Prediction of Reversed-Phase Liquid Chromatography Retention Parameters for Phenylisothiocyanate Derivatives of Amino Acids

Abstract

Abstract We report our experience with highly polar and charged analyte retention parameter prediction for a reversed-phase high-performance liquid chromatographic method. The solvatic retention model has been used to predict retention of phenylisothiocyanate derivatives of 25 natural amino acids under gradient elution conditions. Retention factors have been calculated from molecular parameters of analyte structures and from the column and eluent characteristics. A step-by-step method which includes the first guess prediction of initial conditions from structural formula and fine tuning of the retention model parameters using data from successive runs can substantially save method development time