Coupling Accelerated Molecular Dynamics Methods with Thermodynamic Integration Simulations
Author(s) -
César Augusto F. de Oliveira,
Donald Hamelberg,
J. Andrew McCammon
Publication year - 2008
Publication title -
journal of chemical theory and computation
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/ct800160q
Subject(s) - molecular dynamics , maxima and minima , thermodynamic integration , work (physics) , degrees of freedom (physics and chemistry) , statistical physics , potential energy , energy (signal processing) , coupling (piping) , convergence (economics) , potential of mean force , computer science , chemical physics , physics , chemistry , materials science , thermodynamics , computational chemistry , classical mechanics , mathematics , mathematical analysis , quantum mechanics , economic growth , economics , metallurgy
In this work we propose a straightforward and efficient approach to improve accuracy and convergence of free energy simulations in condensed-phase systems. We also introduce a new accelerated Molecular Dynamics (MD) approach in which molecular conformational transitions are accelerated by lowering the energy barriers while the potential surfaces near the minima are left unchanged. All free energy calculations were performed on the propane-to-propane model system. The accuracy of free energy simulations was significantly improved when sampling of internal degrees of freedom of solute was enhanced. However, accurate and converged results were only achieved when the solvent interactions were taken into account in the accelerated MD approaches. The analysis of the distribution of boost potential along the free energy simulations showed that the new accelerated MD approach samples efficiently both low- and high-energy regions of the potential surface. Since this approach also maintains substantial populations in regions near the minima, the statistics are not compromised in the thermodynamic integration calculations, and, as a result, the ensemble average can be recovered.
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