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EN
Quantitative structure-property relationship (QSPR) modeling is a powerful approach for predicting environmental behavior of organic pollutants with their structure descriptors. This study reports an optimal QSPR model for estimating logarithmic n-octanol/water partition coefficients (log K OW) of polycyclic aromatic hydrocarbons (PAHs). Quantum chemical descriptors computed with density functional theory at B3LYP/6-31G(d) level and partial least squares (PLS) analysis with optimizing procedure were used for generating QSPR models for log K OW of PAHs. The squared correlation coefficient (R 2) of the optimal model was 0.990, and the results of crossvalidation test (Q 2cum=0.976) showed this optimal model had high fitting precision and good predictability. The log K OW values predicted by the optimal model are very close to those observed. The PLS analysis indicated that PAHs with larger electronic spatial extent and lower total energy values tend to be more hydrophobic and lipophilic. [...]
EN
CORAL software (http:/www.insilico.eu/coral) has been used to build up quantitative structure-biodegradation relationships (QSPR). The normalized degradation percentage has been used as the measure of biodegradation (for diverse organic compounds, n=445). Six random splits into sub-training, calibration, and test sets were examined. For each split the QSPR one-variable linear regression model based on the SMILES-based optimal descriptors has been built up. The average values of numbers of compounds and the correlation coefficients (r2) between experimental and calculated biodegradability values of these six models for the test sets are n=88.2±11.7 and r2=0.728±0.05. These six models were further tested against a set of chemicals (n=285) for which only categorical values (biodegradable or not) were available. Thus we also evaluated the use of the model as a classifier. The average values of the sensitivity, specificity, and accuracy were 0.811±0.019, 0.795±0.024, and 0.803±0.008, respectively. [...]
Open Chemistry
|
2005
|
vol. 3
|
issue 4
585-591
EN
A QSPR study is presented for acidities of thirteen N-methoxy-polynitroaniline derivatives. Hammett σ values are known for meta and para substituents, and in the present study values are introduced for ortho-substituents in these N-methoxy-polynitroaniline derivatives. Hammett σ values for ortho-substituents in these N-methoxy-polynitroaniline derivatives were obtained by multiplying para values with 0.65.
EN
Usually, QSPR is not used to model organometallic compounds. We have modeled the octanol/water partition coefficient for organometallic compounds of Na, K, Ca, Cu, Fe, Zn, Ni, As, and Hg by optimal descriptors calculated with simplified molecular input line entry system (SMILES) notations. The best model is characterized by the following statistics: n=54, r2=0.9807, s=0.677, F=2636 (training set); n=26, r2=0.9693, s=0.969, F=759 (test set). Empirical criteria for the definition of the applicability domain for these models are discussed. [...]
EN
Starting from N-hydroxyphthalimide 1 and the reactive fluoro- or chloro-nitroaryl derivatives 2, 3 and 4a-e (2-chloro-3,5-dinitropyridine; 3, NBD-chloride; 4a, 1-fluoro-2,4-dinitrobenzene; 4b, picryl chloride; 4c, 4-chloro-3,5-dinitrobenzotrifluoride; 4d, 2-chloro-3,5- dinitrobenzotrifluoride; 4e, 4-chloro-3,5-dinitrobenzoic acid) the corresponding N-(2-nitroaryloxy)-phthalimide derivatives 5a-e, or 6 and 7 were obtained and characterized by IR, UV-Vis 1H-NMR and 13C-NMR spectroscopy. The TLC behavior and the hydrophobicity of these derivatives have been experimentally evaluated by RM0 parameters (using RP-TLC). The experimental RM0 parameters were compared with the calculated partition coefficient, log P. A QSPR study was also performed to establish possible correlations between the structure and physical properties (λmax and RM0) of compounds 5a-e, 6, and 7. [...]
EN
Predictive quantitative structure - property relationships (QSPR) have been established for normal boiling points and octanol/water partition coefficient for acyclic and cyclic hydrocarbons using optimal descriptors calculated with simplified molecular input line entry system (SMILES). The probabilistic criteria for a rational definition of the domain of applicability of these models are discussed. [...]
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