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Evaluating the utility of a high throughput thiol-containing fluorescent probe to screen for reactivity: A case study with the Tox21 library
Citation:
Patlewicz, G., K. Friedman, K. Houck, L. Zhang, R. Huang, M. Xia, J. Brown, AND S. Simmons. Evaluating the utility of a high throughput thiol-containing fluorescent probe to screen for reactivity: A case study with the Tox21 library. Computational Toxicology. Elsevier B.V., Amsterdam, Netherlands, 26:100271, (2023). https://doi.org/10.1016/j.comtox.2023.100271
Impact/Purpose:
This manuscript summarises the screening of the Tox21 using a HTS fluorescence assay which measures thiol reactivity. The manuscript discusses the development of a ML model to predict thiol reactivity using ToxPrints as inputs as well as the derivation of enriched ToxPrints. The combination of these enriched ToxPrints in conjunction with the model derived were then used to profile the TSCA non CBI active inventory as a use case to demonstrate practical utility.
Description:
High-throughput screening (HTS) assays for bioactivity in the Tox21 program aim to evaluate an array of different biological targets and pathways, but a significant barrier to interpretation of these data is the lack of high-throughput screening (HTS) assays intended to identify non-specific reactive chemicals. This is an important aspect for prioritising chemicals to test in specific assays, identifying promiscuous chemicals based on their reactivity, as well as addressing hazards such as skin sensitisation which are not necessarily initiated by a receptor-mediated effect but act through a non-specific mechanism. Herein, a fluorescence-based HTS assay that allows the identification of thiol-reactive compounds was used to screen 7,872 unique chemicals in the Tox21 10 K chemical library. Active chemicals were compared with profiling outcomes using structural alerts encoding electrophilic information. Random Forest classification models based on chemical fingerprints were developed to predict assay outcomes and evaluated through 10-fold stratified cross validation (CV). The mean CV Balanced Accuracy of the validation set was 0.648. The model developed shows promise as a tool to screen untested chemicals for their potential electrophilic reactivity based solely on chemical structural features.
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DOI: Evaluating the utility of a high throughput thiol-containing fluorescent probe to screen for reactivity: A case study with the Tox21 library