ArticleJournal of immunological methods2017
Prediction of antibody structural epitopes via random peptide library screening and next generation sequencing.
Article in Journal of immunological methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 15 citations in OpenAlex.
- Revolutionizing Synthetic Antibody Design: Harnessing Artificial Intelligence and Deep Sequencing Big Data for Unprecedented Advances.Molecular biotechnology · 2025Review
- Motifier: An IgOme Profiler Based on Peptide Motifs Using Machine Learning.Journal of molecular biology · 2021Article
- Phage-Displayed Peptides for Targeting Tyrosine Kinase Membrane Receptors in Cancer Therapy.Viruses · 2021Review
- Chimeric Antigen Receptor Based Therapy as a Potential Approach in Autoimmune Diseases: How Close Are We to the Treatment?Frontiers in immunology · 2020Review
- The next generation of biopanning: next gen sequencing improves analysis of bacterial display libraries.BMC biotechnology · 2019Article
- A general approach for predicting protein epitopes targeted by antibody repertoires using whole proteomes.PloS one · 2019Article
- Current state of in vivo panning technologies: Designing specificity and affinity into the future of drug targeting.Advanced drug delivery reviews · 2018Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Next generation sequencing (NGS) is widely applied in immunological research, but has yet to become common in antibody epitope mapping. A method utilizing a 12-mer random peptide library expressed in bacteria coupled with magnetic-based cell sorting and NGS correctly identified >75% of epitope residues on the antigens of two monoclonal antibodies (trastuzumab and bevacizumab). PepSurf, a web-based computational method designed for structural epitope mapping was utilized to compare peptides in libraries enriched for monoclonal antibody (mAb) binders to antigen surfaces (HER2 and VEGF-A). Compared to mimotopes recovered from Sanger sequencing of plated colonies from the same sorting protocol, motifs derived from sets of the NGS data improved epitope prediction as defined by sensitivity and precision, from 18% to 82% and 0.27 to 0.51 for trastuzumab and 47% to 76% and 0.19 to 0.27 for bevacizumab. Specificity was similar for Sanger and NGS, 99% and 97% for trastuzumab and 66% and 67% for bevacizumab. These results indicate that combining peptide library screening with NGS yields epitope motifs that can improve prediction of structural epitopes.
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Registered trials
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.