Evaluation of unrestrained replica-exchange simulations using dynamic walkers in temperature space for protein structure refinement.
A central problem of computational structural biology is the refinement of modeled protein structures taken from either comparative modeling or knowledge-based methods. Simulations are commonly used to achieve higher resolution of the structures at the all-atom level, yet methodologies that consistently yield accurate results remain elusive. In this work, we provide an assessment of an adaptive temperature-based replica exchange simulation method where the temperature clients dynamically walk in temperature space to enrich their population and exchanges near steep energetic barriers. This approach is compared to earlier work of applying the conventional method of static temperature clients to refine a dataset of conformational decoys. Our results show that, while an adaptive method has many theoretical advantages over a static distribution of client temperatures, only limited improvement was gained from this strategy in excursions of the downhill refinement regime leading to an increase in the fraction of native contacts. To illustrate the sampling differences between the two simulation methods, energy landscapes are presented along with their temperature client profiles.
Department of Cell Biology and Biochemistry, Molecular and Translational Sciences, USAMRIID, Fredrick, Maryland, United States of America; Advanced Academic Programs, Zanvyl Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, Maryland, United States of America.
Mark A
MA
Olson
Computational Sciences Division, U.S. Army Research Laboratory, Aberdeen Proving Ground, Maryland, United States of America.
Michael S
MS
Lee
D019295:Computational Biology / Q000379:methods*; D056004:Molecular Dynamics Simulation; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry*; D013696:Temperature; D013816:Thermodynamics
D011506:Proteins