Scale-free networks and hubsIn biological systems, processes such as growth, energy generation, cell division and signaling are integrated by large, intricate networks. These biological networks, as well as certain nonbiological networks, especially those involved in communications such as the internet and cellular phone systems, are classified as scale-free networks (SFNs) [1][2][3]. The basic feature that separates these networks from non-SFNs such as regular Proteins participate in complex sets of interactions that represent the mechanistic foundation for much of the physiology and function of the cell. These protein-protein interactions are organized into exquisitely complex networks. The architecture of protein-protein interaction networks was recently proposed to be scale-free, with most of the proteins having only one or two connections but with relatively fewer 'hubs' possessing tens, hundreds or more links. The high level of hub connectivity must somehow be reflected in protein structure. What structural quality of hub proteins enables them to interact with large numbers of diverse targets? One possibility would be to employ binding regions that have the ability to bind multiple, structurally diverse partners. This trait can be imparted by the incorporation of intrinsic disorder in one or both partners. To illustrate the value of such contributions, this review examines the roles of intrinsic disorder in protein network architecture. We show that there are three general ways that intrinsic disorder can contribute: First, intrinsic disorder can serve as the structural basis for hub protein promiscuity; secondly, intrinsically disordered proteins can bind to structured hub proteins; and thirdly, intrinsic disorder can provide flexible linkers between functional domains with the linkers enabling mechanisms that facilitate binding diversity. An important research direction will be to determine what fraction of proteinprotein interaction in regulatory networks relies on intrinsic disorder. Abbreviations CaM, calmodulin; Cdk, cyclin-dependent protein kinase; CKI, Cdk inhibitor protein; GSK3b, glycogen synthase kinase 3 beta; ID, intrinsically disordered; MoRE, molecular recognition element; NER, nucleotide excision repair; PDB, Protein Data Bank; PONDRÒ, predictors of naturally disordered regions; RGN, regular network; RNN, random network; SFN, scale-free network; XPA, xeroderma pigmentosum group A protein; FRAT, frequently rearranged in advanced T-cell lymphomas; Wnt, wingless type MMTV integration site family; HMG, high mobility group; VL-XT, a predictor of intrinsic disorder that integrates various methods-based predictor of long disordered regions and X-ray based N-and Cterminal predictors; VSL1, length-dependent predictor of intrinsic protein disorder; RPA, replication protein A; ERCC1, exchange repair cross complementing complex 1; TFIIH, transcription factor IIH; XAB, XPA binding protein; p27Kip , cyclin-dependent kinase inhibitor protein p27/1B.

Intrinsically disordered proteins and regions carry out varied and vital cellular functions. Proteins with disordered regions are especially common in eukaryotic cells, with a subset of these proteins being mostly disordered, e.g., with more disordered than ordered residues. Two distinct methods have been previously described for using amino acid sequences to predict which proteins are likely to be mostly disordered. These methods are based on the net charge-hydropathy distribution and disorder prediction score distribution. Each of these methods is reexamined, and the prediction results are compared herein. A new prediction method based on consensus is described. Application of the consensus method to whole genomes reveals that approximately 4.5% of Yersinia pestis, 5% of Escherichia coli K12, 6% of Archaeoglobus fulgidus, 8% of Methanobacterium thermoautotrophicum, 23% of Arabidopsis thaliana, and 28% of Mus musculus proteins are mostly disordered. The unexpectedly high frequency of mostly disordered proteins in eukaryotes has important implications both for large-scale, high-throughput projects and also for focused experiments aimed at determination of protein structure and function.