Data quality in the human and environmental health sciences: Using statistical confidence scoring to improve QSAR/QSPR modeling

A greater number of toxicity data are becoming publicly available allowing for in silico modeling. However, questions often arise as how to incorporate data quality and how to deal with contradicting data if more than a single datum point is available for the same compound. In this study, two well-known and studied QSAR/QSPR models for skin permeability and aquatic toxicology have been investigated in the context of statistical data quality. In particular, the potential benefits of the incorporation of the statistical Confidence Scoring (CS) approach within modelling and validation. As a result, robust QSAR/QSPR models for the skin permeability coefficient and the toxicity of nonpolar narcotics to Aliivibrio fischeri assay were created. CSweighted linear regression for training and CS-weighted root mean square error (RMSE) for validation were statistically superior compared to standard linear regression and standard RMSE. Strategies are proposed as to how to interpret data with high and low CS, as well as how to deal with large datasets containing multiple entries

The read-across hypothesis and environmental risk assessment of pharmaceuticals

This article is made available through the Brunel Open Access Publishing Fund. Copyright © 2013 American Chemical Society.Pharmaceuticals in the environment have received increased attention over the past decade, as they are ubiquitous in rivers and waterways. Concentrations are in sub-ng to low μg/L, well below acute toxic levels, but there are uncertainties regarding the effects of chronic exposures and there is a need to prioritise which pharmaceuticals may be of concern. The read-across hypothesis stipulates that a drug will have an effect in non-target organisms only if the molecular targets such as receptors and enzymes have been conserved, resulting in a (specific) pharmacological effect only if plasma concentrations are similar to human therapeutic concentrations. If this holds true for different classes of pharmaceuticals, it should be possible to predict the potential environmental impact from information obtained during the drug development process. This paper critically reviews the evidence for read-across, and finds that few studies include plasma concentrations and mode of action based effects. Thus, despite a large number of apparently relevant papers and a general acceptance of the hypothesis, there is an absence of documented evidence. There is a need for large-scale studies to generate robust data for testing the read-across hypothesis and developing predictive models, the only feasible approach to protecting the environment.BBSRC Industrial Partnership Award BB/ I00646X/1 and BBSRC Industrial CASE Partnership Studentship BB/I53257X/1 with AstraZeneca Safety Health and Environment Research Programme

Compounds from Silicones Alter Enzyme Activity in Curing Barnacle Glue and Model Enzymes

Background: Attachment strength of fouling organisms on silicone coatings is low. We hypothesized that low attachment strength on silicones is, in part, due to the interaction of surface available components with natural glues. Components could alter curing of glues through bulk changes or specifically through altered enzyme activity. Methodology/Principal Findings: GC-MS analysis of silicone coatings showed surface-available siloxanes when the coatings were gently rubbed with a cotton swab for 15 seconds or given a 30 second rinse with methanol. Mixtures of compounds were found on 2 commercial and 8 model silicone coatings. The hypothesis that silicone components alter glue curing enzymes was tested with curing barnacle glue and with commercial enzymes. In our model, barnacle glue curing involves trypsin-like serine protease(s), which activate enzymes and structural proteins, and a transglutaminase which cross-links glue proteins. Transglutaminase activity was significantly altered upon exposure of curing glue from individual barnacles to silicone eluates. Activity of purified trypsin and, to a greater extent, transglutaminase was significantly altered by relevant concentrations of silicone polymer constituents. Conclusions/Significance: Surface-associated silicone compounds can disrupt glue curing and alter enzyme properties

Predictive QSAR models for estimating biodegradation of aromatic compounds

The development of valid structure biodegradation relationships (SBRs) is restricted by the lack of reproducible published data and by the considered endpoint of degradation data. A classification scheme is required for comparative evaluation of degradation data obtained by different test methods. SBRs based on substructure indicators are available for application to most compounds, but the reliability is still uncertain. SBRs based on physico-chemical parameters are only available for a few classes of compounds based on specific test methods. A combination of several SBRs covering the various transformation pathways provides a promising tool for predicting biodegradability. Two models describing biodegradation are introduced

Testbattery for assessment of aquatic toxicity: Dedicated to Prof. Werner Klein on the occasion of his 60th birthday

A testbattery of biochemical and (sub)cellular assays was used to obtain a ranking and classification of aquatic contaminants. The assessment of model compounds with different modes of action by a series of specific (sub)organismic tests was based on the principle of simulating the possible interactions between the contaminants and respective targets in the organisms. The following endpoints were included in the in-vitro testbattery: cytotoxicity in the neutralred and kenacidblue assay with BF-2 fish fibroblasts, decoupling of isolated mitochondria, inhibition of acetylcholinesterase and reaction with glutathion. The response patterns from the individual tests were integrated to obtain the aquatic toxicity profiles. The results show that the in-vitro tests are less sensitive as compared to traditional organismic tests and the objective to serve as monitors of low-level contaminants is not yet achieved with the in-vitro tests used in this study. On the other hand, the testbattery reveal ed high specificity to identify mode of action related response profiles and to provide an unambiguous classification of toxicants whose impacts may be due to particular interactions