Literature DB >> 35031996

A novel model for prediction of stability constants of the thiosemicarbazone ligands with different types of toxic heavy metal ions using structural parameters and multivariate linear regression method.

Mohammad Hossein Keshavarz1, Zeinab Shirazi2, Asileh Barghahi2, Ali Mousaviazar2, Abbas Zali2.   

Abstract

A novel model is presented for reliable estimation of the stability constants of the thiosemicarbazone ligands with different types of toxic heavy metal ions (log β11) in an aqueous solution, which has wide usage in environmental safety and ecotoxicology applications. The biggest reported data of log β11 for 120 metalthiosemicarbazone complexes are used for deriving and testing the novel model. In contrast to available methods where they need the two-dimensional (2D) and three-dimensional (3D) complex molecular descriptors as well as expert users and computer codes, the novel correlation uses four additive and two non-additive structural parameters of thiosemicarbazone ligands. The calculated results of the novel correlation are compared with the outputs of the genetic algorithm with multivariate linear regression method (GA-MLR) as one of the best existing methods, which requires seven complex descriptors. The estimated results for 78 of training as well as 42 of two different test sets were established by external and internal validations. The values of statistical parameters comprising average deviation, average absolute deviation, average absolute relative deviation, absolute maximum deviation, and the coefficient of determination for 73 data of training set of New model/GA-MLR are 0.04/ - 0.25, 1.06/1.31, 14.4/18.7, 3.18/7.92, and 0.830/0.652, respectively. Thus, the predicted results of the new model are worthy as compared to the complex GA-MLR model. Moreover, assessments of various statistical parameters confirm that the new model provides great reliability, goodness-of-fit, accuracy, and precision.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Additive structural parameter; Correlation; Multivariate linear regression method; Non-additive structural parameter; Stability constant; Thiosemicarbazone ligand; Toxic heavy metal ion

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Year:  2022        PMID: 35031996     DOI: 10.1007/s11356-021-17714-w

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  1 in total

1.  A novel approach for assessment of antitrypanosomal activity of sesquiterpene lactones through additive and non-additive molecular structure parameters.

Authors:  Mohammad Hossein Keshavarz; Zeinab Shirazi; Faezeh Sayehvand
Journal:  Mol Divers       Date:  2022-07-17       Impact factor: 3.364

  1 in total

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