Modelling of UPLC behaviour of acylcarnitines by quantitative structure-retention relationships.
In the present work, the retention time (RT) of acylcarnitines, collected by ultra-performance liquid-chromatography after formation of butyl esters, is modelled by quantitative structure-retention relationship (QSRR) method. The investigated set consists of free carnitine and 46 different acylcarnitines, including the isomers commonly monitored in screening metabolic disorders. To describe the structure of (butylated) acylcarnitines, a large number of computational molecular descriptors generated by software Dragon are subjected to variable selection methods aimed at identifying a small informative subset. The QSRR model is established using two different approaches: the multi linear regression (MLR) combined with a genetic algorithm (GA) variable selection and the partial least square (PLS) regression after iterative stepwise elimination (ISE) of useless descriptors. Predictive performance of both models is evaluated using an external set consisting of 10 representative acylcarnitines, and, successively, by repeated random data partitions between the calibration and prediction sets. Finally, a principal component analysis (PCA) is performed on the model variables to facilitate the interpretation of the established QSRRs. A PLS model based on seven latent variables extracted from 20 molecular descriptors selected by ISE permits to calculate/predict the retention time of acylcarnitine with accuracy better than 5%, whereas a 6-dimensional model identified by GA-MLR provides a slightly worse performance.
Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67010 Coppito, L'Aquila, Italy. Electronic address: angeloantonio.darchivio@univaq.it.
Angelo Antonio
AA
D'Archivio
Hortus Novus, Via Collepietro, 67100 L'Aquila, Italy.
Maria Anna
MA
Maggi
Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67010 Coppito, L'Aquila, Italy.
Fabrizio
F
Ruggieri
D000465:Algorithms; D002138:Calibration; D002331:Carnitine / Q000031:analogs & derivatives* / Q000032:analysis / Q000737:chemistry; D002851:Chromatography, High Pressure Liquid / Q000379:methods*; D016018:Least-Squares Analysis; D016014:Linear Models; D008962:Models, Theoretical; D025341:Principal Component Analysis; D021281:Quantitative Structure-Activity Relationship; D015203:Reproducibility of Results
C116917:acylcarnitine; D002331:Carnitine
Acylcarnitines; Molecular descriptors; Quantitative structure–retention relationships; Retention modelling; variable selection