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Self-organized critical model for protein folding

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  • Moret, M.A.

Abstract

The major factor that drives a protein toward collapse and folding is the hydrophobic effect. At the folding process a hydrophobic core is shielded by the solvent-accessible surface area of the protein. We study the fractal behavior of 5526 protein structures present in the Brookhaven Protein Data Bank. Power laws of protein mass, volume and solvent-accessible surface area are measured independently. The present findings indicate that self-organized criticality is an alternative explanation for the protein folding. Also we note that the protein packing is an independent and constant value because the self-similar behavior of the volumes and protein masses have the same fractal dimension. This power law guarantees that a protein is a complex system. From the analyzed data, q-Gaussian distributions seem to fit well this class of systems.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:17:p:3055-3059
    DOI: 10.1016/j.physa.2011.04.008
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    Cited by:

    1. 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).
    2. Phillips, J.C., 2012. "Frequency–rank correlations of rhodopsin mutations with tuned hydropathic roughness based on self-organized criticality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5473-5478.

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