QSAR analysis of 1,4-dihydro-4-oxo-1-(2-thiazolyl)-1,8-naphthyridines with anticancer activity. , 2007, European journal of medicinal chemistry.
[81] Maykel Pérez González,et al. A new search algorithm for QSPR/QSAR theories: Normal boiling points of some organic molecules , 2005 .
[82] Eduardo A. Castro,et al. QSAR Study and Molecular Design of Open-Chain Enaminones as Anticonvulsant Agents , 2011, International journal of molecular sciences.
[83] Eduardo A. Castro,et al. QSAR on aryl-piperazine derivatives with activity on malaria , 2012 .
[84] Pablo R Duchowicz,et al. A comparative QSAR on 1,2,5-thiadiazolidin-3-one 1,1-dioxide compounds as selective inhibitors of human serine proteinases. , 2011, Journal of molecular graphics & modelling.
[85] Shikha Gupta,et al. Nano-QSAR modeling for predicting biological activity of diverse nanomaterials , 2014 .
[86] Ivan Gutman,et al. WIENER-TYPE TOPOLOGICAL INDICES , 1998 .
[87] P. Roy,et al. On Some Aspects of Variable Selection for Partial Least Squares Regression Models , 2008 .
[88] Kunal Roy,et al. First report on development of quantitative interspecies structure-carcinogenicity relationship models and exploring discriminatory features for rodent carcinogenicity of diverse organic chemicals using OECD guidelines. , 2012, Chemosphere.
[89] A. Bianucci,et al. Prediction of hERG potassium channel affinity by the CODESSA approach. , 2006, Bioorganic & medicinal chemistry.
[90] A. Monge,et al. New 1-aryl-3-(4-arylpiperazin-1-yl)propane derivatives, with dual action at 5-HT1A serotonin receptors and serotonin transporter, as a new class of antidepressants. , 2001, Journal of medicinal chemistry.
[91] Eduardo A. Castro,et al. QSAR treatment on a new class of triphenylmethyl-containing compounds as potent anticancer agents , 2011 .
[92] M. Randic,et al. The connectivity index 25 years after. , 2001, Journal of molecular graphics & modelling.
[93] Igor V. Tetko,et al. Estimation of Aqueous Solubility of Chemical Compounds Using E-State Indices , 2001, J. Chem. Inf. Comput. Sci..
[94] Andrey A Toropov,et al. SMILES-based quantitative structure-property relationships for half-wave potential of N-benzylsalicylthioamides. , 2013, European journal of medicinal chemistry.
[95] Andrey A Toropov,et al. CORAL software: prediction of carcinogenicity of drugs by means of the Monte Carlo method. , 2014, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.
[96] Jarmo Huuskonen,et al. Estimation of Aqueous Solubility for a Diverse Set of Organic Compounds Based on Molecular Topology , 2000, J. Chem. Inf. Comput. Sci..
[97] Li Zhang,et al. Computer-based QSARs for predicting mixture toxicity of benzene and its derivatives. , 2007, Chemosphere.
[98] Giuseppina C. Gini,et al. Coral: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical , 2012, J. Comput. Chem..
[99] Andrey A. Toropov,et al. QSPR modeling of the half-wave potentials of benzoxazines by optimal descriptors calculated with the SMILES , 2006, Comput. Biol. Chem..
[100] Biye Ren. Atom-type-based AI topological descriptors for quantitative structure–retention index correlations of aldehydes and ketones , 2003 .
[101] Ivan Gutman. Permanents of Adjacency Matrices and Their Dependence on Molecular Structure , 1998 .
[102] Paola Gramatica,et al. Metabolic biotransformation half-lives in fish: QSAR modeling and consensus analysis. , 2014, The Science of the total environment.
[103] Milan Randic,et al. The Variable Connectivity Index 1f versus the Traditional Molecular Descriptors: A Comparative Study of 1f Against Descriptors of CODESSA , 2001, J. Chem. Inf. Comput. Sci..
[104] David Weininger,et al. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules , 1988, J. Chem. Inf. Comput. Sci..
[105] M. Randic,et al. Graphs with the Same Detour Matrix , 1998 .
[106] Kunal Roy,et al. Development and validation of a robust QSAR model for prediction of carcinogenicity of drugs. , 2011, Indian journal of biochemistry & biophysics.
[107] David S. Wishart,et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets , 2007, Nucleic Acids Res..
[108] Paul J Hergenrother,et al. Triphenylmethylamides (TPMAs): Structure-activity relationship of compounds that induce apoptosis in melanoma cells. , 2008, Bioorganic & medicinal chemistry letters.
[109] Jerzy Leszczynski,et al. QSAR modeling of acute toxicity by balance of correlations. , 2008, Bioorganic & medicinal chemistry.