QSPR Analysis of the Physicochemical Properties for Phthalic Acid Esters

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Based on quantitative structure-property relationship(QSPR)of organic compounds,the molecular connectivity indices of 21 phthalic acid ester compounds were extracted.Relationship between the physicochemical properties(n-octanol/air partition coefficient,vapor pressure,water solubility)and the molecular connectivity indices of phthalic acid ester compounds have been established by multiple linear regression(MLR)method.The results showed that the zero-order valence connectivity index(0Xυ)is the topology parameter which affects octanol/water partition coefficient and water solubility,and the topology parameter which affects vapor pressure is the first-order connectivity index(1X).This indicated to a certain extent that the molecular connectivity indices can be well used to express the quantitative relationship between the physicochemical properties and structure descriptions of phthalic acid ester compounds.The models constructed have good robustness and highly predictive capability. Based on quantitative structure-property relationship (QSPR) of organic compounds, the molecular connectivity indices of 21 phthalic acid ester compounds were extracted. Relationships between the physicochemical properties (n-octanol / air partition coefficient, vapor pressure, water solubility) and the molecular connectivity indices of phthalic acid ester compounds have been established by multiple linear regression (MLR) method. The results showed that the zero-order valence connectivity index (0Xυ) is the topology parameter which affects octanol / water partition coefficient and water solubility, and the topology parameter which affects vapor pressure is the first-order connectivity index (1X) .This indicated to a certain extent that the molecular connectivity indices can be well used to express the quantitative relationship between the physicochemical properties and structure descriptions of phthalic acid ester compounds. The models constructed have good robustness and highly predictive capability.
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