The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.
CERAPP: Collaborative Estrogen Receptor Activity Prediction Project
Open accessAbstract
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
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“The resulting consensus QSAR models leveraged knowledge from the groups and were used to predict ER and AR potentials of 32,464 new chemicals.”
From QSAR without borders (2020) · cites this paper as [89]
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Metadata
- Authors
- Mansouri, K., Abdelaziz, A., Rybacka, A., Roncaglioni, A., Tropsha, A., Varnek, A., Zakharov, A., Worth, A., Richard, A. M., Grulke, C. M., Trisciuzzi, D., Fourches, D., Horvath, D., Benfenati, E., Muratov, E., Wedebye, E. B., Grisoni, F., Mangiatordi, G. F., Incisivo, G. M., Hong, H., Ng, H. W., Tetko, I. V., Balabin, I., Kancherla, J., Shen, J., Burton, J., Nicklaus, M., Cassotti, M., Nikolov, N. G., Nicolotti, O., Andersson, P. L., Zang, Q., Politi, R., Beger, R. D., Todeschini, R., Huang, R., Farag, S., Rosenberg, S. A., Slavov, S., Hu, X., & Judson, R. S.
- Affiliations
- Environmental Protection Agency (US)
- Helmholtz Munich (DE)
- Umeå University (SE)
- Mario Negri Institute for Pharmacological Research (IT)
- University of North Carolina at Chapel Hill (US)
- Université de Strasbourg (FR)
- National Institutes of Health (US)
- European Commission (BE)
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
- University of Bari Aldo Moro (IT)
- Technical University of Denmark (DK)
- University of Milano-Bicocca (IT)
- National Center for Toxicological Research (US)
- Lockheed Martin (United States) (US)
- Research Institute for Fragrance Materials (US)
- Integrated Laboratory Systems, Inc. (US)
- Corresponding author
- Judson, Richard S.
- ORCID
- Mansouri, Kamel
- Roncaglioni, Alessandra
- Tropsha, Alexander
- Varnek, Alexandre
- Zakharov, Alexey
- Worth, Andrew
- Trisciuzzi, Daniela
- Fourches, Denis
- Horvath, Dragos
- Benfenati, Emilio
- Muratov, Eugene
- Wedebye, Eva Bay
- Grisoni, Francesca
- Mangiatordi, Giuseppe F.
- Hong, Huixiao
- Tetko, Igor V.
- Balabin, Ilya
- Kancherla, Jayaram
- Shen, Jie
- Nicklaus, Marc
- Cassotti, Matteo
- Nikolov, Nikolai G.
- Nicolotti, Orazio
- Andersson, Patrik L.
- Zang, Qingda
- Beger, Richard D.
- Todeschini, Roberto
- Huang, Ruili
- Rosenberg, Sine A.
- Slavov, Svetoslav
- Hu, Xin
- Judson, Richard S.
- Venue
- Environmental Health Perspectives
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-02-23
- Volume
- 124
- Issue
- 7
- Pages
- 1023-1033
- ISSN
- 0091-6765 (ISSN-L)
- 1552-9924
- PMC
- PMC4937869
- OpenAlex
- W2394108223
- Cited by
- 375
- References
- 85
- Citations by year
- 2026: 26 · 2025: 46 · 2024: 35 · 2023: 32 · 2022: 36 · 2021: 41 · 2020: 35 · 2019: 30 · 2018: 38 · 2017: 29 · 2016: 27
- FWCI
- 38.02
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- public-domain
- creativecommons.org/licenses/by/4.0/ (vor, 675 d)
- Locations
- Environmental Health Perspectives (publishedVersion, public-domain)
- PubMed Central (publishedVersion, public-domain)
- PubMed (publishedVersion)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by)
- KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
- HAL (submittedVersion, other-oa)
- BOA (University of Milano-Bicocca) (submittedVersion)
- Site cant be reached (submittedVersion, cc-by)
- Joint Research Centre (European Commission) (submittedVersion)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, other-oa)
- CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) (submittedVersion, other-oa)
- Funders
- National Institute of General Medical Sciences (T32GM067553)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Effects and risks of endocrine disrupting chemicals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Endocrinology › Estrogen and related hormone effects
- Keywords
- endocrine disruptors, estrogen receptor, QSAR, molecular docking, consensus model, chemical prioritization, high-throughput screening, chemical risk assessment
- MeSH terms
- Computer Simulation, Receptors, Estrogen, United States, Toxicity Tests, Quantitative Structure-Activity Relationship, Endocrine Disruptors, Environmental Policy
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