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. 2013 Jun 17;26(6):878-95.
doi: 10.1021/tx400021f. Epub 2013 May 16.

Profiling 976 ToxCast chemicals across 331 enzymatic and receptor signaling assays

Nisha S Sipes  1 , Matthew T Martin, Parth Kothiya, David M Reif, Richard S Judson, Ann M Richard, Keith A Houck, David J Dix, Robert J Kavlock, Thomas B Knudsen
Affiliations

Profiling 976 ToxCast chemicals across 331 enzymatic and receptor signaling assays

Nisha S Sipes et al. Chem Res Toxicol. .

Abstract

Understanding potential health risks is a significant challenge due to the large numbers of diverse chemicals with poorly characterized exposures and mechanisms of toxicities. The present study analyzes 976 chemicals (including failed pharmaceuticals, alternative plasticizers, food additives, and pesticides) in Phases I and II of the U.S. EPA's ToxCast project across 331 cell-free enzymatic and ligand-binding high-throughput screening (HTS) assays. Half-maximal activity concentrations (AC50) were identified for 729 chemicals in 256 assays (7,135 chemical-assay pairs). Some of the most commonly affected assays were CYPs (CYP2C9 and CYP2C19), transporters (mitochondrial TSPO, norepinephrine, and dopaminergic), and GPCRs (aminergic). Heavy metals, surfactants, and dithiocarbamate fungicides showed promiscuous but distinctly different patterns of activity, whereas many of the pharmaceutical compounds showed promiscuous activity across GPCRs. Literature analysis confirmed >50% of the activities for the most potent chemical-assay pairs (54) but also revealed 10 missed interactions. Twenty-two chemicals with known estrogenic activity were correctly identified for the majority (77%), missing only the weaker interactions. In many cases, novel findings for previously unreported chemical-target combinations clustered with known chemical-target interactions. Results from this large inventory of chemical-biological interactions can inform read-across methods as well as link potential targets to molecular initiating events in adverse outcome pathways for diverse toxicities.

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Figures

Figure 1
Figure 1
Hierarchical clustering of 976 chemicals by 331 biochemical assays. Hierarchical clustering was based on chemical–assay potency as measured by the inverse log of AC50s (in micromolar) divided by 1,000,000 (−log(AC50/1000000)). Actives with AC50 values ≤1 μM are colored red and others blue. Gray indicates inactive and white not tested in Phase I (hCAR_Agonist assay). (A) Left ribbon indicates clusters of 21 assay categories (see Assay Ribbon Key). Left colored tree structure indicates relatively homogeneous assay category clustering including GPCR (other), red; nuclear receptor (subfamily 3), yellow; kinases and phosphatases, blue; GPCR (aminergic), green. Top bars indicate clusters of 4 chemical use groups. Top colored tree structure indicates highly promiscuous, mostly pharmaceuticals (green) and promiscuous, mostly pesticides (blue). (B) Details for 10 of the most promiscuous chemicals listed in Table 2. Heavy metals (1-phenylmercuric acetate, 2-mercuric chloride, 3-tributyltin methacrylate, 4-tributyltin chloride); surfactants (5-sodium dodecylbenzenesulfonate, 6-perfluorooctane sulfonic acid, and 7-dodecylbenzene sulfonate triethanolamine (1:1)); and dithiocarbamate fungicides (8-mancozeb, 9-maneb, and 10-metiram).
Figure 2
Figure 2
Assay–assay similarity matrix clustered based on chemical–assay profiles. Pearson correlations (−0.3 to 0.5) indicated the strength of associations, which were visualized in the heatmap from blue to red, respectively. Similar assays clustered along the diagonal have high associations. Selected clusters (i, ii, and iii) are shown as examples and listed in Table 5. The left color bar indicates the number of chemicals affecting a given assay.
Figure 3
Figure 3
Chemical–chemical similarity matrix clustered based on chemical–assay profiles. Pearson correlations (−0.3 to 0.5) indicated the strength of associations, which were visualized in the heatmap from blue to red, respectively. Similar chemicals clustered along the diagonal have high associations. Selected clusters (i, ii, iii, and iv) are shown as examples and listed in Table 6. The left color bar indicates the number of assays affected by a given chemical. The right panel indicates the assay enrichment scores (defined in the Experimental Procedures section) for each chemical and can be used to describe the chemicals in the clusters.
Figure 4
Figure 4
Chemical fragment–assay category associations. Univariate associations between chemical-structure fragments and enrichment scores for chemical–assay categories were performed to identify chemical fragments in chemicals specifically enriched for affecting an assay category. Chemical fragment–assay categories with true positives ≥5 and positive predictive value (PPV) >0.5 are visualized. Purple nodes are the chemical fragments, and green diamonds are the assay categories. Example chemical fragment structures are shown for the associations with the highest PPV (indicated by increasing edge thickness). Numbers of true positives are indicated by edge color from gray (5–9) to black (10–26).
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