SEARCH · PubMed Health

Results for “Protein Sorting Signals”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15Linked to original sources

PubMed2006

Prediction of signal peptides using bio-basis function neural networks and decision trees.

Signal peptide identification is of immense importance in drug design. Accurate identification of signal peptides is the first critical step to be able to change the direction of the targeting proteins and use the designed drug to target a specific organelle to correct a defect. Because experimental identification is the most accurate method, but is expensive and time-consuming, an efficient and affordable automated system is of great interest. In this article, we propose using an adapted neural network, called a bio-basis function neural network, and decision trees for predicting signal peptides. The bio-basis function neural network model and decision trees achieved 97.16% and 97.63% accuracy respectively, demonstrating that the methods work well for the prediction of signal peptides. Moreover, decision trees revealed that position P(1'), which is important in forming signal peptides, most commonly comprises either leucine or alanine. This concurs with the (P(3)-P(1)-P(1')) coupling model.

Algorithms↗

PubMed2005

Using string kernel to predict signal peptide cleavage site based on subsite coupling model.

Owing to the importance of signal peptides for studying the molecular mechanisms of genetic diseases, reprogramming cells for gene therapy, and finding new drugs for healing a specific defect, it is in great demand to develop a fast and accurate method to identify the signal peptides. Introduction of the so-called {-3,-1, +1} coupling model (Chou, K. C.: Protein Engineering, 2001, 14-2, 75-79) has made it possible to take into account the coupling effect among some key subsites and hence can significantly enhance the prediction quality of peptide cleavage site. Based on the subsite coupling model, a kind of string kernels for protein sequence is introduced. Integrating the biologically relevant prior knowledge, the constructed string kernels can thus be used by any kernel-based method. A Support vector machines (SVM) is thus built to predict the cleavage site of signal peptides from the protein sequences. The current approach is compared with the classical weight matrix method. At small false positive ratios, our method outperforms the classical weight matrix method, indicating the current approach may at least serve as a powerful complemental tool to other existing methods for predicting the signal peptide cleavage site. The software that generated the results reported in this paper is available upon requirement, and will appear at http://www.pami.sjtu.edu.cn/wm.

Models, Genetic↗

PubMed2001

SRbeta coordinates signal sequence release from SRP with ribosome binding to the translocon.

Protein targeting to the endoplasmic reticulum (ER) membrane is regulated by three GTPases, the 54 kDa subunit of the signal recognition particle (SRP) and the alpha- and beta-subunits of the SRP receptor (SR). Using a soluble form of SR and an XTP-binding mutant of SRbeta, we show that SRbeta is essential for protein translocation across the ER membrane. SRbeta can be cross-linked to a 21 kDa ribosomal protein in its empty and GDP-bound state, but not when GTP is bound. GTP binding to SRbeta is required to induce signal sequence release from SRP. This is achieved by the presence of the translocon, which changes the interaction between the 21 kDa ribosomal protein and SRbeta and thereby allows SRbeta to bind GTP. We conclude that SRbeta coordinates the release of the signal sequence from SRP with the presence of the translocon.

Animals↗

PubMed2001

Native and artificial reticuloplasmins co-accumulate in distinct domains of the endoplasmic reticulum and in post-endoplasmic reticulum compartments.

We compared the subcellular distribution of native and artificial reticuloplasmins in endosperm, callus, and leaf tissues of transgenic rice (Oryza sativa) to determine the distribution of these proteins among endoplasmic reticulum (ER) and post-ER compartments. The native reticuloplasmin was calreticulin. The artificial reticuloplasmin was a recombinant single-chain antibody (scFv), expressed with an N-terminal signal peptide and the C-terminal KDEL sequence for retrieval to the ER (scFvT84.66-KDEL). We found that both molecules were distributed in the same manner. In endosperm, each accumulated in ER-derived prolamine protein bodies, but also in glutelin protein storage vacuoles, even though glutelins are known to pass through the Golgi apparatus en route to these organelles. This finding may suggest that similar mechanisms are involved in the sorting of reticuloplasmins and rice seed storage proteins. However, the presence of reticuloplasmins in protein storage vacuoles could also be due to simple dispersal into these compartments during protein storage vacuole biogenesis, before glutelin deposition. In callus and leaf mesophyll cells, both reticuloplasmins accumulated in ribosome-coated vesicles probably derived directly from the rough ER.

Calcium-Binding Proteins↗

PubMed2002

Expression and purification of the chloroplast putative nitrogen sensor, PII, of Arabidopsis thaliana.

The bacterial PII protein was discovered over 30 years ago and is known to be a key player in orchestrating the coordination of nitrogen metabolism with changes in carbon flux. Bacterial PII is regulated by covalent modification and binding to effector molecules in response to the nitrogen/carbon status of the cell and appropriately coordinates the activity of glutamine synthetase and the transcription of a nitrogen sensitive regulon. Recently, a PII protein was identified in higher plants and the protein was found to be localized to the chloroplast. The Arabidopsis thaliana putative nitrogen sensor protein, PII, was cloned and overexpressed with a C-terminal 6-histidine tag. The full-length protein, which included the chloroplast transit peptide, was overexpressed in Escherichia coli, but was very susceptible to proteolytic degradation. Removal of the transit peptide yielded a highly pure, stable recombinant protein whose identity was established as PII by matrix assisted laser desorption ionization-time of flight mass spectrometry. Polyclonal antibodies generated against the recombinant protein effectively immunoprecipitated PII from an A. thaliana extract and the protein was confirmed to be 17 kDa in mass. The availability of milligram amounts of PII will allow a complete biophysical characterization of the protein and antibodies should aid in the identification of PII interacting proteins and the establishment of the higher plant PII signal transduction cascade.

Amino Acid Sequence↗

PubMed1988

Protein translocation across membranes.

Many newly synthesized proteins must be translocated across a membrane to reach their final destinations. Translocation requires a signal on the protein itself, a loose conformation of the protein, energy, and receptor-like components in the cytosol and on the target membrane.

Animals↗

PubMed2006

The translocation inhibitor CAM741 interferes with vascular cell adhesion molecule 1 signal peptide insertion at the translocon.

The cyclopeptolide CAM741 selectively inhibits cotranslational translocation of vascular cell adhesion molecule 1 (VCAM1), a process that is dependent on its signal peptide. In this study we identified the C-terminal (C-) region upstream of the cleavage site of the VCAM1 signal peptide as most critical for inhibition of translocation by CAM741, but full sensitivity to the compound also requires residues of the hydrophobic (h-) region and the first amino acid of the VCAM1 mature domain. The murine VCAM1 signal peptide, which is less susceptible to translocation inhibition by CAM741, can be converted into a fully sensitive signal peptide by two amino acid substitutions identified as critical for compound sensitivity of the human VCAM1 signal peptide. Using cysteine substitutions of non-critical residues in the human VCAM1 signal peptide and chemical cross-linking of targeted short nascent chains we show that, in the presence of CAM741, the N- and C-terminal segments of the VCAM1 signal peptide could be cross-linked to the cytoplasmic tail of Sec61beta, indicating altered positioning of the VCAM1 signal peptide relative to this translocon component. Moreover, translocation of a tag fused N-terminal to the VCAM1 signal peptide is selectively inhibited by CAM741. Our data indicate that the compound inhibits translocation of VCAM1 by interfering with correct insertion of its signal peptide into the translocon.

Amino Acid Sequence↗

PubMed1999

PHYSEAN: PHYsical SEquence ANalysis for the identification of protein domains on the basis of physical and chemical properties of amino acids.

MOTIVATION: PHYSEAN predicts protein classes with highly variable sequences on the basis of their physical, chemical and biological characteristics such as diverse hydrophobicity, structural propensity and steric properties. These characteristics, calculated from multiple positions in a sequence, may be conserved even between sequences that fail to produce alignments at any acceptable level of statistical significance. PHYSEAN complements methods that require sequence alignments (BLAST, FASTA, dynamic programming) by adding less residue- and position-specific physicochemical information on the protein or the domain. RESULTS: We predict proteins or their domains like signal peptides using physical, chemical, geometric, and biological properties of the 20 amino acids. This comprehensive set of properties may cover the diagnostic functional and structural aspects of a domain or a protein class. We automatically select and weight a subset of properties so as to discriminate between, e.g., signal peptides and amino-termini of cytosolic proteins with the lowest number of incorrect predictions. This optimal selection of properties and their weights significantly decreases the number of incorrect predictions as compared to any single property or any combination of unweighted properties. Weights have been optimized by high-performance linear programming models that systematically find the optimal solution from among an astronomic number of property/weight combinations. PHYSEAN's performance is demonstrated by highly accurate predictions of signal peptides (the vehicles for protein transport across membranes) and their cleavage sites. The results indicate reliable predictions are possible even in the lack of sequence conservation using an automated physical and chemical analysis of proteins.

Algorithms↗

PubMed2004

An unusual signal peptide facilitates late steps in the biogenesis of a bacterial autotransporter.

Bacterial autotransporters are proteins that use a C-terminal porin-like domain to facilitate the transport of an upstream "passenger domain" across the outer membrane. Although autotransporters are translocated across the inner membrane (IM) via the Sec pathway, some of them contain exceptionally long signal peptides distinguished by a unique N-terminal sequence motif. In this study, we used the Escherichia coli O157:H7 autotransporter EspP as a model protein to investigate the function of the unusual signal peptides. We found that removal of the N-terminal motif or replacement of the EspP signal peptide did not affect translocation of the protein across the IM. Remarkably, modification of the signal peptide caused EspP to misfold in the periplasm and blocked transport of the passenger domain across the outer membrane. Further analysis suggested that the EspP signal peptide transits slowly through the Sec machinery. Based on these results, we propose that the unusual signal peptides not only function as targeting signals, but also prevent misfolding of the passenger domain in the periplasm by transiently tethering it to the IM.

Escherichia coli↗

PubMed1991

Protein secretion in bacteria.

Most secretory proteins are synthesized as precursors with an amino-terminal signal peptide. Genetic identification of proteins essential for signal peptide dependent translocation to the Escherichia coli periplasm has led to the biochemical dissection of the secretion pathway. Additional mechanisms exist in Gram-negative bacteria for protein secretion to the extracellular environment.

Bacterial Proteins↗

PubMed2002

Support vector machine prediction of signal peptide cleavage site using a new class of kernels for strings.

A new class of kernels for strings is introduced. These kernels can be used by any kernel-based data analysis method, including support vector machines (SVM). They are derived from probabilistic models to integrate biologically relevant information. We show how to compute the kernels corresponding to several classical probabilistic models, and illustrate their use by building a SVM for the problem of predicting the cleavage site of signal peptides from the amino-acid sequence of a protein. At a given rate of false positive this method retrieves up to 47% more true positives than the classical weight matrix method.

Algorithms↗

PubMed2003

Computational differentiation of N-terminal signal peptides and transmembrane helices.

Signal peptides and transmembrane helices both contain a stretch of hydrophobic amino acids. This common feature makes it difficult for signal peptide and transmembrane helix predictors to correctly assign identity to stretches of hydrophobic residues near the N-terminal methionine of a protein sequence. The inability to reliably distinguish between N-terminal transmembrane helix and signal peptide is an error with serious consequences for the prediction of protein secretory status or transmembrane topology. In this study, we report a new method for differentiating protein N-terminal signal peptides and transmembrane helices. Based on the sequence features extracted from hydrophobic regions (amino acid frequency, hydrophobicity, and the start position), we set up discriminant functions and examined them on non-redundant datasets with jackknife tests. This method can incorporate other signal peptide prediction methods and achieve higher prediction accuracy. For Gram-negative bacterial proteins, 95.7% of N-terminal signal peptides and transmembrane helices can be correctly predicted (coefficient 0.90). Given a sensitivity of 90%, transmembrane helices can be identified from signal peptides with a precision of 99% (coefficient 0.92). For eukaryotic proteins, 94.2% of N-terminal signal peptides and transmembrane helices can be correctly predicted with coefficient 0.83. Given a sensitivity of 90%, transmembrane helices can be identified from signal peptides with a precision of 87% (coefficient 0.85). The method can be used to complement current transmembrane protein prediction and signal peptide prediction methods to improve their prediction accuracies.

Algorithms↗

PubMedDate not supplied

On remaining cytoplasmic.

The published literature contains a number of examples of normally non-cytoplasmic proteins whose transport out of the cytoplasm is not completely abolished by drastic alterations to their routing signals (signal sequences, etc). Furthermore, there are numerous examples of cytoplasmic proteins that can be routed to and across plasma or organelle membranes by fusing them to routing signals. These 2 sets of observations lead to a re-evaluation of the reliability and accuracy of protein routing and to consideration of the consequences of the errors which might occur.

Biological Transport↗

PubMed2000

Oligomerization of pro-opiomelanocortin is independent of pH, calcium and the sorting signal for the regulated secretory pathway.

Studies indicate that pro-opiomelanocortin (POMC) is sorted to the regulated secretory pathway by binding to a sorting receptor identified as membrane-bound carboxypeptidase E (CPE) [Cool et al. (1997) Cell 88, 73-83]. The efficiency of this sorting mechanism could be enhanced if POMC molecules were to self-associate to form oligomers, prior or subsequent to binding to CPE. Using cross-linking and gel filtration techniques, we demonstrated that POMC forms oligomers at both neutral and acidic pHs and calcium was not necessary. delta N-POMC, which lacks the N-terminal sorting signal for the regulated secretory pathway, also formed similar oligomers, indicating that the sorting and oligomerization domains are different.

Animals↗

PubMed2000

Large-scale predictions of secretory proteins from mammalian genomic and EST sequences.

Machine learning techniques have improved predictions of secretory proteins from protein, genomic and expressed sequence tag (EST) sequences. Artificial neural networks, physical sequence analysis using high-performance optimization, and hidden Markov models identify extremely variable signal peptides (the vehicles of protein transport across the endoplasmic reticulum membrane), transmembrane segments, and specific extracellular and intracellular domains as indicators of possible roles in the intercellular and intracellular chemical signaling pathways. The major role of peptide hormones, blood coagulation factors, carcinogenesis agents, and other secretory proteins in orchestrating multicellular life indicates pharmacological potential in the cure of major diseases and numerous biotechnological applications.

Animals↗

PubMed1997

Characterization of a novel tyrosine phosphorylated 100-kDa protein that binds to SHP-2 and phosphatidylinositol 3'-kinase in myeloid cells.

Fms is a tyrosine kinase-containing receptor for macrophage colony-stimulating factor (M-CSF) that regulates survival, growth, and differentiation of cells along the monocyte/macrophage lineage. M-CSF stimulation of murine myeloid FDC-P1 cells expressing Fms resulted in the tyrosine phosphorylation of a number of signal transduction proteins, including an unidentified 100-kDa protein. This 100-kDa protein associated with the tyrosine phosphatase SHP-2 but not with the related phosphatase SHP-1. The kinetics of tyrosine phosphorylation of p100 and SHP-2 suggest that p100 may be a direct substrate of SHP-2. p100 bound directly to the SH2 domains of both SHP-2 and the p85 subunit of phosphatidylinositol 3'-kinase. The 100-kDa protein did not appear to bind directly to Fms, Ship, Cbl, Shc, or Grb2, although all of these proteins were coimmunoprecipitated with p85 after M-CSF stimulation. Association of p100 with SHP-2 and p85 did not require the major autophosphorylation sites on Fms nor binding of p85 to Fms. A tyrosine phosphorylated protein of 100 kDa also coprecipitated with SHP-2 from several other myeloid cell lines after M-CSF stimulation but was not seen in immunoprecipitates from Rat2 fibroblasts expressing Fms. Stimulation of FDC-P1 cells with additional cytokines also resulted in coprecipitation of a 100-kDa protein with SHP-2. p100 may therefore be a common component of the signaling pathways of cytokine receptors in myeloid cells.

Adaptor Proteins, Signal Transducing↗

PubMed2006

Proteomics of plant detergent-resistant membranes.

A large body of evidence from the past decade supports the existence, in membrane from animal and yeast cells, of functional microdomains that play important roles in protein sorting, signal transduction, or infection by pathogens. Recent reports demonstrated the presence, in plants, of detergent-resistant fractions isolated from plasma membrane. Analysis of the lipidic composition of this fraction revealed its enrichment in sphingolipids and sterols and depletion in phospho- and glycerolipids as previously observed for animal microdomains. One-dimensional gel electrophoresis experiments indicated that these detergent-resistant fractions are able to recruit a specific set of plasma membrane proteins and exclude others. In the present study, we used mass spectrometry to give an extensive description of a tobacco plasma membrane fraction resistant to solubilization with Triton X-100. This led to the identification of 145 proteins whose functional and physicochemical characteristics were analyzed in silico. Parameters such as isoelectric point, molecular weight, number and length of transmembrane segments, or global hydrophobicity were analyzed and compared with the data available concerning plant plasma membrane proteins. Post-translational modifications, such as myristoylation, palmitoylation, or presence of a glycosylphosphatidylinositol anchor, were examined in relation to the presence of the corresponding proteins in these microdomains. From a functional point of view, this analysis indicated that if a primary function of the plasma membrane, such as transport, seems under-represented in the detergent-resistant fraction, others undergo a significant increase of their relative importance. Among these are signaling and response to biotic and abiotic stress, cellular trafficking, and cell wall metabolism. This suggests that these domains are likely to constitute, as in animal cells, signaling platforms involved in these physiological functions.

Biological Transport↗

PubMed1995

Secretion and circular dichroism analysis of the C-terminal signal peptides of HlyA and LktA.

The secretion of the 107 kDa hemolysin A (HlyA) from Escherichia coli is mediated by membrane proteins hemolysin B (HlyB) and hemolysin D (HlyD). The signal for transport has been mapped to the C-terminal 60 amino acids of the HylA molecule. We have shown previously that the C-terminal 70 amino acids of leukotoxin (LktA) from Pasteurella hemolytica can substitute functionally for the HlyA signal sequence. This 70 amino acid peptide contains little primary sequence similarity to the HlyA signal sequence, and we have hypothesized that these signal sequences assume a similar higher-order structure which is recognized by the HlyB/D transporter. In the present study, we have expressed and purified small peptides containing the C-terminal 61 amino acids of HlyA and the C-terminal 70 amino acids of LktA. We show that these signal peptides are sufficient for secretion from E. coli in a HlyB/D dependent manner. Circular dichroism analyses show that both molecules exhibit common biophysical properties. In aqueous solution, they appear to be mainly unstructured, but in a membrane mimetic environment they assume a helical secondary structure. The conformational change observed for both peptides going from an aqueous to a membrane mimetic environment may be an important feature of these signal sequences necessary for their recognition and transport.

Bacterial Proteins↗