title: Multivariate analysis of chromatographic retention data as a supplementary means for grouping structurally related compounds.
abstract: In the present study a series of 45 metabolite standards belonging to four chemically similar metabolite classes (sugars, amino acids, nucleosides and nucleobases, and amines) was subjected to LC analysis on three HILIC columns under 21 different gradient conditions with the aim to explore whether the retention properties of these analytes are determined from the chemical group they belong. Two multivariate techniques, principal component analysis (PCA) and discriminant analysis (DA), were used for statistical evaluation of the chromatographic data and extraction similarities between chemically related compounds. The total variance explained by the first two principal components of PCA was found to be about 98%, whereas both statistical analyses indicated that all analytes are successfully grouped in four clusters of chemical structure based on the retention obtained in four or at least three chromatographic runs, which, however should be performed on two different HILIC columns. Moreover, leave-one-out cross-validation of the above retention data set showed that the chemical group in which an analyte belongs can be 95.6% correctly predicted when the analyte is subjected to LC analysis under the same four or three experimental conditions as the all set of analytes was run beforehand. That, in turn, may assist with disambiguation of analyte identification in complex biological extracts.
authors.affiliation: Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
authors.forename: S
authors.initials: S
authors.lastname: Fasoula
authors.affiliation: Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
authors.forename: Ch
authors.initials: Ch
authors.lastname: Zisi
authors.affiliation: Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
authors.forename: I
authors.initials: I
authors.lastname: Sampsonidis
authors.affiliation: Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
authors.forename: Ch
authors.initials: Ch
authors.lastname: Virgiliou
authors.affiliation: Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
authors.forename: G
authors.initials: G
authors.lastname: Theodoridis
authors.affiliation: Department of Chemical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
authors.forename: H
authors.initials: H
authors.lastname: Gika
authors.affiliation: Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
authors.forename: P
authors.initials: P
authors.lastname: Nikitas
authors.affiliation: Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece. Electronic address: apappa@chem.auth.gr.
authors.forename: A
authors.initials: A
authors.lastname: Pappa-Louisi
mesh_terms: D000596:Amino Acids / Q000737:chemistry / Q000302:isolation & purification; D002853:Chromatography, Liquid / Q000379:methods*; D015999:Multivariate Analysis; D009705:Nucleosides / Q000737:chemistry / Q000302:isolation & purification; D025341:Principal Component Analysis
chemical_list: D000596:Amino Acids; D009705:Nucleosides
keywords: Analyte classification; Discriminant analysis; HILIC retention data; Principal component analysis