Powerful sequence similarity search methods and in-depth manual analyses can identify remote homologs in many apparently "orphan" viral proteins.

The genome sequences of new viruses often contain many "orphan" or "taxon-specific" proteins apparently lacking homologs. However, because viral proteins evolve very fast, commonly used sequence similarity detection methods such as BLAST may overlook homologs. We analyzed a data set of proteins from RNA viruses characterized as "genus specific" by BLAST. More powerful methods developed recently, such as HHblits or HHpred (available through web-based, user-friendly interfaces), could detect distant homologs of a quarter of these proteins, suggesting that these methods should be used to annotate viral genomes. In-depth manual analyses of a subset of the remaining sequences, guided by contextual information such as taxonomy, gene order, or domain cooccurrence, identified distant homologs of another third. Thus, a combination of powerful automated methods and manual analyses can uncover distant homologs of many proteins thought to be orphans. We expect these methodological results to be also applicable to cellular organisms, since they generally evolve much more slowly than RNA viruses. As an application, we reanalyzed the genome of a bee pathogen, Chronic bee paralysis virus (CBPV). We could identify homologs of most of its proteins thought to be orphans; in each case, identifying homologs provided functional clues. We discovered that CBPV encodes a domain homologous to the Alphavirus methyltransferase-guanylyltransferase; a putative membrane protein, SP24, with homologs in unrelated insect viruses and insect-transmitted plant viruses having different morphologies (cileviruses, higreviruses, blunerviruses, negeviruses); and a putative virion glycoprotein, ORF2, also found in negeviruses. SP24 and ORF2 are probably major structural components of the virions

PROlocalizer: integrated web service for protein subcellular localization prediction

Subcellular localization is an important protein property, which is related to function, interactions and other features. As experimental determination of the localization can be tedious, especially for large numbers of proteins, a number of prediction tools have been developed. We developed the PROlocalizer service that integrates 11 individual methods to predict altogether 12 localizations for animal proteins. The method allows the submission of a number of proteins and mutations and generates a detailed informative document of the prediction and obtained results. PROlocalizer is available at http://bioinf.uta.fi/PROlocalizer/

Three-dimensional Structure of L-2-Haloacid Dehalogenase from Xanthobacter autotrophicus GJ10 Complexed with the Substrate-analogue Formate

The L-2-haloacid dehalogenase from the 1,2-dichloroethane degrading bacterium Xanthobacter autotrophicus GJ10 catalyzes the hydrolytic dehalogenation of small L-2-haloalkanoic acids to yield the corresponding D-2-hydroxyalkanoic acids. Its crystal structure was solved by the method of multiple isomorphous replacement with incorporation of anomalous scattering information and solvent flattening, and was refined at 1.95-Å resolution to an R factor of 21.3%. The three-dimensional structure is similar to that of the homologous L-2-haloacid dehalogenase from Pseudomonas sp. YL (1), but the X. autotrophicus enzyme has an extra dimerization domain, an active site cavity that is completely shielded from the solvent, and a different orientation of several catalytically important amino acid residues. Moreover, under the conditions used, a formate ion is bound in the active site. The position of this substrate-analogue provides valuable information on the reaction mechanism and explains the limited substrate specificity of the Xanthobacter L-2-haloacid dehalogenase.

More Than 1,001 Problems with Protein Domain Databases: Transmembrane Regions, Signal Peptides and the Issue of Sequence Homology

Large-scale genome sequencing gained general importance for life science because functional annotation of otherwise experimentally uncharacterized sequences is made possible by the theory of biomolecular sequence homology. Historically, the paradigm of similarity of protein sequences implying common structure, function and ancestry was generalized based on studies of globular domains. Having the same fold imposes strict conditions over the packing in the hydrophobic core requiring similarity of hydrophobic patterns. The implications of sequence similarity among non-globular protein segments have not been studied to the same extent; nevertheless, homology considerations are silently extended for them. This appears especially detrimental in the case of transmembrane helices (TMs) and signal peptides (SPs) where sequence similarity is necessarily a consequence of physical requirements rather than common ancestry. Thus, matching of SPs/TMs creates the illusion of matching hydrophobic cores. Therefore, inclusion of SPs/TMs into domain models can give rise to wrong annotations. More than 1001 domains among the 10,340 models of Pfam release 23 and 18 domains of SMART version 6 (out of 809) contain SP/TM regions. As expected, fragment-mode HMM searches generate promiscuous hits limited to solely the SP/TM part among clearly unrelated proteins. More worryingly, we show explicit examples that the scores of clearly false-positive hits, even in global-mode searches, can be elevated into the significance range just by matching the hydrophobic runs. In the PIR iProClass database v3.74 using conservative criteria, we find that at least between 2.1% and 13.6% of its annotated Pfam hits appear unjustified for a set of validated domain models. Thus, false-positive domain hits enforced by SP/TM regions can lead to dramatic annotation errors where the hit has nothing in common with the problematic domain model except the SP/TM region itself. We suggest a workflow of flagging problematic hits arising from SP/TM-containing models for critical reconsideration by annotation users

Generation and physiological roles of linear ubiquitin chains

Ubiquitination now ranks with phosphorylation as one of the best-studied post-translational modifications of proteins with broad regulatory roles across all of biology. Ubiquitination usually involves the addition of ubiquitin chains to target protein molecules, and these may be of eight different types, seven of which involve the linkage of one of the seven internal lysine (K) residues in one ubiquitin molecule to the carboxy-terminal diglycine of the next. In the eighth, the so-called linear ubiquitin chains, the linkage is between the amino-terminal amino group of methionine on a ubiquitin that is conjugated with a target protein and the carboxy-terminal carboxy group of the incoming ubiquitin. Physiological roles are well established for K48-linked chains, which are essential for signaling proteasomal degradation of proteins, and for K63-linked chains, which play a part in recruitment of DNA repair enzymes, cell signaling and endocytosis. We focus here on linear ubiquitin chains, how they are assembled, and how three different avenues of research have indicated physiological roles for linear ubiquitination in innate and adaptive immunity and suppression of inflammation

The Dynamical Mechanism of Auto-Inhibition of AMP-Activated Protein Kinase

We use a novel normal mode analysis of an elastic network model drawn from configurations generated during microsecond all-atom molecular dynamics simulations to analyze the mechanism of auto-inhibition of AMP-activated protein kinase (AMPK). A recent X-ray and mutagenesis experiment (Chen, et al Nature 2009, 459, 1146) of the AMPK homolog S. Pombe sucrose non-fermenting 1 (SNF1) has proposed a new conformational switch model involving the movement of the kinase domain (KD) between an inactive unphosphorylated open state and an active or semi-active phosphorylated closed state, mediated by the autoinhibitory domain (AID), and a similar mutagenesis study showed that rat AMPK has the same auto-inhibition mechanism. However, there is no direct dynamical evidence to support this model and it is not clear whether other functionally important local structural components are equally inhibited. By using the same SNF1 KD-AID fragment as that used in experiment, we show that AID inhibits the catalytic function by restraining the KD into an unproductive open conformation, thereby limiting local structural rearrangements, while mutations that disrupt the interactions between the KD and AID allow for both the local structural rearrangement and global interlobe conformational transition. Our calculations further show that the AID also greatly impacts the structuring and mobility of the activation loop

Transcript Expression Analysis of Putative Trypanosoma brucei GPI-Anchored Surface Proteins during Development in the Tsetse and Mammalian Hosts

Human African Trypanosomiasis is a devastating disease caused by the parasite Trypanosoma brucei. Trypanosomes live extracellularly in both the tsetse fly and the mammal. Trypanosome surface proteins can directly interact with the host environment, allowing parasites to effectively establish and maintain infections. Glycosylphosphatidylinositol (GPI) anchoring is a common posttranslational modification associated with eukaryotic surface proteins. In T. brucei, three GPI-anchored major surface proteins have been identified: variant surface glycoproteins (VSGs), procyclic acidic repetitive protein (PARP or procyclins), and brucei alanine rich proteins (BARP). The objective of this study was to select genes encoding predicted GPI-anchored proteins with unknown function(s) from the T. brucei genome and characterize the expression profile of a subset during cyclical development in the tsetse and mammalian hosts. An initial in silico screen of putative T. brucei proteins by Big PI algorithm identified 163 predicted GPI-anchored proteins, 106 of which had no known functions. Application of a second GPI-anchor prediction algorithm (FragAnchor), signal peptide and trans-membrane domain prediction software resulted in the identification of 25 putative hypothetical proteins. Eighty-one gene products with hypothetical functions were analyzed for stage-regulated expression using semi-quantitative RT-PCR. The expression of most of these genes were found to be upregulated in trypanosomes infecting tsetse salivary gland and proventriculus tissues, and 38% were specifically expressed only by parasites infecting salivary gland tissues. Transcripts for all of the genes specifically expressed in salivary glands were also detected in mammalian infective metacyclic trypomastigotes, suggesting a possible role for these putative proteins in invasion and/or establishment processes in the mammalian host. These results represent the first large-scale report of the differential expression of unknown genes encoding predicted T. brucei surface proteins during the complete developmental cycle. This knowledge may form the foundation for the development of future novel transmission blocking strategies against metacyclic parasites

VASCo: computation and visualization of annotated protein surface contacts

<p>Abstract</p> <p>Background</p> <p>Structural data from crystallographic analyses contain a vast amount of information on protein-protein contacts. Knowledge on protein-protein interactions is essential for understanding many processes in living cells. The methods to investigate these interactions range from genetics to biophysics, crystallography, bioinformatics and computer modeling. Also crystal contact information can be useful to understand biologically relevant protein oligomerisation as they rely in principle on the same physico-chemical interaction forces. Visualization of crystal and biological contact data including different surface properties can help to analyse protein-protein interactions.</p> <p>Results</p> <p>VASCo is a program package for the calculation of protein surface properties and the visualization of annotated surfaces. Special emphasis is laid on protein-protein interactions, which are calculated based on surface point distances. The same approach is used to compare surfaces of two aligned molecules. Molecular properties such as electrostatic potential or hydrophobicity are mapped onto these surface points. Molecular surfaces and the corresponding properties are calculated using well established programs integrated into the package, as well as using custom developed programs. The modular package can easily be extended to include new properties for annotation. The output of the program is most conveniently displayed in PyMOL using a custom-made plug-in.</p> <p>Conclusion</p> <p>VASCo supplements other available protein contact visualisation tools and provides additional information on biological interactions as well as on crystal contacts. The tool provides a unique feature to compare surfaces of two aligned molecules based on point distances and thereby facilitates the visualization and analysis of surface differences.</p

Identification of Giardia lamblia DHHC Proteins and the Role of Protein S-palmitoylation in the Encystation Process

Protein S-palmitoylation, a hydrophobic post-translational modification, is performed by protein acyltransferases that have a common DHHC Cys-rich domain (DHHC proteins), and provides a regulatory switch for protein membrane association. In this work, we analyzed the presence of DHHC proteins in the protozoa parasite Giardia lamblia and the function of the reversible S-palmitoylation of proteins during parasite differentiation into cyst. Two specific events were observed: encysting cells displayed a larger amount of palmitoylated proteins, and parasites treated with palmitoylation inhibitors produced a reduced number of mature cysts. With bioinformatics tools, we found nine DHHC proteins, potential protein acyltransferases, in the Giardia proteome. These proteins displayed a conserved structure when compared to different organisms and are distributed in different monophyletic clades. Although all Giardia DHHC proteins were found to be present in trophozoites and encysting cells, these proteins showed a different intracellular localization in trophozoites and seemed to be differently involved in the encystation process when they were overexpressed. dhhc transgenic parasites showed a different pattern of cyst wall protein expression and yielded different amounts of mature cysts when they were induced to encyst. Our findings disclosed some important issues regarding the role of DHHC proteins and palmitoylation during Giardia encystation.Fil: Merino, Maria Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; ArgentinaFil: Zamponi, Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; ArgentinaFil: Vranych, Cecilia Verónica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; ArgentinaFil: Touz, Maria Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; ArgentinaFil: Ropolo, Andrea Silvana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; Argentin

Glycosylation site prediction using ensembles of Support Vector Machine classifiers

Article discussing the performance of different computational methods for prediction of glycosylation sites from amino acid sequences