Evidence map›Paper›PMID 28527239›Full record

ArticleeLife2017

The structure of a LAIR1-containing human antibody reveals a novel mechanism of antigen recognition.

Fu-Lien Hsieh, Matthew K Higgins

Open access · goldAbstract read
In one paragraph

Article in eLife, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Variable Surface Antigens ofProtein and peptide letters · 2024
    Review
  3. Article
  4. Review
  5. Mechanisms for Host Immune Evasion Mediated byFrontiers in immunology · 2022
    Review
  6. Article
  7. Structure of theProceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  8. Review
  9. Review
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

2 authors at 1 institution in 2 countries.

Fu-Lien HsiehDepartment of Biochemistry, University of Oxford, Oxford, United Kingdom.
Matthew K HigginsDepartment of Biochemistry, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-2870-1955
California Institute of Technology · US

Funding

Wellcome Trust 101020/Z/13/Z
6 · The paper itself

Abstract

Antibodies are critical components of the human adaptive immune system, providing versatile scaffolds to display diverse antigen-binding surfaces. Nevertheless, most antibodies have similar architectures, with the variable immunoglobulin domains of the heavy and light chain each providing three hypervariable loops, which are varied to generate diversity. The recent identification of a novel class of antibody in humans from malaria endemic regions of Africa was therefore surprising as one hypervariable loop contains the entire collagen-binding domain of human LAIR1. Here, we present the structure of the Fab fragment of such an antibody. We show that its antigen-binding site has adopted an architecture that positions LAIR1, while itself being occluded. This therefore represents a novel means of antigen recognition, in which the Fab fragment of an antibody acts as an adaptor, linking a human protein insert with antigen-binding potential to the constant antibody regions which mediate immune cell recruitment.

Indexed as

AntibodiesAntigensBinding SitesCrystallography, X-RayHumansImmunoglobulin Fab FragmentsModels, MolecularProtein BindingProtein ConformationReceptors, ImmunologicAntibodiesAntigensImmunoglobulin Fab Fragmentsleukocyte-associated immunoglobulin-like receptor 1Receptors, Immunologicantibody structureimmunologyLAIR1nonenovel antigen recognition

Identifiers

PMID28527239
PMCPMC5459573
OpenAlexW2615811644

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.