@article {49757, title = {Evolutionarily conserved network properties of intrinsically disordered proteins.}, journal = {PLoS One}, volume = {10}, year = {2015}, month = {2015}, pages = {e0126729}, abstract = {

BACKGROUND: Intrinsically disordered proteins (IDPs) lack a stable tertiary structure in isolation. Remarkably, however, a substantial portion of IDPs undergo disorder-to-order transitions upon binding to their cognate partners. Structural flexibility and binding plasticity enable IDPs to interact with a broad range of partners. However, the broader network properties that could provide additional insights into the functional role of IDPs are not known.

RESULTS: Here, we report the first comprehensive survey of network properties of IDP-induced sub-networks in multiple species from yeast to human. Our results show that IDPs exhibit greater-than-expected modularity and are connected to the rest of the protein interaction network (PIN) via proteins that exhibit the highest betweenness centrality and connect to fewer-than-expected IDP communities, suggesting that they form critical communication links from IDP modules to the rest of the PIN. Moreover, we found that IDPs are enriched at the top level of regulatory hierarchy.

CONCLUSION: Overall, our analyses reveal coherent and remarkably conserved IDP-centric network properties, namely, modularity in IDP-induced network and a layer of critical nodes connecting IDPs with the rest of the PIN.

}, keywords = {Animals, Cluster Analysis, Databases, Protein, Drosophila, Drosophila Proteins, Evolution, Molecular, HUMANS, Intrinsically Disordered Proteins, Metabolic Networks and Pathways, Mice, Osmotic Pressure, Protein Interaction Maps, Saccharomyces cerevisiae, Saccharomyces cerevisiae Proteins}, issn = {1932-6203}, doi = {10.1371/journal.pone.0126729}, author = {Rangarajan, Nivedita and Kulkarni, Prakash and Hannenhalli, Sridhar} } @article {49728, title = {Predicting selective drug targets in cancer through metabolic networks.}, journal = {Mol Syst Biol}, volume = {7}, year = {2011}, month = {2011}, pages = {501}, abstract = {

The interest in studying metabolic alterations in cancer and their potential role as novel targets for therapy has been rejuvenated in recent years. Here, we report the development of the first genome-scale network model of cancer metabolism, validated by correctly identifying genes essential for cellular proliferation in cancer cell lines. The model predicts 52 cytostatic drug targets, of which 40\% are targeted by known, approved or experimental anticancer drugs, and the rest are new. It further predicts combinations of synthetic lethal drug targets, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection. Finally, potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled.

}, keywords = {Cell Line, Tumor, Cell Proliferation, Computational Biology, Cytostatic Agents, Down-Regulation, Drug Delivery Systems, Gene Expression Regulation, Neoplastic, HUMANS, Metabolic Networks and Pathways, Models, Biological, Neoplasms, RNA, Small Interfering}, issn = {1744-4292}, doi = {10.1038/msb.2011.35}, author = {Folger, Ori and Jerby, Livnat and Frezza, Christian and Gottlieb, Eyal and Ruppin, Eytan and Shlomi, Tomer} }