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Updated: Apr 27, 2026

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
Published on: September 2, 2020
[Topological models of retention index of thin-layer chromatogram for chiral organic acids]
Abstract:
On the basis of Kier's molecular connectivity indices and conjugated matrix, novel molecular connectivity indices ((m) G(t)(v)) were defined and calculated for 18 chiral hydroxyl acids and amino acids. The chiral connectivity indices ((m)C(t)(v)) were introduced by extending (m)G(t)(v): (m)C(t)(v) = (m)G(t)(v) x w(j), where w(j) is the chiral index. The quantitative structure-retention index relationship (QSRR) between the retention index (R(M)) of thin-layer chromatogram for the chiral organic acids and (m)C(t)(v) was studied by multivariate statistical regression. By leaps-and-bounds regression analysis, the best four-parameter QSRR model was set up, and the traditional correlation coefficient (R2) and the cross-validation correlation coefficient (Q2) of leave-one-out (LOO) were 0.973 and 0.950, respectively. The results demonstrated that the model was highly reliable and had good predictive ability from the point of view of statistics. From the four parameters (0C(p)(v), 2C(p)(v), C(ch),(v), 5C(p)(v)) of the model, it is known that the dominant influence factors of the retention index were the molecular structure characteristics of two-dimensional and the space factors: the chiral characteristics, the flexibility and the puckered degree of molecules for the chiral organic acids. The results showed that the new parameter mC(t)(v) had good rationality and efficiency for the retention indices of the chiral organic acids. Therefore, an effective method was provided to predict the retention indices of the chiral organic acids.
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