Use of Topological Indices of Organic Sulfur Compounds in Quantitative Structure‐Retention Relationship Study

Abstract

Structure-gas chromatographic retention index models were developed for some organic sulfur compounds at four different temperatures (60, 80, 100 and 120 8C) using only topological descriptors. At first, regression models were generated for each temperature separately with high values of multiple correlation coefficient and Fisher-ratio statistics. The results of cross validation test using leave-one-out (Q 2 ! 0.956) and leave-two-out (Q 2 ! 0.953) methods showed good predictive ability of the models developed. Then, a single combined quantitative structure-retention relationship model, added temperature as a parameter, was also developed for all the temperatures, showing good statistical parameters (R ¼ 0.991 and F ¼ 728.474). The stability and validity of the combined model were verified by both internal (Q 2 > 0.970) and external validation (Q 2 prediction set ¼ 0.993) techniques. The results of the study indicated the efficiency of the classical topological descriptors in simultaneous prediction of retention index values of sulfur compounds at different temperatures. The topological descriptors well covered the molecular properties known to be relevant for gas chromatographic retention data, such as molecular size and degree of branching.

Quantitative Structure Vasodilatory Activity Relationship – Synthesis and “In Silico” and “In Vitro” Evaluation of Resveratrol‐Coumarin Hybrids

“…One of the most widely used techniques is the generation of molecular descriptors that allow statistical relationships to be established between pharmacological activity and molecular structure [6 -8]. A number of these models have been widely used for the development of new compounds with activities such as anti-inflamatory [9], antihypertensive [10], anticancer [11,12], and anti-HIV [13,14] as well as to predict other chemical or physicochemical molecular properties [15,16].…”