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Over the past decades, pharmaceutical companies have conducted a large number of high-quality in vivo repeat-dose toxicity (RDT) studies for regulatory purposes. As part of the eTOX project, a high number of these studies have been compiled and integrated into a database. This valuable resource can be queried directly, but it can be further exploited to build predictive models. As the studies were originally conducted to investigate the properties of individual compounds, the experimental conditions across the studies are highly heterogeneous. Consequently, the original data required normalization/standardization, filtering, categorization and integration to make possible any data analysis (such as building predictive models). Additionally, the primary objectives of the RDT studies were to identify toxicological findings, most of which do not directly translate to in vivo endpoints. This article describes a method to extract datasets containing comparable toxicological properties for a series of compounds amenable for building predictive models. The proposed strategy starts with the normalization of the terms used within the original reports. Then, comparable datasets are extracted from the database by applying filters based on the experimental conditions. Finally, carefully selected profiles of toxicological findings are mapped to endpoints of interest, generating QSAR-like tables. In this work, we describe in detail the strategy and tools used for carrying out these transformations and illustrate its application in a data sample extracted from the eTOX database. The suitability of the resulting tables for developing hazard-predicting models was investigated by building proof-of-concept models for in vivo liver endpoints. [ABSTRACT FROM AUTHOR]

We describe an application (Collector) for obtaining series of compounds annotated with bioactivity data, ready to be used for the development of quantitative structure-activity relationships (QSAR) models. The tool extracts data from the 'Open Pharmacological Space' (OPS) developed by the Open PHACTS project, using as input a valid name of the biological target. Collector uses the OPS ontologies for expanding the query using all known target synonyms and extracts compounds with bioactivity data against the target from multiple sources. The extracted data can be filtered to retain only drug-like compounds and the bioactivities can be automatically summarised to assign a single value per compound, yielding data ready to be used for QSAR modeling. The data obtained is locally stored facilitating the traceability and auditability of the process. Collector was used successfully for the development of models for toxicity endpoints within the eTOX project. [ABSTRACT FROM AUTHOR]

Aims Tungstate reduces blood pressure in experimental animal models of both hypertension and metabolic syndrome, although the underlying mechanisms are not fully understood. Given that the large-conductance voltage- and Ca2+-dependent K+ (BK) channel is a key element in the control of arterial tone, our aim was to evaluate whether BK channel modulation by tungstate can contribute to its antihypertensive effect. Methods and results Patch-clamp studies of heterologously expressed human BK channels (α + β1–4 subunits) revealed that cytosolic tungstate (1 mM) induced a significant left shift (∼20 mV) in the voltage-dependent activation curve only in BK channels containing αβ1 or αβ4 subunits, but reduced the amplitude of K+ currents through all BK channels tested. The β1-dependent activation of BK channels by tungstate was enhanced at cytosolic Ca2+ levels reached during myocyte contraction, and prevented either by removal of cytosolic Mg2+ or by mutations rendering the channel insensitive to Mg2+. A lower concentration of tungstate (0.1 mM) induced voltage-dependent activation of the vascular BKαβ1 channel without reducing current amplitude, and consistently exerted a vasodilatory action on wild-type but not on β1-knockout mouse arteries pre-contracted with endothelin-1. Conclusion Tungstate activates BK channels in a β subunit- and Mg2+-dependent manner and induces vasodilatation only in mouse arteries that express the BK β1 subunit. [ABSTRACT FROM AUTHOR]

Aims The TRPC4 non-selective cation channel is widely expressed in the endothelium, where it generates Ca2+ signals that participate in the endothelium-mediated vasodilatory response. This study sought to identify single-nucleotide polymorphisms (SNPs) in the TRPC4 gene that are associated with myocardial infarction (MI). Methods and results Our candidate-gene association studies identified a missense SNP (TRPC4-I957V) associated with a reduced risk of MI in diabetic patients [odds ratio (OR) = 0.61; confidence interval (CI), 0.40–0.95, P= 0.02]. TRPC4 was also associated with MI in the Wellcome Trust Case–Control Consortium's genome-wide data: an intronic SNP (rs7319926) within the same linkage disequilibrium block as TRPC4-I957V showed an OR of 0.86 (CI, 0.81–0.94; P =10−4). Functional studies of the missense SNP were carried out in HEK293 and CHO cells expressing wild-type or mutant channels. Patch-clamp studies and measurement of intracellular [Ca2+] in response to muscarinic agonists and direct G-protein activation showed increased channel activity in TRPC4-I957V-transfected cells compared with TRPC4-WT. Site-directed mutagenesis and molecular modelling of TRPC4-I957V suggested that the gain of function was due to the presence of a less bulky Val-957. This permits a firmer interaction between the TRPC4 and the catalytic site of the tyrosine kinase that phosphorylates TRPC4 at Tyr-959 and facilitates channel insertion into the plasma membrane. Conclusion We provide evidence for the association of a TRPC4 SNP with MI in population-based genetic studies. The higher Ca2+ signals generated by TRPC4-I957V may ultimately facilitate the generation of endothelium- and nitric oxide-dependent vasorelaxation, thereby explaining its protective effect at the vasculature. [ABSTRACT FROM PUBLISHER]