Cofilin reduces the mechanical properties of actin filaments: approach with coarse-grained methods

2015 ◽  
Vol 17 (12) ◽  
pp. 8148-8158 ◽  
Author(s):  
Jae In Kim ◽  
Junpyo Kwon ◽  
Inchul Baek ◽  
Harold S. Park ◽  
Sungsoo Na
Keyword(s):  
Mechanical Properties ◽  
Normal Mode Analysis ◽  
Beam Theory ◽  
Dynamics Simulation ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Elastic Network Model ◽  
Elastic Network ◽  
Good Agreement ◽  
The Continuum

We applied a coarse-grained molecular dynamics simulation (CGMD) method and constructed elastic network model-based structures, actin and cofilactin filaments. Based on a normal mode analysis, the continuum beam theory was used to calculate the mechanical properties and the results showed good agreement with the established experimental data.

scholarly journals A coarse-grained elastic network atom contact model and its use in the simulation of protein dynamics and the prediction of the effect of mutations

2013 ◽  
Author(s):  
Vincent Frappier ◽  
Rafael Najmanovich
Keyword(s):  
Potential Energy ◽  
Normal Mode Analysis ◽  
Protein Structures ◽  
Normal Modes ◽  
Potential Energy Function ◽  
Contact Model ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Elastic Network Model ◽  
Elastic Network

Normal mode analysis (NMA) methods are widely used to study dynamic aspects of protein structures. Two critical components of NMA methods are coarse-graining in the level of simplification used to represent protein structures and the choice of potential energy functional form. There is a trade-off between speed and accuracy in different choices. In one extreme one finds accurate but slow molecular-dynamics based methods with all-atom representations and detailed atom potentials. On the other extreme, fast elastic network model (ENM) methods with Cαonly representations and simplified potentials that based on geometry alone, thus oblivious to protein sequence. Here we present ENCoM, an Elastic Network Contact Model that employs a potential energy function that includes a pairwise atom-type non-bonded interaction term and thus makes it possible to consider the effect of the specific nature of amino-acids on dynamics within the context of NMA. ENCoM is as fast as existing ENM methods and outperforms such methods in the generation of conformational ensembles. Here we introduce a new application for NMA methods with the use of ENCoM in the prediction of the effect of mutations on protein stability. While existing methods are based on machine learning or enthalpic considerations, the use of ENCoM, based on vibrational normal modes, is based on entropic considerations. This represents a novel area of application for NMA methods and a novel approach for the prediction of the effect of mutations. We compare ENCoM to a large number of methods in terms of accuracy and self-consistency. We show that the accuracy of ENCoM is comparable to that of the best existing methods. We show that existing methods are biased towards the prediction of destabilizing mutations and that ENCoM is less biased at predicting stabilizing mutations.

A complex multiscale virtual particle model based elastic network model (CMVP-ENM) for the normal mode analysis of biomolecular complexes

2019 ◽  
Vol 21 (8) ◽  
pp. 4359-4366 ◽  
Author(s):  
D. Vijay Anand ◽  
Zhenyu Meng ◽  
Kelin Xia
Keyword(s):  
Normal Mode ◽  
Network Model ◽  
Material Properties ◽  
Normal Mode Analysis ◽  
Mode Analysis ◽  
Particle Model ◽  
Elastic Network Model ◽  
Elastic Network ◽  
Virtual Particle ◽  
Biomolecular Complexes

The CMVP-ENM for virus normal mode analysis. With a special ratio parameter, CMVP-ENM can characterize the multi-material properties of biomolecular complexes and systematically enhance or suppress the modes for different components.

scholarly journals Skeletal animation for visualizing dynamic shapes of macromolecules

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Yutaka Ueno ◽  
Shinya Muraoka ◽  
Tetsuo Sato
Keyword(s):  
Computer Graphics ◽  
Normal Mode Analysis ◽  
Normal Modes ◽  
Dynamics Simulation ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Protein Molecules ◽  
Skeletal Animation ◽  
Detailed Computer ◽  
Animation Software

AbstractWe apply a skeletal animation technique developed for general computer graphics animation to display the dynamic shape of protein molecules. Polygon-based models for macromolecules such as atomic representations, surface models, and protein ribbon models are deformed by the motion of skeletal bones that provide coarse-grained descriptions of detailed computer graphics models. Using the animation software Blender, we developed methods to generate the skeletal bones for molecules. Our example of the superposition of normal modes demonstrates the thermal fluctuating motion obtained from normal mode analysis. The method is also applied to display the motions of protein molecules using trajectory coordinates of a molecular dynamics simulation. We found that a standard motion capture file was practical and useful for describing the motion of the molecule using available computer graphics tools.

scholarly journals The Elastic Network Contact Model applied to RNA: enhanced accuracy for conformational space prediction

2017 ◽  
Author(s):  
Olivier Mailhot ◽  
Vincent Frappier ◽  
François Major ◽  
Rafael Najmanovich
Keyword(s):  
Normal Mode Analysis ◽  
Data Bank ◽  
Contact Model ◽  
Conformational Space ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Elastic Network ◽  
Rna Molecules ◽  
Coarse Grained Model ◽  
Anisotropic Network

ABSTRACTMotivationThe use of Normal Mode Analysis (NMA) methods to study both protein and nucleic acid dynamics is well established. However, the most widely used coarse-grained methods are based on backbone geometry alone and do not take into account the chemical nature of the residues. Elastic Network Contact Model (ENCoM) is a coarse-grained NMA method that includes a pairwise atom-type non-bonded interaction term, which makes it sensitive to the sequence of the studied molecule. We adapted ENCoM to simulate the dynamics of ribonucleic acid (RNA) molecules.ResultsENCoM outperforms the most commonly used coarse-grained model on RNA, Anisotropic Network Model (ANM), in the prediction of b-factors, in the prediction of conformational change as measured by overlap (a measure of effective prediction of structural transitions) and in the prediction of structural variance from NMR ensembles. These benchmarks were derived from the set of all RNA structures available from the Protein Data Bank (PDB) and contain more total cases than previous studies applying NMA to RNA. We thus established ENCoM as an attractive tool for fast and accurate exploration of the conformational space of RNA molecules.AvailabilityENCoM is open source software available at https://github.com/NRGlab/ENCoM

scholarly journals Coarse-Grained Protein Dynamics Studies Using Elastic Network Models

2018 ◽  
Vol 19 (12) ◽  
pp. 3899 ◽  
Author(s):  
Yuichi Togashi ◽  
Holger Flechsig
Keyword(s):  
Normal Mode Analysis ◽  
Protein Structures ◽  
Computational Cost ◽  
Network Models ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Nonlinear Phenomena ◽  
Reference Structure ◽  
Elastic Network ◽  
Elastic Network Models

Elastic networks have been used as simple models of proteins to study their slow structural dynamics. They consist of point-like particles connected by linear Hookean springs and hence are convenient for linear normal mode analysis around a given reference structure. Furthermore, dynamic simulations using these models can provide new insights. As the computational cost associated with these models is considerably lower compared to that of all-atom models, they are also convenient for comparative studies between multiple protein structures. In this review, we introduce examples of coarse-grained molecular dynamics studies using elastic network models and their derivatives, focusing on the nonlinear phenomena, and discuss their applicability to large-scale macromolecular assemblies.

Allosteric Conformational Transition in Adenylate Kinase: Dynamic Correlations and Implication for Allostery

2010 ◽  
Vol 63 (3) ◽  
pp. 405 ◽  
Author(s):  
Ming S. Liu ◽  
Billy D. Todd ◽  
Richard J. Sadus
Keyword(s):  
Normal Mode ◽  
Conformational Changes ◽  
Adenylate Kinase ◽  
Conformational Transition ◽  
Normal Mode Analysis ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Elastic Network Model ◽  
Protein Functions ◽  
Correlated Motion

An essential aspect of protein science is to determine the deductive relationship between structure, dynamics, and various sets of functions. The role of dynamics is currently challenging our understanding of protein functions, both experimentally and theoretically. To verify the internal fluctuations and dynamics correlations in an enzyme protein undergoing conformational transitions, we have applied a coarse-grained dynamics algorithm using the elastic network model for adenylate kinase. Normal mode analysis reveals possible dynamical and allosteric pathways for the transition between the open and the closed states of adenylate kinase. As the ligands binding induces significant flexibility changes of the nucleotides monophosphate (NMP) domain and adenosine triphosphate (ATP) domain, the diagonalized correlation between different structural transition states shows that most correlated motions occur between the NMP domain and the helices surrounding the ATP domain. The simultaneous existence of positive and negative correlations indicates that the conformational changes of adenylate kinase take place in an allosteric manner. Analyses of the cumulated normal mode overlap coefficients and long-range correlated motion provide new insights of operating mechanisms and dynamics of adenylate kinase. They also suggest a quantitative dynamics criterion for determining the allosteric cooperativity, which may be applicable to other proteins.

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