Simple but predictive protein models

Ding, Feng; Dokholyan, Nikolay V.

doi:10.1016/j.tibtech.2005.07.001

Cited by 73 publications

(73 citation statements)

References 46 publications

(60 reference statements)

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“…Here, we introduce a discrete molecular dynamics (DMD) (Ding and Dokholyan 2005) approach toward ab initio 3D RNA structure predictions and characterization of RNA folding dynamics using simplified structural models. In contrast to the traditional molecular dynamics simulations, which are computation-intensive and hence expensive in probing RNA folding dynamics over long time scales, the DMD algorithm provides rapid conformational sampling (Ding and Dokholyan 2005).…”

Section: Introductionmentioning

confidence: 99%

“…In contrast to the traditional molecular dynamics simulations, which are computation-intensive and hence expensive in probing RNA folding dynamics over long time scales, the DMD algorithm provides rapid conformational sampling (Ding and Dokholyan 2005). It is demonstrated in numerous studies that the DMD method is suitable for studying various properties of protein folding (Chen et al 2008) and protein aggregation (Ding and Dokholyan 2005), and for probing different biomolecular mechanisms (Ding and Dokholyan 2005;Sharma et al 2006Sharma et al , 2007.…”

Section: Introductionmentioning

confidence: 99%

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Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

Ding

Sharma

Chalasani

et al. 2008

RNA

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265

378

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RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 Å deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNA Phe , pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting nonhierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

Ding

Sharma

Chalasani

et al. 2008

RNA

Self Cite

265

378

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show abstract

“…In the past decade, a variety of coarse-grained protein models, which integrate a large number of degrees of freedom into a few, have been developed and used extensively (for reviews, see Refs. [37,38,39]). …”

Section: Introductionmentioning

confidence: 99%

Computer Simulations of Alzheimers Amyloid β-Protein Folding and Assembly

Urbanc¹,

Cruz²,

Teplow³

et al. 2006

CAR

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Pathological folding and aggregation of the amyloid -protein (A ) are widely perceived as central to understanding Alzheimer's disease (AD) at the molecular level. Experimental approaches to study A self-assembly are limited, because most relevant aggregates are quasi-stable and inhomogeneous. In contrast, simulations can provide significant insights into the problem, including specific sites in the molecule that would be attractive for drug targeting and details of the assembly pathways leading to the production of toxic assemblies. Here we review computer simulation approaches to understanding the structural biology of A . We discuss the ways in which these simulations help guide experimental work, and in turn, how experimental results guide the development of theoretical and simulation approaches that may be of general utility in understanding pathologic protein folding and assembly.

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“…Additionally, faster simulation speeds are attainable with the DMD approach through simplification of protein models. Overall, an increase in simulation speed of 5-10 orders of magnitude is attainable using DMD [62]. Jang et al [56] used DMD and simplified protein models with Gō interactions [63] to probe protein folding kinetics.…”

Section: Studying Protein Foldingmentioning

confidence: 99%

Protein folding: Then and now

Chen

Ding

Nie

et al. 2008

Archives of Biochemistry and Biophysics

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Over the past three decades the protein folding field has undergone monumental changes. Originally a purely academic question, how a protein folds has now become vital in understanding diseases and our abilities to rationally manipulate cellular life by engineering protein folding pathways. We review and contrast past and recent developments in the protein folding field. Specifically, we discuss the progress in our understanding of protein folding thermodynamics and kinetics, the properties of evasive intermediates, and unfolded states. We also discuss how some abnormalities in protein folding lead to protein aggregation and human diseases.

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Simple but predictive protein models

Cited by 73 publications

References 46 publications

Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

Computer Simulations of Alzheimers Amyloid β-Protein Folding and Assembly

Protein folding: Then and now

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Simple but predictive protein models

Cited by 73 publications

References 46 publications

Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

Computer Simulations of Alzheimers Amyloid &#946;-Protein Folding and Assembly

Protein folding: Then and now

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Computer Simulations of Alzheimers Amyloid β-Protein Folding and Assembly