Hazard of pharmaceuticals for aquatic environment: Prioritization by structural approaches and prediction of ecotoxicity. (October 2016)
- Record Type:
- Journal Article
- Title:
- Hazard of pharmaceuticals for aquatic environment: Prioritization by structural approaches and prediction of ecotoxicity. (October 2016)
- Main Title:
- Hazard of pharmaceuticals for aquatic environment: Prioritization by structural approaches and prediction of ecotoxicity
- Authors:
- Sangion, Alessandro
Gramatica, Paola - Abstract:
- Abstract: Active Pharmaceutical Ingredients (APIs) are recognized as Contaminants of Emerging Concern (CEC) since they are detected in the environment in increasing amount, mainly in aquatic compartment, where they may be hazardous for wildlife. The huge lack of experimental data for a large number of end-points requires tools able to quickly highlight the potentially most hazardous and toxic pharmaceuticals, focusing experiments on the prioritized compounds. In silico tools, like QSAR (Quantitative Structure-Activity Relationship) models based on structural molecular descriptors, can predict missing data for toxic end-points necessary to prioritize existing, or even not yet synthesized chemicals for their potential hazard. In the present study, new externally validated QSAR models, specific to predict acute toxicity of APIs in key organisms of the three main aquatic trophic levels, i.e. algae, Daphnia and two species of fish, were developed using the QSARINS software. These Multiple Linear regressions - Ordinary Least Squares (MLR-OLS) models are based on theoretical molecular descriptors calculated by free PaDEL-Descriptor software and selected by Genetic Algorithm. The models are statistically robust, externally predictive and characterized by a wide structural applicability domain. They were applied to predict acute toxicity for a large set of APIs without experimental data. Then predictions were processed by Principal Component Analysis (PCA) and a trend, driven by theAbstract: Active Pharmaceutical Ingredients (APIs) are recognized as Contaminants of Emerging Concern (CEC) since they are detected in the environment in increasing amount, mainly in aquatic compartment, where they may be hazardous for wildlife. The huge lack of experimental data for a large number of end-points requires tools able to quickly highlight the potentially most hazardous and toxic pharmaceuticals, focusing experiments on the prioritized compounds. In silico tools, like QSAR (Quantitative Structure-Activity Relationship) models based on structural molecular descriptors, can predict missing data for toxic end-points necessary to prioritize existing, or even not yet synthesized chemicals for their potential hazard. In the present study, new externally validated QSAR models, specific to predict acute toxicity of APIs in key organisms of the three main aquatic trophic levels, i.e. algae, Daphnia and two species of fish, were developed using the QSARINS software. These Multiple Linear regressions - Ordinary Least Squares (MLR-OLS) models are based on theoretical molecular descriptors calculated by free PaDEL-Descriptor software and selected by Genetic Algorithm. The models are statistically robust, externally predictive and characterized by a wide structural applicability domain. They were applied to predict acute toxicity for a large set of APIs without experimental data. Then predictions were processed by Principal Component Analysis (PCA) and a trend, driven by the combination of toxicities for all the studied organisms, was highlighted. This trend, named Aquatic Toxicity Index (ATI), allowed the raking of pharmaceuticals according to their potential toxicity upon the whole aquatic environment. Finally a QSAR model for the prediction of this Aquatic Toxicity Index (ATI) was proposed to be applicable in QSARINS for the screening of existing APIs for their potential hazard and the a priori chemical design of not environmentally hazardous APIs. Graphical abstract: Highlights: QSAR models to predict the ecotoxicity of pharmaceuticals in the three main aquatic trophic levels Ranking of APIs according to their potential cumulative toxicity for aquatic environment Aquatic Toxicity Index model to predict the aquatic toxicity of new APIs from molecular structure … (more)
- Is Part Of:
- Environment international. Volume 95(2016:Oct.)
- Journal:
- Environment international
- Issue:
- Volume 95(2016:Oct.)
- Issue Display:
- Volume 95 (2016)
- Year:
- 2016
- Volume:
- 95
- Issue Sort Value:
- 2016-0095-0000-0000
- Page Start:
- 131
- Page End:
- 143
- Publication Date:
- 2016-10
- Subjects:
- APIs Active Pharmaceutical Ingredients -- AD applicability domain -- ATI Aquatic Toxicity Index -- PBT Persistence, Bioaccumulation and Toxicity -- CAS Chemical Abstract Service -- CCC concordance correlation coefficient -- CEC Contaminants of Emerging Concern -- ECOSAR Ecological Structure Activity Relationships -- E-State electrotopological state -- ERA Environmental Risk Assessment -- EE2 estrogen ethinyl estradiol -- EMEA European Medicines Agency -- CSTEE European Union Commission's Scientific Committee on Toxicity, Ecotoxicity and Environment -- GA-VSS Genetic Algorithm Variable Subset Selection -- MLR Multiple Linear Regression -- NCCOS National Centre for Coastal Ocean Science -- NOAA National Oceanic and Atmospheric Administration -- ORe Ordered by Response -- OSt Ordered by Structure -- OLS Ordinary Least Square -- OECD Organization for Economic Cooperation and Development -- PCA Principal Component Analysis -- PCs Principal Components -- QSARINS QSAR-INSubria -- QSAR Quantitative Structure Activity Relationship -- QSTR Quantitative Structure Toxicity Relationship -- Rnd Random selection -- RMSE Root Mean Squared of Errors -- SMILES Simplified Molecular Input Line Entry System -- US-EPA United States - Environmental Protection Agency -- WWTPs waste water treatment plants
Pharmaceuticals -- QSARINS -- Ecotoxicity -- PCA -- Ranking -- Aquatic Toxicity Index
Environmental protection -- Periodicals
Environmental health -- Periodicals
Environmental monitoring -- Periodicals
Environmental Monitoring -- Periodicals
Environnement -- Protection -- Périodiques
Hygiène du milieu -- Périodiques
Environnement -- Surveillance -- Périodiques
Environmental health
Environmental monitoring
Environmental protection
Periodicals
333.705 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01604120 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.envint.2016.08.008 ↗
- Languages:
- English
- ISSNs:
- 0160-4120
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3791.330000
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