Abstract
In this study, we have established two-dimensional quantitative structure propriety relationships (2D-QSPR) model, for a group of 78 molecules based on pyrazine, these molecules were subjected to a 2D-QSPR analyze for their odors thresholds propriety using stepwise Multiple Linear Regression (MLR). The 35 parameters are calculated for the 78 studied compounds using the Gaussian 09W, ChemOffice and ChemSketch softwares. Quantum chemical calculations are used to calculate electronic and quantum chemical descriptors, using the density functional theory (B3LYP/6-31G (d) DFT) methods.The model was used to predict the odors thresholds propriety of the test and training set compounds, and the statistical results exhibited high internal and external consistency as demonstrated by the validation methods.
Highlights
Pyrazine derivatives, a class of heterocyclic nitrogen-containing compounds, can be formed chemically or metabolically through different reaction processes [1, 2], and have been reported as important flavor ingredients and arouse great interest because of their high odor and flavor characteristics [3, 4].The rapid development of computer science in relation to theoretical chemical studies makes it possible to obtain quickly and precisely the physico-chemical parameters of the molecules by calculation
These structural parameters introduce as variables used to construct models of the multidimensional quantitative structure activity / property relationship (QSAR / QSPR) can increase the interpretability and predict the activity / property of new organic compounds using statistical methods that relates these descriptors with a biological activity or a chemical property of molecules [5, 6]
The two-dimensional quantitative structure activity / property relationship (2D-QSAR / QSPR) is one of the most widely used calculation methods for predicting the activities and properties of existing or hypothetical molecules, and this is the goal of several studies [7,8,9]
Summary
A class of heterocyclic nitrogen-containing compounds, can be formed chemically or metabolically through different reaction processes [1, 2], and have been reported as important flavor ingredients and arouse great interest because of their high odor and flavor characteristics [3, 4]. The rapid development of computer science in relation to theoretical chemical studies makes it possible to obtain quickly and precisely the physico-chemical parameters (descriptors) of the molecules by calculation. These structural parameters introduce as variables used to construct models of the multidimensional quantitative structure activity / property relationship (QSAR / QSPR) can increase the interpretability and predict the activity / property of new organic compounds using statistical methods that relates these descriptors with a biological activity or a chemical property of molecules [5, 6]. We propose quantitative models, and we try to interpret the property of the studied compounds from 2D-QSPR study [20, 21]
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