Adsorption of Proteins onto Ion-Exchange Chromatographic Media: A Molecular Dynamics Study

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

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.

Modeling Chromatography Binding through Molecular Dynamics Simulations with Resin Fragments

Accurate atomistic modeling of the interactions of a chromatography resin with a solute can inform the selection of purification conditions for a product, an important problem in the biotech and pharmaceutical industries. We present a molecular dynamics simulation-based approach for the qualitative prediction of interaction sites (specificity) and retention times (affinity) of a protein for a given chromatography resin. We mimicked the resin with an unrestrained ligand composed of the resin headgroup coupled with successively larger fragments of the agarose backbone. The interactions of the ligand with the protein are simulated in an explicit solvent using the Replica Exchange Molecular Dynamics enhanced sampling approach in conjunction with Hydrogen Mass Repartitioning (REMD-HMR). We computed the ligand interaction surface from the simulation trajectories and correlated the features of the interaction surface with experimentally determined retention times. The simulation and analysis protocol were first applied to a series of ubiquitin mutants for which retention times on Capto MMC resin are available. The ubiquitin simulations helped identify the optimal ligand that was used in subsequent simulations on six proteins for which Capto MMC elution times are available. For each of the six proteins, we computed the interaction surface and characterized it in terms of a range of simulation-averaged residue-level physicochemical descriptors. Modeling of the salt concentrations required for elution with respect to the descriptors resulted in a linear fit in terms of aromaphilicity and Kyte-Doolittle hydrophobicity that was robust to outliers, showed high correlation, and correctly ranked the protein elution order. The physics-based model building approach described here does not require a large experimental data set and can be readily applied to different resins and diverse biomolecules.

A novel approach to calculate protein adsorption isotherms by molecular dynamics simulations

Protein adsorption plays a role in many fields, where in some it is desirable to maximize the amount adsorbed, in others it is important to avoid protein adsorption altogether. Therefore, theoretical methods are needed for a better understanding of the underlying processes and for the prediction of adsorption quantities. In this study, we present a proof-of-concept that the calculation of protein adsorption isotherms by molecular dynamics (MD) simulations is possible using the steric mass action (SMA) theory. Here we are investigating the adsorption of bovine/human serum albumin (BSA/HSA) and hemoglobin (bHb) on Q Sepharose FF. Protein adsorption isotherms were experimentally determined and modeled. Free energy profiles of protein adsorption were calculated by MD simulations to determine the Henry isotherms as a first step. Although each simulation contained only one protein, notably the calculated isotherms are in reasonably good agreement with the experimental isotherms. Hence, we could show that MD data can lead to protein adsorption data in good agreement with experimental data. The results were critically discussed and requirements for future applications are identified.

Understanding the curvature effect of silica nanoparticles on lysozyme adsorption orientation and conformation: a mesoscopic coarse-grained simulation study

In nanobiotechnology applications, curvature of nanoparticles has a significant effect on protein activities. In this work, lysozyme adsorption on different-sized silica nanoparticles (SNPs) was simulated at the microsecond timescale by using mesoscopic coarse-grained molecular dynamics simulations. It is found that, with the increase of nanoparticle size, which indicates a decrease of surface curvature, adsorbed lysozyme shows a narrower orientation distribution and a greater conformation change, as the electrostatic attraction dominates lysozyme adsorption, and this trend is more pronounced on larger SNPs. Interestingly, the effect induced by different SNP surface curvatures is not related to the direct contact area between lysozyme and SNPs, but to the interfacial hydration layer above the silica surface, since a smaller curvature can lead to a stronger interfacial hydration and make the distribution of interfacial water molecules more ordered. Besides, at higher ionic strength, lysozyme conformation is less affected by strongly negatively charged SNPs, especially for larger nanoparticles. This work might shed some light on how to prepare protein coronas with higher bioactivities in nanobiotechnology.

Modeling and simulation of protein-surface interactions: achievements and challenges

Understanding protein-inorganic surface interactions is central to the rational design of new tools in biomaterial sciences, nanobiotechnology and nanomedicine. Although a significant amount of experimental research on protein adsorption onto solid substrates has been reported, many aspects of the recognition and interaction mechanisms of biomolecules and inorganic surfaces are still unclear. Theoretical modeling and simulations provide complementary approaches for experimental studies, and they have been applied for exploring protein-surface binding mechanisms, the determinants of binding specificity towards different surfaces, as well as the thermodynamics and kinetics of adsorption. Although the general computational approaches employed to study the dynamics of proteins and materials are similar, the models and force-fields (FFs) used for describing the physical properties and interactions of material surfaces and biological molecules differ. In particular, FF and water models designed for use in biomolecular simulations are often not directly transferable to surface simulations and vice versa. The adsorption events span a wide range of time- and length-scales that vary from nanoseconds to days, and from nanometers to micrometers, respectively, rendering the use of multi-scale approaches unavoidable. Further, changes in the atomic structure of material surfaces that can lead to surface reconstruction, and in the structure of proteins that can result in complete denaturation of the adsorbed molecules, can create many intermediate structural and energetic states that complicate sampling. In this review, we address the challenges posed to theoretical and computational methods in achieving accurate descriptions of the physical, chemical and mechanical properties of protein-surface systems. In this context, we discuss the applicability of different modeling and simulation techniques ranging from quantum mechanics through all-atom molecular mechanics to coarse-grained approaches. We examine uses of different sampling methods, as well as free energy calculations. Furthermore, we review computational studies of protein-surface interactions and discuss the successes and limitations of current approaches.

Probing immobilization mechanism of alpha-chymotrypsin onto carbon nanotube in organic media by molecular dynamics simulation

The enzyme immobilization has been adopted to enhance the activity and stability of enzymes in non-aqueous enzymatic catalysis. However, the activation and stabilization mechanism has been poorly understood on experiments. Thus, we used molecular dynamics simulation to study the adsorption of α-chymotrypsin (α-ChT) on carbon nanotube (CNT) in aqueous solution and heptane media. The results indicate that α-ChT has stronger affinity with CNT in aqueous solution than in heptane media, as confirmed by more adsorption atoms, larger contact area and higher binding free energies. Although the immobilization causes significant structure deviations from the crystal one, no significant changes in secondary structure of the enzyme upon adsorption are observed in the two media. Different from aqueous solution, the stabilization effects on some local regions far from the surface of CNT were observed in heptane media, in particular for S1 pocket, which should contribute to the preservation of specificity reported by experiments. Also, CNT displays to some extent stabilization role in retaining the catalytic H-bond network of the active site in heptane media, which should be associated with the enhanced activity of enzymes. The observations from the work can provide valuable information for improving the catalytic properties of enzymes in non-aqueous media.