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A Computational Protocol to Analyze PDZ/PBM Affinity Data Obtained by High-Throughput Holdup Assay.

Pau Jané1, Lionel Chiron2, Goran Bich1

  • 1(Equipe labelisée Ligue, 2015) Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U1258 / CNRS UMR 7104 / Université de Strasbourg, Illkirch, France.

Methods in Molecular Biology (Clifton, N.J.)
|May 20, 2021
PubMed
Summary

The holdup assay quantifies protein-protein interactions using chromatography. Bioinformatic tools improve data accuracy for analyzing PDZ domain-motif binding specificities.

Keywords:
Computational approachElectropherogram superimpositionHoldup assayPDZ–PBM interactionProcessing accuracy

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Molecular Biology

Background:

  • The holdup assay is a high-throughput method for measuring binding intensities (BI) and equilibrium binding affinity constants.
  • It is routinely used to profile the binding specificity of PDZ-binding motifs (PBMs) against the human PDZome.
  • Electropherogram quality from capillary electrophoresis can affect assay accuracy and reproducibility.

Purpose of the Study:

  • To present a curated bioinformatic method for processing holdup assay data.
  • To improve the accuracy and reproducibility of binding intensity measurements.
  • To introduce new methods for plotting and comparing PBM-PDZ interaction data.

Main Methods:

  • Utilizing bioinformatic tools for enhanced electropherogram superimposition.
  • Applying curated protocols for processing holdup assay data.
  • Employing open Python packages for computational analysis.

Main Results:

  • Improved extraction of reliable binding intensities (BI) from electropherograms.
  • Enhanced accuracy and reproducibility in measuring PBM-PDZ interactions.
  • Development of novel visualization techniques for binding specificity profiles.

Conclusions:

  • Bioinformatic processing significantly enhances holdup assay reliability.
  • The presented protocol offers a robust approach for PBM-PDZ interaction analysis.
  • Open-source computational tools facilitate the application of this method.