https://orcid.org/0000-0002-8490-7536
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ABSTRACT
Asparagine (Asn) deamidation and aspartic acid (Asp) isomerization are common degradation pathways that affect the stability of therapeutic antibodies. These modifications can pose a significant challenge in the development of biopharmaceuticals. As such, the early engineering and selection of chemically stable monoclonal antibodies (mAbs) can substantially mitigate the risk of subsequent failure. In this study, we introduce a novel in silico approach for predicting deamidation and isomerization sites in therapeutic antibodies by analyzing the structural environment surrounding asparagine and aspartate residues. The resulting quantitative structure-activity relationship (QSAR) model was trained using previously published forced degradation data from 57 clinical-stage mAbs. The predictive accuracy of the model was evaluated for four different states of the protein structure: (1) static homology models, (2) enhancing low-frequency vibrational modes during short molecular dynamics (MD) runs, (3) a combination of (2) with a protonation state reassignment, and (4) conventional full-atomistic MD simulations. The most effective QSAR model considered the accessible surface area (ASA) of the residue, the pKa value of the backbone amide, and the root mean square deviations of both the alpha carbon and the side chain. The accuracy was further enhanced by incorporating the QSAR model into a decision tree, which also includes empirical information about the sequential successor and the position in the protein. The resulting model has been implemented as a plugin named “Forecasting Reactivity of Isomerization and Deamidation in Antibodies” in MOE software, completed with a user-friendly graphical interface to facilitate its use.
Abbreviations
| Asn (N) | = | Asparagine |
| Asp (D) | = | Aspartic Acid |
| ASA | = | Accessible Surface Area |
| AUC | = | Area under the curve |
| Cα | = | Alpha Carbon in Asn/Asp side chain |
| Cγ | = | Gamma Carbon in Asn/Asp side chain |
| CDR | = | Complementary-Determining Region |
| CQAs | = | Critical Quality Attributes |
| Fv | = | Variable region |
| Iso-Asp | = | Iso-aspartic acid |
| mAbs | = | Monoclonal Antibodies |
| MD | = | Molecular Dynamics |
| NHn + 1 | = | Backbone Nitrogen of successor amino acid |
| NPV | = | Negative predictive value |
| OH− | = | Hydroxyl Ion |
| QSAR | = | Quantitative Structure-Activity Relationship |
| R&D | = | Research and Development |
| RMSD | = | Root Mean Square Deviation |
| ROC-curve | = | Receiver Operating Characteristic Curve |
| SASA | = | Solvent Accessible Surface Area |
| TN | = | True Negative |
| TNR | = | True Negative Rate |
| TP | = | True Positive |
| TPR | = | True Positive Rate |
Acknowledgments
This research was supported by Boehringer Ingelheim Pharma GmbH & Co KG. We gratefully acknowledge the whole In Silico Team (IST) at Boehringer Ingelheim for excellent discussions.
Disclosure statement
D. Hoffmann, J. Bauer, A.R. Karow-Zwick and G. Licari were employees of Boehringer Ingelheim Pharma GmbH & Co.KG during the project.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/19420862.2024.2333436