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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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Disentangling Intrachain Folding from Interchain Assembly through Multidimensional Visualization.

Murilo N Sanches1, Pritam Ganguly2, Joan-Emma Shea3,4

  • 1Department of Physics, Institute of Biosciences, Humanities and Exact Sciences, São Paulo State University (UNESP), São José do Rio Preto, São Paulo 15054-000, Brazil.

The Journal of Physical Chemistry. B
|June 19, 2026
PubMed
Summary
This summary is machine-generated.

We enhanced the Energy Landscape Visualization Method (ELViM) to map protein structures, revealing how the tau P301L mutation promotes aggregation by stabilizing specific conformations. This tool aids in understanding protein folding and disease pathways.

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Published on: September 17, 2017

Area of Science:

  • Biophysics
  • Computational Biology
  • Structural Biology

Background:

  • Intrinsically disordered proteins (IDPs) exhibit conformational heterogeneity crucial for their function and disease association.
  • Characterizing IDP conformational landscapes is challenging due to their dynamic and diverse structures.

Purpose of the Study:

  • To introduce an enhanced algorithmic framework for the Energy Landscape Visualization Method (ELViM) for simultaneous mapping of monomeric and oligomeric conformational spaces.
  • To enable systematic disentanglement of intrachain folding dynamics from interchain assembly interactions driving protein aggregation.

Main Methods:

  • Developed an extended ELViM using a distance-based similarity metric and force projection embedding for unbiased low-dimensional representations.
  • Integrated density-guided Local Conformational Signature analysis and a consensus interchain contact mapping protocol.
  • Applied the enhanced ELViM to replica exchange molecular dynamics data of a tau protein fragment (wild type vs. P301L mutant).

Main Results:

  • The enhanced ELViM effectively captured continuous conformational transitions and identified key structural motifs like the aggregation-prone PHF6 segment.
  • The P301L mutation was shown to stabilize the tau protein, favoring compact ensembles with increased interchain contacts around the PHF6 region.
  • The method successfully distinguished between intrachain folding and interchain aggregation dynamics.

Conclusions:

  • The enhanced ELViM provides a quantitative and intuitive framework for exploring heterogeneous protein ensembles.
  • This workflow has broad applicability for studying protein folding, protein-protein interactions, and complex aggregation pathways, particularly in neurodegenerative diseases.
  • The findings offer insights into the molecular mechanisms underlying tau aggregation and the role of mutations.