Frontier Expansion Sampling: A Method to Accelerate Conformational Search by Identifying Novel Seed Structures for Restart

Abstract

Traditional molecular dynamics (MD) simulations have difficulties in tracking the slow molecular motions, at least partially due to the waste of sampling in already sampled regions. Here, we proposed a new enhanced sampling method, frontier expansion sampling (FEXS), to improve the sampling efficiency of molecular simulations by iteratively selecting seed structures diversely distributed at the "frontier" of an already sampled region to initiate new simulations. Different from other enhanced sampling methods, FEXS identifies the "frontier" seeds by integrating the Gaussian mixture model and the convex hull algorithm, which effectively improves the structural variation among the selected seeds and thus the descendant simulations. Validation in three protein systems, including the folding of chignolin, open-to-closed transition of maltodextrin binding protein, and internal conformational change of bovine pancreatic trypsin inhibitor, confirmed the effectiveness of this novel method in enhancing the sampling of conventional MD simulations to observe the large-scale protein conformational changes. When compared with other enhanced sampling methods like the structural dissimilarity sampling (SDS), FEXS reached at least the same level of sampling efficiency but was capable of providing complementary information in the three tested protein systems.

Recent Force Field Strategies for Intrinsically Disordered Proteins

“…By circularly running this workflow, the sampling points will gradually escape from the initial potential energy trap. The structure dissimilarity sampling (SDS), parallel cascade selection MD (PaCS-MD), − self-avoiding conformational sampling (SACS), complementary coordinates MD (CoCo-MD), and frontier expansion sampling (FES) all belongs to this type. The only difference between these methods is the algorithm they use to find the frontier structures, like the convex hull algorithm used in the FES method.…”

Global Fold Switching of the RafH Protein: Diverse Structures with a Conserved Pathway

“…teDA2 belongs to the “splitting strategy” framework for sampling. Still, its strategies, such as driving conformational changes, are very different from other methods (e.g., weighted ensemble path sampling and frontier expansion sampling) in this category. The details of teDA2 have been described in our previous paper .…”

Identifying a Feasible Transition Pathway between Two Conformational States for a Protein

“…For example, energy boosts are exerted on the original potential to reduce the heights of local barriers in accelerated MD (aMD); local minima in the already-sampled region are filled with positive history-dependent Gaussian potentials to avoid redundant sampling in metadynamics − and its variants; − deep-learning techniques are engaged for dimensionality reduction in VAE, , AE, , and VAMPnet as well as fitting free energy surface or biasing potential in reinforced dynamics, DeepVES and TALOS . Another class of methods enhances the sampling in the less sampled regions by iteratively selecting suitable seed structures as restarting points for new simulations, including but not limited to FEXS, SDS, CoCo MD, and weighted ensemble. , Besides, novel machine-learning-based methods trying to draw independent samples from the equilibrium states in one shot have emerged, exemplified by variational autoregressive networks and Boltzmann generators…”