Intrinsic structural disorder in cytoskeletal proteins.

Cytoskeleton, the internal scaffold of the cell, displays an exceptional combination of stability and dynamics. It is composed of three major filamentous networks, microfilaments (actin filaments), intermediate filaments (neurofilaments), and microtubules. Together, they ensure the physical and structural stability of the cell, whereby also mediating its large-scale structural rearrangements, motility, stress response, division, and internal transport. All three cytoskeletal systems are built upon the same basic design: they have a central repetitive scaffold assembled from folded building elements, surrounded and regulated by accessory regions/proteins that regulate its formation and mediate its countless interactions with its environment, serving to send regulatory signals to and from the cytoskeleton. Here, we elaborate on the idea that the opposing features of stability and dynamics are also manifest in the dichotomy of the structural status of its components, the core being highly structured and the accessory proteins/regions being highly disordered, and are responsible for most of the regulatory (post-translational) input promoting adaptive responses and providing dynamics necessary for each of the cytoskeletal systems. This pattern entails special consequences, in which the manifold functional advantages of structural disorder, most pronounced in regulatory and signaling functions, are all exploited by nature. (c) 2013 Wiley Periodicals, Inc

Flexible construction of hierarchical scale-free networks with general exponent

Extensive studies have been done to understand the principles behind architectures of real networks. Recently, evidences for hierarchical organization in many real networks have also been reported. Here, we present a new hierarchical model which reproduces the main experimental properties observed in real networks: scale-free of degree distribution $P(k)$ (frequency of the nodes that are connected to $k$ other nodes decays as a power-law $P(k)\sim k^{-\gamma}$) and power-law scaling of the clustering coefficient $C(k)\sim k^{-1}$. The major novelties of our model can be summarized as follows: {\it (a)} The model generates networks with scale-free distribution for the degree of nodes with general exponent $\gamma > 2$, and arbitrarily close to any specified value, being able to reproduce most of the observed hierarchical scale-free topologies. In contrast, previous models can not obtain values of $\gamma > 2.58$. {\it (b)} Our model has structural flexibility because {\it (i)} it can incorporate various types of basic building blocks (e.g., triangles, tetrahedrons and, in general, fully connected clusters of $n$ nodes) and {\it (ii)} it allows a large variety of configurations (i.e., the model can use more than $n-1$ copies of basic blocks of $n$ nodes). The structural features of our proposed model might lead to a better understanding of architectures of biological and non-biological networks.Comment: RevTeX, 5 pages, 4 figure

A diversity-aware computational framework for systems biology

L'abstract è presente nell'allegato / the abstract is in the attachmen