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A predicted structural interactome reveals binding interference from intrinsically disordered regions.

Junhui Peng1, Li Zhao1

  • 1Laboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY 10065, USA.

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|September 2, 2025
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Summary
This summary is machine-generated.

This study predicts protein-protein interactions in Drosophila using AlphaFold2, revealing that functional data and disordered regions are key to accurate predictions. An interactive web interface is provided for further research.

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Area of Science:

  • Molecular Biology
  • Structural Biology
  • Bioinformatics

Background:

  • Cellular processes rely on complex protein-protein interaction networks.
  • Understanding these interactions is crucial, yet many remain poorly characterized, especially in non-mammalian species like Drosophila.
  • Deep learning advances offer new avenues for predicting molecular interactions.

Purpose of the Study:

  • To predict protein-protein interactions in Drosophila using AlphaFold2 multimer.
  • To investigate the contribution of physical and functional datasets to prediction accuracy.
  • To analyze the role of intrinsically disordered regions in high-confidence interactions.

Main Methods:

  • Utilized AlphaFold2 multimer for predicting protein-protein interactions.
  • Integrated both physical and functional association datasets for Drosophila.
  • Performed detailed structural analysis of predicted interactions.

Main Results:

  • Functional associations significantly improved the confidence of predicted protein-protein interactions.
  • Intrinsically disordered regions were identified as important in high-confidence predicted interactions.
  • An interactive web interface was developed to present interaction predictions.

Conclusions:

  • Functional data integration enhances the accuracy of physical protein-protein interaction predictions.
  • Disordered regions play a critical role in mediating protein-protein interactions.
  • The developed interface facilitates further research into Drosophila protein interactions.