Abstract
Modified quantitative structure retention relationships (QSRRs) are proposed and applied to describe two retention data sets: A set of 94 metabolites studied by a hydrophilic interaction chromatography system under organic content gradient conditions and a set of tryptophan and its major metabolites analyzed by a reversed-phase chromatographic system under isocratic as well as pH and/or simultaneous pH and organic content gradient conditions. According to the proposed modification, an additional descriptor is added to a conventional QSRR expression, which is the analyte retention time, tR(R), measured under the same elution conditions, but in a second chromatographic column considered as a reference one. The 94 metabolites were studied on an Amide column using a Bare Silica column as a reference. For the second dataset, a Kinetex EVO C18 and a Gemini-NX column were used, where each of them was served as a reference column of the other. We found in all cases a significant improvement of the performance of the QSRR models when the descriptor tR(R) was considered.
Highlights
In metabolomics, the identification of metabolites in biological samples is of a great importance.Liquid chromatography couple to mass spectrometry (LC-MS) is widely used in metabolomics.even if accurate measurements of mass-over-charge ratio, m/z, have been taken, only the molecular type of the metabolite can be determined
We propose a modification of conventional quantitative structure retention relationships (QSRRs) models by adding an extra term, which is the metabolite retention time measured under the same experimental conditions in a second chromatographic column
From the results presented in this table, we conclude that the six-parameter QSRR models describe the retention data on both columns satisfactorily
Summary
The identification of metabolites in biological samples is of a great importance. That happens because there are many analytes that have the same molecular weight For this reason, the use of retention data is of great help for the identification of metabolites in metabolomics and in this direction, quantitative structure-retention relationship (QSRR) models are used more frequently [1]. QSRR models relate chromatographic retention data with molecular descriptors (MDs)—i.e., theoretical or experimental properties of molecules—in order to predict the retention time and to annotate the metabolites. We propose a modification of conventional QSRR models by adding an extra term, which is the metabolite retention time measured under the same experimental conditions in a second (reference) chromatographic column. Where tR (A), tR (R) are the metabolite retention times measured under the same conditions in the chromatographic column under study (A) and in the reference column (R), MD1 , . The first dataset consisted of 94 metabolite standards and the second one consisted of eight solutes, which were tryptophan and its major metabolites
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