A simple 2D-QSPR model for the prediction of Setschenow constants of organic compounds

Authors

  • Qi Xu College of Materials Science & Engineering, College of Textile Science & Engineering, Wuhan Textile University, 430200, Wuhan
  • Lingling Fan College of Materials Science & Engineering, College of Textile Science & Engineering, Wuhan Textile University, 430200, Wuhan
  • Jie Xu College of Materials Science & Engineering, College of Textile Science & Engineering, Wuhan Textile University, 430200, Wuhan

DOI:

https://doi.org/10.20450/mjcce.2016.848

Keywords:

QSPR, Setschenow constants, 2D descriptor, multilinear regression analysis

Abstract

A quantitative structure-property relationship (QSPR) analysis of the Setschenow constants (Ksalt) of organic compounds in a sodium chloride solution was carried out using only two-dimensional (2D) descriptors as input parameters. The whole set of 101 compounds was split into a training set of 71 compounds and a validation set of 30 compounds by means of the Kennard and Stones algorithm. A general four-parameter equation, with correlation coefficient (R) of 0.887 and standard error of estimation (s) of 0.031, was obtained by stepwise multilinear regression analysis (MLRA) on the training set. The reliability and robustness of the present model was verified with leave-one-out cross-validation, randomization tests, and the external validation set. All of the descriptors contained in this model are calculated directly from the molecular 2D structures; thus, this model can be used to easily predict the Ksalt of other compounds not involved in the present dataset.

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Published

2016-04-18

How to Cite

Xu, Q., Fan, L., & Xu, J. (2016). A simple 2D-QSPR model for the prediction of Setschenow constants of organic compounds. Macedonian Journal of Chemistry and Chemical Engineering, 35(1), 53–62. https://doi.org/10.20450/mjcce.2016.848

Issue

Vol. 35 No. 1 (2016)

Section

Theoretical Chemistry

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