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Quantifying Asymmetry of Multimeric Proteins.

Julian T Brennecke1, Bert L de Groot1

  • 1Department of Theoretical and Computational Biophysics, Computational Biomolecular, Dynamics Group , Max Planck Institute for Biophysical Chemistry , Göttingen , Germany.

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|September 8, 2018
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Summary
This summary is machine-generated.

New computational tools, continuous symmetry measure (CSM) extension and functional asymmetry measure (FAME), quantify protein asymmetry. These methods analyze subunit contributions and functional motions in homooligomeric proteins, overcoming limitations of existing symmetric analysis approaches.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Structural Biology

Background:

  • Many proteins function as homooligomers, exhibiting either symmetric or asymmetric behavior.
  • Existing computational tools often average protein motions, masking asymmetric signals and hindering analysis of asymmetric dynamics.
  • Quantifying protein asymmetry is crucial for understanding the function of homooligomeric proteins.

Purpose of the Study:

  • To develop novel computational tools for quantifying asymmetry in homooligomeric proteins.
  • To extend the continuous symmetry measure (CSM) for detailed subunit contribution analysis.
  • To introduce the functional asymmetry measure (FAME) for assessing asymmetry related to protein function.

Main Methods:

  • Extension of the continuous symmetry measure (CSM) to analyze subunit contributions to asymmetry.
  • Development of the functional asymmetry measure (FAME) algorithm, based on predicting functionally relevant motions (PLS-FMA).
  • Application and validation of CSM and FAME on potassium channels (TREK-2, KcsA) and Transthyretin unfolding.

Main Results:

  • The extended CSM successfully quantified overall and subunit-based asymmetry in KcsA.
  • FAME identified and quantified asymmetric functional motions in TREK-2 and the unfolding pathway of Transthyretin.
  • Both developed algorithms demonstrated accurate prediction of protein asymmetry.

Conclusions:

  • The developed CSM extension and FAME provide powerful tools for analyzing asymmetry in homooligomeric proteins.
  • These methods overcome limitations of traditional symmetric analysis, enabling deeper insights into protein dynamics and function.
  • The tools are publicly available for application to diverse homooligomeric systems.