All-atom modeling of methacrylate-based multi-modal chromatography resins for Langmuir constant prediction of peptides

  • Autor:

    Ballweg, T. / Liu, M. / Grimm, J. / Sedghamiz, E. / Wenzel, W. / Franzreb, M. (2024)

  • Quelle:

    Journal of Chromatography A, 2024, 1730, 465089

  • Datum: August 2024
  • Abstract

    In downstream processing, the intricate nature of the interactions between biomolecules and adsorbent materials presents a significant challenge in the prediction of their binding and elution behaviors. This complexity is further heightened in multi-modal chromatography (MMC), which employs two distinct binding mechanisms. To gain a deeper understanding of the involved interactions, simulating the adsorption of biomolecules on resin surfaces is a focal point of ongoing research. However, previous studies often simplified the adsorbent surface, modeling it as a flat or slightly curved plane without including a realistic backbone structure. Here, we introduce and validate two novel workflows aimed at predicting peptide binding behaviors in MMC, specifically targeting methacrylate-based resins. Our first achievement was the development of an all-atom model of a commercial MMC resin surface, incorporating its polymethacrylic backbone. Furthermore, we established and tested a workflow for rapid calculations of binding free energies (ΔG) with 10 linear peptides as target molecules. These ΔG calculations were effectively used to predict Langmuir constants, achieving a high coefficient of determination (R²) of 0.96. In subsequent benchmarking tests, our model outperformed established, simpler resin surface models in terms of predictive capabilities.

     

     Download