Possible Occurrence of Scale-Free Topology in Highly Statistically Associated Polymorphic Positions in Two Potyviral Proteins

We examined the associations between polymorphic positions of two Potyviral proteins, HCPro and NIb, using a combined statistical and bioinformatic methodology. We constructed the relevant graph for each protein by assigning the polymorphic positions as vertices and the identified associations between them as links. We found that the relationships among positions in both molecules displayed a complex topology. In addition, the degree distribution of each network adequately fit a power law distribution, with a small number of vertices dominating a large number of associations. The graphs for both proteins shared similar topological features despite differences in protein size, similarity, functionality, and location of the coding regions in the potyviral genome. Our findings suggest that the intramolecular associations of potyviral proteins display scale free architecture, implying that this system may undergo developmental processes similar to those described for other scale free systems.

[1]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[2]  A. Barabasi,et al.  Evolution of the social network of scientific collaborations , 2001, cond-mat/0104162.

[3]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

[4]  A. Barabasi,et al.  Quantifying social group evolution , 2007, Nature.

[5]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[6]  Albert-László Barabási,et al.  COMMUNITY DYNAMICS IN SOCIAL NETWORKS , 2007 .

[7]  A. Barabasi,et al.  Predicting synthetic rescues in metabolic networks , 2008, Molecular systems biology.

[8]  A. Lapedes,et al.  Covariation of mutations in the V3 loop of human immunodeficiency virus type 1 envelope protein: an information theoretic analysis. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Sophia Tsoka,et al.  Robustness of the p53 network and biological hackers , 2005, FEBS letters.

[10]  Albert-László Barabási,et al.  Internet: Diameter of the World-Wide Web , 1999, Nature.

[11]  E. Domingo,et al.  Quasispecies : concept and implications for virology , 2006 .

[12]  A. Barabasi,et al.  Scale-free characteristics of random networks: the topology of the world-wide web , 2000 .

[13]  Fidel Ramírez,et al.  Computing topological parameters of biological networks , 2008, Bioinform..

[14]  A. Valencia,et al.  High-confidence prediction of global interactomes based on genome-wide coevolutionary networks , 2008, Proceedings of the National Academy of Sciences.

[15]  A. Barabasi,et al.  Functional and topological characterization of protein interaction networks , 2004, Proteomics.

[16]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.