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Updated: Jun 24, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Published on: July 14, 2015
Liaison amid disorder: non-native interactions may underpin long-range coupling in proteins
1Department of Biochemistry, University of Toronto, 1 King's College Circle, Toronto, Ontario, Canada. chan@arrhenius.med.toronto.edu
Interactions in non-native protein conformations reveal thermodynamic coupling between distant residues. This lattice-model study highlights the role of disordered conformational ensembles in protein behavior.
Area of Science:
- Protein structural biology
- Biophysics
- Computational biology
Background:
- Understanding protein behavior relies on characterizing residue interactions.
- Disordered conformational ensembles are increasingly recognized for their importance in protein function.
- Thermodynamic coupling between amino acid residues influences protein stability and dynamics.
Purpose of the Study:
- To investigate thermodynamic coupling between distant residues in globular proteins.
- To explore the role of non-native conformations in protein behavior.
- To contribute to the understanding of disordered conformational ensembles.
Main Methods:
- Utilized a lattice-model simulation approach.
- Analyzed double-mutant cycles to assess thermodynamic coupling.
- Studied interactions within non-native protein conformations.
Main Results:
- Demonstrated that interactions in non-native conformations can induce thermodynamic coupling between distant residues.
- Provided evidence for the significant role of disordered conformational ensembles in protein behavior.
- Quantified the coupling effects in a model protein system.
Conclusions:
- Non-native conformations are critical for understanding thermodynamic coupling in proteins.
- Disordered conformational ensembles play a crucial, often underestimated, role in protein dynamics and function.
- Lattice-model studies offer valuable insights into complex protein interactions.
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