Nonlinear gradient isotherm parameter estimation for proteins with consideration of salt competition and multiple...

Area of Science:

• Biochemistry
• Chemical Engineering
• Chromatography

Background:

• Salt gradients in ion-exchange chromatography are crucial for efficient protein separation and concentration.
• Accurate protein equilibrium data as a function of salt concentration is essential for optimizing these gradients.
• Understanding salt effects, conformational changes, and aggregation is key for precise isotherm parameter estimation.

Purpose of the Study:

• To develop and validate a predictive model for protein elution in ion-exchange chromatography using salt gradients.
• To assess the accuracy of a salt-modulated nonlinear isotherm in predicting gradient elution behavior.
• To investigate the impact of protein aggregation and denaturation on isotherm parameter estimation and gradient elution.

Main Methods:

• Gradient elution of bovine serum albumin (BSA) in anion exchange chromatography.
• Development and application of a salt-modulated nonlinear isotherm model.
• Comparison of model predictions with experimental batch equilibrium and gradient elution data.
• Utilizing the VERSE-LC advanced rate model to consider multiple binding forms.

Main Results:

• The salt-modulated nonlinear isotherm accurately predicted BSA gradient elution using batch equilibrium data.
• The model successfully predicted elution across various gradient slopes when fitted to intermediate slope data.
• Isotherm parameters are averaged in batch and gradient experiments due to long equilibration times and gradient merging effects.
• Discrepancies in isocratic elution arise when reaction rates are insufficient for peak merging; slower flow rates can mitigate this.
• The VERSE-LC model, considering two binding forms, showed good agreement with experimental data across all salt gradient durations.

Conclusions:

• A salt-modulated nonlinear isotherm effectively predicts protein gradient elution in ion-exchange chromatography.
• The model's ability to incorporate salt competition enhances its predictive power for gradient optimization.
• While averaged parameters are often obtained, advanced rate models like VERSE-LC can provide more accurate predictions by accounting for multiple binding forms.
• This work provides a framework for systematic optimization of salt gradient elution in protein separations.