Literature DB >> 16937389

Direct correlation between proteins' folding rates and their amino acid compositions: an ab initio folding rate prediction.

Bin-Guang Ma1, Jian-Xiu Guo, Hong-Yu Zhang.   

Abstract

Discovering the mechanism of protein folding, in molecular biology, is a great challenge. A key step to this end is to find factors that correlate with protein folding rates. Over the past few years, many empirical parameters, such as contact order, long-range order, total contact distance, secondary structure contents, have been developed to reflect the correlation between folding rates and protein tertiary or secondary structures. However, the correlation between proteins' folding rates and their amino acid compositions has not been explored. In the present work, we examined systematically the correlation between proteins' folding rates and their amino acid compositions for two-state and multistate folders and found that different amino acids contributed differently to the folding progress. The relation between the amino acids' molecular weight and degeneracy and the folding rates was examined, and the role of hydrophobicity in the protein folding process was also inspected. As a consequence, a new indicator called composition index was derived, which takes no structure factors into account and is merely determined by the amino acid composition of a protein. Such an indicator is found to be highly correlated with the protein's folding rate (r > 0.7). From the results of this work, three points of concluding remarks are evident. (1) Two-state folders and multistate folders have different rate-determining amino acids. (2) The main determining information of a protein's folding rate is largely reflected in its amino acid composition. (3) Composition index may be the best predictor for an ab initio protein folding rate prediction directly from protein sequence from the standpoint of practical application. (c) 2006 Wiley-Liss, Inc.

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Year:  2006        PMID: 16937389     DOI: 10.1002/prot.21140

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  7 in total

1.  Real value prediction of protein folding rate change upon point mutation.

Authors:  Liang-Tsung Huang; M Michael Gromiha
Journal:  J Comput Aided Mol Des       Date:  2012-03-18       Impact factor: 3.686

2.  Effects of metabolic rate on protein evolution.

Authors:  James F Gillooly; Michael W McCoy; Andrew P Allen
Journal:  Biol Lett       Date:  2007-12-22       Impact factor: 3.703

3.  Protein Folding Database (PFD 2.0): an online environment for the International Foldeomics Consortium.

Authors:  Kate F Fulton; Mark A Bate; Noel G Faux; Khalid Mahmood; Chris Betts; Ashley M Buckle
Journal:  Nucleic Acids Res       Date:  2006-12-14       Impact factor: 16.971

4.  KineticDB: a database of protein folding kinetics.

Authors:  Natalya S Bogatyreva; Alexander A Osypov; Dmitry N Ivankov
Journal:  Nucleic Acids Res       Date:  2008-10-08       Impact factor: 16.971

5.  Machine Learning: How Much Does It Tell about Protein Folding Rates?

Authors:  Marc Corrales; Pol Cuscó; Dinara R Usmanova; Heng-Chang Chen; Natalya S Bogatyreva; Guillaume J Filion; Dmitry N Ivankov
Journal:  PLoS One       Date:  2015-11-25       Impact factor: 3.240

6.  Sequence analysis on the information of folding initiation segments in ferredoxin-like fold proteins.

Authors:  Masanari Matsuoka; Takeshi Kikuchi
Journal:  BMC Struct Biol       Date:  2014-05-23

Review 7.  Solution of Levinthal's Paradox and a Physical Theory of Protein Folding Times.

Authors:  Dmitry N Ivankov; Alexei V Finkelstein
Journal:  Biomolecules       Date:  2020-02-06
  7 in total

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