We propose a general framework for the efficient sampling of conformational equilibria in complex systems and the generation of associated free energy hypersurfaces in terms of a set of collective variables. The method is a strategic synthesis of the adiabatic free energy dynamics approach, previously introduced by us and others, and existing schemes using Gaussian-based adaptive bias potentials to disfavor previously visited regions. In addition, we suggest sampling the thermodynamic force instead of the probability density to reconstruct the free energy hypersurface. All these elements are combined into a robust extended phase-space formalism that can be easily incorporated into existing molecular dynamics packages. The unified scheme is shown to outperform both metadynamics and adiabatic free energy dynamics in generating two-dimensional free energy surfaces for several example cases including the alanine dipeptide in the gas and aqueous phases and the met-enkephalin oligopeptide. In addition, the method can efficiently generate higher dimensional free energy landscapes, which we demonstrate by calculating a four-dimensional surface in the Ramachandran angles of the gas-phase alanine tripeptide.
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Physical and Theoretical Chemistry