Optimization of reversed-phase chromatography methods for peptide analytics

The analytical description and quantification of peptide solutions is an essential part in the quality control of peptide production processes and in peptide mapping techniques. Traditionally, an important tool is analytical reversed phase liquid chromatography. In this work, we develop a model-based tool to find optimal analytical conditions in a clear, efficient and robust manner. The model, based on the Van't Hoff equation, the linear solvent strength correlation, and an analytical solution of the mass balance on a chromatographic column describing peptide retention in gradient conditions is used to optimize the analytical scale separation between components in a peptide mixture. The proposed tool is then applied in the design of analytical reversed phase liquid chromatography methods of five different peptide mixtures.