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MAVENs: Motion analysis and visualization of elastic networks and structural ensembles

BACKGROUND: The ability to generate, visualize, and analyze motions of biomolecules has made a significant impact upon modern biology. Molecular Dynamics has gained substantial use, but remains computationally demanding and difficult to setup for many biologists. Elastic network models (ENMs) are an...

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Autores principales: Zimmermann, Michael T, Kloczkowski, Andrzej, Jernigan, Robert L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3213244/
https://www.ncbi.nlm.nih.gov/pubmed/21711533
http://dx.doi.org/10.1186/1471-2105-12-264
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author Zimmermann, Michael T
Kloczkowski, Andrzej
Jernigan, Robert L
author_facet Zimmermann, Michael T
Kloczkowski, Andrzej
Jernigan, Robert L
author_sort Zimmermann, Michael T
collection PubMed
description BACKGROUND: The ability to generate, visualize, and analyze motions of biomolecules has made a significant impact upon modern biology. Molecular Dynamics has gained substantial use, but remains computationally demanding and difficult to setup for many biologists. Elastic network models (ENMs) are an alternative and have been shown to generate the dominant equilibrium motions of biomolecules quickly and efficiently. These dominant motions have been shown to be functionally relevant and also to indicate the likely direction of conformational changes. Most structures have a small number of dominant motions. Comparing computed motions to the structure's conformational ensemble derived from a collection of static structures or frames from an MD trajectory is an important way to understand functional motions as well as evaluate the models. Modes of motion computed from ENMs can be visualized to gain functional and mechanistic understanding and to compute useful quantities such as average positional fluctuations, internal distance changes, collectiveness of motions, and directional correlations within the structure. RESULTS: Our new software, MAVEN, aims to bring ENMs and their analysis to a broader audience by integrating methods for their generation and analysis into a user friendly environment that automates many of the steps. Models can be constructed from raw PDB files or density maps, using all available atomic coordinates or by employing various coarse-graining procedures. Visualization can be performed either with our software or exported to molecular viewers. Mixed resolution models allow one to study atomic effects on the system while retaining much of the computational speed of the coarse-grained ENMs. Analysis options are available to further aid the user in understanding the computed motions and their importance for its function. CONCLUSION: MAVEN has been developed to simplify ENM generation, allow for diverse models to be used, and facilitate useful analyses, all on the same platform. This represents an integrated approach that incorporates all four levels of the modeling process - generation, evaluation, analysis, visualization - and also brings to bear multiple ENM types. The intension is to provide a versatile modular suite of programs to a broader audience. MAVEN is available for download at http://maven.sourceforge.net.
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spelling pubmed-32132442011-11-11 MAVENs: Motion analysis and visualization of elastic networks and structural ensembles Zimmermann, Michael T Kloczkowski, Andrzej Jernigan, Robert L BMC Bioinformatics Software BACKGROUND: The ability to generate, visualize, and analyze motions of biomolecules has made a significant impact upon modern biology. Molecular Dynamics has gained substantial use, but remains computationally demanding and difficult to setup for many biologists. Elastic network models (ENMs) are an alternative and have been shown to generate the dominant equilibrium motions of biomolecules quickly and efficiently. These dominant motions have been shown to be functionally relevant and also to indicate the likely direction of conformational changes. Most structures have a small number of dominant motions. Comparing computed motions to the structure's conformational ensemble derived from a collection of static structures or frames from an MD trajectory is an important way to understand functional motions as well as evaluate the models. Modes of motion computed from ENMs can be visualized to gain functional and mechanistic understanding and to compute useful quantities such as average positional fluctuations, internal distance changes, collectiveness of motions, and directional correlations within the structure. RESULTS: Our new software, MAVEN, aims to bring ENMs and their analysis to a broader audience by integrating methods for their generation and analysis into a user friendly environment that automates many of the steps. Models can be constructed from raw PDB files or density maps, using all available atomic coordinates or by employing various coarse-graining procedures. Visualization can be performed either with our software or exported to molecular viewers. Mixed resolution models allow one to study atomic effects on the system while retaining much of the computational speed of the coarse-grained ENMs. Analysis options are available to further aid the user in understanding the computed motions and their importance for its function. CONCLUSION: MAVEN has been developed to simplify ENM generation, allow for diverse models to be used, and facilitate useful analyses, all on the same platform. This represents an integrated approach that incorporates all four levels of the modeling process - generation, evaluation, analysis, visualization - and also brings to bear multiple ENM types. The intension is to provide a versatile modular suite of programs to a broader audience. MAVEN is available for download at http://maven.sourceforge.net. BioMed Central 2011-06-28 /pmc/articles/PMC3213244/ /pubmed/21711533 http://dx.doi.org/10.1186/1471-2105-12-264 Text en Copyright © 2011 Zimmermann et al; licensee BioMed Central Ltd. https://creativecommons.org/licenses/by/2.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Zimmermann, Michael T
Kloczkowski, Andrzej
Jernigan, Robert L
MAVENs: Motion analysis and visualization of elastic networks and structural ensembles
title MAVENs: Motion analysis and visualization of elastic networks and structural ensembles
title_full MAVENs: Motion analysis and visualization of elastic networks and structural ensembles
title_fullStr MAVENs: Motion analysis and visualization of elastic networks and structural ensembles
title_full_unstemmed MAVENs: Motion analysis and visualization of elastic networks and structural ensembles
title_short MAVENs: Motion analysis and visualization of elastic networks and structural ensembles
title_sort mavens: motion analysis and visualization of elastic networks and structural ensembles
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3213244/
https://www.ncbi.nlm.nih.gov/pubmed/21711533
http://dx.doi.org/10.1186/1471-2105-12-264
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