Application of QSPR for prediction of the complexation stabilities of Sm(III) with ionophores applied in lanthanoid sensors

作者：Kiani Anbouhi Roya; Ganjali Mohammad Reza^*; Norouzi Parviz

来源：Journal of Inclusion Phenomena and Macrocyclic Chemistry, 2015, 81(3-4): 441-450.

DOI：10.1007/s10847-014-0472-9

• Samarium-selective electrode
• Complex stability constant
• QSPR
• Genetic algorithms
• Multiple linear regression
• Chemometrics

The increase use of ion sensors in different fields leads to many intensive studies to introduce sensing materials or selectophores in the fabrication of ion-selective electrodes. In this study the complexation stability of samarium ion with different ionophores was efficiently predicted by the QSPR model. Since the selectivity of ionophores can be defined by the stability constants of samarium-ionophore complexes, quantitative structure-property relationship (QSPR) studies on complex stability constants (log K) were carried out. The suitable subset of molecular descriptors was calculated and the genetic algorithm was employed to select those descriptors that resulted in the best-fit models. The multiple linear regression (MLR) method was utilized to construct the linear QSPR models. The best model showed most accurate predictions with the Leave-One-Out cross validation (Q(LOO)(2) = 0.912), Leave-Group-Out cross validation (Q(LGO)(2) = 0.907), external test set and Y-randomization. Also, the applicability domain of the model was analysed by the leverage approach. According to the best of our knowledge, this is the first research on QSPR studies for testing and estimating selectophores in samarium sensors based on complex stability constants. This report could be an experimental guide to find and design of highly selective sensors for Sm(III) ions.

• 出版日期2015-4