Investigation of protein selectivity in multimodal chromatography using in silico designed Fab fragment variants

Abstract

In this study, a unique set of antibody Fab fragments was designed in silico and produced to examine the relationship between protein surface properties and selectivity in multimodal chromatographic systems. We hypothesized that multimodal ligands containing both hydrophobic and charged moieties would interact strongly with protein surface regions where charged groups and hydrophobic patches were in close spatial proximity. Protein surface property characterization tools were employed to identify the potential multimodal ligand binding regions on the Fab fragment of a humanized antibody and to evaluate the impact of mutations on surface charge and hydrophobicity. Twenty Fab variants were generated by site-directed mutagenesis, recombinant expression, and affinity purification. Column gradient experiments were carried out with the Fab variants in multimodal, cation-exchange, and hydrophobic interaction chromatographic systems. The results clearly indicated that selectivity in the multimodal system was different from the other chromatographic modes examined. Column retention data for the reduced charge Fab variants identified a binding site comprising light chain CDR1 as the main electrostatic interaction site for the multimodal and cation-exchange ligands. Furthermore, the multimodal ligand binding was enhanced by additional hydrophobic contributions as evident from the results obtained with hydrophobic Fab variants. The use of in silico protein surface property analyses combined with molecular biology techniques, protein expression, and chromatographic evaluations represents a previously undescribed and powerful approach for investigating multimodal selectivity with complex biomolecules.

Homology modeling and structure-based design improve hydrophobic interaction chromatography behavior of integrin binding antibodies

“…12–14 More recently, multi-parameter protein quantitative structure-property relationship (QSPR) models have been developed to predict high-concentration viscosities of mAbs using surface hydrophobicity and charge descriptors from full antibody homology models and similar protein QSPR models have been reported for predicting chromatographic behavior, including HIC. 15–17 The earlier work of building single-parameter hydrophobic patch predictors was validated appropriately using experimental data for fewer than twenty sequences.…”

Optimizing selectivity of anion hydrophobic multimodal chromatography for purification of a single‐chain variable fragment

“…A total of 100 variants were generated followed by a restraint minimization using the flag beta and the lowest scoring model was selected. The surface properties of the model scFv were evaluated by SAP and spatial distribution of electrostatic potential (EP) maps in the BIOVIA Discovery Studio 2018 software (Accelrys, USA). SAP values were calculated using a radius of 10 Å as it has been shown to be the most appropriate for identifying hydrophobic patches .…”

“…The surface characteristic of the scFv was visualized by both spatial aggregation propensity (SAP) map [21][22][23], which was originally developed for analysis of aggregation prone regions of hydrophobic nature [24], and spatial distribution of electrostatic potential (EP) map. SAP and EP maps have previously been shown to be powerful tools for explaining selectivity of different mixed-mode adsorbents for antigen binding fragments differing in hydrophobicity and surface charge [25,26]. Robinson et al [27] recently reported that retention of mAbs and their fragments on different mixed-mode adsorbents can be related to distinct surface properties elucidated by these surface property maps.…”

Implementation of an experimental and computational tool set to study protein‐mAb interactions

“…Further, the determination of electrostatic potential (EP) based on Poisson‐Boltzmann calculations allows the identification of positive and negative EP regions on a protein surface . We have employed these protein surface characterization techniques to identify potential chromatographic ligand binding sites on a homologous set of Fabs and to help guide the modification of these protein surfaces to impact ligand binding …”

“…42,43 We have employed these protein surface characterization techniques to identify potential chromatographic ligand binding sites on a homologous set of Fabs and to help guide the modification of these protein surfaces to impact ligand binding. 44,45 The current work focuses on the development of a combined experimental and computational tool set to study protein-mAb interactions as shown in Figure 1. A model protein library is first screened using cross interaction chromatography with an immobilized mAb resin to identify proteins with the strongest retention.…”