Protein sequence complexity revisited. Relationship with fractal 3D structure, topological and kinetic parameters
作者： E. Tejera , J. Nieto-Villar , I. Rebelo
DOI: 10.1016/J.PHYSA.2014.05.019
关键词: Fractal dimension 、 Mathematics 、 Sequence 、 Biological system 、 Folding (DSP implementation) 、 Correlation 、 Order (biology) 、 Fractal 、 Protein secondary structure 、 Protein sequencing 、 Discrete mathematics
摘要: Abstract The study of protein sequence complexity is not a new area and several methodological approaches are available in order to describe or represent the information. present explored relationship between structural fractal dimension, secondary structure information, number domains also kinetic parameters considering methodologies. Our results indicate that some indexes sensitive enough differentiate native from random sequences, even when differences small. We found proteins with increased higher domains, length mean solvent accessibility. Moreover, lower revealed an folding unfolding constant rate. Interestingly, we significant correlation dimension effect classes.
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Pier Luigi Luisi, Fabio Polticelli, Giovanni Minervini, Giuseppe Evangelista, RANDOMBLAST A TOOL TO GENERATE RANDOM “NEVER BORN PROTEIN” SEQUENCES Bio-Algorithms and Med-Systems. ,vol. 3, pp. 27- 31 ,(2007)
Ambarnil Ghosh, Ashesh Nandy, Graphical representation and mathematical characterization of protein sequences and applications to viral proteins. Advances in Protein Chemistry. ,vol. 83, pp. 1- 42 ,(2011) , 10.1016/B978-0-12-381262-9.00001-X
Paolo De Los Rios, Yi-Cheng Zhang, Universal 1/f Noise from Dissipative Self-Organized Criticality Models Physical Review Letters. ,vol. 82, pp. 472- 475 ,(1999) , 10.1103/PHYSREVLETT.82.472
Joshua S. Richman, J. Randall Moorman, Physiological time-series analysis using approximate entropy and sample entropy American Journal of Physiology-heart and Circulatory Physiology. ,vol. 278, ,(2000) , 10.1152/AJPHEART.2000.278.6.H2039
Ray G. Huffaker, Phase Space Reconstruction from Econommic Time Series Data: Improving Models of Complex Real-World Dynamic Systems International Journal on Food System Dynamics. ,vol. 1, pp. 184- 193 ,(2010) , 10.18461/IJFSD.V1I3.132
Dmitry N. Ivankov, Alexei V. Finkelstein, Prediction of protein folding rates from the amino acid sequence-predicted secondary structure. Proceedings of the National Academy of Sciences of the United States of America. ,vol. 101, pp. 8942- 8944 ,(2004) , 10.1073/PNAS.0402659101
B.J. Strait, T.G. Dewey, The Shannon information entropy of protein sequences. Biophysical Journal. ,vol. 71, pp. 148- 155 ,(1996) , 10.1016/S0006-3495(96)79210-X
E. Tejera, A.I. Rodrigues, M.J. Areias, I. Rebelo, J.M. Nieto-Villar, Network centrality and multiscale transition asymmetry in the heart rate variability analysis of normal and preeclamptic pregnancies Communications in Nonlinear Science and Numerical Simulation. ,vol. 16, pp. 1589- 1596 ,(2011) , 10.1016/J.CNSNS.2010.07.009
Laurence Lins, Annick Thomas, Robert Brasseur, Analysis of accessible surface of residues in proteins Protein Science. ,vol. 12, pp. 1406- 1417 ,(2003) , 10.1110/PS.0304803
Shlomi Reuveni, Rony Granek, Joseph Klafter, Proteins: Coexistence of Stability and Flexibility Physical Review Letters. ,vol. 100, pp. 208101- 208101 ,(2008) , 10.1103/PHYSREVLETT.100.208101