Function Of New Proteins Research Articles

DomainViz: intuitive visualization of consensus domain distributions across groups of proteins.

The prediction of functional domains is typically among the first steps towards understanding the function of new proteins and protein families. There are numerous databases of annotated protein domains that permit researchers to identify domains on individual proteins of interest. However, it is necessary to perform high-throughput domain searches to gain evolutionary insight into the functions of proteins and protein families. Unfortunately, at present, it is difficult to search for, and visualize domain conservation across multiple proteins and/or multiple groups of proteins in an intuitive manner. Here we present DomainViz, a new web-server that streamlines the identification and visualization of domains across multiple protein sequences. Currently, DomainViz uses the well-established PFAM and Prosite databases for domain searching and assembles intuitive, publication-ready ‘monument valley’ plots (mv-plots) that display the extent of domain conservation along two dimensions: positionality and frequency of occurrence in the input protein sequences. In addition, DomainViz produces a conventional domain-ordering figure. DomainViz can be used to explore the conservation of domains within a single protein family, across multiple families, and across families from different species to support studies into protein function and evolution. The web-server is publicly available at: https://uhrigprotools.biology.ualberta.ca/domainviz.

Quality control of chemical libraries

The complete sequence of the human genome has been deciphered at the dawn of the new century. This historic event immediately challenged researchers with new needs both in terms of concepts and of working methods. Each scientific community considered how it could tackle these new challenges and it quickly became clear that using small chemical molecules would help discovering and characterizing the function of new proteins. The importance of the genes that the encode new proteins could thus be established in cells, organs and whole organisms. At the initiative of a handful of researchers, French chemists have organized the collection of their molecules and provided them to biologists. By doing so they killed two birds with one stone: on the one hand they created a unique opportunity to add value to their molecules by creating the first academic chemical library, and on the other hand they stimulated the launch of biologically active molecules discovery programs by biologists from the academic sector. It was necessary, however, to raise many compounds and ensure consistent quality control, which quickly became a priority for the chemical libraries to become reliable tools.

Improving enzyme regulatory protein classification by means of SVM-RFE feature selection

Enzyme regulation proteins are very important due to their involvement in many biological processes that sustain life. The complexity of these proteins, the impossibility of identifying direct quantification molecular properties associated with the regulation of enzymatic activities, and their structural diversity creates the necessity for new theoretical methods that can predict the enzyme regulatory function of new proteins. The current work presents the first classification model that predicts protein enzyme regulators using the Markov mean properties. These protein descriptors encode the topological information of the amino acid into contact networks based on amino acid distances and physicochemical properties. MInD-Prot software calculated these molecular descriptors for 2415 protein chains (350 enzyme regulators) using five atom physicochemical properties (Mulliken electronegativity, Kang-Jhon polarizability, vdW area, atom contribution to P) and the protein 3D regions. The best classification models to predict enzyme regulators have been obtained with machine learning algorithms from Weka using 18 features. K* has been demonstrated to be the most accurate algorithm for this protein function classification. Wrapper Subset Evaluator and SVM-RFE approaches were used to perform a feature subset selection with the best results obtained from SVM-RFE. Classification performance employing all the available features can be reached using only the 8 most relevant features selected by SVM-RFE. Thus, the current work has demonstrated the possibility of predicting new molecular targets involved in enzyme regulation using fast theoretical algorithms.

Pclust: protein network visualization highlighting experimental data

One approach to infer functions of new proteins from their homologs utilizes visualization of an all-against-all pairwise similarity network (A2ApsN) that exploits the speed of BLAST and avoids the complexity of multiple sequence alignment. However, identifying functions of the protein clusters in A2ApsN is never trivial, due to a lack of linking characterized proteins to their relevant information in current software packages. Given the database errors introduced by automatic annotation transfer, functional deduction should be made from proteins with experimental studies, i.e. 'reference proteins'. Here, we present a web server, termed Pclust, which provides a user-friendly interface to visualize the A2ApsN, placing emphasis on such 'reference proteins' and providing access to their full information in source databases, e.g. articles in PubMed. The identification of 'reference proteins' and the ease of cross-database linkage will facilitate understanding the functions of protein clusters in the network, thus promoting interpretation of proteins of interest. The Pclust server is freely available at http://prodata.swmed.edu/pclust

ChemInform Abstract: Surface Plasmon Resonance Biosensorics in Urine Proteomics

AbstractReview: 45 refs.

Mitotic Moonlighting Functions for Membrane Trafficking Proteins

In recent years, cell biologists have uncovered a number of new functions for proteins that were previously thought to operate solely in membrane trafficking. These alternative roles, termed moonlighting functions, can occur at distinct intracellular sites or at different stages of the cell cycle. Here, I evaluate the evidence for mitotic moonlighting functions of proteins that have membrane trafficking roles during interphase. The aim is to identify key issues facing the field and to outline important questions for future work.

Spatial localization of unknown proteins in the endoplasmic reticulum predicts functions

Protein synthesis, folding and degradation functions are spatially segregated in the endoplasmic reticulum (ER) with respect to the membrane and the ribosome (rough and smooth ER). Interrogation of a proteomics resource characterizing rough and smooth ER membranes subfractionated into cytosolic, membrane, and soluble fractions gives a spatial map of known proteins involved in ER function. The spatial localization of 224 identified unknown proteins in the ER is predicted to give insight into their function. Here we provide evidence that the proteomics resource accurately predicts the function of new proteins involved in protein synthesis (nudilin), protein translocation across the ER membrane (nicalin), co-translational protein folding (stexin), and distal protein folding in the lumen of the ER (erlin-1, TMX2). Proteomics provides the spatial localization of proteins and can be used to accurately predict protein function.

Molecular basis of protein S deficiency

Protein S deficiency (PSD) has been the most difficult to study among the classical inherited thrombophilic factors. This is in part due to the peculiar biology of protein S (PS), which has an anticoagulant role but no enzymatic activity, and because it interacts with plasma components that function in both haemostasis and inflammation. Clinically, it also has been difficult to define and standardise valuable assays to determine PS status and implication in thrombosis. Despite these drawbacks, at present heterozygous PS deficiency is well established as an autosomal dominant trait associated with an increased risk of thrombosis from data on familial and population studies. Almost two-hundred mutations have been characterised in PROS1, and approximately 30% of them have been characterised in vitro, clarifying the mechanisms leading to PSD. Furthermore, recent studies on the presence of large deletions in PROS1 have increased the number of PSD associated to PROS1 mutations. Finally, the discovery of new functions for PS, both in the anticoagulant system as well as in the interaction with cellular components through receptor tyrosine kinases, is broadening the importance of this molecule in the context of biomedicine.

CLANS: a Java application for visualizing protein families based on pairwise similarity.

The main source of hypotheses on the structure and function of new proteins is their homology to proteins with known properties. Homologous relationships are typically established through sequence similarity searches, multiple alignments and phylogenetic reconstruction. In cases where the number of potential relationships is large, for example in P-loop NTPases with many thousands of members, alignments and phylogenies become computationally demanding, accumulate errors and lose resolution. In search of a better way to analyze relationships in large sequence datasets we have developed a Java application, CLANS (CLuster ANalysis of Sequences), which uses a version of the Fruchterman-Reingold graph layout algorithm to visualize pairwise sequence similarities in either two-dimensional or three-dimensional space. CLANS can be downloaded at http://protevo.eb.tuebingen.mpg.de/download.

Automatic annotation of protein function based on family identification.

Although genomes are being sequenced at an impressive rate, the information generated tells us little about protein function, which is slow to characterize by traditional methods. Automatic protein function annotation based on computational methods has alleviated this imbalance. The most powerful current approach for inferring the function of new proteins is by studying the annotations of their homologues, since their common origin is assumed to be reflected in their structure and function. Unfortunately, as proteins evolve they acquire new functions, so annotation based on homology must be carried out in the context of orthologues or subfamilies. Evolution adds new complications through domain shuffling: homology (or orthology) frequently corresponds to domains rather than complete proteins. Moreover, the function of a protein may be seen as the result of combining the functions of its domains. Additionally, automatic annotation has to deal with problems related to the annotations in the databases: errors (which are likely to be propagated), inconsistencies, or different degrees of function specification. We describe a method that addresses these difficulties for the annotation of protein function. Sequence relationships are detected and measured to obtain a map of the sequence space, which is searched for differentiated groups of proteins (similar to islands on the map), which are expected to have a common function and correspond to groups of orthologues or subfamilies. This mapmaking is done by applying a clustering algorithm based on Normalized cuts in graphs. The domain problem is addressed in a simple way: pairwise local alignments are analyzed to determine the extent to which they cover the entire sequence lengths of the two proteins. This analysis determines both what homologues are preferred for functional inheritance and the level of confidence of the annotation. To alleviate the problems associated with database annotations, the information on all the homologues that are grouped together with the query protein are taken into account to select the most representative functional descriptors. This method has been applied for the annotation of the genome of Buchnera aphidicola (specific host Baizongia pistaciae). Human inspection of the annotations allowed an estimation of accuracy of 94%; the different kinds of error that may appear when using this approach are described. Results can be accessed at http://www.pdg.cnb.uam.es/funcut.html. The programs are available upon request, although installation in other systems may be complicated.

Homologous (beta/alpha)8-barrel enzymes that catalyze unrelated reactions: orotidine 5'-monophosphate decarboxylase and 3-keto-L-gulonate 6-phosphate decarboxylase.

The 3-keto-L-gulonate 6-phosphate decarboxylase (KGPDC) encoded by the ulaD gene in the Escherichia coli genome [Yew, W. S., and Gerlt, J. A. (2002) J. Bacteriol. 184, 302-306] and orotidine 5'-monophosphate decarboxylase (OMPDC) are homologous (derived from a common ancestor) but catalyze different reactions. The metal-independent decarboxylation reaction catalyzed by OMPDC avoids the formation of a vinyl anion intermediate; the Mg2+-dependent decarboxylation reaction catalyzed by KGPDC involves the formation of an enediolate anion intermediate. Based on the available structures of OMPDC, a sequence alignment allows the predictions that (1) KGPDC is a dimer of (beta/alpha)8-barrels, with the active sites located at the dimer interface; (2) KGPDC and OMPDC share an aspartate residue at the end of the first beta-strand and an Asp-x-Lys-x-x-Asp motif at the end of the third beta-strand with OMPDC; but (3) KGPDC has a Glu instead of a Lys at the end of the second beta-strand. The structure of KGPDC has been determined in the presence of Mg2+ and the substrate analogue L-gulonate 6-phosphate and confirms these predictions. The carboxylate functional groups at the ends of the first, second, and third beta-strands in KGPDC are ligands of the Mg2+; in OMPDC, the homologues of these residues participate in a hydrogen-bonded network that facilitates the decarboxylation reaction. The 3-OH group of the substrate analogue is coordinated to the Mg2+, supporting the hypothesis that the mechanism of the decarboxylation catalyzed by KGPDC involves stabilization of an enediolate anion intermediate. These structural studies establish the existence of the OMPDC "suprafamily," in which members catalyze reactions that occur in different metabolic pathways and share no mechanistic relationship. The existence of this suprafamily demonstrates that divergent evolution can be opportunistic, conscripting active site features of a progenitor to catalyze unrelated functions. Accordingly, sequence or structure homology alone cannot be used to infer the functions of new proteins discovered in genome projects.

Effect of Heat Shock on Neuronal Cultures: Importance of Protein Synthesis and HSP72 Induction for Induced Tolerance and Survival

In this study the effects of 30 min heat-shock, ranging from 42 degrees C to 46 degrees C, on survival, protein synthesis and HSP72 expression were investigated in primary rat neuronal cultures. Heat-shock of 44 degrees C resulted in a complete, but transient inhibition of protein synthesis which recovered within 24 h. 46 degrees C heat-shock resulted in an irreversible inhibition of protein synthesis and complete neuronal loss within 24 h. Cycloheximide treatment of neuronal cultures resulted in aggravation of neuronal cell damage after heat-shock of 44 degrees C, indicating that the capacity for recovery of the overall protein synthesis is an important survival factor. In addition, the reduction of neuronal cell damage mediated by heat conditioning was abolished by cycloheximide treatment, indicating that the function of new proteins is important for induced thermotolerance. Induction of the strictly inducible member of the heat-shock protein 70kDa family, HSP72, was found in those few astrocytes which were contaminating the neuronal cell cultures, but not in neurons. These results indicate that newly synthesised proteins other than HSP72 are likely to mediate neuronal protection following heat shock in our experiments. These findings raise the possibility that induced tolerance may not necessarily be mediated by HSP72.