Computational model for the IGF-II/IGF2r complex that is predictive of mutational and surface plasmon resonance data

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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Philippe Roche1, James Brown, Adam Denley

  • 1Division of Structural Biology, University of Oxford, Henry Wellcome Building for Genomic Medicine, Oxford, United Kingdom. robert@strubi.ox.ac.uk

Proteins
|June 3, 2006
PubMed

Insights

Insulin-like growth factors (IGFs) regulate cell growth and are crucial in cancer. This study models the interaction between IGF-II and its receptor (IGF2R) to understand IGF-II availability and its role in cancer development.

Area of Science:

  • Molecular biology
  • Biochemistry
  • Structural biology

Background:

  • Insulin-like growth factors (IGFs) are critical regulators of cell proliferation, differentiation, and transformation, playing a pivotal role in cancers like breast, prostate, and colon.
  • The availability of IGF-II for signaling IGF receptors is modulated by binding to the non-signaling IGF-II receptor (IGF2R).
  • Domain 11 of IGF2R (IGF2R-d11) is essential for mediating IGF-II binding.

Purpose of the Study:

  • To model the in silico protein-protein interaction between IGF-II and IGF2R-d11.
  • To identify the specific binding interface and structural basis for IGF-II and IGF2R-d11 interaction.
  • To provide experimental validation for the proposed binding model.

Main Methods:

  • Utilized crystal structure of IGF2R-d11 and NMR solution structure of IGF-II.
  • Employed 3D-Dock program for in silico modeling of protein-protein interaction.
  • Applied ensemble docking using 20 IGF-II structures and filtered models based on essential residue Ile1572.
  • Validated models using mutagenesis data and in vitro binding assays with IGF chimeras.

Main Results:

  • A plausible in silico model of the IGF-II and IGF2R-d11 complex was generated.
  • The model highlights the critical role of residue Ile1572 in IGF2R-d11 for IGF-II binding.
  • In vitro experiments using IGF chimeras provided supporting evidence for the proposed binding model.

Conclusions:

  • The study presents a detailed structural model for IGF-II binding to IGF2R domain 11.
  • This model enhances understanding of IGF-II availability regulation.
  • The findings contribute to comprehending the role of IGF signaling in cancer and offer potential therapeutic targets.

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