{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Garcia-Martin JA"],"funding":["the Spanish Ministry of Economy and Competitiveness with European Regional Development Fund","the SETH","Projects of the Spanish Ministry of Science and Innovation, the MADONNA","SynBio4Flav","BioRoboost","SyCoLiM","Contracts of the European Union, as well as the InGEMICS-CM","MIX-UP"],"pagination":["bpaa025"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7750720"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["5(1)"],"pubmed_abstract":["The environmental fate of many functional molecules that are produced on a large scale as precursors or as additives to specialty goods (plastics, fibers, construction materials, etc.), let alone those synthesized by the pharmaceutical industry, is generally unknown. Assessing their environmental fate is crucial when taking decisions on the manufacturing, handling, usage, and release of these substances, as is the evaluation of their toxicity in humans and other higher organisms. While this data are often hard to come by, the experimental data already available on the biodegradability and toxicity of many unusual compounds (including genuinely xenobiotic molecules) make it possible to develop machine learning systems to predict these features. As such, we have created a predictor of the \"risk\" associated with the use and release of any chemical. This new system merges computational methods to predict biodegradability with others that assess biological toxicity. The combined platform, named <i>BiodegPred</i> (https://sysbiol.cnb.csic.es/BiodegPred/), provides an informed prognosis of the chance a given molecule can eventually be catabolized in the biosphere, as well as of its eventual toxicity, all available through a simple web interface. While the platform described does not give much information about specific degradation kinetics or particular biodegradation pathways, <i>BiodegPred</i> has been instrumental in anticipating the probable behavior of a large number of new molecules (e.g. antiviral compounds) for which no biodegradation data previously existed."],"journal":["Biology methods & protocols"],"pubmed_title":["Concomitant prediction of environmental fate and toxicity of chemical compounds."],"pmcid":["PMC7750720"],"funding_grant_id":["RTI2018-095584-B-C42, MINECO/FEDER","Project of the Comunidad de Madrid—European Structural and Investment Funds (FSE, FECER)","H2020-NMBP-BIO-CSA-2018-820699","S2017/BMD-3691","MIX-UP H2020-BIO-CN-2019-870294","SAF2016-78041-C2-2-R","ERA-COBIOTECH 2018—PCI2019-111859-2","H2020-FET-OPEN-RIA-2017-1-766975","H2020-NMBP-TR-IND/H2020-NMBP-BIO-2018-814650"],"pubmed_authors":["Pazos F","de Lorenzo V","Chavarria M","Garcia-Martin JA"],"additional_accession":[]},"is_claimable":false,"name":"Concomitant prediction of environmental fate and toxicity of chemical compounds.","description":"The environmental fate of many functional molecules that are produced on a large scale as precursors or as additives to specialty goods (plastics, fibers, construction materials, etc.), let alone those synthesized by the pharmaceutical industry, is generally unknown. Assessing their environmental fate is crucial when taking decisions on the manufacturing, handling, usage, and release of these substances, as is the evaluation of their toxicity in humans and other higher organisms. While this data are often hard to come by, the experimental data already available on the biodegradability and toxicity of many unusual compounds (including genuinely xenobiotic molecules) make it possible to develop machine learning systems to predict these features. As such, we have created a predictor of the \"risk\" associated with the use and release of any chemical. This new system merges computational methods to predict biodegradability with others that assess biological toxicity. The combined platform, named <i>BiodegPred</i> (https://sysbiol.cnb.csic.es/BiodegPred/), provides an informed prognosis of the chance a given molecule can eventually be catabolized in the biosphere, as well as of its eventual toxicity, all available through a simple web interface. While the platform described does not give much information about specific degradation kinetics or particular biodegradation pathways, <i>BiodegPred</i> has been instrumental in anticipating the probable behavior of a large number of new molecules (e.g. antiviral compounds) for which no biodegradation data previously existed.","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020","modification":"2024-11-14T19:44:09.319Z","creation":"2021-02-20T16:51:23Z"},"accession":"S-EPMC7750720","cross_references":{"pubmed":["33376807"],"doi":["10.1093/biomethods/bpaa025"]}}