Molecular simulations of protein disorderThis paper is one of a selection of papers published in this special issue entitled “Canadian Society of Biochemistry, Molecular &amp; Cellular Biology 52nd Annual Meeting — Protein Folding: Principles and Diseases” and has undergone the Journal's usual peer review process.

Rauscher, Sarah; Pomès, Régis

doi:10.1139/o09-169

Cited by 70 publications

(34 citation statements)

References 169 publications

(319 reference statements)

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“…The recent focus on MD as a tool for exploring nonequilibrium processes has driven the simulations to longer timescales than ever before [10-13]. The data gathered from such simulations can be extensive so clustering has a key role to play in summarizing the simulation output without losing the key properties and behaviors of interest.…”

Section: Introductionmentioning

confidence: 99%

Validating clustering of molecular dynamics simulations using polymer models

2011

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BackgroundMolecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models.ResultsWe develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters.ConclusionsWe have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.

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Section: Introductionmentioning

confidence: 99%

Validating clustering of molecular dynamics simulations using polymer models

2011

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“…For intrinsically disordered proteins (IDPs) in general, recent computational and experimental advances have provided insights into a number of normal and pathological cellular processes. [21][22][23][24][25][26] In the present study, we build off of these advances to map the conformational free energy surface of CcdA, paying particular attention to the disordered C-terminal arms. Our free energy simulations are compared to experimental data from single-pair Fšrster resonance energy transfer (spFRET) and existing NMR measurements.…”

Section: Introductionmentioning

confidence: 99%

Hidden States within Disordered Regions of the CcdA Antitoxin Protein

et al. 2017

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The bacterial toxin-antitoxin system CcdB-CcdA provides a mechanism for the control of cell death and quiescence. The antitoxin CcdA protein is a homodimer composed of two monomers that each contain a folded N-terminal region and an intrinsically disordered C-terminal arm.Binding of the intrinsically disordered C-terminal arm of CcdA to the toxin CcdB prevents CcdB from inhibiting DNA Gyrase and thereby averts cell-death. Accurate models of the unfolded state of the partially disordered CcdA antitoxin can therefore provide insight into general mechanisms whereby protein disorder regulates events that are crucial to cell survival. Previous structural studies were able to model only two of three distinct structural states Ð a closed state and an open state Ð that were adopted by the C-terminal arm of CcdA. Using a combination of free energy simulations, single-pair Fšrster resonance energy transfer experiments, and existing NMR data, we developed structural models for all three states of the protein. Contrary to prior studies, we find that CcdA samples a previously unknown state where only one of the disordered C-terminal arms makes extensive contacts with the folded N-terminal domain. Moreover, our data suggest that previously unobserved conformational states play a role in regulating antitoxin concentrations and the activity of CcdAÕs cognate toxin. These data demonstrate that intrinsic disorder in CcdA provides a mechanism for regulating cell-fate.3

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“…the number of experimental observables is below the number of conformational states. Computational studies are, in principle, ideally suited for the study of IDPs, allowing single molecule investigation with a spatial resolution up to single atoms and a time resolution of femtoseconds [15]. Especially in combination with experimental techniques like nuclear magnetic resonance (NMR) spectroscopy an atomistic understanding of the range of accessible conformations is available [16, 17].…”

Section: Introductionmentioning

confidence: 99%

Transient helicity in intrinsically disordered Axin-1 studied by NMR spectroscopy and molecular dynamics simulations

et al. 2017

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Many natural proteins are, as a whole or in part, intrinsically disordered. Frequently, such intrinsically disordered regions (IDRs) undergo a transition to a defined and often helical conformation upon binding to partner molecules. The intrinsic propensity of an IDR sequence to fold into a helical conformation already in the absence of a binding partner can have a decisive influence on the binding process and affinity. Using a combination of NMR spectroscopy and molecular dynamics (MD) simulations we have investigated the tendency of regions of Axin-1, an intrinsically disordered scaffolding protein of the WNT signaling pathway, to form helices in segments interacting with binding partners. Secondary chemical shifts from NMR measurements show an increased helical population in these regions. Systematic application of MD advanced sampling approaches on peptide segments of Axin-1 reproduces the experimentally observed tendency and allows insights into the distribution of segment conformations and free energies of helix formation. The results, however, were found to dependent on the force field water model. Recent water models specifically designed for IDRs significantly reduce the predicted helical content and do not improve the agreement with experiment.

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Cited by 70 publications

References 169 publications

Validating clustering of molecular dynamics simulations using polymer models

Validating clustering of molecular dynamics simulations using polymer models

Hidden States within Disordered Regions of the CcdA Antitoxin Protein

Transient helicity in intrinsically disordered Axin-1 studied by NMR spectroscopy and molecular dynamics simulations

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