Evidence map›Paper›PMID 33828549›Full record

ArticleFrontiers in immunology2021

A Predictive Model of Antibody Binding in the Presence of IgG-Interacting Bacterial Surface Proteins.

Vibha Kumra Ahnlide, Therese de Neergaard, Martin Sundwall, Tobias Ambjörnsson, Pontus Nordenfelt

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Evaluation of Flathead Grey Mullets (International journal of molecular sciences · 2023
    Article
  3. Article
  4. Article
  5. Article
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

5 authors at 1 institution in 1 country.

Vibha Kumra AhnlideDivision of Infection Medicine, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden.
Therese de NeergaardDivision of Infection Medicine, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden.
Martin SundwallDivision of Infection Medicine, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden.
Tobias AmbjörnssonComputational Biology and Biological Physics, Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden.
Pontus NordenfeltDivision of Infection Medicine, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden.
Lund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many bacteria can interfere with how antibodies bind to their surfaces. This bacterial antibody targeting makes it challenging to predict the immunological function of bacteria-associated antibodies. The M and M-like proteins of group A streptococci (GAS) exhibit IgGFc-binding regions, which they use to reverse IgG binding orientation depending on the host environment. Unraveling the mechanism behind these binding characteristics may identify conditions under which bound IgG can drive an efficient immune response. Here, we have developed a biophysical model for describing these complex protein-antibody interactions. We show how the model can be used as a tool for studying the binding behavior of various IgG samples to M protein by performing

Indexed as

Models, ImmunologicalAntibodies, BacterialAntibodies, MonoclonalAntibody SpecificityAntigens, BacterialBacterial Outer Membrane ProteinsBinding, CompetitiveBinding Sites, AntibodyCarrier ProteinsEpitopesHumansImmunoglobulin GPhagocytosisProtein BindingStreptococcus pyogenesTHP-1 CellsAntibodies, BacterialAntibodies, MonoclonalAntigens, BacterialBacterial Outer Membrane ProteinsCarrier ProteinsEpitopesImmunoglobulin Gstreptococcal M proteinantibody bindingantibody interactionsantibody treatmentbiophysical modelgroup A StreptoccocusM protein

Identifiers

PMID33828549
PMCPMC8019711
OpenAlexW3136391590

What Socratic 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 Socratic graph.