Using enveloping distribution sampling to compute the folding free enthalpy of a β-peptide with a very unstable folded conformation in solution: The advantage of focused sampling using EDS

- Enveloping distribution sampling (EDS) is more efficient than standard MD simulation.
- EDS allows wider sampling than standard umbrella sampling.
- EDS can be used to obtain free energies and other properties of unstable conformations.

A peptide or a protein adopts a dynamic ensemble of conformations rather than a single structure in solution, although this ensemble may be dominated by one or a few particular folds. Computer simulation can be used to simulate the folding equilibria of peptides from which free energy differences between different conformations can be calculated. However, standard molecular dynamics (MD) simulation is rather inefficient when the relative free energy of a rather unstable fold is to be calculated. Here, we show, using a hepta-β-peptide with a very unstable 314-helical conformation as an example, that the method of enveloping distribution sampling (EDS) offers a much more efficient alternative to compute the relative free energy of different folds. The folding free energies obtained using the EDS method are compared with those obtained from three other methods: a standard MD simulation, from reweighting trajectories generated using hydrogen-bond restraints as umbrella potential energy term to enhance the sampling of a particular fold, and from one-step perturbation. The EDS method yields the widest sampling of relevant conformations and shows the fastest convergence.