Relationship between potential aggregation-prone regions and HLA-DR-binding T-cell immune epitopes: implications for rational design of novel and follow-on therapeutic antibodies
Abstract
Aggregation and unwanted immunogenicity are hurdles to avoid in successful commercial development of antibody-based therapeutics. In this article, the relationship between aggregation-prone regions (APRs), capable of forming cross-β motifs/amyloid fibrils, and major histocompatibility complex class II-restricted human leukocyte antigen (HLA)-DR-binding T-cell immune epitopes (TcIEs) is analyzed using amino acid sequences of 25 therapeutic antibodies, 55 TcIEs recognized by T-regulatory cells (tregitopes), 1000 randomly generated 15-residue-long peptides, 2257 human self-TcIEs (autoantigens), and 11 peptides in HLA-peptide cocrystal structures. Sequence analyses from these diverse sources consistently show a high level of correlation between APRs and TcIEs: approximately one-third of TcIEs contain APRs, but the majority of APRs occur within TcIE regions (TcIERs). Tregitopes also contain APRs. Most APR-containing TcIERs can bind multiple HLA-DR alleles, suggesting that aggregation-driven adverse immune responses could impact a broad segment of patient population. This article has identified common molecular sequence-structure loci that potentially contribute toward both manufacturability and safety profiles of the therapeutic antibodies, thereby laying a foundation for simultaneous optimization of these attributes in novel and follow-on candidates. Incidence of APRs within TcIERs is not special to biotherapeutics, self-TcIEs from human proteins, involved in various diseases, also contain predicted APRs and experimentally proven amyloid-fibril-forming peptide sequence portions.
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Kumar and co-workers have observed an overlap between potential immune epitopes and aggregation prone regions (APRs) around the CDRs of therapeutic antibodies.
“Kumar and co-workers have observed an overlap between potential immune epitopes and aggregation prone regions (APRs) around the CDRs of therapeutic antibodies [195, 196].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [196]
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Computational approaches to therapeutic antibody design: established methods and emerging trends
Norman, R. A., Ambrosetti, F., Bonvin, A. M. J. J., Colwell, L. J., Kelm, S., Kumar, S., & Krawczyk, K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz095 · Cited by 219 · see citing works
“workers have observed an overlap between potential immune epitopes and aggregation prone regions (APRs) around the CDRs of therapeutic antibodies [195, 196].”
BackgroundSelf-citation
- Authors
- Kumar, S., Mitchell, M. A., Rup, B., & Singh, S. K.
- Affiliations
- Pfizer (United States) (US)
- Corresponding author
- Kumar, Sandeep
- Venue
- Journal of Pharmaceutical Sciences
- Publisher
- Elsevier BV
- Published
- 2012-08
- Volume
- 101
- Issue
- 8
- Pages
- 2686-2701
- ISSN
- 0022-3549 (ISSN-L)
- OpenAlex
- W2030023123
- Cited by
- 33
- References
- 72
- Citations by year
- 2026: 1 · 2024: 3 · 2021: 2 · 2020: 1 · 2019: 3 · 2018: 3 · 2017: 5 · 2016: 3 · 2015: 7 · 2013: 3 · 2012: 2
- FWCI
- 1.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Pharmaceutical Sciences (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein purification and stability
- Keywords
- aggregation-prone regions, HLA-DR binding, therapeutic antibodies, antibody aggregation, immunogenicity, amyloid fibrils, autoantigens, antibody design, sequence-structure correlation
- MeSH terms
- Amino Acid Sequence, Amyloid, Antibodies, HLA-DR Antigens, Humans, Models, Molecular, Molecular Sequence Data, Peptides, Drug Design, Sequence Alignment, Computer-Aided Design, Epitopes, T-Lymphocyte
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