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Adaptive enhanced sampling with a path-variable for the simulation of protein folding and aggregation.

Emanuel K Peter1

  • 1Department of Pharmacy and Chemistry, Institute of Physical and Theoretical Chemistry, University of Regensburg, Regensburg, Germany.

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|December 10, 2017
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We developed a new adaptive enhanced sampling molecular dynamics (MD) method to speed up simulations of protein folding and aggregation. This method improves sampling efficiency and reveals entropic barriers in Alzheimer's amyloid-beta aggregation.

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Area of Science:

  • Computational Chemistry
  • Biophysics
  • Molecular Dynamics

Background:

  • Protein folding and aggregation are complex processes crucial for biological function and disease.
  • Accelerating molecular dynamics (MD) simulations is essential for studying these large-scale phenomena.
  • Existing enhanced sampling methods have limitations in efficiency and applicability.

Purpose of the Study:

  • To introduce a novel adaptive enhanced sampling molecular dynamics (MD) method for accelerated simulations.
  • To develop and validate algorithms for enhanced sampling of biomolecular processes.
  • To investigate protein folding and aggregation mechanisms, including amyloid-beta peptide aggregation.

Main Methods:

  • Development of a path-variable based on unbiased momenta and displacements for bias definition.
  • Derivation of three algorithms: general adaptive bias MD, adaptive path-sampling, and a hybrid method.
  • Application of the methods to SPC/E water, dialanine, TrpCage folding, and Alzheimer's amyloid-beta (Aβ 25-35) hexamer aggregation.

Main Results:

  • The hybrid methodology demonstrated improved force correlation and accelerated phase space sampling.
  • Simulations of dialanine and TrpCage folding showed good agreement with literature data.
  • Analysis of Aβ 25-35 hexamer aggregation indicated that transitions are dominated by entropic barriers.

Conclusions:

  • The novel adaptive enhanced sampling MD method effectively accelerates simulations of protein folding and aggregation.
  • Conformational entropy appears to be a significant rate-limiting factor in amyloid fibril formation.
  • The developed algorithms provide a powerful tool for studying complex biomolecular systems.