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FOLD-RATE: prediction of protein folding rates from amino acid sequence

We have developed a web server, FOLD-RATE, for predicting the folding rates of proteins from their amino acid sequences. The relationship between amino acid properties and protein folding rates has been systematically analyzed and a statistical method based on linear regression technique has been pr...

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Detalles Bibliográficos
Autores principales: Gromiha, M. Michael, Thangakani, A. Mary, Selvaraj, S.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1538837/
https://www.ncbi.nlm.nih.gov/pubmed/16845101
http://dx.doi.org/10.1093/nar/gkl043
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author Gromiha, M. Michael
Thangakani, A. Mary
Selvaraj, S.
author_facet Gromiha, M. Michael
Thangakani, A. Mary
Selvaraj, S.
author_sort Gromiha, M. Michael
collection PubMed
description We have developed a web server, FOLD-RATE, for predicting the folding rates of proteins from their amino acid sequences. The relationship between amino acid properties and protein folding rates has been systematically analyzed and a statistical method based on linear regression technique has been proposed for predicting the folding rate of proteins. We found that the classification of proteins into different structural classes shows an excellent correlation between amino acid properties and folding rates of two and three-state proteins. Consequently, different regression equations have been developed for proteins belonging to all-α, all-β and mixed class. We observed an excellent agreement between predicted and experimentally observed folding rates of proteins; the correlation coefficients are, 0.99, 0.97 and 0.90, respectively, for all-α, all-β and mixed class proteins. The prediction server is freely available at .
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spelling pubmed-15388372006-08-18 FOLD-RATE: prediction of protein folding rates from amino acid sequence Gromiha, M. Michael Thangakani, A. Mary Selvaraj, S. Nucleic Acids Res Article We have developed a web server, FOLD-RATE, for predicting the folding rates of proteins from their amino acid sequences. The relationship between amino acid properties and protein folding rates has been systematically analyzed and a statistical method based on linear regression technique has been proposed for predicting the folding rate of proteins. We found that the classification of proteins into different structural classes shows an excellent correlation between amino acid properties and folding rates of two and three-state proteins. Consequently, different regression equations have been developed for proteins belonging to all-α, all-β and mixed class. We observed an excellent agreement between predicted and experimentally observed folding rates of proteins; the correlation coefficients are, 0.99, 0.97 and 0.90, respectively, for all-α, all-β and mixed class proteins. The prediction server is freely available at . Oxford University Press 2006-07-01 2006-07-14 /pmc/articles/PMC1538837/ /pubmed/16845101 http://dx.doi.org/10.1093/nar/gkl043 Text en © The Author 2006. Published by Oxford University Press. All rights reserved
spellingShingle Article
Gromiha, M. Michael
Thangakani, A. Mary
Selvaraj, S.
FOLD-RATE: prediction of protein folding rates from amino acid sequence
title FOLD-RATE: prediction of protein folding rates from amino acid sequence
title_full FOLD-RATE: prediction of protein folding rates from amino acid sequence
title_fullStr FOLD-RATE: prediction of protein folding rates from amino acid sequence
title_full_unstemmed FOLD-RATE: prediction of protein folding rates from amino acid sequence
title_short FOLD-RATE: prediction of protein folding rates from amino acid sequence
title_sort fold-rate: prediction of protein folding rates from amino acid sequence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1538837/
https://www.ncbi.nlm.nih.gov/pubmed/16845101
http://dx.doi.org/10.1093/nar/gkl043
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