Structural requirements for interaction of peroxisomal targeting signal 2 and its receptor PEX7.

The import of a subset of peroxisomal matrix proteins is mediated by the peroxisomal targeting signal 2 (PTS2). The results of our sequence and physical property analysis of known PTS2 signals and of a mutational study of the least characterized amino acids of a canonical PTS2 motif indicate that PTS2 forms an amphipathic helix accumulating all conserved residues on one side. Three-dimensional structural modeling of the PTS2 receptor PEX7 reveals a groove with an evolutionarily conserved charge distribution complementary to PTS2 signals. Mammalian two-hybrid assays and cross-complementation of a mutation in PTS2 by a compensatory mutation in PEX7 confirm the interaction site. An unstructured linker region separates the PTS2 signal from the core protein. This additional information on PTS2 signals was used to generate a PTS2 prediction algorithm that enabled us to identify novel PTS2 signals within human proteins and to describe KChIP4 as a novel peroxisomal protein.

pkaPS: prediction of protein kinase A phosphorylation sites with the simplified kinase-substrate binding model.

BACKGROUND: Protein kinase A (cAMP-dependent kinase, PKA) is a serine/threonine kinase, for which ca. 150 substrate proteins are known. Based on a refinement of the recognition motif using the available experimental data, we wished to apply the simplified substrate protein binding model for accurate prediction of PKA phosphorylation sites, an approach that was previously successful for the prediction of lipid posttranslational modifications and of the PTS1 peroxisomal translocation signal. RESULTS: Approximately 20 sequence positions flanking the phosphorylated residue on both sides have been found to be restricted in their sequence variability (region -18...+23 with the site at position 0). The conserved physical pattern can be rationalized in terms of a qualitative binding model with the catalytic cleft of the protein kinase A. Positions -6...+4 surrounding the phosphorylation site are influenced by direct interaction with the kinase in a varying degree. This sequence stretch is embedded in an intrinsically disordered region composed preferentially of hydrophilic residues with flexible backbone and small side chain. This knowledge has been incorporated into a simplified analytical model of productive binding of substrate proteins with PKA. CONCLUSION: The scoring function of the pkaPS predictor can confidently discriminate PKA phosphorylation sites from serines/threonines with non-permissive sequence environments (sensitivity of appoximately 96% at a specificity of approximately 94%). The tool "pkaPS" has been applied on the whole human proteome. Among new predicted PKA targets, there are entirely uncharacterized protein groups as well as apparently well-known families such as those of the ribosomal proteins L21e, L22 and L6. AVAILABILITY: The supplementary data as well as the prediction tool as WWW server are available at http://mendel.imp.univie.ac.at/sat/pkaPS. REVIEWERS: Erik van Nimwegen (Biozentrum, University of Basel, Switzerland), Sandor Pongor (International Centre for Genetic Engineering and Biotechnology, Trieste, Italy), Igor Zhulin (University of Tennessee, Oak Ridge National Laboratory, USA).

Application of a sensitive collection heuristic for very large protein families: evolutionary relationship between adipose triglyceride lipase (ATGL) and classic mammalian lipases.

BACKGROUND: Manually finding subtle yet statistically significant links to distantly related homologues becomes practically impossible for very populated protein families due to the sheer number of similarity searches to be invoked and analyzed. The unclear evolutionary relationship between classical mammalian lipases and the recently discovered human adipose triglyceride lipase (ATGL; a patatin family member) is an exemplary case for such a problem. RESULTS: We describe an unsupervised, sensitive sequence segment collection heuristic suitable for assembling very large protein families. It is based on fan-like expanding, iterative database searches. To prevent inclusion of unrelated hits, additional criteria are introduced: minimal alignment length and overlap with starting sequence segments, finding starting sequences in reciprocal searches, automated filtering for compositional bias and repetitive patterns. This heuristic was implemented as FAMILYSEARCHER in the ANNIE sequence analysis environment and applied to search for protein links between the classical lipase family and the patatin-like group. CONCLUSION: The FAMILYSEARCHER is an efficient tool for tracing distant evolutionary relationships involving large protein families. Although classical lipases and ATGL have no obvious sequence similarity and differ with regard to fold and catalytic mechanism, homology links detected with FAMILYSEARCHER show that they are evolutionarily related. The conserved sequence parts can be narrowed down to an ancestral core module consisting of three beta-strands, one alpha-helix and a turn containing the typical nucleophilic serine. Moreover, this ancestral module also appears in numerous enzymes with various substrate specificities, but that critically rely on nucleophilic attack mechanisms.

Hidden localization motifs: naturally occurring peroxisomal targeting signals in non-peroxisomal proteins.

BACKGROUND: Can sequence segments coding for subcellular targeting or for posttranslational modifications occur in proteins that are not substrates in either of these processes? Although considerable effort has been invested in achieving low false-positive prediction rates, even accurate sequence-analysis tools for the recognition of these motifs generate a small but noticeable number of protein hits that lack the appropriate biological context but cannot be rationalized as false positives. RESULTS: We show that the carboxyl termini of a set of definitely non-peroxisomal proteins with predicted peroxisomal targeting signals interact with the peroxisomal matrix protein receptor peroxin 5 (PEX5) in a yeast two-hybrid test. Moreover, we show that examples of these proteins - chicken lysozyme, human tyrosinase and the yeast mitochondrial ribosomal protein L2 (encoded by MRP7) - are imported into peroxisomes in vivo if their original sorting signals are disguised. We also show that even prokaryotic proteins can contain peroxisomal targeting sequences. CONCLUSIONS: Thus, functional localization signals can evolve in unrelated protein sequences as a result of neutral mutations, and subcellular targeting is hierarchically organized, with signal accessibility playing a decisive role. The occurrence of silent functional motifs in unrelated proteins is important for the development of sequence-based function prediction tools and the interpretation of their results. Silent functional signals have the potential to acquire importance in future evolutionary scenarios and in pathological conditions.

Fat mobilization in adipose tissue is promoted by adipose triglyceride lipase.

Mobilization of fatty acids from triglyceride stores in adipose tissue requires lipolytic enzymes. Dysfunctional lipolysis affects energy homeostasis and may contribute to the pathogenesis of obesity and insulin resistance. Until now, hormone-sensitive lipase (HSL) was the only enzyme known to hydrolyze triglycerides in mammalian adipose tissue. Here, we report that a second enzyme, adipose triglyceride lipase (ATGL), catalyzes the initial step in triglyceride hydrolysis. It is interesting that ATGL contains a "patatin domain" common to plant acyl-hydrolases. ATGL is highly expressed in adipose tissue of mice and humans. It exhibits high substrate specificity for triacylglycerol and is associated with lipid droplets. Inhibition of ATGL markedly decreases total adipose acyl-hydrolase activity. Thus, ATGL and HSL coordinately catabolize stored triglycerides in adipose tissue of mammals.

Prediction of sequence signals for lipid post-translational modifications: insights from case studies.

In silico annotation techniques for post-translational modifications (PTMs) are important to generate biologically meaningful descriptions for sequences of experimentally uncharacterized proteins. Having previously contributed with predictors for lipid PTMs, we summarize our methodological experience. Rather than only looking for the sequence pattern in substrate sequences, a strategy aimed at creating a generalized model of substrate protein/enzyme interaction appears more appropriate since the number of known substrate sequences is small, and some of them are not sufficiently verified experimentally. Such a physical approach (in contrast to a mere textual analysis of substrate sequences) can also take into account other, heterogeneous biological data (mutations of substrate sequences, kinetic data, enzyme sequences/structures) with simple analytical expressions in the score function. Several lipid PTMs are encoded in the form of a small sequence region (with pronounced amino acid type preferences) that is connected to the substrate protein by a linker region with many conformationally flexible, hydrophilic residues. A score function composed of terms penalizing sequence properties known to be incompatible with productive substrate protein/enzyme complexes essentially unselects inappropriate queries. Also, we estimate the number of nonredundant sequences necessary for robust profile computation with statistical criteria, a number that is not reached in most cases of PTM prediction. Finally, we discuss the usage of evolutionary information in evaluating the functional importance of predicted PTMs in cases of motif conservation within sequence families.

Prediction of lipid posttranslational modifications and localization signals from protein sequences: big-Pi, NMT and PTS1.

Many posttranslational modifications (N-myristoylation or glycosylphosphatidylinositol (GPI) lipid anchoring) and localization signals (the peroxisomal targeting signal PTS1) are encoded in short, partly compositionally biased regions at the N- or C-terminus of the protein sequence. These sequence signals are not well defined in terms of amino acid type preferences but they have significant interpositional correlations. Although the number of verified protein examples is small, the quantification of several physical conditions necessary for productive protein binding with the enzyme complexes executing the respective transformations can lead to predictors that recognize the signals from the amino acid sequence of queries alone. Taxon-specific prediction functions are required due to the divergent evolution of the active complexes. The big-Pi tool for the prediction of the C-terminal signal for GPI lipid anchor attachment is available for metazoan, protozoan and plant sequences. The myristoyl transferase (NMT) predictor recognizes glycine N-myristoylation sites (at the N-terminus and for fragments after processing) of higher eukaryotes (including their viruses) and fungi. The PTS1 signal predictor finds proteins with a C-terminus appropriate for peroxisomal import (for metazoa and fungi). Guidelines for application of the three WWW-based predictors (http://mendel.imp.univie.ac.at/) and for the interpretation of their output are described.

Motif refinement of the peroxisomal targeting signal 1 and evaluation of taxon-specific differences.

Eukaryote peroxisomes, plant glyoxysomes and trypanosomal glycosomes belong to the microbody family of organelles that compartmentalise a variety of biochemical processes. The interaction between the PTS1 signal and its cognate receptor Pex5 initiates the major import mechanism for proteins into the matrix of these organelles. Relying on the analysis of amino acid sequence variability of known PTS1-targeted proteins and PTS1-containing peptides that interact with Pex5 in the yeast two-hybrid assay, on binding site studies of the Pex5-ligand complex crystal structure, 3D models and sequences of Pex5 proteins from various taxa, we derived the requirements for a C-terminal amino acid sequence to interact productively with Pex5. We found evidence that, at least the 12 C-terminal residues of a given substrate protein are implicated in PTS1 signal recognition. This motif can be structurally and functionally divided into three regions: (i) the C-terminal tripeptide, (ii) a region interacting with the surface of Pex5 (about four residues further upstream), and (iii) a polar, solvent-accessible and unstructured region with linker function (the remaining five residues). Specificity differences are confined to taxonomic subgroups (metazoa and fungi) and are connected with amino acid type preferences in region 1 and deviating hydrophobicity patterns in region 2.

Prediction of peroxisomal targeting signal 1 containing proteins from amino acid sequence.

Peroxisomal matrix proteins have to be imported into their target organelle post-translationally. The major translocation pathway depends on a C-terminal targeting signal, termed PTS1. Our previous analysis of sequence variability in the PTS1 motif revealed that, in addition to the known C-terminal tripeptide, at least nine residues directly upstream are important for signal recognition in the PTS1-Pex5 receptor complex. The refined PTS1 motif description was implemented in a prediction tool composed of taxon-specific functions (metazoa, fungi, remaining taxa), capable of recognising potential PTS1s in query sequences. The composite score function consists of classical profile terms and additional terms penalising deviations from the derived physical property pattern over sequence segments. The prediction algorithm has been validated with a self-consistency and three different cross-validation tests. Additionally, we tested the tool on a large set of non-peroxisomal negatives, on mutation data, and compared the prediction rate to the PTS1 component of the PSORT2 program. The sensitivity of our predictor in recognising documented PTS1 signal containing proteins is close to 90% for reliable prediction. The predictor distinguishes even SKL-appended non-peroxisomally targeted proteins such as a mouse dihydrofolate reductase-SKL construct. The corresponding rate of false positives is not worse than 0.8%; thus, the tool can be applied for large-scale unsupervised sequence database annotation. A scan of public protein databases uncovered a number of yet uncharacterised proteins for which the PTS1 signal might be critical for biological function. The predicted presence of a PTS1 signal implies peroxisomal localisation in the absence of N-terminal targeting sequences such as the mitochondrial import signal.