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Deciphering Allosteric Disease Mutations Through Intrinsic Dynamics.

Berat Kaskaloglu1, Ozge Duman1, Yigit Kutlu1

  • 1Department of Chemical Engineering, Bogazici University, 34342 Istanbul, Turkey; Polymer Research Center, Bogazici University, 34342 Istanbul, Turkey.

Journal of Molecular Biology
|July 5, 2025
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Summary
This summary is machine-generated.

Disease-causing mutations disrupt protein dynamics by altering allosteric regulation. This study reveals how mutations impact protein function through analysis of collective information flow, offering new insights into disease mechanisms.

Keywords:
Gaussian Network Modelallosteric dynamicscollectivitydiseases mutationstransfer entropy

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Area of Science:

  • Computational Biology
  • Structural Biology
  • Genomics

Background:

  • Allosteric regulation is crucial for biological processes, involving protein conformational changes.
  • Understanding how missense mutations affect protein function, especially indirectly, is a key challenge in disease genomics.

Purpose of the Study:

  • To investigate the link between somatic missense mutations and intrinsic protein dynamics.
  • To explore the allosteric roles of mutations in human diseases.

Main Methods:

  • Analysis of 2549 mutations across 190 human proteins from the ClinVar dataset.
  • Application of the Gaussian Network Model (GNM) based Transfer Entropy (TE) method.
  • Case study using the Transient Receptor Potential Mucolipin 1 (TRPML1) channel.

Main Results:

  • Sequential removal of global modes revealed layered, causal allosteric interactions.
  • Functional sites were observed to recur or emerge across various dynamic contexts.
  • Pathogenic mutations were found to coincide with key information sources/sinks in collective information flow.

Conclusions:

  • Disease-associated mutations perturb protein dynamics, impacting allosteric regulation.
  • The study provides mechanistic insights into mutation effects on protein function.
  • The framework offers a path toward allosteric-based interpretation of mutational impact in human disease.