ProSNEx: a web-based application for exploration and analysis of protein structures using network formalism.

ProSNEx (Protein Structure Network Explorer) is a web service for construction and analysis of Protein Structure Networks (PSNs) alongside amino acid flexibility, sequence conservation and annotation features. ProSNEx constructs a PSN by adding nodes to represent residues and edges between these nodes using user-specified interaction distance cutoffs for either carbon-alpha, carbon-beta or atom-pair contact networks. Different types of weighted networks can also be constructed by using either (i) the residue-residue interaction energies in the format returned by gRINN, resulting in a Protein Energy Network (PEN); (ii) the dynamical cross correlations from a coarse-grained Normal Mode Analysis (NMA) of the protein structure; (iii) interaction strength. Upon construction of the network, common network metrics (such as node centralities) as well as shortest paths between nodes and k-cliques are calculated. Moreover, additional features of each residue in the form of conservation scores and mutation/natural variant information are included in the analysis. By this way, tool offers an enhanced and direct comparison of network-based residue metrics with other types of biological information. ProSNEx is free and open to all users without login requirement at http://prosnex-tool.com.

Residue packing in globular and intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs)/regions do not have well-defined secondary and tertiary structures, however, they are functional and it is critical to gain a deep understanding of their residue packing. The shape distributions methodology, which is usually utilized in pattern recognition, clustering, and classification studies in computer science, may be adopted to study the residue packing of the proteins. In this study, shape distributions of the globular proteins and IDPs were obtained to shed light on the residue packing of their structures. The shape feature that was used is the sphericity of tetrahedra obtained by Delaunay Tessellation of points of Cα coordinates. Then the sphericity probability distributions were compared by using Principal Component Analysis. This computational structural study shows that the set of IDPs constitute a more diverse set than the set of globular proteins in terms of the geometrical properties of their network structures.