ArticlePharmaceutical research2010
Potential aggregation-prone regions in complementarity-determining regions of antibodies and their contribution towards antigen recognition: a computational analysis.
Article in Pharmaceutical research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 75 citations in OpenAlex.
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- Intrinsic physicochemical profile of marketed antibody-based biotherapeutics.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
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- Interaction of clinical-stage antibodies with heme predicts their physiochemical and binding qualities.Communications biology · 2021Article
- Local environment effects on charged mutations for developing aggregation-resistant monoclonal antibodies.Scientific reports · 2020Article
- Toward Drug-Like Multispecific Antibodies by Design.International journal of molecular sciences · 2020Review
- Computational approaches to therapeutic antibody design: established methods and emerging trends.Briefings in bioinformatics · 2020Review
- Protein engineering approaches for antibody fragments: directed evolution and rational design approaches.Turkish journal of biology = Turk biyoloji dergisi · 2019Article
- Understanding and overcoming trade-offs between antibody affinity, specificity, stability and solubility.Biochemical engineering journal · 2018Article
- In Silico Methods in Antibody Design.Antibodies (Basel, Switzerland) · 2018Review
- Prediction and Reduction of the Aggregation of Monoclonal Antibodies.Journal of molecular biology · 2017Article
- De Novo Sequencing and Resurrection of a Human Astrovirus-Neutralizing Antibody.ACS infectious diseases · 2016Article
- Early implementation of QbD in biopharmaceutical development: a practical example.BioMed research international · 2015Review
- Article
- Concentration dependent viscosity of monoclonal antibody solutions: explaining experimental behavior in terms of molecular properties.Pharmaceutical research · 2014Article
- On the role of aggregation prone regions in protein evolution, stability, and enzymatic catalysis: insights from diverse analyses.PLoS computational biology · 2013Article
- IgG Fab fragments forming bivalent complexes by a conformational mechanism that is reversible by osmolytes.The Journal of biological chemistry · 2012Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo analyze contribution of short aggregation-prone regions (APRs), which may self-associate via cross-beta motif and were earlier identified in therapeutic mAbs, towards antigen recognition via structural analyses of antibody-antigen complexes.
methodsA dataset of 29 publically available high-resolution crystal structures of Fab-antigen complexes was collected. Contribution of APRs towards the surface areas of the Fabs buried by the cognate antigens was computed. Propensities of amino acids to occur in APRs and to be involved in antigen binding were compared. Coincidence between APRs and individual CDR loops was examined.
resultsAll Fabs in the dataset contain at least one APR in CDR loops and adjacent framework beta-strands. The average contribution of APRs towards buried surface area of Fabs is 16.0 +/- 10.7%. Aggregation and antigen recognition may be coupled via aromatic residues (Tyr, Trp), which occur with high propensities in both APRs and antigen binding sites. APRs are infrequent in the heavy chain CDR 3 (H3) loops (7%), but are frequent in H2 loops (45%).
conclusionsCo-incidence of APRs with antigen recognition sites can potentially lead to the loss of function upon aggregation. Rational structure-based design or selection strategies are suggested for biotherapeutics with improved druggability while maintaining potency.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.