Essential slow degrees of freedom in protein-surface simulations: A metadynamics investigation

Biochem Biophys Res Commun. 2018 Mar 29;498(2):274-281. doi: 10.1016/j.bbrc.2017.07.066. Epub 2017 Jul 15.

Abstract

Many proteins exhibit strong binding affinities to surfaces, with binding energies much greater than thermal fluctuations. When modelling these protein-surface systems with classical molecular dynamics (MD) simulations, the large forces that exist at the protein/surface interface generally confine the system to a single free energy minimum. Exploring the full conformational space of the protein, especially finding other stable structures, becomes prohibitively expensive. Coupling MD simulations with metadynamics (enhanced sampling) has fast become a common method for sampling the adsorption of such proteins. In this paper, we compare three different flavors of metadynamics, specifically well-tempered, parallel-bias, and parallel-tempering in the well-tempered ensemble, to exhaustively sample the conformational surface-binding landscape of model peptide GGKGG. We investigate the effect of mobile ions and ion charge, as well as the choice of collective variable (CV), on the binding free energy of the peptide. We make the case for explicitly biasing ions to sample the true binding free energy of biomolecules when the ion concentration is high and the binding free energies of the solute and ions are similar. We also make the case for choosing CVs that apply bias to all atoms of the solute to speed up calculations and obtain the maximum possible amount of information about the system.

Keywords: Adsorption; Metadynamics; Molecular dynamics simulations.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Electrolytes / chemistry
  • Hydrogen-Ion Concentration
  • Molecular Dynamics Simulation*
  • Peptides / chemistry*
  • Peptides / metabolism*
  • Silicon Dioxide
  • Thermodynamics

Substances

  • Electrolytes
  • Peptides
  • Silicon Dioxide