Protein sequence complexity revisited. Relationship with fractal 3D structure, topological and kinetic parameters

被引：1
作者：
Tejera, E. [1 ]
Nieto-Villar, J. [2 ,3 ]
Rebelo, I. [1 ]
机构：
[1] Univ Porto, Dept Bioquim, Inst Biol Mol & Celular, Fac Farm, P-4100 Oporto, Portugal
[2] Univ La Habana, Dpto Quim Fis, Fac Quim, Havana, Cuba
[3] Univ La Habana, Catedra Sistemas Complejos H Poincare, Havana, Cuba
来源：
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2014年 / 410卷
关键词：
Fractal dimension; Protein length; Folding rate; Networks topology; Recurrence analysis; Protein sequence; RECURRENCE QUANTIFICATION ANALYSIS; AMINO-ACID-SEQUENCE; SECONDARY STRUCTURE; FOLDING RATE; TIME-SERIES; PATTERN-RECOGNITION; CONTACT ORDER; PREDICTION; REPRESENTATION; 2-STATE;
D O I：
10.1016/j.physa.2014.05.019
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
The study of protein sequence complexity is not a new area and several methodological approaches are available in order to describe or represent the protein sequence information. The present study explored the relationship between sequence complexity and structural fractal dimension, secondary structure information, number of domains and also kinetic parameters considering several methodologies. Our results indicate that some sequence complexity indexes are sensitive enough to differentiate native from random sequences, even when the differences are small. We also found that proteins with increased complexity present a higher number of domains, increased length and mean solvent accessibility. Moreover, proteins with lower complexity revealed an increased folding and unfolding constant rate. Interestingly, we found a significant correlation between protein sequence complexity and structural fractal dimension and a significant effect of the secondary structure classes. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码：287 / 301
页数：15
相关论文
共 57 条
[1]  
AHDESMAKI M, 2007, IEEE INT WORKSH GEN
[2]   A Signal Analysis Approach Applied to the Study of Sequence, Structure and Function of the Proteins [J].
Benigni, Romualdo ;
Giuliani, Alessandro ;
Zbilut, Joseph P. ;
Ellis, Solo W. ;
Allorge, Delphine .
CURRENT COMPUTER-AIDED DRUG DESIGN, 2006, 2 (02) :189-201
[3]   The Protein Data Bank [J].
Berman, HM ;
Westbrook, J ;
Feng, Z ;
Gilliland, G ;
Bhat, TN ;
Weissig, H ;
Shindyalov, IN ;
Bourne, PE .
NUCLEIC ACIDS RESEARCH, 2000, 28 (01) :235-242
[4]   Topological thermal instability and length of proteins [J].
Burioni, R ;
Cassi, D ;
Cecconi, F ;
Vulpiani, A .
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2004, 55 (03) :529-535
[5]   Structure-related statistical singularities along protein sequences: A correlation study [J].
Colafranceschi, M ;
Colosimo, A ;
Zbilut, JP ;
Uversky, VN ;
Giuliani, A .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2005, 45 (01) :183-189
[6]   Low-complexity regions within protein sequences have position-dependent roles [J].
Coletta, Alain ;
Pinney, John W. ;
Solis, David Y. Weiss ;
Marsh, James ;
Pettifer, Steve R. ;
Attwood, Teresa K. .
BMC SYSTEMS BIOLOGY, 2010, 4
[7]   Universal 1/f noise from dissipative self-organized criticality models [J].
De Los Rios, P ;
Zhang, YC .
PHYSICAL REVIEW LETTERS, 1999, 82 (03) :472-475
[8]   Do Natural Proteins Differ from Random Sequences Polypeptides? Natural vs. Random Proteins Classification Using an Evolutionary Neural Network [J].
De Lucrezia, Davide ;
Slanzi, Debora ;
Poli, Irene ;
Polticelli, Fabio ;
Minervini, Giovanni .
PLOS ONE, 2012, 7 (05)
[9]   Evolutionary Optimization of Protein Folding [J].
Debes, Cedric ;
Wang, Minglei ;
Caetano-Anolles, Gustavo ;
Graeter, Frauke .
PLOS COMPUTATIONAL BIOLOGY, 2013, 9 (01)
[10]   What properties characterize the hub proteins of the protein-protein interaction network of Saccharomyces cerevisiae? [J].
Ekman, Diana ;
Light, Sara ;
Bjorklund, Asa K. ;
Elofsson, Arne .
GENOME BIOLOGY, 2006, 7 (06)
123456