Abstract
Simulating the functional motions of biomolecular systems requires large computational resources. We introduce a computationally inexpensive protocol for the systematic testing of hypotheses regarding the dynamic behavior of proteins and nucleic acids. The protocol is based on natural move Monte Carlo, a highly efficient conformational sampling method with built-in customization capabilities that allows researchers to design and perform a large number of simulations to investigate functional motions in biological systems. We demonstrate the use of this protocol on both a protein and a DNA case study. Firstly, we investigate the plasticity of a class II major histocompatibility complex in the absence of a bound peptide. Secondly, we study the effects of the epigenetic mark 5-hydroxymethyl on cytosine on the structure of the Dickerson-Drew dodecamer. We show how our customized natural moves protocol can be used to investigate causal relationships of functional motions in biological systems.
Highlights
Functional motions in biomolecules are central to many biological processes [1]
In a recent study we showed that natural-move Monte Carlo (NMMC) yields comparable results to and is three orders-of-magnitude faster than conventional molecular dynamics (MD) when simulating peptide detachment from class I major histocompatibility complex (MHC I) molecules [21]
We investigate functional motions in the class II major histocompatibility complex (MHC II) and in the second, we study the structural effects of an epigenetic mark on a DNA model system
Summary
Functional motions in biomolecules are central to many biological processes [1]. Molecular simulations are often used as a tool to investigate these dynamics and interpret [2,3] and/or refine [4] experimental data or inspire new experiments [5].Large improvements in computational resources and algorithms have been made since the first molecular simulation of a protein in 1977 [6,7]. Recent milestones include the 50-ns molecular dynamics (MD) simulation of the full satellite tobacco mosaic virus with 1,000,000 particles [8], the Folding@Home project that used >400,000 personal computers to study challenging problems such as protein folding [9], and a study that presented millisecond simulations to study the folding pathways of small fast-folding proteins [10]. Despite these advances, the high dimensionality and complex energy surfaces still pose a challenge for simulations of large biomolecules [11,12]. Essential dynamics coarse-graining (ED-CG) identifies sites that reflect the essential dynamics
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