Phyloproteomic Analysis of 11780 Six-Residue-Long Motifs Occurrences

Disordered Residues and Patterns in the Protein Data Bank

We created a new library of disordered patterns and disordered residues in the Protein Data Bank (PDB). To obtain such datasets, we clustered the PDB and obtained the groups of chains with different identities and marked disordered residues. We elaborated a new procedure for finding disordered patterns and created a new version of the library. This library includes three sets of patterns: unique patterns, patterns consisting of two kinds of amino acids, and homo-repeats. Using this database, the user can: (1) find homologues in the entire Protein Data Bank; (2) perform a statistical analysis of disordered residues in protein structures; (3) search for disordered patterns and homo-repeats; (4) search for disordered regions in different chains of the same protein; (5) download clusters of protein chains with different identity from our database and library of disordered patterns; and (6) observe 3D structure interactively using MView. A new library of disordered patterns will help improve the accuracy of predictions for residues that will be structured or unstructured in a given region.

Is there codon usage bias for poly-Q stretches in the human proteome?

We have analyzed codon usage for poly-Q stretches of different lengths for the human proteome. First, we have obtained that all long poly-Q stretches in Protein Data Bank (PDB) belong to the disordered regions. Second, we have found the bias for codon usage for glutamine homo-repeats in the human proteome. In the cases when the same codon is used for poly-Q stretches only CAG triplets are found. Similar results are obtained for human proteins with glutamine homo-repeats associated with diseases. Moreover, for proteins associated with diseases (from the HraDis database), the fraction of proteins for which the same codon is used for glutamine homo-repeats is less (22%) than for proteins from the human proteome (26%). We have demonstrated for poly-Q stretches in the human proteome that in some cases (28) the splicing sites correspond to the homo-repeats and in 11 cases, these sites appear at the C -terminal part of the homo-repeats with statistical significance 10 -8 .

Proteome-scale relationships between local amino acid composition and protein fates and functions

Proteins with low-complexity domains continue to emerge as key players in both normal and pathological cellular processes. Although low-complexity domains are often grouped into a single class, individual low-complexity domains can differ substantially with respect to amino acid composition. These differences may strongly influence the physical properties, cellular regulation, and molecular functions of low-complexity domains. Therefore, we developed a bioinformatic approach to explore relationships between amino acid composition, protein metabolism, and protein function. We find that local compositional enrichment within protein sequences is associated with differences in translation efficiency, abundance, half-life, protein-protein interaction promiscuity, subcellular localization, and molecular functions of proteins on a proteome-wide scale. However, local enrichment of related amino acids is sometimes associated with opposite effects on protein regulation and function, highlighting the importance of distinguishing between different types of low-complexity domains. Furthermore, many of these effects are discernible at amino acid compositions below those required for classification as low-complexity or statistically-biased by traditional methods and in the absence of homopolymeric amino acid repeats, indicating that thresholds employed by classical methods may not reflect biologically relevant criteria. Application of our analyses to composition-driven processes, such as the formation of membraneless organelles, reveals distinct composition profiles even for closely related organelles. Collectively, these results provide a unique perspective and detailed insights into relationships between amino acid composition, protein metabolism, and protein functions.

Low-complexity domains in protein sequences are regions that are composed of only a few amino acids in the protein “alphabet”. These domains often have unique chemical properties and play important biological roles in both normal and disease-related processes. While a number of approaches have been developed to define low-complexity domains, these methods each possess conceptual limitations. Therefore, we developed a complementary approach that focuses on local amino acid composition (i.e. the amino acid composition within small regions of proteins). We find that high local composition of individual amino acids is associated with pervasive effects on protein metabolism, subcellular localization, and molecular function on a proteome-wide scale. Importantly, the nature of the effects depend on the type of amino acid enriched within the examined domains, and are observable in the absence of classically-defined low-complexity (and related) domains. Furthermore, we define the compositions of proteins involved in the formation of membraneless, protein-rich organelles such as stress granules and P-bodies. Our results provide a coherent view and unprecedented resolution of the effects of local amino acid enrichment on protein biology.

Protein lipograms

Linguistic analysis of protein sequences is an underexploited technique. Here, we capitalize on the concept of the lipogram to characterize sequences at the proteome levels. A lipogram is a literary composition which omits one or more letters. A protein lipogram likewise omits one or more types of amino acid. In this article, we establish a usable terminology for the decomposition of a sequence collection in terms of the lipogram. Next, we characterize Uniref50 using a lipogram decomposition. At the global level, protein lipograms exhibit power-law properties. A clear correlation with metabolic cost is seen. Finally, we use the lipogram construction to assign proteomes to the four branches of the tree-of-life: archaea, bacteria, eukaryotes and viruses. We conclude from this pilot study that the lipogram demonstrates considerable potential as an additional tool for sequence analysis and proteome classification.

How Common Is Disorder? Occurrence of Disordered Residues in Four Domains of Life

Disordered regions play important roles in protein adaptation to challenging environmental conditions. Flexible and disordered residues have the highest propensities to alter the protein packing. Therefore, identification of disordered/flexible regions is important for structural and functional analysis of proteins. We used the IsUnstruct program to predict the ordered or disordered status of residues in 122 proteomes, including 97 eukaryotic and 25 large bacterial proteomes larger than 2,500,000 residues. We found that bacterial and eukaryotic proteomes contain comparable fraction of disordered residues, which was 0.31 in the bacterial and 0.38 in the eukaryotic proteomes. Additional analysis of the total of 1540 bacterial proteomes of various sizes yielded a smaller fraction of disordered residues, which was only 0.26. Together, the results showed that the larger is the size of the proteome, the larger is the fraction of the disordered residues. A continuous dependence of the fraction of disordered residues on the size of the proteome is observed for four domains of life: Eukaryota, Bacteria, Archaea, and Viruses. Furthermore, our analysis of 122 proteomes showed that the fraction of disordered residues increased with increasing the length of homo-repeats for polar, charged, and small residues, and decreased for hydrophobic residues. The maximal fraction of disordered residues was obtained for proteins containing lysine and arginine homo-repeats. The minimal fraction was found in valine and leucine homo-repeats. For 15-residue long homo-repeats these values were 0.2 (for Val and Leu) and 0.7 (for Lys and Arg).