All-atom unbiased molecular dynamics simulations are now able to explore the microsecond to millisecond time scale for simple biological macromolecules in an explicit solvent. This allows for a careful comparison of the efficiency and accuracy of enhanced sampling methods versus long unbiased molecular dynamics in reconstructing conformational free energy surfaces. Here, we use an equilibrium microsecond-long molecular dynamics simulation as a reference to analyze the convergence properties of well-tempered metadynamics with two different sets of collective variables. In the case of the small and very diffusive Met-enkephalin pentapeptide, we find that the performance strongly depends on the choice of the collective variables (CVs). Using a set of principal component analysis derived eigenvectors, the convergence of the FES is faster than with both hand-picked CVs and unbiased molecular dynamics.
Comparing the efficiency of biased and unbiased molecular dynamics in reconstructing the free energy landscape of Met-enkephalin / Sutto, Ludovico; D'Abramo, Marco; Gervasio, Francesco Luigi. - In: JOURNAL OF CHEMICAL THEORY AND COMPUTATION. - ISSN 1549-9618. - 6:12(2010), pp. 3640-3646. [10.1021/ct100413b]
Comparing the efficiency of biased and unbiased molecular dynamics in reconstructing the free energy landscape of Met-enkephalin
D'ABRAMO, Marco;
2010
Abstract
All-atom unbiased molecular dynamics simulations are now able to explore the microsecond to millisecond time scale for simple biological macromolecules in an explicit solvent. This allows for a careful comparison of the efficiency and accuracy of enhanced sampling methods versus long unbiased molecular dynamics in reconstructing conformational free energy surfaces. Here, we use an equilibrium microsecond-long molecular dynamics simulation as a reference to analyze the convergence properties of well-tempered metadynamics with two different sets of collective variables. In the case of the small and very diffusive Met-enkephalin pentapeptide, we find that the performance strongly depends on the choice of the collective variables (CVs). Using a set of principal component analysis derived eigenvectors, the convergence of the FES is faster than with both hand-picked CVs and unbiased molecular dynamics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.