Elastic Network Models For Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses

Lezon, Timothy R.; Shrivastava, Indira H.; Yang, Zheng; Bahar, İvet

doi:10.1142/9789812838803_0007

Cited by 18 publications

(21 citation statements)

References 71 publications

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“…The ENM also lends itself to use in mixed models, in which specific regions of the molecule are modeled in detail and the remainder at low resolution (43), and to rigid blocking schemes as in the rotating-translating blocks model (66). Clearly, the scalability of ENMs makes them particularly useful for investigating large complexes/assemblies or supramolecular systems (79), or even organelles such as the nuclear pore complex (46) or intact viruses (47), i.e., bimolecular systems that are well beyond the scope of exploration via conventional molecular models and simulations.…”

Section: Elastic Network Models: Theory and Assumptionsmentioning

confidence: 99%

Global Dynamics of Proteins: Bridging Between Structure and Function

Bahar

Lezon

Yang

et al. 2010

Annu. Rev. Biophys.

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546

612

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Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold.

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Section: Elastic Network Models: Theory and Assumptionsmentioning

confidence: 99%

Global Dynamics of Proteins: Bridging Between Structure and Function

Bahar

Lezon

Yang

et al. 2010

Annu. Rev. Biophys.

Self Cite

546

612

View full text Add to dashboard Cite

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“…21,22 Furthermore, issues regarding the assembly of biomolecules on a large scale can be caused by leaving out the protein folding in the rigid coarse-grained representation of the capsomers. 35 An alternative way to overcome these limitations is to combine the coarse-grained model with a supportive elastic network based on the structural fluctuations of the capsomer, an approach able to correctly predict the conformational flexibilities and properties of large capsid fragments of Cowpea Chlorotic Mottle Virus. 36 In this paper, one examines the co-assembly kinetics of an icosahedral capsid enclosing an oppositely charged polyion when an artificial network is added on top of a coarsegrained capsomer in order to amend some of the aforementioned model limitations.…”

Section: Introductionmentioning

confidence: 99%

Assembled viral-like nanoparticles from elastic capsomers and polyion

Angelescu

2017

The Journal of Chemical Physics

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Molecular dynamics simulations are carried out on a coarse-grained model to describe the polyion driven co-assembly of elastic capsomers as viral-like aggregates. The kinetics and structural properties of the complexes are examined using cationic capsomers, an anionic polyion, both modelled using beads connected by springs, and counterions neutralizing separately the two charged species. Polyion overcharging the capsid is encapsulated owing to combined effects of the capsomer-capsomer short-range interactions, the polyion ability to follow a Hamiltonian path, and Donnan equilibrium. Conditions leading to a high yield of viral-like nanoparticles are found, and the simulations demonstrate that the capsomer elasticity provides mechanisms that improve the reliability toward correctly formed capsids. These mechanisms are related to a highly irregular capsomer cluster growth followed by the appearance of two stable capsomer clusters with the polyion acting as a tether between them. Elevated capsomeric flexibility provides an additional pathway to anneal the kinetically trapped structures by the ejection of a capsomeric monomer from a malformed complex followed by a rebinding step to form a correct capsid.

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“…In certain cases, large‐amplitude functionally relevant deformations are harmonic, aligning with the macromolecular intrinsic normal modes . Consequently, several studies have attempted to project macromolecular dynamics using elastic network models (ENM), where the macromolecule is defined as a set of nodes connected by harmonic springs . Normal modes/collective coordinates are then derived from this simplistic harmonic approximation of the potential energy function near equilibrium.…”

Section: Introductionmentioning

confidence: 99%

DIRECT‐ID: An automated method to identify and quantify conformational variations—application to β₂‐adrenergic GPCR

et al. 2015

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The conformational dynamics of a macromolecule can be modulated by a number of factors, including changes in environment, ligand binding and interactions with other macromolecules, among others. We present a method that quantifies the differences in macromolecular conformational dynamics and automatically extracts the structural features responsible for these changes. Given a set of molecular dynamics (MD) simulations of a macromolecule, the norms of the differences in covariance matrices are calculated for each pair of trajectories. A matrix of these norms thus quantifies the differences in conformational dynamics across the set of simulations. For each pair of trajectories, covariance difference matrices are parsed to extract structural elements that undergo changes in conformational properties. As a demonstration of its applicability to biomacromolecular systems, the method, referred to as DIRECT-ID, was used to identify relevant ligand-modulated structural variations in the β2-adrenergic (β2AR) G-protein coupled receptor. Micro-second MD simulations of the β2AR in an explicit lipid bilayer were run in the apo state and complexed with the ligands: BI-167107 (agonist), epinephrine (agonist), salbutamol (long-acting partial agonist) or carazolol (inverse agonist). Each ligand modulated the conformational dynamics of β2AR differently and DIRECT-ID analysis of the inverse-agonist vs. agonist-modulated β2AR identified residues known through previous studies to selectively propagate deactivation/activation information, along with some previously unidentified ligand-specific microswitches across the GPCR. This study demonstrates the utility of DIRECT-ID to rapidly extract functionally relevant conformational dynamics information from extended MD simulations of large and complex macromolecular systems.

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Elastic Network Models For Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses

Cited by 18 publications

References 71 publications

Global Dynamics of Proteins: Bridging Between Structure and Function

Global Dynamics of Proteins: Bridging Between Structure and Function

Assembled viral-like nanoparticles from elastic capsomers and polyion

DIRECT‐ID: An automated method to identify and quantify conformational variations—application to β₂‐adrenergic GPCR

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Elastic Network Models For Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses

Cited by 18 publications

References 71 publications

Global Dynamics of Proteins: Bridging Between Structure and Function

Global Dynamics of Proteins: Bridging Between Structure and Function

Assembled viral-like nanoparticles from elastic capsomers and polyion

DIRECT‐ID: An automated method to identify and quantify conformational variations—application to β2‐adrenergic GPCR

Contact Info

Product

Resources

About

DIRECT‐ID: An automated method to identify and quantify conformational variations—application to β₂‐adrenergic GPCR