Hierarchical classification of G-protein-coupled receptors with data-driven selection of attributes and classifiers

We address the important bioinformatics problem of predicting protein function from a protein's primary sequence. We consider the functional classification of G-Protein-Coupled Receptors (GPCRs), whose functions are specified in a class hierarchy. We tackle this task using a novel top-down hierarchical classification system where, for each node in the class hierarchy, the predictor attributes to be used in that node and the classifier to be applied to the selected attributes are chosen in a data-driven manner. Compared with a previous hierarchical classification system selecting classifiers only, our new system significantly reduced processing time without significantly sacrificing predictive accuracy.

Protein-protein interactions classification from text via local learning with class priors

Text classification is essential for narrowing down the number of documents relevant to a particular topic for further pursual, especially when searching through large biomedical databases. Protein-protein interactions are an example of such a topic with databases being devoted specifically to them. This paper proposed a semi-supervised learning algorithm via local learning with class priors (LL-CP) for biomedical text classification where unlabeled data points are classified in a vector space based on their proximity to labeled nodes. The algorithm has been evaluated on a corpus of biomedical documents to identify abstracts containing information about protein-protein interactions with promising results. Experimental results show that LL-CP outperforms the traditional semisupervised learning algorithms such as SVMand it also performs better than local learning without incorporating class priors.

On the hierarchical classification of G protein-coupled receptors

MOTIVATION: G protein-coupled receptors (GPCRs) play an important role in many physiological systems by transducing an extracellular signal into an intracellular response. Over 50% of all marketed drugs are targeted towards a GPCR. There is considerable interest in developing an algorithm that could effectively predict the function of a GPCR from its primary sequence. Such an algorithm is useful not only in identifying novel GPCR sequences but in characterizing the interrelationships between known GPCRs. RESULTS: An alignment-free approach to GPCR classification has been developed using techniques drawn from data mining and proteochemometrics. A dataset of over 8000 sequences was constructed to train the algorithm. This represents one of the largest GPCR datasets currently available. A predictive algorithm was developed based upon the simplest reasonable numerical representation of the protein's physicochemical properties. A selective top-down approach was developed, which used a hierarchical classifier to assign sequences to subdivisions within the GPCR hierarchy. The predictive performance of the algorithm was assessed against several standard data mining classifiers and further validated against Support Vector Machine-based GPCR prediction servers. The selective top-down approach achieves significantly higher accuracy than standard data mining methods in almost all cases.

AtPIN: Arabidopsis thaliana Protein Interaction Network

Background: Protein-protein interactions (PPIs) constitute one of the most crucial conditions to sustain life in living organisms. To study PPI in Arabidopsis thaliana we have developed AtPIN, a database and web interface for searching and building interaction networks based on publicly available protein-protein interaction datasets. Description: All interactions were divided into experimentally demonstrated or predicted. The PPIs in the AtPIN database present a cellular compartment classification (C(3)) which divides the PPI into 4 classes according to its interaction evidence and subcellular localization. It has been shown in the literature that a pair of genuine interacting proteins are generally expected to have a common cellular role and proteins that have common interaction partners have a high chance of sharing a common function. In AtPIN, due to its integrative profile, the reliability index for a reported PPI can be postulated in terms of the proportion of interaction partners that two proteins have in common. For this, we implement the Functional Similarity Weight (FSW) calculation for all first level interactions present in AtPIN database. In order to identify target proteins of cytosolic glutamyl-tRNA synthetase (Cyt-gluRS) (AT5G26710) we combined two approaches, AtPIN search and yeast two-hybrid screening. Interestingly, the proteins glutamine synthetase (AT5G35630), a disease resistance protein (AT3G50950) and a zinc finger protein (AT5G24930), which has been predicted as target proteins for Cyt-gluRS by AtPIN, were also detected in the experimental screening. Conclusions: AtPIN is a friendly and easy-to-use tool that aggregates information on Arabidopsis thaliana PPIs, ontology, and sub-cellular localization, and might be a useful and reliable strategy to map protein-protein interactions in Arabidopsis. AtPIN can be accessed at http://bioinfo.esalq.usp.br/atpin.

Protein sequence threading, the alignment problem, and a two-step strategy

Conventionally, protein structure prediction via threading relies on some nonoptimal method to align a protein sequence to each member of a library of known structures. We show how a score function (force field) can be modified so as to allow the direct application of a dynamic programming algorithm to the problem. This involves an approximation whose damage can be minimized by an optimization process during score function parameter determination. The method is compared to sequence to structure alignments using a more conventional pair-wise score function and the frozen approximation. The new method produces results comparable to the frozen approximation, but is faster and has fewer adjustable parameters. It is also free of memory of the template's original amino acid sequence, and does not suffer from a problem of nonconvergence, which can be shown to occur with the frozen approximation. Alignments generated by the simplified score function can then be ranked using a second score function with the approximations removed. (C) 1999 John Wiley & Sons, Inc.

Cutaneous vasculitis in systemic lupus erythematosus: association with anti-ribosomal P protein antibody and Raynaud phenomenon

Ninety-one consecutive systemic lupus erythematosus (SLE) patients (American College of Rheumatology criteria) with a history of cutaneous vasculitis were compared to 163 SLE controls without this clinical manifestation from July to December 2007 in order to determine the possible clinical and serological association of this manifestation. Data were obtained in an ongoing electronic database protocol and autoantibodies to anti-double-stranded DNA, anti-Sm, anti-RNP, anti-Ro/SS-A, anti-La/SS-B, and anticardiolipin and ribosomal P protein antibody (anti-P) were detected by standard techniques. Exclusion criteria were the presence of anti-phospholipid syndrome or antibodies, Sjogren syndrome, and a history of thrombosis. The mean age (38.5 +/- 11.5 vs. 37.8 +/- 11.6 years, p = 0.635), disease duration (12.5 +/- 7.8 vs. 11.8 +/- 7.9 years, p = 0.501), and frequency of white race (71.4% vs. 70.5%, p = 0.872) and female sex (96.8% vs. 93.7%, p = 0.272) were comparable in both groups. The vasculitis group had a higher frequency of malar rash (97.9% vs. 87.4%, p = 0.004), photosensitivity (91.4% vs. 81.6%, p = 0.030), and Raynaud phenomenon (RP; 27.7% vs. 7.5%, p < 0.001), whereas all other clinical manifestation including renal and central nervous system involvements were similar to the control group. Laboratorial data revealed that only anti-P (35.1% vs. 12.1%, p < 0.001) was more frequent in patients with vasculitis. In a multivariate logistic regression model, cutaneous vasculitis was associated to the presence of RP (OR = 3.70; 95% confidence interval [CI] = 1.73-8.00) and anti-P (OR = 3.42; 95% CI = 1.76-6.66). In summary, SLE cutaneous vasculitis characterizes a subgroup of patients with more RP and anti-P antibodies but not accompanied by a higher frequency of renal and central nervous system involvements.

Updated Clinical Classification of Pulmonary Hypertension

The aim of a clinical classification of pulmonary hypertension (PH) is to group together different manifestations of disease sharing similarities in pathophysiologic mechanisms, clinical presentation, and therapeutic approaches. In 2003, during the 3rd World Symposium on Pulmonary Hypertension, the clinical classification of PH initially adopted in 1998 during the 2nd World Symposium was slightly modified. During the 4th World Symposium held in 2008, it was decided to maintain the general architecture and philosophy of the previous clinical classifications. The modifications adopted during this meeting principally concern Group 1, pulmonary arterial hypertension (PAH). This subgroup includes patients with PAH with a family history or patients with idiopathic PAH with germline mutations (e. g., bone morphogenetic protein receptor-2, activin receptor-like kinase type 1, and endoglin). In the new classification, schistosomiasis and chronic hemolytic anemia appear as separate entities in the subgroup of PAH associated with identified diseases. Finally, it was decided to place pulmonary venoocclusive disease and pulmonary capillary hemangiomatosis in a separate group, distinct from but very close to Group 1 (now called Group 1`). Thus, Group 1 of PAH is now more homogeneous. (J Am Coll Cardiol 2009;54:S43-54) (C) 2009 by the American College of Cardiology Foundation

The mouse secretome: functional classification of the proteins secreted into the extracellular environment

We have developed a computational strategy to identify the set of soluble proteins secreted into the extracellular environment of a cell. Within the protein sequences predominantly derived from the RIKEN representative transcript and protein set, we identified 2033 unique soluble proteins that are potentially secreted from the cell. These proteins contain a signal peptide required for entry into the secretory pathway and lack any transmembrane domains or intracellular localization signals. This class of proteins, which we have termed the mouse secretome, included >500 novel proteins and 92 proteins

Surfactant protein-D and exposure to bioaerosols in wastewater and garbage workers.

PURPOSE: Bioaerosols and their constituents, such as endotoxins, are capable of causing an inflammatory reaction at the level of the lung-blood barrier, which becomes more permeable. Thus, it was hypothesized that occupational exposure to bioaerosols can increase leakage of surfactant protein-D (SP-D), a lung-specific protein, into the bloodstream. METHODS: SP-D was determined by ELISA in 316 wastewater workers, 67 garbage collectors, and 395 control subjects. Exposure was assessed with four interview-based indicators and by preliminary endotoxin measurements using the Limulus amoebocyte lysate assay. Influence of exposure on serum SP-D was assessed by multiple linear regression considering smoking, glomerular function, lung diseases, obesity, and other confounders. RESULTS: Overall, mean exposure levels to endotoxins were below 100 EU/m(3). However, special tasks of wastewater workers caused higher endotoxin exposure. SP-D concentration was slightly increased in this occupational group and associated with the occurrence of splashes and contact to raw sewage. No effect was found in garbage collectors. Smoking increased serum SP-D. No clinically relevant correlation between spirometry results and SP-D concentrations appeared. CONCLUSIONS: These results support the hypothesis that inhalation of bioaerosols, even at low concentrations, has a subclinical effect on the lung-blood barrier, the permeability of which increases without associated spirometric changes.

Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes.

The development of targeted treatment strategies adapted to individual patients requires identification of the different tumor classes according to their biology and prognosis. We focus here on the molecular aspects underlying these differences, in terms of sets of genes that control pathogenesis of the different subtypes of astrocytic glioma. By performing cDNA-array analysis of 53 patient biopsies, comprising low-grade astrocytoma, secondary glioblastoma (respective recurrent high-grade tumors), and newly diagnosed primary glioblastoma, we demonstrate that human gliomas can be differentiated according to their gene expression. We found that low-grade astrocytoma have the most specific and similar expression profiles, whereas primary glioblastoma exhibit much larger variation between tumors. Secondary glioblastoma display features of both other groups. We identified several sets of genes with relatively highly correlated expression within groups that: (a). can be associated with specific biological functions; and (b). effectively differentiate tumor class. One prominent gene cluster discriminating primary versus nonprimary glioblastoma comprises mostly genes involved in angiogenesis, including VEGF fms-related tyrosine kinase 1 but also IGFBP2, that has not yet been directly linked to angiogenesis. In situ hybridization demonstrating coexpression of IGFBP2 and VEGF in pseudopalisading cells surrounding tumor necrosis provided further evidence for a possible involvement of IGFBP2 in angiogenesis. The separating groups of genes were found by the unsupervised coupled two-way clustering method, and their classification power was validated by a supervised construction of a nearly perfect glioma classifier.

Historical review: Negative efficacy and the constitutive activity of G-protein-coupled receptors.

The idea that a receptor can produce signalling without agonist intervention and that several antagonists can be 'active' in repressing such spontaneous activity is contained in the concept of ligand-induced conformational changes. Yet, this idea was neglected by pharmacologists for many years. In this article, we review the events that brought inverse agonism and constitutive activity to general attention and made this phenomenon a topic of current research. We also suggest a classification of antagonists based on the cooperativity that links their primary site of interaction with other functional domains of the receptor.

SNARE protein expression in synaptic terminals and astrocytes in the adult hippocampus: a comparative analysis.

Several evidences suggest that astrocytes release small transmitter molecules, peptides, and protein factors via regulated exocytosis, implying that they function as specialized neurosecretory cells. However, very little is known about the molecular and functional properties of regulated secretion in astrocytes in the adult brain. Establishing these properties is central to the understanding of the communication mode(s) of these cells and their role(s) in the control of synaptic functions and of cerebral blood flow. In this study, we have set-up a high-resolution confocal microscopy approach to distinguish protein expression in astrocytic structures and neighboring synaptic terminals in adult brain tissue. This approach was applied to investigate the expression pattern of core SNARE proteins for vesicle fusion in the dentate gyrus and CA1 regions of the mouse hippocampus. Our comparative analysis shows that astrocytes abundantly express, in their cell body and main processes, all three protein partners necessary to form an operational SNARE complex but not in the same isoforms expressed in neighbouring synaptic terminals. Thus, SNAP25 and VAMP2 are absent from astrocytic processes and typically concentrated in terminals, while SNAP23 and VAMP3 have the opposite expression pattern. Syntaxin 1 is present in both synaptic terminals and astrocytes. These data support the view that astrocytes in the adult hippocampus can communicate via regulated exocytosis and also indicates that astrocytic exocytosis may differ in its properties from action potential-dependent exocytosis at neuronal synapses, as it relies on a distinctive set of SNARE proteins.

Seroreactivity to new Mycobacterium leprae protein antigens in different leprosy-endemic regions in Brazil

New Mycobacterium leprae protein antigens can contribute to improved serologic tests for leprosy diagnosis/classification and multidrug therapy (MDT) monitoring. This study describes seroreactivity to M. leprae proteins among participants from three highly endemic leprosy areas in Brazil: central-western Goiânia/Goiás (GO) (n = 225), Rondonópolis/Mato Grosso (MT) (n = 764) and northern Prata Village/Pará (PA) (n = 93). ELISA was performed to detect IgG to proteins (92f, 46f, leprosy IDRI diagnostic-1, ML0405, ML1213) and IgM to phenolic glycolipid-I (PGL-I). Multibacillary (MB) leprosy had positive rates for PGL-I that were similar to those for proteins; however, some anti-PGL-I-negative subjects were positive for proteins, suggesting that adding protein antigen to PGL-I can enhance the sensitivity of MB leprosy detection. In MT, different degrees of seroreactivity were observed and ranked for MB, former patients after MDT, paucibacillary (PB) leprosy, household contact (HHC) and endemic control (EC) groups. The seroreactivity of PB patients was low in GO and MT. HHCs from different endemic sites had similar IgG antibody responses to proteins. 46f and 92f were not recognised by most tuberculosis patients, ECs or HHCs within GO, an area with high BCG vaccination coverage. Low positivity in EC and HHC was observed in PA and MT. Our results provide evidence for the development of an improved serologic test that could be widely applicable for MB leprosy testing in Brazil.

Microtubule-associated protein-2 immunoreactivity: a useful tool in the differential diagnosis of low-grade neuroepithelial tumors.

Complex and variable morphological phenotypes pose a major challenge to the histopathological classification of neuroepithelial tumors. This applies in particular for low-grade gliomas and glio-neuronal tumors. Recently, we and others have identified microtubule-associated protein-2 (MAP2) as an immunohistochemical marker expressed in the majority of glial tumors. Characteristic cell morphologies can be recognized by MAP2 immunoreactivity in different glioma entities, i.e., process sparse oligodendroglial versus densely ramified astrocytic elements. Here, we describe MAP2-immunoreactivity patterns in a large series of various neuroepithelial tumors and related neoplasms (n = 960). Immunohistochemical analysis led to the following conclusions: (1) specific pattern of MAP2-positive tumor cells can be identified in 95% of glial neoplasms; (2) ependymal tumors do not express MAP2 in their rosette-forming cell component; (3) tumors of the pineal gland as well as malignant embryonic tumors are also characterized by abundant MAP2 immunoreactivity; (4) virtually no MAP2 expression can be observed in the neoplastic glial component of glio-neuronal tumors, i.e. gangliogliomas; (5) malignant glial tumor variants (WHO grade III or IV) exhibit different and less specific MAP2 staining patterns compared to their benign counterparts (WHO grade I or II); (6) with the exception of melanomas and small cell lung cancers, MAP2 expression is very rare in metastatic and non-neuroepithelial tumors; (7) glial MAP2 expression was not detected in 56 non-neoplastic lesions. These data point towards MAP2 as valuable diagnostic tool for pattern recognition and differential diagnosis of low-grade neuroepithelial tumors.

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network.

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.