81 research outputs found
Hg-supported phospholipid monolayer as rapid screening device for low molecular weight narcotic compounds in water
This study positions the fabricated Pt/Hg-supported phospholipid sensor element in the context of more conventional biomembrane-based screening platforms. The technology has been used together with immobilised artificial membrane (IAM) chromatography and COSMOmic simulation methods to screen the interaction of a series of low molecular weight narcotic organic compounds in water with phosphatidylcholine (PC) membranes. For these chemicals it is shown that toxicity to aquatic species is related to compound hydrophobicity which is associated with compound accumulation in the phospholipid membrane as modelled by IAM chromatography measurements and COSMOmic simulations. In contrast, the Hg-supported dioleoyl phosphatidylcholine (DOPC) sensor element records membrane damage/modification which is indirectly related to general toxicity and directly related to compound structure. Electrochemical limit of detection (LoD) values depend on molecular structure and range from 20âŻÎŒmolLâ1 for substituted phenols to 23âŻmmolLâ1 for aliphatics. Rapid cyclic voltammetry (RCV) âfingerprintsâ showed that the major structural classes of compounds: alkyl/chlorobenzenes, substituted phenols, quaternary ammonium compounds and neutral amines interacted distinctively with the DOPC on Hg and that these observations correlated with and supported those predicted by the COSMOmic simulations of the compound/DMPC association. In addition, the compatibility of the electrochemical and COSMOmic methods validates the electrochemical device as a meaningful high throughput technology to screen compounds in water and report on the mechanistic details of their interaction with phospholipid layers
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A History of the Molecular Initiating Event
The adverse outcome pathway (AOP) framework provides an alternative to traditional experiments for the risk assessment of chemicals. AOPs consist of a number of key events (KEs) linked by key event relationships across a range of biological organization backed by scientific evidence. The first KE in the pathway is the molecular initiating event (MIE)-the initial chemical trigger that starts an AOP. Over the past 3 years the AOP conceptual framework has gained a large amount of momentum in toxicology as an alternative to animal methods, and so the MIE has come into the spotlight. What is an MIE? How can MIEs be measured or predicted? What research is currently contributing to our understanding of MIEs? In this Perspective we outline answers to these key questions.The authors acknowledge financial support from Unilever
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Using Molecular Initiating Events To Generate 2D Structure-Activity Relationships for Toxicity Screening
Molecular initiating events (MIEs) can be boiled down to chemical interactions. Chemicals that interact must have intrinsic properties that allow them to exhibit this behavior, be these properties stereochemical, electronic, or otherwise. In an attempt to discover some of these chemical characteristics, we have constructed structural alert-style structure-activity relationships (SARs) to computationally predict MIEs. This work utilizes chemical informatics approaches, searching the ChEMBL database for molecules that bind to a number of pharmacologically important human toxicology targets, including G-protein coupled receptors, enzymes, ion channels, nuclear receptors, and transporters. By screening these compounds to find common 2D fragments and combining this approach with a good understanding of the literature, bespoke 2D structural alerts have been written. These SARs form the beginning of a tool for screening novel chemicals to establish the kind of interactions that they may be able to make in humans. These SARs have been run through an internal validation to test their quality, and the results of this are also discussed. MIEs have proven to be difficult to find and characterize, but we believe we have taken a key first step with this work.Unileve
Using Molecular Initiating Events To Generate 2D Structure-Activity Relationships for Toxicity Screening
Molecular initiating events (MIEs) can be boiled down to chemical interactions. Chemicals that interact must have intrinsic properties that allow them to exhibit this behavior, be these properties stereochemical, electronic, or otherwise. In an attempt to discover some of these chemical characteristics, we have constructed structural alert-style structure-activity relationships (SARs) to computationally predict MIEs. This work utilizes chemical informatics approaches, searching the ChEMBL database for molecules that bind to a number of pharmacologically important human toxicology targets, including G-protein coupled receptors, enzymes, ion channels, nuclear receptors, and transporters. By screening these compounds to find common 2D fragments and combining this approach with a good understanding of the literature, bespoke 2D structural alerts have been written. These SARs form the beginning of a tool for screening novel chemicals to establish the kind of interactions that they may be able to make in humans. These SARs have been run through an internal validation to test their quality, and the results of this are also discussed. MIEs have proven to be difficult to find and characterize, but we believe we have taken a key first step with this work.Unileve
Construction of an In Silico Structural Profiling Tool Facilitating Mechanistically Grounded Classification of Aquatic Toxicants.
The performance of chemical safety assessment within the domain of environmental toxicology is often impeded by a shortfall of appropriate experimental data describing potential hazards across the many compounds in regular industrial use. In silico schemes for assigning aquatic-relevant modes or mechanisms of toxic action to substances, based solely on consideration of chemical structure, have seen widespread employmentâincluding those of Verhaar, Russom, and later Bauer (MechoA). Recently, development of a further system was reported by Sapounidou, which, in common with MechoA, seeks to ground its classifications in understanding and appreciation of molecular initiating events. Until now, this Sapounidou scheme has not seen implementation as a tool for practical screening use. Accordingly, the primary purpose of this study was to create such a resourceâin the form of a computational workflow. This exercise was facilitated through the formulation of 183 structural alerts/rules describing molecular features associated with narcosis, chemical reactivity, and specific mechanisms of action. Output was subsequently compared relative to that of the three aforementioned alternative systems to identify strengths and shortcomings as regards coverage of chemical space
EEG ERP preregistration template
This preregistration template guides researchers who wish to preregister their EEG projects, more specifically studies investigating event-related potentials (ERPs) in the sensor space
A scheme to evaluate structural alerts to predict toxicity â Assessing confidence by characterising uncertainties
Structure-activity relationships (SARs) in toxicology have enabled the formation of structural rules which, when coded as structural alerts, are an essential tool in in silico toxicology. Whilst other in silico methods have approaches for their evaluation, there is no formal process to assess the confidence that may be associated with a structural alert. This investigation proposes twelve criteria to assess the uncertainty associated with structural alerts, allowing for an assessment of confidence. The criteria are based around the stated purpose, description of the chemistry, toxicology and mechanism, performance and coverage, as well as corroborating and supporting evidence of the alert. Alerts can be given a confidence assessment and score, enabling the identification of areas where more information may be beneficial. The scheme to evaluate structural alerts was placed in the context of various use cases for industrial and regulatory applications. The analysis of alerts, and consideration of the evaluation scheme, identifies the different characteristics an alert may have, such as being highly specific or generic. These characteristics may determine when an alert can be used for specific uses such as identification of analogues for read-across or hazard identification
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Data-driven learning of narcosis mode of action identifies a CNS transcriptional signature shared between whole organism Caenorhabditis elegans and a fish gill cell line
Supplementary data related to this article: Supplementary material, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc1.docx (Word document35, 5KB)); Supplementary Data 1. These are the chemicals along with their properties and the calculated doses given for the C. elegans (Caenorhabditis elegans), available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc2.xls (spreadsheet, 68KB); Supplementary Data 2. These are the chemicals and the doses given for the trout gill cell line (Rtgill-WT1). The codes here relate to the same codes on the microarray data, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc3.xlsx (spreadsheet; 11KB); Supplementary Data 3. These are the probes found to be significantly different between exposed and unexposed C. elegans for each of the narcotic chemicals tested, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc4.xlsx (spreadsheet, 363KB); Supplementary Data 4. The file provide the metabolite composition of the three clusters identified by running a metabolic-based predictive model, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc5.xlsx (spreadsheet, 10KB).Copyright © 2022 The Authors. With the large numbers of man-made chemicals produced and released in the environment, there is a need to provide assessments on their potential effects on environmental safety and human health. Current regulatory frameworks rely on a mix of both hazard and risk-based approaches to make safety decisions, but the large number of chemicals in commerce combined with an increased need to conduct assessments in the absence of animal testing makes this increasingly challenging. This challenge is catalysing the use of more mechanistic knowledge in safety assessment from both in silico and in vitro approaches in the hope that this will increase confidence in being able to identify modes of action (MoA) for the chemicals in question. Here we approach this challenge by testing whether a functional genomics approach in C. elegans and in a fish cell line can identify molecular mechanisms underlying the effects of narcotics, and the effects of more specific acting toxicants. We show that narcosis affects the expression of neuronal genes associated with CNS function in C. elegans and in a fish cell line. Overall, we believe that our study provides an important step in developing mechanistically relevant biomarkers which can be used to screen for hazards, and which prevent the need for repeated animal or cross-species comparisons for each new chemical.Unilever Ltd
Group membership and racial bias modulate the temporal estimation of in-group/out-group body movements
Social group categorization has been mainly studied in relation to ownership manipulations involving highly-salient multisensory cues. Here, we propose a novel paradigm that can implicitly activate the embodiment process in the presence of group affiliation information, whilst participants complete a task irrelevant to social categorization. Ethnically White participants watched videos of White- and Black-skinned models writing a proverb. The writing was interrupted 7, 4 or 1 s before completion. Participants were tasked with estimating the residual duration following interruption. A video showing only hand kinematic traces acted as a control condition. Residual duration estimates for out-group and control videos were significantly lower than those for in-group videos only for the longest duration. Moreover, stronger implicit racial bias was negatively correlated to estimates of residual duration for out-group videos. The underestimation bias for the out-group condition might be mediated by implicit embodiment, affective and attentional processes, and finalized to a rapid out-group categorization
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