Literature DB >> 8790365

Evidence for nonrandom hydrophobicity structures in protein chains.

A Irbäck1, C Peterson, F Potthast.   

Abstract

The question of whether proteins originate from random sequences of amino acids is addressed. A statistical analysis is performed in terms of blocked and random walk values formed by binary hydrophobic assignments of the amino acids along the protein chains. Theoretical expectations of these variables from random distributions of hydrophobicities are compared with those obtained from functional proteins. The results, which are based upon proteins in the SWISS-PROT data base, convincingly show that the amino acid sequences in proteins differ from what is expected from random sequences in a statistically significant way. By performing Fourier transforms on the random walks, one obtains additional evidence for nonrandomness of the distributions. We have also analyzed results from a synthetic model containing only two amino acid types, hydrophobic and hydrophilic. With reasonable criteria on good folding properties in terms of thermodynamical and kinetic behavior, sequences that fold well are isolated. Performing the same statistical analysis on the sequences that fold well indicates similar deviations from randomness as for the functional proteins. The deviations from randomness can be interpreted as originating from anticorrelations in terms of an Ising spin model for the hydrophobicities. Our results, which differ from some previous investigations using other methods, might have impact on how permissive with respect to sequence specificity protein folding process is-only sequences with nonrandom hydrophobicity distributions fold well. Other distributions give rise to energy landscapes with poor folding properties and hence did not survive the evolution.

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Year:  1996        PMID: 8790365      PMCID: PMC38463          DOI: 10.1073/pnas.93.18.9533

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  11 in total

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Authors:  U Hobohm; M Scharf; R Schneider; C Sander
Journal:  Protein Sci       Date:  1992-03       Impact factor: 6.725

2.  Toy model for protein folding.

Authors: 
Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics       Date:  1993-08

3.  Optimal neural networks for protein-structure prediction.

Authors: 
Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics       Date:  1993-08

4.  Statistical distribution of hydrophobic residues along the length of protein chains. Implications for protein folding and evolution.

Authors:  S H White; R E Jacobs
Journal:  Biophys J       Date:  1990-04       Impact factor: 4.033

5.  The Protein Data Bank: a computer-based archival file for macromolecular structures.

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Journal:  J Mol Biol       Date:  1977-05-25       Impact factor: 5.469

6.  Nonrandomness in protein sequences: evidence for a physically driven stage of evolution?

Authors:  V S Pande; A Y Grosberg; T Tanaka
Journal:  Proc Natl Acad Sci U S A       Date:  1994-12-20       Impact factor: 11.205

7.  The SWISS-PROT protein sequence data bank: current status.

Authors:  A Bairoch; B Boeckmann
Journal:  Nucleic Acids Res       Date:  1994-09       Impact factor: 16.971

8.  Kinetics of protein folding. A lattice model study of the requirements for folding to the native state.

Authors:  A Sali; E Shakhnovich; M Karplus
Journal:  J Mol Biol       Date:  1994-02-04       Impact factor: 5.469

9.  Enlarged representative set of protein structures.

Authors:  U Hobohm; C Sander
Journal:  Protein Sci       Date:  1994-03       Impact factor: 6.725

10.  The hydrophobic moment detects periodicity in protein hydrophobicity.

Authors:  D Eisenberg; R M Weiss; T C Terwilliger
Journal:  Proc Natl Acad Sci U S A       Date:  1984-01       Impact factor: 11.205

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  17 in total

1.  Three-helix-bundle protein in a Ramachandran model.

Authors:  A Irbäck; F Sjunnesson; S Wallin
Journal:  Proc Natl Acad Sci U S A       Date:  2000-12-05       Impact factor: 11.205

2.  On hydrophobicity correlations in protein chains.

Authors:  A Irbäck; E Sandelin
Journal:  Biophys J       Date:  2000-11       Impact factor: 4.033

3.  Recombinatoric exploration of novel folded structures: a heteropolymer-based model of protein evolutionary landscapes.

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Journal:  Proc Natl Acad Sci U S A       Date:  2002-01-22       Impact factor: 11.205

4.  The Ising model in physics and statistical genetics.

Authors:  J Majewski; H Li; J Ott
Journal:  Am J Hum Genet       Date:  2001-08-20       Impact factor: 11.025

5.  Correlation between sequence hydrophobicity and surface-exposure pattern of database proteins.

Authors:  Susanne Moelbert; Eldon Emberly; Chao Tang
Journal:  Protein Sci       Date:  2004-02-06       Impact factor: 6.725

6.  Designing human m1 muscarinic receptor-targeted hydrophobic eigenmode matched peptides as functional modulators.

Authors:  Karen A Selz; Arnold J Mandell; Michael F Shlesinger; Vani Arcuragi; Michael J Owens
Journal:  Biophys J       Date:  2004-03       Impact factor: 4.033

7.  Localization of ligand binding site in proteins identified in silico.

Authors:  Michal Brylinski; Marek Kochanczyk; Elzbieta Broniatowska; Irena Roterman
Journal:  J Mol Model       Date:  2007-03-30       Impact factor: 1.810

8.  A Shift in Aggregation Avoidance Strategy Marks a Long-Term Direction to Protein Evolution.

Authors:  Scott G Foy; Benjamin A Wilson; Jason Bertram; Matthew H J Cordes; Joanna Masel
Journal:  Genetics       Date:  2019-01-28       Impact factor: 4.562

9.  Enumerating Designing Sequences in the HP Model.

Authors:  Anders Irbäck; Carl Troein
Journal:  J Biol Phys       Date:  2002-03       Impact factor: 1.365

10.  Biophysics of protein evolution and evolutionary protein biophysics.

Authors:  Tobias Sikosek; Hue Sun Chan
Journal:  J R Soc Interface       Date:  2014-11-06       Impact factor: 4.118

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