Background:Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program.Objectives:We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing.Methods:CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure–activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies.Results:Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing.Conclusion:This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points.Citation:Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E, Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg SA, Slavov S, Hu X, Judson RS. 2016. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environ Health Perspect 124:1023–1033; http://dx.doi.org/10.1289/ehp.1510267

Advances in fluorescence-based imaging technologies have helped propel the study of real-time biological readouts and analysis across many different areas. In particular the use of fluorescent ligands as chemical tools to study proteins such as G protein-coupled receptors (GPCRs) has received ongoing interest. Methods to improve the efficient chemical synthesis of fluorescent ligands remain of paramount importance to ensure this area of bioanalysis continues to advance. Here we report conversion of the non-selective GPCR adenosine receptor antagonist Xanthine Amine Congener into higher affinity and more receptor subtype-selective fluorescent antagonists. This was achieved through insertion and optimisation of a dipeptide linker between the adenosine receptor pharmacophore and the fluorophore. Fluorescent probe 27 containing BODIPY 630/650 (pK(D) = 9.12 ± 0.05 [hA3AR]), and BODIPY FL-containing 28 (pK(D) = 7.96 ± 0.09 [hA3AR]) demonstrated clear, displaceable membrane binding using fluorescent confocal microscopy. From in silico analysis of the docked ligand-receptor complexes of 27, we suggest regions of molecular interaction that could account for the observed selectivity of these peptide-linker based fluorescent conjugates. This general approach of converting a non-selective ligand to a selective biological tool could be applied to other ligands of interest.

One endocrine disruption mechanism is through binding to nuclear receptors such as the androgen receptor (AR) and estrogen receptor (ER) in target cells. The concentration of a chemical in serum is important for its entry into the target cells to bind the receptors, which is regulated by the serum proteins. Human sex hormone-binding globulin (SHBG) is the major transport protein in serum that can bind androgens and estrogens and thus change a chemical's availability to enter the target cells. Sequestration of an androgen or estrogen in the serum can alter the chemical elicited AR- and ER-mediated responses. To better understand the chemical-induced endocrine activity, we developed a competitive binding assay using human pregnancy plasma and measured the binding to the human SHBG for 125 structurally diverse chemicals, most of which were known to bind AR and ER. Eighty seven chemicals were able to bind the human SHBG in the assay, whereas 38 chemicals were nonbinders. Binding data for human SHBG are compared with that for rat α-fetoprotein, ER and AR. Knowing the binding profiles between serum and nuclear receptors will improve assessment of a chemical's potential for endocrine disruption. The SHBG binding data reported here represent the largest data set of structurally diverse chemicals tested for human SHBG binding. Utilization of the SHBG binding data with AR and ER binding data could enable better evaluation of endocrine disrupting potential of chemicals through AR- and ER-mediated responses since sequestration in serum could be considered.