[Cloning and characterization of a novel trinucleotide repeat-containing gene GARP from Euplotes octocarinatus]

The alphabet of intrinsic disorder: II. Various roles of glutamic acid in ordered and intrinsically disordered proteins

The ability of a protein to fold into unique functional state or to stay intrinsically disordered is encoded in its amino acid sequence. Both ordered and intrinsically disordered proteins (IDPs) are natural polypeptides that use the same arsenal of 20 proteinogenic amino acid residues as their major building blocks. The exceptional structural plasticity of IDPs, their capability to exist as heterogeneous structural ensembles and their wide array of important disorder-based biological functions that complements functional repertoire of ordered proteins are all rooted within the peculiar differential usage of these building blocks by ordered proteins and IDPs. In fact, some residues (so-called disorder-promoting residues) are noticeably more common in IDPs than in sequences of ordered proteins, which, in their turn, are enriched in several order-promoting residues. Furthermore, residues can be arranged according to their “disorder promoting potencies,” which are evaluated based on the relative abundances of various amino acids in ordered and disordered proteins. This review continues a series of publications on the roles of different amino acids in defining the phenomenon of protein intrinsic disorder and concerns glutamic acid, which is the second most disorder-promoting residue.

Uncovering Biological Network Function via Graphlet Degree Signatures

Motivation

Proteins are essential macromolecules of life and thus understanding their function is of great importance. The number of functionally unclassified proteins is large even for simple and well studied organisms such as baker's yeast. Methods for determining protein function have shifted their focus from targeting specific proteins based solely on sequence homology to analyses of the entire proteome based on protein-protein interaction (PPI) networks. Since proteins interact to perform a certain function, analyzing structural properties of PPI networks may provide useful clues about the biological function of individual proteins, protein complexes they participate in, and even larger subcellular machines.

Results

We design a sensitive graph theoretic method for comparing local structures of node neighborhoods that demonstrates that in PPI networks, biological function of a node and its local network structure are closely related. The method summarizes a protein's local topology in a PPI network into the vector of graphlet degrees called the signature of the protein and computes the signature similarities between all protein pairs. We group topologically similar proteins under this measure in a PPI network and show that these protein groups belong to the same protein complexes, perform the same biological functions, are localized in the same subcellular compartments, and have the same tissue expressions. Moreover, we apply our technique on a proteome-scale network data and infer biological function of yet unclassified proteins demonstrating that our method can provide valuable guidelines for future experimental research such as disease protein prediction.

Availability

Data is available upon request.