Modeling the impact of amino acid substitution in a monoclonal antibody on cation exchange chromatography

Abstract

A vital part of biopharmaceutical research is decision making around which lead candidate should be progressed in early-phase development. When multiple antibody candidates show similar biological activity, developability aspects are taken into account to ease the challenges of manufacturing the potential drug candidate.While current strategies for developability assessment mainly focus on drug product stability, only limited information is available on how antibody candidates with minimal differences in their primary structure behave during downstream processing. With increasing time-to-market pressure and an abundance of monoclonal antibodies (mAbs) in development pipelines, developability assessments should also consider the ability of mAbs to integrate into the downstream platform. This study investigates the influence of amino acid substitutions in the complementaritydetermining region (CDR) of a full-length IgG1 mAb on the elution behavior in preparative cation exchange chromatography. Single amino acid substitutions within the investigated mAb resulted in an additional positive charge in the light chain (L) and heavy chain (H) CDR, respectively. The mAb variants showed an increased retention volume in linear gradient elution compared with the wild-type antibody.Furthermore, the substitution of tryptophan with lysine in the H-CDR3 increased charge heterogeneity of the product. A multiscale in silico analysis, consisting of homology modeling, protein surface analysis, and mechanistic chromatography modeling increased understanding of the adsorption mechanism. The results reveal the potential effects of lead optimization during antibody drug discovery on downstream processing.

A multiscale modeling method for therapeutic antibodies in ion exchange chromatography

“…Feature selection and QSPR modeling revealed quantitative relationships between the structure of therapeutic antibodies and their adsoprtion model parameters. These relationships were also suggested by a previous work of our group, where single amino acid substitution in the CDR of mAbs had a significant impact on $<math altimg="urn:x-wiley:00063592:media:bit28258:bit28258-math-0115" wiley:location="equation/bit28258-math-0115.png" xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mrow><msub><mi>k</mi><mrow><mi>e</mi><mi>q</mi><mo>,</mo><mi>i</mi></mrow></msub></mrow></mrow></math>$ parameters (Saleh et al, 2021). The three IgG1 mAbs with single amino acid substitution were also included in the present data set of 21 mAbs, increasing the predictive power of the QSPR model for $<math altimg="urn:x-wiley:00063592:media:bit28258:bit28258-math-0116" wiley:location="equation/bit28258-math-0116.png" xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mrow><msub><mi>k</mi><mrow><mi>e</mi><mi>q</mi><mo>,</mo><mi>i</mi></mrow></msub></mrow></mrow></math>$.…”

“…However, the increasing structural complexity of antibody formats and the poorly understood adsorption mechanisms in preparative chromatography challenge downstream processing (DSP) under standardized conditions. For cation exchange (CEX) chromatography, the antibody format (Luo et al, 2015(Luo et al, , 2014 as well as minimal changes in the primary structure of mAbs (Saleh et al, 2021) influence elution profiles and the resulting optimal operating conditions. Multiple authors propose to increase process understanding by using mechanistic models as digital twins of the manufacturing process (Cardillo et al, 2021;Narayanan et al, 2020;Smiatek et al, 2020).…”

Recent Advances and Future Directions in Downstream Processing of Therapeutic Antibodies

“…This involves protein engineering via sequence modifications to modify mAb properties to improve protein purification outcomes, at least for proof-of-concept evaluation of potential lead candidates. This has been demonstrated, for example, by modifying residues within a mAb heavy chain that result in changes in elution behavior in cation exchange chromatography [ 9 ]. A second example is the engineering of amino acid charge differences (EEE/RRR) into two different heavy chain sequences used to construct bi-specific antibodies, facilitating the separation of the desired heterodimers from homodimers post-mixing in vitro [ 10 ].…”

The use of predictive models to develop chromatography-based purification processes

“…The SMA model is often used to describe sorption during ion exchange chromatography (IEX) and specifically accounts for the salt concentration, number of interacting ligands, and steric shielding of the ligand by bound proteins ( Parente and Wetlaufer 1986 ; Degerman et al, 2007 ; Osberghaus et al, 2012a ; Bernau et al, 2021 ). Currently, more than 15 isotherms are available for the description of chromatography modalities such as IEX and HIC ( Guo et al, 2020 ; Kumar and Lenhoff 2020 ; Saleh et al, 2021a ; Saleh et al, 2021b ; Kumar et al, 2021 ) as has been reviewed elsewhere ( Wang et al, 2016 ; Shekhawat and Rathore 2019 ). In contrast, few isotherms are available for mixed-mode or multi-modal chromatography (MMC), probably due to the yet incomplete understanding of the mechanistic basis of this process ( Kumar and Lenhoff 2020 ) and/or because the corresponding resins are often used in flow-through mode to bind HCPs.…”

“…For example, the experimental effort required to model a cation exchange chromatography step for a monoclonal antibody in silico was reduced by ∼75% compared to traditional laboratory-based process characterization ( Saleh et al, 2021c ). This reflected the ability of the model to predict the effect of changes in protein surface charge on separation a priori , thus accounting for the impact on purification ( Saleh et al, 2021a ). Similarly, mechanistic models can augment SDM-based data by incorporating process information about loading density, bed height or mobile phase properties ( Saleh et al, 2021b ).…”