ArticleeLife2017
Computationally-driven identification of antibody epitopes.
Article in eLife, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Identification and Validation of B-Cell Epitopes on the VP1 Protein of Parvovirus B19 through Molecular Docking and Dynamics Simulation.ACS omega · 2025Article
- EpiScan: accurate high-throughput mapping of antibody-specific epitopes using sequence information.NPJ systems biology and applications · 2024Article
- Structure-based design of nanobodies that inhibit seeding of Alzheimer's patient-extracted tau fibrils.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Recent Progress in Antibody Epitope Prediction.Antibodies (Basel, Switzerland) · 2023Review
- The ClusPro AbEMap web server for the prediction of antibody epitopes.Nature protocols · 2023Review
- Structure-free antibody paratope similarity prediction foriScience · 2023Article
- Article
- IGPred-HDnet: Prediction of Immunoglobulin Proteins Using Graphical Features and the Hierarchal Deep Learning-Based Approach.Computational intelligence and neuroscience · 2023Article
- Development and characterization of a camelid derived antibody targeting a linear epitope in the hinge domain of human PCSK9 protein.Scientific reports · 2022Article
- Article
- Computational epitope binning reveals functional equivalence of sequence-divergent paratopes.Computational and structural biotechnology journal · 2022Article
- Design of peptides with high affinity binding to a monoclonal antibody as a basis for immunotherapy.Peptides · 2021Article
- An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants.Structure (London, England : 1993) · 2021Article
- Challenges in Detection of Serum Oncoprotein: Relevance to Breast Cancer Diagnostics.Breast cancer (Dove Medical Press) · 2021Review
- Robustification of RosettaAntibody and Rosetta SnugDock.PloS one · 2021Article
- Deimmunization of protein therapeutics - Recent advances in experimental and computational epitope prediction and deletion.Computational and structural biotechnology journal · 2021Review
- Computational approaches to therapeutic antibody design: established methods and emerging trends.Briefings in bioinformatics · 2020Review
- Characterizing Epitope Binding Regions of Entire Antibody Panels by Combining Experimental and Computational Analysis of Antibody: Antigen Binding Competition.Molecules (Basel, Switzerland) · 2020Article
- Computer-guided binding mode identification and affinity improvement of an LRR protein binder without structure determination.PLoS computational biology · 2020Article
- How repertoire data are changing antibody science.The Journal of biological chemistry · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Understanding where antibodies recognize antigens can help define mechanisms of action and provide insights into progression of immune responses. We investigate the extent to which information about binding specificity implicitly encoded in amino acid sequence can be leveraged to identify antibody epitopes. In computationally-driven epitope localization, possible antibody-antigen binding modes are modeled, and targeted panels of antigen variants are designed to experimentally test these hypotheses. Prospective application of this approach to two antibodies enabled epitope localization using five or fewer variants per antibody, or alternatively, a six-variant panel for both simultaneously. Retrospective analysis of a variety of antibodies and antigens demonstrated an almost 90% success rate with an average of three antigen variants, further supporting the observation that the combination of computational modeling and protein design can reveal key determinants of antibody-antigen binding and enable efficient studies of collections of antibodies identified from polyclonal samples or engineered libraries.
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What OpenQuestion holds
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.