Evidence map›Paper›PMID 28232828›Full record

ArticleFrontiers in immunology2017

Novel Structural Parameters of Ig-Ag Complexes Yield a Quantitative Description of Interaction Specificity and Binding Affinity.

Simon Marillet, Marie-Paule Lefranc, Pierre Boudinot, Frédéric Cazals

Abstract read
In one paragraph

Article in Frontiers in immunology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

  1. Review
  2. IMGTAntibodies (Basel, Switzerland) · 2026
    Review
  3. Article
  4. Article
  5. Antibody Sequence and Structure Analyses Using IMGTMethods in molecular biology (Clifton, N.J.) · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. IMGTAntibodies (Basel, Switzerland) · 2019
    Review
  14. Article
  15. Article
  16. 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

4 authors.

Simon MarilletVIM, INRA and Université Paris-Saclay, Jouy-en-josas, France; Université Côte d'Azur and Inria, Sophia Antipolis, France.
Marie-Paule LefrancIMGT, IGH, CNRS , Montpellier , France.
Pierre BoudinotVIM, INRA and Université Paris-Saclay , Jouy-en-josas , France.
Frédéric CazalsUniversité Côte d'Azur and Inria , Sophia Antipolis , France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibody-antigen complexes challenge our understanding, as analyses to date failed to unveil the key determinants of binding affinity and interaction specificity. We partially fill this gap based on novel quantitative analyses using two standardized databases, the IMGT/3Dstructure-DB and the structure affinity benchmark. First, we introduce a statistical analysis of interfaces which enables the classification of ligand types (protein, peptide, and chemical; cross-validated classification error of 9.6%) and yield binding affinity predictions of unprecedented accuracy (median absolute error of 0.878 kcal/mol). Second, we exploit the contributions made by CDRs in terms of position at the interface and atomic packing properties to show that in general, VH CDR3 and VL CDR3 make dominant contributions to the binding affinity, a fact also shown to be consistent with the enthalpy-entropy compensation associated with preconfiguration of CDR3. Our work suggests that the affinity prediction problem could be partially solved from databases of high resolution crystal structures of complexes with known affinity.

Indexed as

antibody–antigen complexbinding affinity predictioncomplementarity determining region 3interaction specificitymolecular recognition

Identifiers

PMID28232828
PMCPMC5298999

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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.