Evidence map›Paper›PMID 34898603›Full record

ArticlePLoS computational biology2021

Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies.

Sarah A Robinson, Matthew I J Raybould, Constantin Schneider, Wing Ki Wong, Claire Marks, Charlotte M Deane

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
2.8field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 55 citations in OpenAlex.

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  12. Computational detection of antigen-specific B cell receptors following immunization.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  13. Article
  14. Building Representation Learning Models for Antibody Comprehension.Cold Spring Harbor perspectives in biology · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Sarah A RobinsonOxford Protein Informatics Group, Department of Statistics, University of Oxford, United Kingdom.ORCID 0000-0003-2500-0173
Matthew I J RaybouldOxford Protein Informatics Group, Department of Statistics, University of Oxford, United Kingdom.ORCID 0000-0002-5663-5297
Constantin SchneiderOxford Protein Informatics Group, Department of Statistics, University of Oxford, United Kingdom.ORCID 0000-0002-2579-0307
Wing Ki WongOxford Protein Informatics Group, Department of Statistics, University of Oxford, United Kingdom.ORCID 0000-0003-4029-6902
Claire MarksOxford Protein Informatics Group, Department of Statistics, University of Oxford, United Kingdom.ORCID 0000-0001-5931-2437
Charlotte M DeaneOxford Protein Informatics Group, Department of Statistics, University of Oxford, United Kingdom.
Oxford Research Group · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying the epitope of an antibody is a key step in understanding its function and its potential as a therapeutic. Sequence-based clonal clustering can identify antibodies with similar epitope complementarity, however, antibodies from markedly different lineages but with similar structures can engage the same epitope. We describe a novel computational method for epitope profiling based on structural modelling and clustering. Using the method, we demonstrate that sequence dissimilar but functionally similar antibodies can be found across the Coronavirus Antibody Database, with high accuracy (92% of antibodies in multiple-occupancy structural clusters bind to consistent domains). Our approach functionally links antibodies with distinct genetic lineages, species origins, and coronavirus specificities. This indicates greater convergence exists in the immune responses to coronaviruses than is suggested by sequence-based approaches. Our results show that applying structural analytics to large class-specific antibody databases will enable high confidence structure-function relationships to be drawn, yielding new opportunities to identify functional convergence hitherto missed by sequence-only analysis.

Indexed as

Amino Acid SequenceAnimalsAntibodies, NeutralizingAntibodies, ViralAntibody SpecificityAntigen-Antibody ComplexAntigen-Antibody ReactionsAntigens, ViralComputational BiologyCoronavirusCOVID-19Databases, ChemicalEpitope MappingEpitopes, B-LymphocyteHumansMiceAntibodies, NeutralizingAntibodies, ViralAntigen-Antibody ComplexAntigens, ViralEpitopes, B-LymphocyteSingle-Domain Antibodies

Identifiers

PMID34898603
PMCPMC8700021
OpenAlexW4200425120

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.