QSRR analysis in characterization of some benzimidazole derivatives

Authors

  • Milica Karadžić University of Novi Sad, Faculty of Technology
  • Sanja Podunavac-Kuzmanović University of Novi Sad, Faculty of Technology
  • Lidija Jevrić University of Novi Sad, Faculty of Technology
  • Strahinja Kovačević University of Novi Sad, Faculty of Technology

DOI:

https://doi.org/10.17344/acsi.2014.1134

Keywords:

benzimidazole, multiple linear regression, principal component analysis, hierarchical cluster analysis

Abstract

In this paper, quantitative structure-retention relationship study has been applied in order to correlate obtained retention parameter RM0 and two groups of molecular descriptors, for eleven investigated benzimidazole derivatives. Principal component analysis (PCA), followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR), was applied in order to identify the most important molecular descriptors. Mathematical models were established and the best models were further validated by leave-on-out (LOO) technique as well as by the calculation of the statistical parameters. Statistically significant models were established.

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Published

17.11.2015

Issue

Vol. 62 No. 4 (2015)

Section

Applied chemistry

License

Except where otherwise noted, articles in this journal are published under the Creative Commons Attribution 4.0 International License