GPCR-OKB: the G protein coupled receptor oligomer knowledge base

Rapid expansion of available data about G Protein Coupled Receptor (GPCR) dimers/oligomers over the past few years requires an effective system to organize this information electronically. Based on an ontology derived from a community dialog involving colleagues using experimental and computational methodologies, we developed the GPCR-Oligomerization Knowledge Base (GPCR-OKB). GPCR-OKB is a system that supports browsing and searching for GPCR oligomer data. Such data were manually derived from the literature. While focused on GPCR oligomers, GPCR-OKB is seamlessly connected to GPCRDB, facilitating the correlation of information about GPCR protomers and oligomers

Coordinating the impact of structural genomics on the human α-helical transmembrane proteome

Given the recent successes in determining membrane-protein structures, we explore the tractability of determining representatives for the entire human membrane proteome. This proteome contains 2,925 unique integral α-helical transmembrane-domain sequences that cluster into 1,201 families sharing more than 25% sequence identity. Structures of 100 optimally selected targets would increase the fraction of modelable human α-helical transmembrane domains from 26% to 58%, providing structure and function information not otherwise available

In Silico Veritas: The Pitfalls and Challenges of Predicting

Recently the first community-wide assessments of the prediction of the structures of complexes between proteins and small molecule ligands have been reported in the so-called GPCR Dock 2008 and 2010 assessments. In the current review we discuss the different steps along the protein-ligand modeling workflow by critically analyzing the modeling strategies we used to predict the structures of protein-ligand complexes we submitted to the recent GPCR Dock 2010 challenge. These representative test cases, focusing on the pharmaceutically relevant G Protein-Coupled Receptors, are used to demonstrate the strengths and challenges of the different modeling methods. Our analysis indicates that the proper performance of the sequence alignment, introduction of structural adjustments guided by experimental data, and the usage of experimental data to identify protein-ligand interactions are critical steps in the protein-ligand modeling protocol. © 2011 by the authors; licensee MDPI, Basel, Switzerland

Active Case Finding for Communicable Diseases in Prison Settings: Increasing Testing Coverage and Uptake Among the Prison Population in the European Union/European Economic Area

Prison populations are disproportionally affected by communicable diseases when compared with the general community because of a complex mix of socioeconomic determinants and environmental factors. Tailored and adequate health care provision in prisons has the potential to reach vulnerable and underserved groups and address their complex needs. We investigated the available evidence on modalities and effectiveness of active case-finding interventions in prisons by searching PubMed, Embase, and the Cochrane Library for records on prison and active case finding with no language limit. Conference abstracts and unpublished research reports also were retrieved. We analyzed the findings by testing modality, outcomes, and study quality. The included 90 records-63 peer-reviewed, 26 from gray literature, and 1 systematic review-reported variously on viral hepatitis, human immunodeficiency virus, sexually transmitted infections, and tuberculosis. No records were retrieved for other communicable diseases. Provider-initiated opt-in testing was the most frequently investigated modality. Testing at entry and provider-initiated testing were reported to result in comparatively higher uptake ranges. However, no comparative studies were identified that reported statistically significant differences between testing modalities. Positivity rates among tested inmates ranged broadly but were generally high for all diseases. The evidence on active case finding in correctional facilities is limited, heterogeneous, and of low quality, making it challenging to draw conclusions on the effect of different testing modalities. Scale-up of provider-initiated testing in European correctional facilities could substantially reduce the undiagnosed fraction and, hence, prevent additional disease transmission in both prison settings and the community at large

GPCRDB: information system for G protein-coupled receptors

The GPCRDB is a Molecular Class-Specific Information System (MCSIS) that collects, combines, validates and disseminates large amounts of heterogeneous data on G protein-coupled receptors (GPCRs). The GPCRDB contains experimental data on sequences, ligand-binding constants, mutations and oligomers, as well as many different types of computationally derived data such as multiple sequence alignments and homology models. The GPCRDB provides access to the data via a number of different access methods. It offers visualization and analysis tools, and a number of query systems. The data is updated automatically on a monthly basis. The GPCRDB can be found online at http://www.gpcr.org/7tm/

GPCRDB: information system for G protein-coupled receptors

The GPCRDB is a Molecular Class-Specific Information System (MCSIS) that collects, combines, validates and disseminates large amounts of heterogeneous data on G protein-coupled receptors (GPCRs). The GPCRDB contains experimental data on sequences, ligand-binding constants, mutations and oligomers, as well as many different types of computationally derived data such as multiple sequence alignments and homology models. The GPCRDB provides access to the data via a number of different access methods. It offers visualization and analysis tools, and a number of query systems. The data is updated automatically on a monthly basis. The GPCRDB can be found online at http://www.gpcr.org/7tm/

Circulating endothelial cells are an early predictor in renal cell carcinoma for tumor response to sunitinib

<p>Abstract</p> <p>Background</p> <p>Tyrosine kinase inhibitors (TKI) have enriched the therapeutic options in patients with renal cell carcinoma (RCC), which frequently induce morphological changes in tumors. However, only little is known about the biological activity of TKI. Circulating endothelial cells (CEC) have been associated with endothelial damage and, hence, may serve as a putative marker for the biological activity of TKI. The main objective of our study was to evaluate the predictive value of CEC, monocytes, and soluble vascular endothelial growth factor receptor (sVEGFR)-2 in RCC patients receiving sunitinib treatment.</p> <p>Methods</p> <p>Analyses of CEC, monocytes, and sVEGFR-2 were accomplished for twenty-six consecutive patients with metastatic RCC who received treatment with sunitinib (50 mg, 4 wks on 2 wks off schedule) at our institution in 2005 and 2006.</p> <p>Results</p> <p>In RCC patients CEC are elevated to 49 ± 44/ml (control 8 ± 8/ml; P = 0.0001). Treatment with sunitinib is associated with an increase in CEC within 28 days of treatment in patients with a Progression free survival (PFS) above the median to 111 ± 61 (P = 0.0109), whereas changes in patients with a PFS below the median remain insignificant 69 ± 61/ml (P = 0.1848). Monocytes and sVEGFR2 are frequently altered upon sunitinib treatment, but fail to correlate with clinical response, defined by PFS above or below the median.</p> <p>Conclusions</p> <p>Sunitinib treatment is associated with an early increase of CEC in responding patients, suggesting superior endothelial cell damage in these patients as a putative predictive biomarker.</p

Homology modelling and spectroscopy, a never-ending love story

Homology modelling is normally the technique of choice when experimental structure data are not available but three-dimensional coordinates are needed, for example, to aid with detailed interpretation of results of spectroscopic studies. Herein, the state of the art of homology modelling will be described in the light of a series of recent developments, and an overview will be given of the problems and opportunities encountered in this field. The major topic, the accuracy and precision of homology models, will be discussed extensively due to its influence on the reliability of conclusions drawn from the combination of homology models and spectroscopic data. Three real-world examples will illustrate how both homology modelling and spectroscopy can be beneficial for (bio)medical research