Protein-surface interaction maps for ion-exchange chromatography

Molecular surface descriptors to predict antibody developability: sensitivity to parameters, structure models, and conformational sampling

In silico assessment of antibody developability during early lead candidate selection and optimization is of paramount importance, offering a rapid and material-free screening approach. However, the predictive power and reproducibility of such methods depend heavily on the selection of molecular descriptors, model parameters, accuracy of predicted structure models, and conformational sampling techniques. Here, we present a set of molecular surface descriptors specifically designed for predicting antibody developability. We assess the performance of these descriptors by benchmarking their correlations with an extensive array of experimentally determined biophysical properties, including viscosity, aggregation, hydrophobic interaction chromatography, human pharmacokinetic clearance, heparin retention time, and polyspecificity. Further, we investigate the sensitivity of these surface descriptors to methodological nuances, such as the choice of interior dielectric constant, hydrophobicity scales, structure prediction methods, and the impact of conformational sampling. Notably, we observe systematic shifts in the distribution of surface descriptors depending on the structure prediction method used, driving weak correlations of surface descriptors across structure models. Averaging the descriptor values over conformational distributions from molecular dynamics mitigates the systematic shifts and improves the consistency across different structure prediction methods, albeit with inconsistent improvements in correlations with biophysical data. Based on our benchmarking analysis, we propose six in silico developability risk flags and assess their effectiveness in predicting potential developability issues for a set of case study molecules.

Evaluation of preferred binding regions on ubiquitin and IgG1 FC for interacting with multimodal cation exchange resins using DEPC labeling/mass spectrometry

There is significant interest in identifying the preferred binding domains of biological products to various chromatographic materials. In this work, we develop a biophysical technique that uses diethyl pyrocarbonate (DEPC) based covalent labeling in concert with enzymatic digestion and mass spectrometry to identify the binding patches for proteins bound to commercially available multimodal (MM) cation exchange chromatography resins. The technique compares the changes in covalent labeling of the protein in solution and in the bound state and uses the differences in this labeling to identify residues that are sterically shielded upon resin binding and, therefore, potentially involved in the resin binding process. Importantly, this approach enables the labeling of many amino acids and can be carried out over a pH range of 5.5-7.5, thus enabling the protein surface mapping at conditions of interest in MM cation exchange systems. The protocol is first developed using the model protein ubiquitin and the results indicate that lysine residues located on the front face of the protein show dramatic changes in DEPC labeling while residues present on other regions have minimal or no reductions. This indicates that the front face of ubiquitin is likely involved in resin binding. In addition, surface property maps indicate that the hypothesized front face binding region consists of overlapping positively charged and hydrophobic patches. The technique is then employed with an IgG1 F_C and the results indicate that residues on the C_H 2-C_H 3 interface and the hinge are significantly sterically shielded upon binding to the resin. Further, these regions are again associated with significant overlap of positively charged and hydrophobic patches. On the other hand, while, residues on the C_H 2 and the front face of the IgG1 F_C also exhibited some changes in DEPC labeling upon binding, these regions have less distinct charged and hydrophobic patches. Importantly, the hypothesized binding patches identified for both ubiquitin and F_C using this approach are shown to be consistent with previously reported NMR studies. In contrast to NMR, this new approach enables the identification of preferred binding regions without the need for isotopically labeled proteins or chemical shift assignments. The technique developed in this work sets the stage for the evaluation of the binding domains of a wide range of biological products to chromatographic surfaces, with important implications for designing biomolecules with improved biomanufacturability properties.

Impact of the isoelectric point of model parvoviruses on viral retention in anion-exchange chromatography

Anion-exchange chromatography (AEX) is used in the downstream purification of monoclonal antibodies to remove impurities and potential viral contamination based on electrostatic interactions. Although the isoelectric point (pI) of viruses is considered a key factor predicting the virus adsorption to the resin, the precise molecular mechanisms involved remain unclear. To address this question, we compared structurally homologous parvoviruses that only differ in their surface charge distribution. A single charged amino acid substitution on the capsid surface of minute virus of mice (MVM) provoked an increased apparent pI (pI_app ) 6.2 compared to wild-type MVM (pI_app  = 4.5), as determined by chromatofocusing. Despite their radically different pI_app , both viruses displayed the same interaction profile in Mono Q AEX at different pH conditions. In contrast, the closely related canine parvovirus (pI_app  = 5.3) displayed a significantly different interaction at pH 5. The detailed structural analysis of the intricate three-dimensional structure of the capsids suggests that the charge distribution is critical, and more relevant than the pI, in controlling the interaction of a virus with the chromatographic resin. This study contributes to a better understanding of the molecular mechanisms governing virus clearance by AEX, which is crucial to enable robust process design and maximize safety.

Single Molecule Force Spectroscopy and Molecular Dynamics Simulations as a Combined Platform for Probing Protein Face-Specific Binding

Biomolecular interactions frequently occur in orientation-specific manner. For example, prior nuclear magnetic resonance spectroscopy experiments in our lab have suggested the presence of a group of strongly binding residues on a particular face of the protein ubiquitin for interactions with Capto MMC multimodal ligands ("Capto" ligands) (Srinivasan, K.; et al. Langmuir 2014, 30 (44), 13205-13216). We present a clear confirmation of those studies by performing single-molecule force spectroscopy (SMFS) measurements of unbinding complemented with molecular dynamics (MD) calculations of the adsorption free energy of ubiquitin in two distinct orientations with self-assembled monolayers (SAMs) functionalized with "Capto" ligands. These orientations were maintained in the SMFS experiments by tethering ubiquitin mutants to SAM surfaces through strategically located cysteines, thus exposing the desired faces of the protein. Analogous orientations were maintained in MD simulations using suitable constraining methods. Remarkably, despite differences between the finer details of experimental and simulation methodologies, they confirm a clear preference for the previously hypothesized binding face of ubiquitin. Furthermore, MD simulations provided significant insights into the mechanism of protein binding onto this multimodal surface. Because SMFS and MD simulations both directly probe protein-surface interactions, this work establishes a key link between experiments and simulations at molecular scale through the determination of protein face-specific binding energetics. Our approach may have direct applications in biophysical systems where face- or orientation-specific interactions are important, such as biomaterials, sensors, and biomanufacturing.

Probing protein orientation near charged nanosurfaces for simulation-assisted biosensor design

Protein-surface interactions are ubiquitous in biological processes and bioengineering, yet are not fully understood. In biosensors, a key factor determining the sensitivity and thus the performance of the device is the orientation of the ligand molecules on the bioactive device surface. Adsorption studies thus seek to determine how orientation can be influenced by surface preparation, varying surface charge, and ambient salt concentration. In this work, protein orientation near charged nanosurfaces is obtained under electrostatic effects using the Poisson-Boltzmann equation, in an implicit-solvent model. Sampling the free energy for protein G B1 D4' at a range of tilt and rotation angles with respect to the charged surface, we calculated the probability of the protein orientations and observed a dipolar behavior. This result is consistent with published experimental studies and combined Monte Carlo and molecular dynamics simulations using this small protein, validating our method. More relevant to biosensor technology, antibodies such as immunoglobulin G are still a formidable challenge to molecular simulation, due to their large size. With the Poisson-Boltzmann model, we obtained the probability distribution of orientations for the iso-type IgG2a at varying surface charge and salt concentration. This iso-type was not found to have a preferred orientation in previous studies, unlike the iso-type IgG1 whose larger dipole moment was assumed to make it easier to control. Our results show that the preferred orientation of IgG2a can be favorable for biosensing with positive charge on the surface of 0.05 C/m(2) or higher and 37 mM salt concentration. The results also show that local interactions dominate over dipole moment for this protein. Improving immunoassay sensitivity may thus be assisted by numerical studies using our method (and open-source code), guiding changes to fabrication protocols or protein engineering of ligand molecules to obtain more favorable orientations.