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Inferring topological features of proteins from amino acid residue networks

Author

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  • Alves, Nelson Augusto
  • Martinez, Alexandre Souto

Abstract

Topological properties of native folds are obtained from statistical analysis of 160 low homology proteins covering the four structural classes. This is done analyzing one, two and three-vertex joint distribution of quantities related to the corresponding network of amino acid residues. Emphasis on the amino acid residue hydrophobicity leads to the definition of their center of mass as vertices in this contact network model with interactions represented by edges. The network analysis helps us to interpret experimental results such as hydrophobic scales and fraction of buried accessible surface area in terms of the network connectivity. Moreover, those networks show assortative mixing by degree. To explore the vertex-type dependent correlations, we build a network of hydrophobic and polar vertices. This procedure presents the wiring diagram of the topological structure of globular proteins leading to the following attachment probabilities between hydrophobic–hydrophobic 0.424(5), hydrophobic-polar 0.419(2) and polar–polar 0.157(3) residues.

Suggested Citation

  • Alves, Nelson Augusto & Martinez, Alexandre Souto, 2007. "Inferring topological features of proteins from amino acid residue networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(1), pages 336-344.
    • Handle: RePEc:eee:phsmap:v:375:y:2007:i:1:p:336-344
    DOI: 10.1016/j.physa.2006.09.014
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    References listed on IDEAS

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    1. Bagler, Ganesh & Sinha, Somdatta, 2005. "Network properties of protein structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(1), pages 27-33.
    2. Catanzaro, Michele & Caldarelli, Guido & Pietronero, Luciano, 2004. "Social network growth with assortative mixing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 119-124.
    3. Kundu, Sudip, 2005. "Amino acid network within protein," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(1), pages 104-109.
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