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Optimal design of thermally stable proteins

Motivation: For many biotechnological purposes, it is desirable to redesign proteins to be more structurally and functionally stable at higher temperatures. For example, chemical reactions are intrinsically faster at higher temperatures, so using enzymes that are stable at higher temperatures would...

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Detalles Bibliográficos
Autores principales: Bannen, Ryan M., Suresh, Vanitha, Phillips, George N., Wright, Stephen J., Mitchell, Julie C.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2562006/
https://www.ncbi.nlm.nih.gov/pubmed/18723523
http://dx.doi.org/10.1093/bioinformatics/btn450
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author Bannen, Ryan M.
Suresh, Vanitha
Phillips, George N.
Wright, Stephen J.
Mitchell, Julie C.
author_facet Bannen, Ryan M.
Suresh, Vanitha
Phillips, George N.
Wright, Stephen J.
Mitchell, Julie C.
author_sort Bannen, Ryan M.
collection PubMed
description Motivation: For many biotechnological purposes, it is desirable to redesign proteins to be more structurally and functionally stable at higher temperatures. For example, chemical reactions are intrinsically faster at higher temperatures, so using enzymes that are stable at higher temperatures would lead to more efficient industrial processes. We describe an innovative and computationally efficient method called Improved Configurational Entropy (ICE), which can be used to redesign a protein to be more thermally stable (i.e. stable at high temperatures). This can be accomplished by systematically modifying the amino acid sequence via local structural entropy (LSE) minimization. The minimization problem is modeled as a shortest path problem in an acyclic graph with nonnegative weights and is solved efficiently using Dijkstra's method. Contact: mitchell@biochem.wisc.edu
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spelling pubmed-25620062009-02-25 Optimal design of thermally stable proteins Bannen, Ryan M. Suresh, Vanitha Phillips, George N. Wright, Stephen J. Mitchell, Julie C. Bioinformatics Original Papers Motivation: For many biotechnological purposes, it is desirable to redesign proteins to be more structurally and functionally stable at higher temperatures. For example, chemical reactions are intrinsically faster at higher temperatures, so using enzymes that are stable at higher temperatures would lead to more efficient industrial processes. We describe an innovative and computationally efficient method called Improved Configurational Entropy (ICE), which can be used to redesign a protein to be more thermally stable (i.e. stable at high temperatures). This can be accomplished by systematically modifying the amino acid sequence via local structural entropy (LSE) minimization. The minimization problem is modeled as a shortest path problem in an acyclic graph with nonnegative weights and is solved efficiently using Dijkstra's method. Contact: mitchell@biochem.wisc.edu Oxford University Press 2008-10-15 2008-08-22 /pmc/articles/PMC2562006/ /pubmed/18723523 http://dx.doi.org/10.1093/bioinformatics/btn450 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Bannen, Ryan M.
Suresh, Vanitha
Phillips, George N.
Wright, Stephen J.
Mitchell, Julie C.
Optimal design of thermally stable proteins
title Optimal design of thermally stable proteins
title_full Optimal design of thermally stable proteins
title_fullStr Optimal design of thermally stable proteins
title_full_unstemmed Optimal design of thermally stable proteins
title_short Optimal design of thermally stable proteins
title_sort optimal design of thermally stable proteins
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2562006/
https://www.ncbi.nlm.nih.gov/pubmed/18723523
http://dx.doi.org/10.1093/bioinformatics/btn450
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