title: The Monte Carlo technique as a tool to predict LOAEL.
abstract: Quantitative structure - activity relationships (QSARs) for the Lowest Observed Adverse Effect Level (LOAEL) for a large set of organic compounds (n = 341) are suggested. The molecular structures of these compounds are represented by Simplified Molecular Input-Line Entry Systems (SMILES). A criteria for the estimation quality of split into the "visible" training set (used for developing a model) and "invisible" external validation set is suggested. The correlation between the above criterion and the predictive potential of developed QSAR model (root-mean-square error for "invisible" validation set) has been detected. One-variable models are built up for several different splits into the "visible" training set and "invisible" validation set. The statistical quality of these models is quite good. Mechanistic interpretation and the domain of applicability for these models are defined according to probabilistic point of view. The methodology for defining applicability domain in QSAR modeling with SMILES notation based optimal descriptors is presented.
authors.affiliation: University of Niš, Faculty of Medicine, Department of Chemistry, Niš, Serbia.
authors.forename: Jovana B
authors.initials: JB
authors.lastname: Veselinović
authors.affiliation: University of Niš, Faculty of Medicine, Department of Chemistry, Niš, Serbia.
authors.forename: Aleksandar M
authors.initials: AM
authors.lastname: Veselinović
authors.affiliation: IRCCS- Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy. Electronic address: alla.toropova@marionegri.it.
authors.forename: Alla P
authors.initials: AP
authors.lastname: Toropova
authors.affiliation: IRCCS- Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy.
authors.forename: Andrey A
authors.initials: AA
authors.lastname: Toropov
mesh_terms: D019295:Computational Biology; D009010:Monte Carlo Method; D009930:Organic Chemicals / Q000009:adverse effects* / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D012984:Software
chemical_list: D009930:Organic Chemicals
keywords: Drug toxicity; Ecology; LOAEL; Optimal descriptor; QSAR; SMILES