https://www.cbs.dtu.dk/services/SignalP-4.1/paper-3.0.pdf

Improved Prediction of Signal Peptides: SignalP 3.0

Mitochondria play a key part in the regulation of apoptosis (cell death). Their intermembrane space contains several proteins that are liberated through the outer membrane in order to participate in the degradation phase of apoptosis. Here we report the identification and cloning of an apoptosis-inducing factor, AIF, which is sufficient to induce apoptosis of isolated nuclei. AIF is a flavoprotein of relative molecular mass 57,000 which shares homology with the bacterial oxidoreductases; it is normally confined to mitochondria but translocates to the nucleus when apoptosis is induced. Recombinant AIF causes chromatin condensation in isolated nuclei and large-scale fragmentation of DNA. It induces purified mitochondria to release the apoptogenic proteins cytochrome c and caspase-9. Microinjection of AIF into the cytoplasm of intact cells induces condensation of chromatin, dissipation of the mitochondrial transmembrane potential, and exposure of phosphatidylserine in the plasma membrane. None of these effects is prevented by the wide-ranging caspase inhibitor known as Z-VAD.fmk. Overexpression of Bcl-2, which controls the opening of mitochondrial permeability transition pores, prevents the release of AIF from the mitochondrion but does not affect its apoptogenic activity. These results indicate that AIF is a mitochondrial effector of apoptotic cell death.

Molecular characterization of mitochondrial apoptosis-inducing factor

Determining the subcellular localization of a protein is an important first step toward understanding its function. Here, we describe the properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts, and sketch a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties. We then outline how to use a number of internet-accessible tools to arrive at a reliable subcellular localization prediction for eukaryotic and prokaryotic proteins. In particular, we provide detailed step-by-step instructions for the coupled use of the amino-acid sequence-based predictors TargetP, SignalP, ChloroP and TMHMM, which are all hosted at the Center for Biological Sequence Analysis, Technical University of Denmark. In addition, we describe and provide web references to other useful subcellular localization predictors. Finally, we discuss predictive performance measures in general and the performance of TargetP and SignalP in particular.

/pdf/locating-proteins-in-the-cell-using-targetp-signalp-and-39i9pd64rh.pdf

Locating proteins in the cell using TargetP, SignalP and related tools

PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization.

The cellular attributes of a protein, such as which compartment of a cell it belongs to and how it is associated with the lipid bilayer of an organelle, are closely correlated with its biological functions. The success of human genome project and the rapid increase in the number of protein sequences entering into data bank have stimulated a challenging frontier: How to develop a fast and accurate method to predict the cellular attributes of a protein based on its amino acid sequence? The existing algorithms for predicting these attributes were all based on the amino acid composition in which no sequence order effect was taken into account. To improve the prediction quality, it is necessary to incorporate such an effect. However, the number of possible patterns for protein sequences is extremely large, which has posed a formidable difficulty for realizing this goal. To deal with such a difficulty, the pseudo-amino acid composition is introduced. It is a combination of a set of discrete sequence correlation factors and the 20 components of the conventional amino acid composition. A remarkable improvement in prediction quality has been observed by using the pseudo-amino acid composition. The success rates of prediction thus obtained are so far the highest for the same classification schemes and same data sets. It has not escaped from our notice that the concept of pseudo-amino acid composition as well as its mathematical framework and biochemical implication may also have a notable impact on improving the prediction quality of other protein features.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.1072

Prediction of protein cellular attributes using pseudo‐amino acid composition

Relation between amino acid composition and cellular location of proteins.

The thermal stability of proteins was studied, 195 single amino acid residue replacements reported elsewhere being analysed for several protein conformational characteristics: type of residue replacement; conservative versus nonconservative substitution; replacement being in a homologous stretch of amino acid residues; change in hydrogen bond, van der Waals and secondary structure propensities; solvent-accessible versus inaccessible replacement; type of secondary structure involved in the substitution; the physico-chemical characteristics to which the thermostability enhancement can be attributed; and the relationship of the replacement site to the folding intermediates of the protein, when known. From the above analyses, some general rules arise which suggest where amino acid substitutions can be made to enhance protein thermostability: substitutions are conservative according to the Dayhoff matrix; mainly occur on conserved stretches of residues; preferentially occur on solvent-accessible residues; maintain or enhance the secondary structure propensity upon substitution; contribute to neutralize the dipole moment of the caps of helices and strands; and tend to increase the number of potential hydrogen bonding or van der Waals contacts or improve hydrophobic packing.

/pdf/analysis-of-protein-conformational-characteristics-related-1tckw6vhqi.pdf

Analysis of protein conformational characteristics related to thermostability

A Bacillus licheniformis gene coding for an endo-beta-1,3-1,4-D-glucanase have been cloned in Escherichia coli and sequenced. The open reading frame contains a sequence of 731 bp, encoding a polypeptide of 243 amino acid residues, with a molecular mass of 27404 Da (24418 Da without the putative signal peptide), which corresponds to the enzyme we had previously isolated and characterized. The signal peptide is functional in E. coli. More than 60% of the endo-beta-1,3-1,4-D-glucanase activity is extracellular or periplasmic. The polypeptide is highly similar to other reported Bacillus beta-glucanases. Several structural predictive analyses (secondary structure, hydropathic plots, similarity with other related enzymes, etc.) have been performed. From these analyses we assign a tentative three-functional-domain structure for the enzyme (signal peptide, substrate binding and catalytic domains) and a putative lysozyme-like active site.

Molecular cloning, expression and nucleotide sequence of the endo-beta-1,3-1,4-D-glucanase gene from Bacillus licheniformis. Predictive structural analyses of the encoded polypeptide.

Josep A. Pérez-Pons

Papers

Relation between amino acid composition and cellular location of proteins.

Analysis of protein conformational characteristics related to thermostability

Molecular cloning, expression and nucleotide sequence of the endo-beta-1,3-1,4-D-glucanase gene from Bacillus licheniformis. Predictive structural analyses of the encoded polypeptide.

Glycoprotein E of bovine herpesvirus type 1 is involved in virus transmission by direct cell-to-cell spread

Properties of a novel glucose-enhanced β-glucosidase purified from Streptomyces sp. (ATCC 11238)