Constrained geometric simulation of diffusive motion in proteins

Wells, Stephen A.; Menor, Scott; Hespenheide, Brandon M.; Thorpe, M. F.

doi:10.1088/1478-3975/2/4/s07

Cited by 176 publications

(233 citation statements)

References 39 publications

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“…Unfortunately, protein dynamics on the microsecond-to-millisecond timescale is currently out of reach for conventional molecular-dynamics simulations. To overcome this restriction, a large variety of approaches that simplify force fields have been developed, including normal mode analysis 50,51 , gaussian network models 52 , FIRST (floppy inclusion and rigid substructure topography) 53 , FRODA (framework rigidity optimized dynamic algorithm) 54 and Gō models 49 . Alternatively, the dynamic process is accelerated by external force to access this timescale (used in methods such as targeted, steered and accelerated molecular-dynamics simulations 47,[55][56][57] ), or prior knowledge about features of the reaction coordinate (umbrella sampling algorithms to construct a potential of mean force 58 ) or the transition end points (transition-path sampling 59 ) is necessary.…”

Section: Methodsmentioning

confidence: 99%

Dynamic personalities of proteins

Henzler-Wildman

Kern

2007

Nature

2,142

2,222

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Life is marked by change over time, and biologists explore this phenomenon by watching, for example, Caenorhabditis elegans developing from embryos into adults, mice running in a cage, and nerve cells firing. In search of how and why, biology arrived at the molecular level. Understanding protein function on an atomic level has been revolutionized by high-resolution X-ray crystallography, resulting in a surge in studies of structure-function relationships. The detail in these colourful structures flooding the covers of modern journals can be deceptive, suggesting that one unique structure, the 'folded state' , is the final answer. Ironically, the dynamic nature of biology seems to have been forgotten at this microscopic level.Physicists, however, will object to a static picture: they see proteins as soft materials that sample a large ensemble of conformations around the average structure as a result of thermal energy. A complete description of proteins requires a multidimensional energy landscape that defines the relative probabilities of the conformational states (thermodynamics) and the energy barriers between them (kinetics). In biology, this concept has recently gained traction, leading to an extension of the structure-function paradigm to include dynamics. To understand proteins in action, the fourth dimension, time, must be added to the snapshots of proteins frozen in crystal structures. A major obstacle is that it is not possible to watch experimentally individual atoms moving within a protein. Instead, sophisticated biophysical methods are needed to measure the physical properties from which the dynamics can be inferred.In this review, we discuss how protein function is rooted in the energy landscape. The basic concepts and the biophysical methods are illustrated by several examples. To avoid past semantic confusion about the term protein dynamics, we define it as any time-dependent change in atomic coordinates. Protein dynamics thus includes both equilibrium fluctuations and non-equilibrium effects. The fluctuations observed at equilibrium seem to govern biological function in processes both near and far from equilibrium; therefore, we focus on these motions. Non-equilibrium effects are also called dynamical effects 1 (the source of confusion 2 ), and they have a minimal effect on the overall rates of biological processes 3,4 . Biological motors that convert chemical energy to mechanical energy 5,6 are not discussed here. The energy landscapeAlthough the idea of an energy landscape might be most familiar in the context of protein folding (for example, the folding funnel hypothesis) [7][8][9] , this concept had already been applied to folded proteins more than 30 years ago by Frauenfelder and co-workers . Subsequent studies on myoglobin led to the idea that substates are in thermal equilibrium and that both solvent 13-15 and ligands influence the landscape (Fig. 1a). At the glass transition temperature 10,12 , an increase in anharmonic dynamics occurs in proteins, and this is interpreted as the protein no...

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Section: Methodsmentioning

confidence: 99%

Dynamic personalities of proteins

Henzler-Wildman

Kern

2007

Nature

2,142

2,222

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“…[28] The 'FRODA' approach (framework rigidity optimised dynamic algorithm) makes use of templates to represent the geometry of portions of a protein structure. Rigid groups are identified using the 'FIRST' rigidity analysis software, [29] within which FRODA is implemented, and vary in size from single methyl groups to clusters spanning multiple secondary structure units or entire protein domains, depending on the distribution of covalent and non-covalent constraints in the protein.…”

Section: Protein Flexibility In Structural Biologymentioning

confidence: 99%

GASP: software for geometric simulations of flexibility in polyhedral and molecular framework structures

Wells

Sartbaeva

2015

Molecular Simulation

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Template-based geometric simulation is a specialised method for modelling flexible framework structures made up of rigid units using a simplified, localised physical model. The strengths of the method are its ability to handle large all-atom structural models rapidly and at minimal computational expense, and to provide insights into the links between local bonding and steric geometry and global flexibility. We review the implementation of geometric simulation in the 'GASP' software, and its application to the study of materials including zeolites, perovskites and metal -organic frameworks. The latest version (5) of GASP has significant improvements and extensions, in particular an improved algorithm for relaxation of atomic positions, and the capacity to handle both polyhedral and molecular structural units. GASP is freely available to researchers.

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“…Instead, excluded volume effects due to van der Waals interactions are included in geometrical simulation that allows rigid clusters to wiggle about without violating any distance constraint, or without atoms passing through one another. FRODA (Framework Rigidity Optimized Dynamics Algorithm) is one method [Wells, et al 2005;Farrell, et al 2010], among others [Lei, et al 2004;Thomas, et al 2007;Jimenez-Roldan, et al 2011;Yao, et al 2012] that uses FIRST to identify a native RCD that is preserved during the simulation. FRODA efficiently explores the native state ensemble of conformations [Jacobs, 2010;David & Jacobs 2011].…”

Section: Draconian View Of Network-rigiditymentioning

confidence: 99%

An Interfacial Thermodynamics Model for Protein Stability

Jacobs¹

2012

Biophysics

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Constrained geometric simulation of diffusive motion in proteins

Cited by 176 publications

References 39 publications

Dynamic personalities of proteins

Dynamic personalities of proteins

GASP: software for geometric simulations of flexibility in polyhedral and molecular framework structures

An Interfacial Thermodynamics Model for Protein Stability

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