558 research outputs found
Co-evolutions of correlations for QSAR of toxicity of organometallic and inorganic substances: An unexpected good prediction based on a model that seems untrustworthy
No full textSimplified Molecular Input-Line Entry System and International Chemical Identifier in the QSAR Analysis of Styrylquinoline Derivatives as HIV-1 Integrase Inhibitors
No full textQSAR Models for Toxicity of Organic Substances to Daphnia magna Built up by Using the CORAL Freeware
No full textCORAL (CORrelations And Logic, ) is a freeware available on the Internet. This freeware is designed to build up quantitative structure property/activity relationships. The molecular structure for CORAL should be represented by the simplified molecular input line entry system (SMILES). Optimal descriptors calculated with SMILES are a mathematical function of the presence or absence of SMILES elements. The essence of this approach is the calculation of correlation weights for each element or combination of the elements by the Monte Carlo method. These coefficients serve to calculate the descriptors correlated with the endpoint for the training set, hoping that this correlation will also hold for the external test set. These descriptors can be improved by taking into account global physicochemical situations in molecules. An example of the physicochemical situation is the presence of oxygen and nitrogen. One can calculate these situations with SMILES and represent them by combining 0 (absence) and 1 (presence). The involving in the modelling of correlation weights of aforementioned physicochemical situations gave improvement in accuracy of models of toxicity to Daphnia magna for test set: ntest = 75, r2 = 0.7322, r2pred = 0.7193, r2m = 0.6549 (without correlation weights of the physicochemical situations); and ntest = 75, r2 = 0.7897, r2pred = 0.7790, r2m = 0.6850 (with aforementioned correlation weights of physicochemical situations)
A new bioconcentration factor model based on SMILES and indices of presence of atoms
No full textIndices of the presence of atoms (IPA) encode the presence or absence of atoms, such as nitrogen, oxygen, sulphur, phosphorus, fluorine, chlorine, and bromine in a molecule. They are calculated with the simplified molecular input line entry system (SMILES). Using the Monte Carlo method for correlation
weights of these indices, one can improve the predictive ability of optimal SMILES-based descriptors in quantitative structure activity relationships (QSAR) for bioconcentration factor
CORAL: Building up the model for bioconcentration factor and defining it's applicability domain
No full textRigid and flexible topological indices: variety of the representations of the molecular structures.
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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
No full textChemical Physics Letter
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