Abstract
Chromatography modeling for simulation is a tool that can help to predict the separation of molecules inside the column. Knowledge of sorption isotherms in chromatography modeling is a crucial step and methods such as frontal analysis or batch are used to obtain sorption isotherm parameters, but they require a significant quantity of samples. This study aims to predict Langmuir isotherm parameters from Surface Plasmon Resonance (SPR) affinity data (requiring less quantity of sample) to simulate metal chelating peptides (MCPs) separation in Immobilized Metal ion Affinity Chromatography (IMAC), thanks to the analogy between both techniques. The validity of simulation was evaluated by comparing the peptide’s simulated retention time with its experimental retention time obtained by IMAC. Results showed that the peptide affinity constant (KA) can be conserved between SPR and IMAC. However, the maximal capacity (qmax) must be adjusted by a correction factor to overcome the geometry differences between IMAC (spherical particles) and SPR (plane sensor ship). Therefore, three approaches were studied; the best one was to use qmax,IMAC imidazole determined experimentally while a correction factor was applied on qmax,SPR to obtain the qmax,IMAC of the peptide, thus minimizing the discrepancy between the experimental and simulated retention times of a peptide.