You are here:
Combining in silico structure-based methods and enrichment analysis to increase confidence in HTS results: Application to Tox21 TRHR assay
Citation:
Shobair, Mahmoud A., Chris Grulke, D. Chang, R. Lougee, K. Paul-Friedman, AND A. Richard. Combining in silico structure-based methods and enrichment analysis to increase confidence in HTS results: Application to Tox21 TRHR assay. Society of Toxicology 2021 Virtual Annual Meeting, RTP, NC, March 12 - 26, 2021. https://doi.org/10.23645/epacomptox.14474052
Impact/Purpose:
Poster presented to the Society of Toxicology 2021 Virtual Annual Meeting March 2021. Application of high-throughput screening (HTS) to toxicology faces the challenge of relating HTS data to molecular initiating events (MIEs) and adverse outcome pathways (AOP) even when the relationship between the HTS output and MIE is indirect. Thyrotropin-Release Hormone Receptor (TRHR) activation is a MIE in the AOP network for thyroid hormone (TH) disruption, but the ability of environmental chemicals to perturb TRHR signaling is unknown. A Tox21 HTS biochemical assay is available, but no orthogonal or confirmatory Tox21 or ToxCast assays can be used to differentiate TRHR true positive responses. To test the hypothesis that environmentally-relevant chemicals can directly interact with TRHR, we developed an in silico cheminformatic workflow to identify chemicals predicted to interfere with TRH binding.
Description:
Despite progress in applying high-throughput screening (HTS) technologies to toxicology, exemplified by the Tox21 and ToxCast programs, the challenge of relating biochemical outputs to molecular initiating events (MIEs) and adverse outcome pathways (AOPs) remains challenging, particularly when the relationship between the biochemical output and MIE is indirect. To increase confidence in HTS results for hazard evaluation, a structure-based data enrichment and knowledge contextualization workflow was developed to identify likely false positives and discriminate true receptor binders. The tiered approach was applied to evaluate in vitro data for the Thyrotropin-Release Hormone Receptor (TRHR), an MIE in the thyroid hormone AOP. The tiered approach: 1) identifies structure-activity patterns using chemotype-enrichment analysis; 2) filters noise from cytotoxicity or assay interference; 3) uses 3D pharmacophore modeling to prioritize chemicals capable of binding to TRHR as well as modulators likely to interfere with binding. Preliminary results suggest that less than 11% of actives in the Tox21 assay actives exhibit binding features of known TRHR receptor binders. These results presume conservation of the TRHR ligand binding site and structural similarity to known TRHR modulators, benzodiazepines and neuropeptides. The presented tiered workflow is grounded by physical determinants directly related to relevant signals in experimental results, thereby increasing the value of in vitro data for chemical prioritization. The workflow can be generalized to other in vitro biochemical assays and suggest that combining structure-based methods and data enrichment analysis can increase confidence in HTS results and define a scope of prediction for risk assessment. This abstract does not reflect EPA policy.
URLs/Downloads:
DOI: Combining in silico structure-based methods and enrichment analysis to increase confidence in HTS results: Application to Tox21 TRHR assay
SHOBAIR_SOT2021_TRHR_WORKFLOW_20210223.PDF (PDF, NA pp, 1574.466 KB, about PDF)