Enhanced sampling method with coarse graining of conformational space

The sampling of conformations in the molecular simulations for systems with complicated free energy landscapes is always difficult. Here, we report a method for enhanced sampling based on the coarse-graining of conformational space. In this method, the locally converged region of the conformational space is coarse-grained with its population characterized by the related average residence time and visiting number, and at the same time, the direct simulations inside it are eliminated. The detailed balance is satisfied by updating the visiting number and generating outgoing trajectories of this region. This kind of coarse-graining operation can be further carried out by merging all the neighboring regions which are already converged together. The global equilibrium is achieved when the local equilibrated regions cover all the interested areas of the landscape. We tested the method by applying it to two model potentials and one protein system with multiple-basin energy landscapes. The sampling efficiency is found to be enhanced by more than three orders of magnitude compared to conventional molecular simulations, and are comparable with other widely used enhanced sampling methods. In addition, the kinetic information can also be well captured. All these results demonstrate that our method can help to solve the sampling problems efficiently and precisely without applying high temperatures or biasing potentials.

Automated summary

A method for enhanced sampling based on the coarse-graining of conformational space is proposed in this study, which significantly improves sampling efficiency and achieves global equilibrium when local equilibrated regions cover all interested areas of the landscape. Tested on model potentials and a protein system, the method showed enhanced sampling efficiency by more than three orders of magnitude, demonstrating its ability to efficiently solve sampling problems without high temperatures or biasing potentials.