title: The application of new HARD-descriptor available from the CORAL software to building up NOAEL models.
abstract: Continuous QSAR models have been developed and validated for the prediction of no-observed-adverse-effect (NOAEL) in rats, using training and test sets from the Fraunhofer RepDose® database and EFSA's Chemical Hazards Database: OpenFoodTox. This paper demonstrates that the HARD index, as an integrated attribute of SMILES, improves the prediction power of NOAEL values using the continuous QSAR models and Monte Carlo simulations. The HARD-index is a line of eleven symbols, which represents the presence, or absence of eight chemical elements (nitrogen, oxygen, sulfur, phosphorus, fluorine, chlorine, bromine, and iodine) and different kinds of chemical bonds (double bond, triple bond, and stereo chemical bond). Optimal molecular descriptors calculated with the Monte Carlo technique (maximization of correlation coefficient between the descriptor and endpoint) give satisfactory predictive models for NOAEL. Optimal molecular descriptors calculated in this way with the Monte Carlo technique (maximization of correlation coefficient between the descriptor and endpoint) give amongst the best results available in the literature. The models are built up in accordance with OECD principles.
authors.affiliation: Department of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano, Italy. Electronic address: alla.toropova@marionegri.it.
authors.forename: Alla P
authors.initials: AP
authors.lastname: Toropova
authors.affiliation: Department of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano, Italy.
authors.forename: Andrey A
authors.initials: AA
authors.lastname: Toropov
authors.affiliation: Department of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Marzo
authors.affiliation: Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, Hannover, Germany.
authors.forename: Sylvia E
authors.initials: SE
authors.lastname: Escher
authors.affiliation: Scientific Committee and Emerging Risks Unit, European Food Safety Authority, Via Carlo Magno 1A, 43126 Parma, Italy.
authors.forename: Jean Lou
authors.initials: JL
authors.lastname: Dorne
authors.affiliation: Scientific Committee and Emerging Risks Unit, European Food Safety Authority, Via Carlo Magno 1A, 43126 Parma, Italy.
authors.forename: Nikolaos
authors.initials: N
authors.lastname: Georgiadis
authors.affiliation: Department of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano, Italy.
authors.forename: Emilio
authors.initials: E
authors.lastname: Benfenati
mesh_terms: D000818:Animals; D003198:Computer Simulation; D016208:Databases, Factual; D006219:Halogens / Q000737:chemistry; D008956:Models, Chemical; D009010:Monte Carlo Method; D009584:Nitrogen / Q000737:chemistry; D019055:No-Observed-Adverse-Effect Level; D010100:Oxygen / Q000737:chemistry; D010758:Phosphorus / Q000737:chemistry; D021281:Quantitative Structure-Activity Relationship; D051381:Rats; D012984:Software; D013455:Sulfur / Q000737:chemistry
chemical_list: D006219:Halogens; D010758:Phosphorus; D013455:Sulfur; D009584:Nitrogen; D010100:Oxygen
keywords: CORAL software; Monte Carlo method; NOAEL; OECD principles; QSAR