Functional grouping based on signatures in protein termini

The carboxy-terminus, a key regulator of protein function

All proteins end with a carboxyl terminus that has unique biophysical properties and is often disordered. Although there are examples of important C-termini functions, a more global role for the C-terminus is not yet established. In this review, we summarize research on C-termini, a unique region in proteins that cells exploit. Alternative splicing and proteolysis increase the diversity of proteins and peptides in cells with unique C-termini. The C-termini of proteins contain minimotifs, short peptides with an encoded function generally characterized as binding, posttranslational modifications, and trafficking. Many of these activities are specific to minimotifs on the C-terminus. Approximately 13% of C-termini in the human proteome have a known minimotif, and the majority, if not all of the remaining termini have conserved motifs inferring a function that remains to be discovered. C-termini, their predictions, and their functions are collated in the C-terminome, Proteus, and Terminus Oriented Protein Function INferred Database (TopFIND) database/web systems. Many C-termini are well conserved, and some have a known role in health and disease. We envision that this summary of C-termini will guide future investigation of their biochemical and physiological significance.

The Functional Human C-Terminome

All translated proteins end with a carboxylic acid commonly called the C-terminus. Many short functional sequences (minimotifs) are located on or immediately proximal to the C-terminus. However, information about the function of protein C-termini has not been consolidated into a single source. Here, we built a new "C-terminome" database and web system focused on human proteins. Approximately 3,600 C-termini in the human proteome have a minimotif with an established molecular function. To help evaluate the function of the remaining C-termini in the human proteome, we inferred minimotifs identified by experimentation in rodent cells, predicted minimotifs based upon consensus sequence matches, and predicted novel highly repetitive sequences in C-termini. Predictions can be ranked by enrichment scores or Gene Evolutionary Rate Profiling (GERP) scores, a measurement of evolutionary constraint. By searching for new anchored sequences on the last 10 amino acids of proteins in the human proteome with lengths between 3-10 residues and up to 5 degenerate positions in the consensus sequences, we have identified new consensus sequences that predict instances in the majority of human genes. All of this information is consolidated into a database that can be accessed through a C-terminome web system with search and browse functions for minimotifs and human proteins. A known consensus sequence-based predicted function is assigned to nearly half the proteins in the human proteome. Weblink: http://cterminome.bio-toolkit.com.

Combining heterogeneous data sources for accurate functional annotation of proteins

Combining heterogeneous sources of data is essential for accurate prediction of protein function. The task is complicated by the fact that while sequence-based features can be readily compared across species, most other data are species-specific. In this paper, we present a multi-view extension to GOstruct, a structured-output framework for function annotation of proteins. The extended framework can learn from disparate data sources, with each data source provided to the framework in the form of a kernel. Our empirical results demonstrate that the multi-view framework is able to utilize all available information, yielding better performance than sequence-based models trained across species and models trained from collections of data within a given species. This version of GOstruct participated in the recent Critical Assessment of Functional Annotations (CAFA) challenge; since then we have significantly improved the natural language processing component of the method, which now provides performance that is on par with that provided by sequence information. The GOstruct framework is available for download at http://strut.sourceforge.net.

C-terminal motif prediction in eukaryotic proteomes using comparative genomics and statistical over-representation across protein families

Background

The carboxy termini of proteins are a frequent site of activity for a variety of biologically important functions, ranging from post-translational modification to protein targeting. Several short peptide motifs involved in protein sorting roles and dependent upon their proximity to the C-terminus for proper function have already been characterized. As a limited number of such motifs have been identified, the potential exists for genome-wide statistical analysis and comparative genomics to reveal novel peptide signatures functioning in a C-terminal dependent manner. We have applied a novel methodology to the prediction of C-terminal-anchored peptide motifs involving a simple z-statistic and several techniques for improving the signal-to-noise ratio.

Results

We examined the statistical over-representation of position-specific C-terminal tripeptides in 7 eukaryotic proteomes. Sequence randomization models and simple-sequence masking were applied to the successful reduction of background noise. Similarly, as C-terminal homology among members of large protein families may artificially inflate tripeptide counts in an irrelevant and obfuscating manner, gene-family clustering was performed prior to the analysis in order to assess tripeptide over-representation across protein families as opposed to across all proteins. Finally, comparative genomics was used to identify tripeptides significantly occurring in multiple species. This approach has been able to predict, to our knowledge, all C-terminally anchored targeting motifs present in the literature. These include the PTS1 peroxisomal targeting signal (SKL*), the ER-retention signal (K/HDEL*), the ER-retrieval signal for membrane bound proteins (KKxx*), the prenylation signal (CC*) and the CaaX box prenylation motif. In addition to a high statistical over-representation of these known motifs, a collection of significant tripeptides with a high propensity for biological function exists between species, among kingdoms and across eukaryotes. Motifs of note include a serine-acidic peptide (DSD*) as well as several lysine enriched motifs found in nearly all eukaryotic genomes examined.

Conclusion

We have successfully generated a high confidence representation of eukaryotic motifs anchored at the C-terminus. A high incidence of true-positives in our results suggests that several previously unidentified tripeptide patterns are strong candidates for representing novel peptide motifs of a widely employed nature in the C-terminal biology of eukaryotes. Our application of comparative genomics, statistical over-representation and the adjustment for protein family homology has generated several hypotheses concerning the C-terminal topology as it pertains to sorting and potential protein interaction signals. This approach to background reduction could be expanded for application to protein motif prediction in the protein interior. A parallel N-terminal analysis is presented as supplementary data.