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Energy Landscape and Global Optimization for a Frustrated Model Protein

[Image: see text] The three-color (BLN) 69-residue model protein was designed to exhibit frustrated folding. We investigate the energy landscape of this protein using disconnectivity graphs and compare it to a Go̅ model, which is designed to reduce the frustration by removing all non-native attracti...

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Autores principales: Oakley, Mark T., Wales, David J., Johnston, Roy L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2011
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3182752/
https://www.ncbi.nlm.nih.gov/pubmed/21866973
http://dx.doi.org/10.1021/jp207246m
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author Oakley, Mark T.
Wales, David J.
Johnston, Roy L.
author_facet Oakley, Mark T.
Wales, David J.
Johnston, Roy L.
author_sort Oakley, Mark T.
collection PubMed
description [Image: see text] The three-color (BLN) 69-residue model protein was designed to exhibit frustrated folding. We investigate the energy landscape of this protein using disconnectivity graphs and compare it to a Go̅ model, which is designed to reduce the frustration by removing all non-native attractive interactions. Finding the global minimum on a frustrated energy landscape is a good test of global optimization techniques, and we present calculations evaluating the performance of basin-hopping and genetic algorithms for this system. Comparisons are made with the widely studied 46-residue BLN protein. We show that the energy landscape of the 69-residue BLN protein contains several deep funnels, each of which corresponds to a different β-barrel structure.
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spelling pubmed-31827522011-09-30 Energy Landscape and Global Optimization for a Frustrated Model Protein Oakley, Mark T. Wales, David J. Johnston, Roy L. J Phys Chem B [Image: see text] The three-color (BLN) 69-residue model protein was designed to exhibit frustrated folding. We investigate the energy landscape of this protein using disconnectivity graphs and compare it to a Go̅ model, which is designed to reduce the frustration by removing all non-native attractive interactions. Finding the global minimum on a frustrated energy landscape is a good test of global optimization techniques, and we present calculations evaluating the performance of basin-hopping and genetic algorithms for this system. Comparisons are made with the widely studied 46-residue BLN protein. We show that the energy landscape of the 69-residue BLN protein contains several deep funnels, each of which corresponds to a different β-barrel structure. American Chemical Society 2011-08-26 2011-10-06 /pmc/articles/PMC3182752/ /pubmed/21866973 http://dx.doi.org/10.1021/jp207246m Text en Copyright © 2011 American Chemical Society http://pubs.acs.org This is an open-access article distributed under the ACS AuthorChoice Terms & Conditions. Any use of this article, must conform to the terms of that license which are available at http://pubs.acs.org.
spellingShingle Oakley, Mark T.
Wales, David J.
Johnston, Roy L.
Energy Landscape and Global Optimization for a Frustrated Model Protein
title Energy Landscape and Global Optimization for a Frustrated Model Protein
title_full Energy Landscape and Global Optimization for a Frustrated Model Protein
title_fullStr Energy Landscape and Global Optimization for a Frustrated Model Protein
title_full_unstemmed Energy Landscape and Global Optimization for a Frustrated Model Protein
title_short Energy Landscape and Global Optimization for a Frustrated Model Protein
title_sort energy landscape and global optimization for a frustrated model protein
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3182752/
https://www.ncbi.nlm.nih.gov/pubmed/21866973
http://dx.doi.org/10.1021/jp207246m
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