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Exploring the Effect of Enhanced Sampling on Protein Stability Prediction.

Daniel MarkthalerMaximilian FleckBartosz StankiewiczNiels Hansen
Published in: Journal of chemical theory and computation (2022)
Changes in protein stability due to side-chain mutations are evaluated by alchemical free-energy calculations based on classical molecular dynamics (MD) simulations in explicit solvent using the GROMOS force field. Three proteins of different complexity with a total number of 93 single-point mutations are analyzed, and the relative free-energy differences are discussed with respect to configurational sampling and (dis)agreement with experimental data. For the smallest protein studied, a 34-residue WW domain, the starting structure dependence of the alchemical free-energy changes, is discussed in detail. Deviations from previous simulations for the two other proteins are shown to result from insufficient sampling in the earlier studies. Hamiltonian replica exchange in combination with multiple starting structures and sufficient sampling time of more than 100 ns per intermediate alchemical state is required in some cases to reach convergence.
Keyphrases
  • molecular dynamics
  • density functional theory
  • protein protein
  • high resolution
  • small molecule
  • electronic health record
  • machine learning
  • big data
  • case control
  • artificial intelligence