IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v562y2021ics0378437120307056.html
   My bibliography  Save this article

Long-range correlation and critical fluctuations in coevolution networks of protein sequences

Author

Listed:
  • Xu, Xiu-Lian
  • Shi, Jin-Xuan
  • Wang, Jun
  • Li, Wenfei

Abstract

Stability and adaptability are two conflicting requirements of living systems. Previous statistical survey on the structural ensembles of folded proteins showed that natural proteins have evolved to critical point, at which the proteins have the maximal adaptability but simultaneously maintaining the structural integrity. Here we study the correlation and fluctuation properties of natural proteins from the sequence level by using complex network methods. By performing direct coupling analysis to the amino acid sequences of homologous proteins, we constructed the coevolution networks for the protein families and analyzed the statistical and correlation properties. The results showed that the edge weights of the networks, which were characterized by the direct information of the coevolutionary analysis, have power law distributions. In addition, the correlation length of the fluctuations is proportional to the topological sizes of the proteins, demonstrating scale-free feature of the correlated fluctuations. Our results provide new signature of critical behaviors of the proteins based on the information of amino acid sequences, supporting the previous proposal that natural proteins have evolved to the vicinity of critical point.

Suggested Citation

  • Xu, Xiu-Lian & Shi, Jin-Xuan & Wang, Jun & Li, Wenfei, 2021. "Long-range correlation and critical fluctuations in coevolution networks of protein sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
  • Handle: RePEc:eee:phsmap:v:562:y:2021:i:c:s0378437120307056
    DOI: 10.1016/j.physa.2020.125339
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120307056
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2020.125339?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Farkas, I. & Jeong, H. & Vicsek, T. & Barabási, A.-L. & Oltvai, Z.N., 2003. "The topology of the transcription regulatory network in the yeast, Saccharomyces cerevisiae," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(3), pages 601-612.
    2. Michael Socolich & Steve W. Lockless & William P. Russ & Heather Lee & Kevin H. Gardner & Rama Ranganathan, 2005. "Evolutionary information for specifying a protein fold," Nature, Nature, vol. 437(7058), pages 512-518, September.
    3. Moret, M.A., 2011. "Self-organized critical model for protein folding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(17), pages 3055-3059.
    4. James J. Collins & Carson C. Chow, 1998. "It's a small world," Nature, Nature, vol. 393(6684), pages 409-410, June.
    5. Sachdeva, Vedant & Phillips, James C., 2016. "Oxygen channels and fractal wave–particle duality in the evolution of myoglobin and neuroglobin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 1-11.
    6. An, Xin-lei & Zhang, Li & Li, Yin-zhen & Zhang, Jian-gang, 2014. "Synchronization analysis of complex networks with multi-weights and its application in public traffic network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 149-156.
    7. Phillips, J.C., 2014. "Fractals and self-organized criticality in proteins," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 440-448.
    8. William P. Russ & Drew M. Lowery & Prashant Mishra & Michael B. Yaffe & Rama Ranganathan, 2005. "Natural-like function in artificial WW domains," Nature, Nature, vol. 437(7058), pages 579-583, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yasser Roudi & Sheila Nirenberg & Peter E Latham, 2009. "Pairwise Maximum Entropy Models for Studying Large Biological Systems: When They Can Work and When They Can't," PLOS Computational Biology, Public Library of Science, vol. 5(5), pages 1-18, May.
    2. Phillips, J.C., 2017. "Giant hub Src and Syk tyrosine kinase thermodynamic profiles recapitulate evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 330-336.
    3. Hugo Jacquin & Amy Gilson & Eugene Shakhnovich & Simona Cocco & Rémi Monasson, 2016. "Benchmarking Inverse Statistical Approaches for Protein Structure and Design with Exactly Solvable Models," PLOS Computational Biology, Public Library of Science, vol. 12(5), pages 1-18, May.
    4. Tiberiu Teşileanu & Lucy J Colwell & Stanislas Leibler, 2015. "Protein Sectors: Statistical Coupling Analysis versus Conservation," PLOS Computational Biology, Public Library of Science, vol. 11(2), pages 1-20, February.
    5. Phillips, J.C., 2017. "Hidden thermodynamic information in protein amino acid mutation tables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 676-680.
    6. Phillips, J.C. & Moret, Marcelo A. & Zebende, Gilney F. & Chow, Carson C., 2022. "Phase transitions may explain why SARS-CoV-2 spreads so fast and why new variants are spreading faster," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    7. Wen, Tao & Jiang, Wen, 2018. "An information dimension of weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 388-399.
    8. Masa Tsuchiya & Vincent Piras & Sangdun Choi & Shizuo Akira & Masaru Tomita & Alessandro Giuliani & Kumar Selvarajoo, 2009. "Emergent Genome-Wide Control in Wildtype and Genetically Mutated Lipopolysaccarides-Stimulated Macrophages," PLOS ONE, Public Library of Science, vol. 4(3), pages 1-13, March.
    9. Lahmiri, Salim, 2016. "Clustering of Casablanca stock market based on hurst exponent estimates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 310-318.
    10. Gerhardt, Günther J.L. & Lemke, Ney & Corso, Gilberto, 2006. "Network clustering coefficient approach to DNA sequence analysis," Chaos, Solitons & Fractals, Elsevier, vol. 28(4), pages 1037-1045.
    11. Marcelo A. Moret & James C. Phillips, 2024. "Why and how did the COVID pandemic end abruptly?," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(8), pages 1-4, August.
    12. Shi, Jinyao & Zhou, Peipei & Cai, Shuiming & Jia, Qiang, 2023. "Exponential synchronization for multi-weighted dynamic networks via finite-level quantized control with adaptive scaling gain," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    13. Phillips, J.C., 2016. "Bioinformatic scaling of allosteric interactions in biomedical isozymes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 289-294.
    14. Phillips, J.C., 2015. "Similarity is not enough: Tipping points of Ebola Zaire mortalities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 277-281.
    15. Yu Wei & Sun Ning, 2018. "Establishment and Analysis of the Supernetwork Model for Nanjing Metro Transportation System," Complexity, Hindawi, vol. 2018, pages 1-11, December.
    16. Zhang, Qi & Luo, Chuanhai & Li, Meizhu & Deng, Yong & Mahadevan, Sankaran, 2015. "Tsallis information dimension of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 707-717.
    17. Shou-Wen Wang & Anne-Florence Bitbol & Ned S Wingreen, 2019. "Revealing evolutionary constraints on proteins through sequence analysis," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-16, April.
    18. Phillips, J.C., 2017. "Autoantibody recognition mechanisms of MUC1," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 244-249.
    19. Zhang, Chunmei & Han, Bang-Sheng, 2020. "Stability analysis of stochastic delayed complex networks with multi-weights based on Razumikhin technique and graph theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    20. Marr, Carsten & Hütt, Marc-Thorsten, 2005. "Topology regulates pattern formation capacity of binary cellular automata on graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 641-662.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:562:y:2021:i:c:s0378437120307056. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.