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Because of the importance of amino acids as the basic tiles of protein and their application in drug and food industries, there is a lot of interest in their separation and identification using simple and inexpensive approaches. Application of predictive models for determination of the behavior of AAs can reduce trial-and-error experiments. Here, the retardation factor (RF) of 21 protein AAs were studied using the quantitative structure-retardation factor (QSRR) model. The RF of the AAs in ethanol–sodium azide solution as the mobile phase of reversed phase thin layer chromatography (RP-TLC) was correlated with the AAs structural properties. The suggested QSRR indicated excellent fitting and prediction ability (R2train=0.95 and R2test=0.94). Furthermore, other statistical tests such as y-scrambling, cross validation and Williams plot confirmed the stability, absence of chance and the suitable applicability domain, respectively. It was shown that the sum of geometrical distances between oxygen and nitrogen atoms in AA molecule is an important factor in RF values of AAs in the ethanol–sodium azide.

Prediction of retardation factor of protein amino acids in reversed phase TLC and ethanol-sodium azide solution as the mobile phase using QSRR