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Sampling Long- versus Short-Range Interactions Defines the Ability of Force Fields To Reproduce the Dynamics of Intrinsically Disordered Proteins.

Davide MercadanteJohannes A WagnerIker V AramburuEdward A LemkeFrauke Gräter
Published in: Journal of chemical theory and computation (2017)
Molecular dynamics (MD) simulations have valuably complemented experiments describing the dynamics of intrinsically disordered proteins (IDPs), particularly since the proposal of models to solve the artificial collapse of IDPs in silico. Such models suggest redefining nonbonded interactions, by either increasing water dispersion forces or adopting the Kirkwood-Buff force field. These approaches yield extended conformers that better comply with experiments, but it is unclear if they all sample the same intrachain dynamics of IDPs. We have tested this by employing MD simulations and single-molecule Förster resonance energy transfer spectroscopy to sample the dimensions of systems with different sequence compositions, namely strong and weak polyelectrolytes. For strong polyelectrolytes in which charge effects dominate, all the proposed solutions equally reproduce the expected ensemble's dimensions. For weak polyelectrolytes, at lower cutoffs, force fields abnormally alter intrachain dynamics, overestimating excluded volume over chain flexibility or reporting no difference between the dynamics of different chains. The TIP4PD water model alone can reproduce experimentally observed changes in extensions (dimensions), but not quantitatively and with only weak statistical significance. Force field limitations are reversed with increased interaction cutoffs, showing that chain dynamics are critically defined by the presence of long-range interactions. Force field analysis aside, our study provides the first insights into how long-range interactions critically define IDP dimensions and raises the question of which length range is crucial to correctly sample the overall dimensions and internal dynamics of the large group of weakly charged yet highly polar IDPs.
Keyphrases
  • single molecule
  • molecular dynamics
  • energy transfer
  • density functional theory
  • living cells
  • emergency department
  • quantum dots
  • high resolution
  • machine learning
  • amino acid