Evaluation of unrestrained replica-exchange simulations using dynamic walkers in temperature space for protein structure refinement.

Mark A Olson,Michael S Lee

doi:10.1371/journal.pone.0096638

Abstract

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.

Highlights

The structure-based discovery of small-molecule protein inhibitors and protein-derived biopharmaceuticals requires the structural target to be of sufficient resolution to capture accurate modeling details
A common approach for the conformational sampling of decoy structures is the application of molecular dynamics parallel tempering, or commonly known as temperature-based replica exchange (T-ReX) [15]
Computational sampling is conducted by combining the selfguided Langevin dynamics (SGLD) simulation method with replica-exchange simulations [23,24], and we provide a comparison between the application of dynamic client walkers in temperature space and that of using a static distribution of temperatures

Summary

Introduction

The structure-based discovery of small-molecule protein inhibitors and protein-derived biopharmaceuticals requires the structural target to be of sufficient resolution to capture accurate modeling details. A common approach for the conformational sampling of decoy structures is the application of molecular dynamics parallel tempering, or commonly known as temperature-based replica exchange (T-ReX) [15]. Unlike traditional molecular dynamics simulations, T-ReX is a generalized ensemble method of applying multiple parallel simulations in which each replica is executed at a different temperature. While a fixed temperature distribution is thought to be ideal for many applications [16], it becomes pathological for cases where a sharp energy barrier separates conformational states [17]. A sharp transition is common to modeling protein folding-unfolding events [17], in general a highly frustrated energy landscape can hinder temperature swapping among clients

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Results

Conclusion