Network strategies to understand the aging process and help age-related drug design

Recent studies have demonstrated that network approaches are highly appropriate tools to understand the extreme complexity of the aging process. The generality of the network concept helps to define and study the aging of technological, social networks and ecosystems, which may give novel concepts to cure age-related diseases. The current review focuses on the role of protein-protein interaction networks (interactomes) in aging. Hubs and inter-modular elements of both interactomes and signaling networks are key regulators of the aging process. Aging induces an increase in the permeability of several cellular compartments, such as the cell nucleus, introducing gross changes in the representation of network structures. The large overlap between aging genes and genes of age-related major diseases makes drugs which aid healthy aging promising candidates for the prevention and treatment of age-related diseases, such as cancer, atherosclerosis, diabetes and neurodegenerative disorders. We also discuss a number of possible research options to further explore the potential of the network concept in this important field, and show that multi-target drugs (representing "magic-buckshots" instead of the traditional "magic bullets") may become an especially useful class of age-related future drugs.Comment: an invited paper to Genome Medicine with 8 pages, 2 figures, 1 table and 46 reference

Correlations of game centrality (GC) with degree, betweenness centrality and phenotypic potential of proteins in a high fidelity yeast interactome.

a<p>Simulations of the prisoner’s dilemma game were performed as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#s4" target="_blank">Methods</a> using the parameter set of (R = 3, T = 6, S = 0, P = 1). Correlation values between degree, betweenness centrality, GC in prisoner’s dilemma game, as well as phenotypic potential <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Levy1" target="_blank">[44]</a> were calculated for the 2,444 proteins of the high fidelity yeast interactome of Ekman <i>et al.</i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Ekman1" target="_blank">[36]</a>.</p>b<p>Data represent Goodman-Kruskal’s gamma values ± standard errors. Significance levels in parentheses were also calculated using Goodman-Kruskal’s gamma test (the null hypothesis being that the correlation is different from zero).</p>c<p>Using the R-package correlation test (<a href="http://personality-project.org/r/html/r.test.html" target="_blank">http://personality-project.org/r/html/r.test.html</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Steiger1" target="_blank">[62]</a>) the correlation between phenotypic potential and game centrality was significantly larger than the correlation between phenotypic potential and degree, or the correlation between phenotypic potential and betweenness centrality.</p

Average game centrality (GC) values for <i>E. coli</i> methionyl-tRNA synthetase amino acids.

a<p>Protein structure network of <i>E coli</i> methionyl-tRNA-synthetase was constructed, Prisoner’s dilemma game was simulated, and game centrality measures were calculated as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#s4" target="_blank">Methods</a>.</p>b<p>Domains from top to bottom: the catalytic domain including the Rossmann-fold-1 (catalytic function), Rossmann-fold-2 and stem contact fold (KMSKS) sub-domains; the connecting peptide (CP) domain; the anticodon binding, carboxy-terminal domain, 43 signaling amino acids involved in the transmission of conformational change as shown by Ghosh and Vishveshwara <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Ghosh2" target="_blank">[46]</a>, whole methionyl-tRNA synthetase.</p

Game centralities of <i>E.</i><i>coli</i> methionyl-tRNA synthetase amino acids.

<p>The protein structure network of <i>E. coli</i> methionyl-tRNA-synthetase was constructed, prisoner’s dilemma game was simulated, and game centrality measures were calculated as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#s4" target="_blank">Methods</a>. Game centralities were overlaid to the 3D image of the protein and tRNA made by the PyMOL program package <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-DeLano1" target="_blank">[66]</a>. tRNA^Met is shown in green, the most influential amino acids spreading defection are marked red (these amino acids have the largest game centrality, GC values) and the least influential amino acids are blue (having the smallest GC values).</p

Game centrality of party hubs, date hubs and randomly selected nodes of a high-fidelity yeast protein-protein interaction network.

a<p>Prisoner’s dilemma game was simulated using the high-fidelity yeast interactome of Ekman <i>et al.</i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Ekman1" target="_blank">[36]</a>, and game centrality measures were calculated as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#s4" target="_blank">Methods</a>.</p>b<p>Initially all 2,444 nodes were cooperating except for 30 defecting nodes, which were randomly sampled 2000 times from 63 consensus party hubs (compiled as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Kovcs1" target="_blank">[43]</a>, see Table S1 of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159.s001" target="_blank">Text S1</a>), from 145 consensus date hubs (compiled as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Kovcs1" target="_blank">[43]</a>, see Table S2 of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159.s001" target="_blank">Text S1</a>), as well as from all the 2,444 nodes in the network.</p>c<p>Data represent sample means ± standard error. The distributions of the game centrality values were significantly different according to the chi-square test (χ²>400).</p

Functional analysis of yeast proteins having the largest game centralities.

<p>Prisoner’s dilemma game was simulated on a high-fidelity yeast interactome <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Ekman1" target="_blank">[36]</a>, and game centrality measures were calculated as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#s4" target="_blank">Methods</a>. 171 proteins out of the 2,444 nodes of the high-fidelity yeast interactome were selected by selecting nodes, which diminished the cooperation level from ∼1 to 0.9 or below. Functional analysis of the 171 proteins was performed using the Cytoscape plug-in, BiNGO <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Maere1" target="_blank">[63]</a> to assess the over-representation of associated Gene Ontology molecular function terms. Gene Ontology Slim definitions for <i>Saccharomyces cerevisiae </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-TheGeneOntology1" target="_blank">[64]</a> were used discarding the evidence codes IEA (inferred from electronic annotation), ISS (inferred from sequence structural similarity) and NAS (non-traceable author statement). A hypergeometric test with false discovery rate correction <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067159#pone.0067159-Benjamini1" target="_blank">[65]</a> was used to select and visualize the significantly enriched GO functions at a level p<0.001, using the GO-s of the entire network as reference set. Colors represent functional categories: red, nucleus-related; blue, transport-related; green, signaling-related; yellow denotes other functions. The size of the circles represents the number of proteins found in the category.</p