Method for the simultaneous enantioselective analysis of 21 natural amino acids and its application to analytics of fluorenylmethoxycarbonyl-derivatives under liquid chromatography conditions

• Method for chiral analysis of 21 AAs in a single column and within 5 min (AQC derivatized). • Simultaneous chiral determination of free and protected AA impurities in Fmoc samples. • Conditions applicable to LC-MS and UV detection. The aim of this short communication is to show effective solutions for the control of enantiomeric excess simultaneously on free and protected amino acids (AAs). Such development has interest in the easy implementation of QC control of raw materials in peptide synthesis. Enantiomeric purity of Fmoc-L-AAs (containing fluorenylmethoxycarbonyl amine protecting group) is controlled on a routine base to determine the content of the Fmoc D-counterpart which can be present as impurity. However, the current analytical methods do not allow the simultaneous determination of potential unprotected L- and D-AAs which can be also present as impurities (in the same sample). The analytical conditions described in this publication were specifically achieved on a single ionic chiral column offering enantiomeric selectivity for free AAs derivatized with AQC (6-aminoquinolyl-N-hydroxysuccinimidyl carbamate) and for Fmoc-protected AAs. Only Fmoc-Proline quality control required the use of a different column, but with a similar mobile phase. The proposed methods enable both total and enantioselective AA quantification in a single chromatographic run. The workflow includes pre-column derivatization of the free AAs and optimization of chromatographic conditions for both derivatized and protected AA versions to be resolved in their enantiomeric forms in the same run. Representative results for the resolution of 21 AAs as AQC-derivatives are shown along with their retention behaviour. Subsequently, the analysis of every Fmoc-AA with their protected and unprotected chiral impurities is presented. The methods provide high resolution and selectivity as well as good reproducibility, which will facilitate efficient AAs profiling in diverse matrices.