Literature DB >> 15498936

To be folded or to be unfolded?

Sergiy O Garbuzynskiy1, Michail Yu Lobanov, Oxana V Galzitskaya.   

Abstract

The lack of ordered structure in "natively unfolded" proteins raises a general question: Are there intrinsic properties of amino acid residues that are responsible for the absence of fixed structure at physiological conditions? In this article, we demonstrate that the competence of a protein to be folded or to be unfolded may be determined by the property of amino acid residues to form a sufficient number of contacts in a globular state. The expected average number of contacts per residue calculated from the amino acid sequence alone (using the average number of contacts for 20 amino acid residues in globular proteins) can be used as one of the simple indicators of natively unfolded proteins. The prediction accuracy for the sets of 80 folded and 90 natively unfolded proteins reaches 89% if the expected average number of contacts is used as a parameter and 83% in the case of hydrophobicity. An optimal set of artificial parameters for 20 amino acid residues obtained by Monte Carlo algorithm to maximally separate the sets of 90 natively unfolded and 80 folded proteins demonstrates the upper limit for prediction accuracy, which is 95%.

Mesh:

Year:  2004        PMID: 15498936      PMCID: PMC2286584          DOI: 10.1110/ps.04881304

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  16 in total

1.  Optimal region of average side-chain entropy for fast protein folding.

Authors:  O V Galzitskaya; A K Surin; H Nakamura
Journal:  Protein Sci       Date:  2000-03       Impact factor: 6.725

2.  Folding minimal sequences: the lower bound for sequence complexity of globular proteins.

Authors:  P Romero; Z Obradovic; A K Dunker
Journal:  FEBS Lett       Date:  1999-12-03       Impact factor: 4.124

3.  Why are "natively unfolded" proteins unstructured under physiologic conditions?

Authors:  V N Uversky; J R Gillespie; A L Fink
Journal:  Proteins       Date:  2000-11-15

Review 4.  What does it mean to be natively unfolded?

Authors:  Vladimir N Uversky
Journal:  Eur J Biochem       Date:  2002-01

Review 5.  Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm.

Authors:  P E Wright; H J Dyson
Journal:  J Mol Biol       Date:  1999-10-22       Impact factor: 5.469

Review 6.  Insights into the structure and dynamics of unfolded proteins from nuclear magnetic resonance.

Authors:  H Jane Dyson; Peter E Wright
Journal:  Adv Protein Chem       Date:  2002

7.  Predicting intrinsic disorder from amino acid sequence.

Authors:  Zoran Obradovic; Kang Peng; Slobodan Vucetic; Predrag Radivojac; Celeste J Brown; A Keith Dunker
Journal:  Proteins       Date:  2003

8.  Protein disorder and the evolution of molecular recognition: theory, predictions and observations.

Authors:  A K Dunker; E Garner; S Guilliot; P Romero; K Albrecht; J Hart; Z Obradovic; C Kissinger; J E Villafranca
Journal:  Pac Symp Biocomput       Date:  1998

9.  Flavors of protein disorder.

Authors:  Slobodan Vucetic; Celeste J Brown; A Keith Dunker; Zoran Obradovic
Journal:  Proteins       Date:  2003-09-01

10.  Protein flexibility and intrinsic disorder.

Authors:  Predrag Radivojac; Zoran Obradovic; David K Smith; Guang Zhu; Slobodan Vucetic; Celeste J Brown; J David Lawson; A Keith Dunker
Journal:  Protein Sci       Date:  2004-01       Impact factor: 6.725

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  23 in total

Review 1.  Understanding protein non-folding.

Authors:  Vladimir N Uversky; A Keith Dunker
Journal:  Biochim Biophys Acta       Date:  2010-02-01

2.  TOP-IDP-scale: a new amino acid scale measuring propensity for intrinsic disorder.

Authors:  Andrew Campen; Ryan M Williams; Celeste J Brown; Jingwei Meng; Vladimir N Uversky; A Keith Dunker
Journal:  Protein Pept Lett       Date:  2008       Impact factor: 1.890

3.  The twilight zone between protein order and disorder.

Authors:  A Szilágyi; D Györffy; P Závodszky
Journal:  Biophys J       Date:  2008-04-25       Impact factor: 4.033

4.  H-DROP: an SVM based helical domain linker predictor trained with features optimized by combining random forest and stepwise selection.

Authors:  Teppei Ebina; Ryosuke Suzuki; Ryotaro Tsuji; Yutaka Kuroda
Journal:  J Comput Aided Mol Des       Date:  2014-06-26       Impact factor: 3.686

Review 5.  A comprehensive overview of computational protein disorder prediction methods.

Authors:  Xin Deng; Jesse Eickholt; Jianlin Cheng
Journal:  Mol Biosyst       Date:  2011-08-26

Review 6.  Intrinsic disorder and functional proteomics.

Authors:  Predrag Radivojac; Lilia M Iakoucheva; Christopher J Oldfield; Zoran Obradovic; Vladimir N Uversky; A Keith Dunker
Journal:  Biophys J       Date:  2006-12-08       Impact factor: 4.033

7.  Library of disordered patterns in 3D protein structures.

Authors:  Michail Yu Lobanov; Eugeniya I Furletova; Natalya S Bogatyreva; Michail A Roytberg; Oxana V Galzitskaya
Journal:  PLoS Comput Biol       Date:  2010-10-14       Impact factor: 4.475

8.  Structural disorder within Henipavirus nucleoprotein and phosphoprotein: from predictions to experimental assessment.

Authors:  Johnny Habchi; Laurent Mamelli; Hervé Darbon; Sonia Longhi
Journal:  PLoS One       Date:  2010-07-21       Impact factor: 3.240

9.  Predictors of natively unfolded proteins: unanimous consensus score to detect a twilight zone between order and disorder in generic datasets.

Authors:  Antonio Deiana; Andrea Giansanti
Journal:  BMC Bioinformatics       Date:  2010-04-21       Impact factor: 3.169

10.  Rules governing selective protein carbonylation.

Authors:  Etienne Maisonneuve; Adrien Ducret; Pierre Khoueiry; Sabrina Lignon; Sonia Longhi; Emmanuel Talla; Sam Dukan
Journal:  PLoS One       Date:  2009-10-05       Impact factor: 3.240

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