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CERAPP :
CERAPP : Collaborative Estrogen Receptor Activity Prediction Project
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- Mansouri, Kamel (författare)
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
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- Abdelaziz, Ahmed (författare)
- Institute of Structural Biology, Helmholtz Zentrum Muenchen – German Research Center for Environmental Health (GmbH), Munich, Germany
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- Rybacka, Aleksandra (författare)
- Umeå universitet,Kemiska institutionen
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- Roncaglioni, Alessandra (författare)
- Environmental Chemistry and Toxicology Laboratory, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
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- Tropsha, Alexander (författare)
- Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA
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- Varnek, Alexandre (författare)
- Laboratoire de Chemoinformatique, University of Strasbourg, Strasbourg, France
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- Zakharov, Alexey (författare)
- National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
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- Worth, Andrew (författare)
- Institute for Health and Consumer Protection (IHCP), Joint Research Centre of the European Commission in Ispra, Ispra, Italy
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- Richard, Ann M. (författare)
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
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- Grulke, Christopher M. (författare)
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
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- Trisciuzzi, Daniela (författare)
- Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy
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- Fourches, Denis (författare)
- Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA
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- Horvath, Dragos (författare)
- Laboratoire de Chemoinformatique, University of Strasbourg, Strasbourg, France
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- Benfenati, Emilio (författare)
- Environmental Chemistry and Toxicology Laboratory, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
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- Muratov, Eugene (författare)
- Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA
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- Wedebye, Eva Bay (författare)
- National Food Institute, Division of Toxicology and Risk Assessment, Technical University of Denmark, Copenhagen, Denmark
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- Grisoni, Francesca (författare)
- Milano Chemometrics and QSAR Research Group, University of Milano-Bicocca, Milan, Italy
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- Mangiatordi, Giuseppe F. (författare)
- Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy
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- Incisivo, Giuseppina M. (författare)
- Environmental Chemistry and Toxicology Laboratory, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
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- Hong, Huixiao (författare)
- National Center for Toxicological Research, Division of Bioinformatics and Biostatistics, U.S. Food and Drug Administration, Jefferson, Arizona, USA
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- Ng, Hui W. (författare)
- National Center for Toxicological Research, Division of Bioinformatics and Biostatistics, U.S. Food and Drug Administration, Jefferson, Arizona, USA
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- Tetko, Igor V. (författare)
- Institute of Structural Biology, Helmholtz Zentrum Muenchen – German Research Center for Environmental Health (GmbH), Munich, Germany
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- Balabin, Ilya (författare)
- High Performance Computing, Lockheed Martin, Research Triangle Park, North Carolina, USA
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- Kancherla, Jayaram (författare)
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
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- Shen, Jie (författare)
- Research Institute for Fragrance Materials, Inc., Woodcliff Lake, New Jersey, USA
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- Burton, Julien (författare)
- Institute for Health and Consumer Protection (IHCP), Joint Research Centre of the European Commission in Ispra, Ispra, Italy
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- Nicklaus, Marc (författare)
- National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
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- Cassotti, Matteo (författare)
- Milano Chemometrics and QSAR Research Group, University of Milano-Bicocca, Milan, Italy
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- Nikolov, Nikolai G. (författare)
- National Food Institute, Division of Toxicology and Risk Assessment, Technical University of Denmark, Copenhagen, Denmark
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- Nicolotti, Orazio (författare)
- Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy
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- Andersson, Patrik L. (författare)
- Umeå universitet,Kemiska institutionen
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- Zang, Qingda (författare)
- Integrated Laboratory Systems, Inc., Research Triangle Park, North Carolina, USA
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- Politi, Regina (författare)
- Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA
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- Beger, Richard D. (författare)
- National Center for Toxicological Research, Division of Systems Biology, U.S. Food and Drug Administration, Jefferson, Arizona, USA
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- Todeschini, Roberto (författare)
- Milano Chemometrics and QSAR Research Group, University of Milano-Bicocca, Milan, Italy
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- Huang, Ruili (författare)
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA
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- Farag, Sherif (författare)
- Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA
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- Rosenberg, Sine A. (författare)
- National Food Institute, Division of Toxicology and Risk Assessment, Technical University of Denmark, Copenhagen, Denmark
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- Slavov, Svetoslav (författare)
- National Center for Toxicological Research, Division of Systems Biology, U.S. Food and Drug Administration, Jefferson, Arizona, USA
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- Hu, Xin (författare)
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA
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- Judson, Richard S. (författare)
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
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National Center for Computational Toxicology, US. Environmental Protection Agency, Research Triangle Park, North Carolina, USA Institute of Structural Biology, Helmholtz Zentrum Muenchen – German Research Center for Environmental Health (GmbH), Munich, Germany (creator_code:org_t)
- Environmental Health Perspectives, 2016
- 2016
- Engelska.
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Ingår i: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 124:7, s. 1023-1033
- Relaterad länk:
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https://doi.org/10.1...
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https://umu.diva-por... (primary) (Raw object)
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https://ehp.niehs.ni...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- NATURVETENSKAP -- Kemi (hsv//swe)
- NATURAL SCIENCES -- Chemical Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
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Mansouri, Kamel
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Abdelaziz, Ahmed
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Rybacka, Aleksan ...
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Roncaglioni, Ale ...
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Tropsha, Alexand ...
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Varnek, Alexandr ...
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visa fler...
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Zakharov, Alexey
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Worth, Andrew
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Richard, Ann M.
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Grulke, Christop ...
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Trisciuzzi, Dani ...
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Fourches, Denis
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Horvath, Dragos
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Benfenati, Emili ...
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Muratov, Eugene
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Wedebye, Eva Bay
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Grisoni, Frances ...
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Mangiatordi, Giu ...
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Incisivo, Giusep ...
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Hong, Huixiao
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Ng, Hui W.
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Tetko, Igor V.
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Balabin, Ilya
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Kancherla, Jayar ...
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Shen, Jie
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Burton, Julien
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Nicklaus, Marc
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Cassotti, Matteo
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Nikolov, Nikolai ...
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Nicolotti, Orazi ...
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Andersson, Patri ...
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Zang, Qingda
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Politi, Regina
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Beger, Richard D ...
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Todeschini, Robe ...
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Huang, Ruili
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Farag, Sherif
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Rosenberg, Sine ...
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Slavov, Svetosla ...
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Hu, Xin
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Judson, Richard ...
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- NATURVETENSKAP
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NATURVETENSKAP
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och Kemi
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- NATURVETENSKAP
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NATURVETENSKAP
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och Datavetenskap
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