ArticlePloS one2019
A general approach for predicting protein epitopes targeted by antibody repertoires using whole proteomes.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 18 citations in OpenAlex.
- Reconstructing pathogen-specific antibody binding epitopes and age-dependent immune signatures from proteomic-scale peptide libraries.Science advances · 2026Article
- Antibody-drug conjugates for infectious and neglected tropical diseases: chemical design principles, target biology, and translational challenges.Frontiers in chemistry · 2026Review
- Reconstructing pathogen-specific antibody binding epitopes and age-dependent immune signatures from proteomic-scale peptide libraries.medRxiv : the preprint server for health sciences · 2025Article
- Revolutionizing Synthetic Antibody Design: Harnessing Artificial Intelligence and Deep Sequencing Big Data for Unprecedented Advances.Molecular biotechnology · 2025Review
- A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024Review
- Article
- Serum Epitope Repertoire Analysis Enables Early Detection of Lyme Disease with Improved Sensitivity in an Expandable Multiplex Format.Journal of clinical microbiology · 2021Article
- Protein-Based Immunome Wide Association Studies (PIWAS) for the Discovery of Significant Disease-Associated Antigens.Frontiers in immunology · 2021Article
- Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antibodies are essential to functional immunity, yet the epitopes targeted by antibody repertoires remain largely uncharacterized. To aid in characterization, we developed a generalizable strategy to predict antibody-binding epitopes within individual proteins and entire proteomes. Specifically, we selected antibody-binding peptides for 273 distinct sera out of a random library and identified the peptides using next-generation sequencing. To predict antibody-binding epitopes and the antigens from which these epitopes were derived, we tiled the sequences of candidate antigens into short overlapping subsequences of length k (k-mers). We used the enrichment over background of these k-mers in the antibody-binding peptide dataset to predict antibody-binding epitopes. As a positive control, we used this approach, termed K-mer Tiling of Protein Epitopes (K-TOPE), to predict epitopes targeted by monoclonal and polyclonal antibodies of well-characterized specificity, accurately recovering their known epitopes. K-TOPE characterized a commonly targeted antigen from Rhinovirus A, predicting four epitopes recognized by antibodies present in 87% of sera (n = 250). An analysis of 2,908 proteins from 400 viral taxa that infect humans predicted seven enterovirus epitopes and five Epstein-Barr virus epitopes recognized by >30% of specimens. Analysis of Staphylococcus and Streptococcus proteomes similarly predicted 22 epitopes recognized by >30% of specimens. Twelve of these common viral and bacterial epitopes agreed with previously mapped epitopes with p-values < 0.05. Additionally, we predicted 30 HSV2-specific epitopes that were 100% specific against HSV1 in novel and previously reported antigens. Experimentally validating these candidate epitopes could help identify diagnostic biomarkers, vaccine components, and therapeutic targets. The K-TOPE approach thus provides a powerful new tool to elucidate the organisms, antigens, and epitopes targeted by human antibody repertoires.
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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.