Optimized parallel tempering simulations of proteins

Abstract

We apply a recently developed adaptive algorithm that systematically improves the efficiency of parallel tempering or replica exchange methods in the numerical simulation of small proteins. Feedback iterations allow us to identify an optimal set of temperatures/replicas which are found to concentrate at the bottlenecks of the simulations. A measure of convergence for the equilibration of the parallel tempering algorithm is discussed. We test our algorithm by simulating the 36-residue villin headpiece sub-domain HP-36 wherewe find a lowest-energy configuration with a root-mean-square-deviation of less than 4 Angstroem to the experimentally determined structure.

22 pages, 7 figures

References in corpus (2)

• Optimizing the ensemble for equilibration in broad-histogram Monte Carlo simulations
• Performance Limitations of Flat Histogram Methods and Optimality of Wang-Landau Sampling

Cited by in corpus (21)

• Enhanced sampling methods for molecular dynamics simulations
• Generalized Ensemble and Tempering Simulations: A Unified View
• Make life simple: unleash the full power of the parallel tempering algorithm
• Comparing Monte Carlo methods for finding ground states of Ising spin glasses: population annealing, simulated annealing and parallel tempering
• Machine Learning Implicit Solvation for Molecular Dynamics
• From data to noise to data: mixing physics across temperatures with generative artificial intelligence
• On Dynamics and Optimal Number of Replicas in Parallel Tempering Simulations
• Optimizing Replica Exchange Moves For Molecular Dynamics
• Physics-Inspired Heuristics for Soft MIMO Detection in 5G New Radio and Beyond
• Correlations between the dynamics of parallel tempering and the free-energy landscape in spin glasses
• Annealed importance sampling of dileucine peptide
• Equilibrium Sampling in Biomolecular Simulation
• Comparing parallel and simulated tempering enhanced sampling algorithms at phase transition regimes
• Protein simulations combining an all-atom force field with a Go term
• Optimized Broad-Histogram Ensembles for the Simulation of Quantum Systems
• Backbone and Sidechain Ordering in a small Protein
• Side chain and backbone ordering in a polypeptide
• Optimized broad-histogram simulations for strong first-order phase transitions: Droplet transitions in the large-Q Potts model
• Efficiency of Monte Carlo Sampling in Chaotic Systems
• Optimized Folding Simulations of Protein A
• Exploring Quantum Annealing for Coarse-Grained Protein Folding