





Modeling of Log Kow of a Series of PAHs using Computational Chemistry
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The importance of Chemometrics Methods in Modeling (in QSAR analysis) of the mathematical modelβs study of large datasets of molecules with huge numbers of physicochemical and structural parameters quantitative structure-Toxicity relationship (QSTR) are mainly based on multiple regression analysis in QSAR analysis The study of Least Square in deriving QSTR models for datasets of Quantitative Structure-Toxicity relationship on Log k ow (Octanol-water partition coefficient) for 16 Hydrocarbons compounds has been using the software Hyperchem 6.3 for computing descriptors and MINITAB 16 for data modeling. A three -descriptors model [two electronics moleculesβ descriptors (QSER descriptor), HOMO (is Highest occupied molecular orbital) and LUMO (Lowest unoccupied molecular orbital), one QSAR descriptor πΈπ» (Hydration Energy) by Least Squares with correlation coefficient r=0.868, S=0.635, R 2 = 75.4%, R 2 ajd=73.7% and Durbin-Watson statistic =1.85277 and graphical analysis by diagram of goodness of fit and line plot. The results statistical of new model after removing the aberrant compounds (Toxicity compounds) shows high Coefficient of correlation r=0.9581, S=0.4316, determination coefficient R 2 =91. 8%, ajustemed R 2 ajd = 89.3%, Durbin-Watson statistic D=2.373, Three explanatory Variable model selected is robust and has good fitness. Two influential compounds detected and important the model and absence aberant compounds of the studied sample.
Keywords
Hydrocarbons (PAHs), toxicity πΏππ πππ€,HOMO, LUMO,πΈπ»,Multiple linearregression, Aberant compounds.
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