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Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450

The nature of changes involved in crossed-sequence scale and inner-sequence scale is very challenging in protein biology. This study is a new attempt to assess with a phenomenological approach the non-stationary and nonlinear fluctuation of changes encountered in protein sequence. We have computed f...

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Autores principales: Cadet, Xavier F., Dehak, Reda, Chin, Sang Peter, Bessafi, Miloud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515381/
http://dx.doi.org/10.3390/e21090852
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author Cadet, Xavier F.
Dehak, Reda
Chin, Sang Peter
Bessafi, Miloud
author_facet Cadet, Xavier F.
Dehak, Reda
Chin, Sang Peter
Bessafi, Miloud
author_sort Cadet, Xavier F.
collection PubMed
description The nature of changes involved in crossed-sequence scale and inner-sequence scale is very challenging in protein biology. This study is a new attempt to assess with a phenomenological approach the non-stationary and nonlinear fluctuation of changes encountered in protein sequence. We have computed fluctuations from an encoded amino acid index dataset using cumulative sum technique and extracted the departure from the linear trend found in each protein sequence. For inner-sequence analysis, we found that the fluctuations of changes statistically follow a −5/3 Kolmogorov power and behave like an incremental Brownian process. The pattern of the changes in the inner sequence seems to be monofractal in essence and to be bounded between Hurst exponent [1/3,1/2] range, which respectively corresponds to the Kolmogorov and Brownian monofractal process. In addition, the changes in the inner sequence exhibit moderate complexity and chaos, which seems to be coherent with the monofractal and stochastic process highlighted previously in the study. The crossed-sequence changes analysis was achieved using an external parameter, which is the activity available for each protein sequence, and some results obtained for the inner sequence, specifically the drift and Kolmogorov complexity spectrum. We found a significant linear relationship between activity changes and drift changes, and also between activity and Kolmogorov complexity. An analysis of the mean square displacement of trajectories in the bivariate space (drift, activity) and (Kolmogorov complexity spectrum, activity) seems to present a superdiffusive law with a 1.6 power law value.
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spelling pubmed-75153812020-11-09 Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450 Cadet, Xavier F. Dehak, Reda Chin, Sang Peter Bessafi, Miloud Entropy (Basel) Article The nature of changes involved in crossed-sequence scale and inner-sequence scale is very challenging in protein biology. This study is a new attempt to assess with a phenomenological approach the non-stationary and nonlinear fluctuation of changes encountered in protein sequence. We have computed fluctuations from an encoded amino acid index dataset using cumulative sum technique and extracted the departure from the linear trend found in each protein sequence. For inner-sequence analysis, we found that the fluctuations of changes statistically follow a −5/3 Kolmogorov power and behave like an incremental Brownian process. The pattern of the changes in the inner sequence seems to be monofractal in essence and to be bounded between Hurst exponent [1/3,1/2] range, which respectively corresponds to the Kolmogorov and Brownian monofractal process. In addition, the changes in the inner sequence exhibit moderate complexity and chaos, which seems to be coherent with the monofractal and stochastic process highlighted previously in the study. The crossed-sequence changes analysis was achieved using an external parameter, which is the activity available for each protein sequence, and some results obtained for the inner sequence, specifically the drift and Kolmogorov complexity spectrum. We found a significant linear relationship between activity changes and drift changes, and also between activity and Kolmogorov complexity. An analysis of the mean square displacement of trajectories in the bivariate space (drift, activity) and (Kolmogorov complexity spectrum, activity) seems to present a superdiffusive law with a 1.6 power law value. MDPI 2019-08-31 /pmc/articles/PMC7515381/ http://dx.doi.org/10.3390/e21090852 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cadet, Xavier F.
Dehak, Reda
Chin, Sang Peter
Bessafi, Miloud
Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450
title Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450
title_full Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450
title_fullStr Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450
title_full_unstemmed Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450
title_short Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450
title_sort non-linear dynamics analysis of protein sequences. application to cyp450
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515381/
http://dx.doi.org/10.3390/e21090852
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