Enhanced conformational sampling using enveloping distribution sampling.

To lessen the problem of insufficient conformational sampling in biomolecular simulations is still a major challenge in computational biochemistry. In this article, an application of the method of enveloping distribution sampling (EDS) is proposed that addresses this challenge and its sampling efficiency is demonstrated in simulations of a hexa-β-peptide whose conformational equilibrium encompasses two different helical folds, i.e., a right-handed 2.7(10∕12)-helix and a left-handed 3(14)-helix, separated by a high energy barrier. Standard MD simulations of this peptide using the GROMOS 53A6 force field did not reach convergence of the free enthalpy difference between the two helices even after 500 ns of simulation time. The use of soft-core non-bonded interactions in the centre of the peptide did enhance the number of transitions between the helices, but at the same time led to neglect of relevant helical configurations. In the simulations of a two-state EDS reference Hamiltonian that envelops both the physical peptide and the soft-core peptide, sampling of the conformational space of the physical peptide ensures that physically relevant conformations can be visited, and sampling of the conformational space of the soft-core peptide helps to enhance the transitions between the two helices. The EDS simulations sampled many more transitions between the two helices and showed much faster convergence of the relative free enthalpy of the two helices compared with the standard MD simulations with only a slightly larger computational effort to determine optimized EDS parameters. Combined with various methods to smoothen the potential energy surface, the proposed EDS application will be a powerful technique to enhance the sampling efficiency in biomolecular simulations.