{"title":"持久性、流动性和毒性药物(PMT)的计算机预测:巴西圣保罗大都会区的案例研究","authors":"Vinicius Roveri , Luciana Lopes Guimarães","doi":"10.1016/j.comtox.2022.100254","DOIUrl":null,"url":null,"abstract":"<div><p>Computational modelling (in silico) methods based on quantitative structure-activity relationship ((Q)SAR) models, are powerful tools for the assessment of the potential “persistency, mobility, and toxicity” (PMT) of pharmaceuticals compounds. Moreover, the use of (Q)SAR models, is recommended by European Union’s REACH Regulation. In this context, the aims of this research were estimating, for the first time and based by REACH guidelines, the PMT potentials of 115 most sold pharmaceuticals in São Paulo Metropolitan Region (a megacity with 21 million of Brazilian), through five (Q)SAR updated models, namely: the OPERA QSAR; the VEGA QSAR (Version 1.1.5); the <em>EPI</em> Suite (Version 4.11); the ECOSAR (Version, 2.0); and the QSAR Toolbox (Version 4.5). This study prioritized the in-silico predictions from the OPERA and the VEGA, because both QSARs can generate reliable predictions, i.e., they have detailed information about the applicability domains. In silico predictions were performed considering ten endpoints: (i) Molecular weight (MW); (ii) “STP total removal”: Sewage Treatment Plant; (iii) Octanol-water partition coefficient (KOW); (iv) Predicted ready biodegradability; (v) Soil organic adsorption coefficient (KOC); (vi) “Short-term and long-term ecological assessments”; (vii) “Carcinogenicity”; (viii) “Mutagenicity”; (ix) “Estrogen receptor binding”; (x) “Cramer decision tree”. The main results showed that: (a) These 115 pharmaceuticals cover a wide range of so-called small molecules (range from 100 to 600 MW); (b) In STP, a predicted removal lower than 10 % was found for 76 pharmaceuticals; (c) Additionally, 101 chemicals has low (Log KOW <2.5), or medium sorption potential (2.5< log KOW <4.0); (d) Ultimately, 36 PPCPs were considered “persistent” after a weight-of-evidence assessment. In addiction, 17 among these 36 persistent chemicals, were classified as “very mobile” in water (log KOC <3). Finally, only three among 17 PPCPs, namely ciprofibrate, fluconazole and metoclopramide, exhibited one or more toxic characteristics (described in items vi – x). These results it will be possible to alert about the potential risks arising from the indiscriminate disposal of these PPCPs along the water sources of this Brazilian mega metropolis.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"In silico prediction of persistent, mobile, and toxic pharmaceuticals (PMT): A case study in São Paulo Metropolitan Region, Brazil\",\"authors\":\"Vinicius Roveri , Luciana Lopes Guimarães\",\"doi\":\"10.1016/j.comtox.2022.100254\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Computational modelling (in silico) methods based on quantitative structure-activity relationship ((Q)SAR) models, are powerful tools for the assessment of the potential “persistency, mobility, and toxicity” (PMT) of pharmaceuticals compounds. Moreover, the use of (Q)SAR models, is recommended by European Union’s REACH Regulation. In this context, the aims of this research were estimating, for the first time and based by REACH guidelines, the PMT potentials of 115 most sold pharmaceuticals in São Paulo Metropolitan Region (a megacity with 21 million of Brazilian), through five (Q)SAR updated models, namely: the OPERA QSAR; the VEGA QSAR (Version 1.1.5); the <em>EPI</em> Suite (Version 4.11); the ECOSAR (Version, 2.0); and the QSAR Toolbox (Version 4.5). This study prioritized the in-silico predictions from the OPERA and the VEGA, because both QSARs can generate reliable predictions, i.e., they have detailed information about the applicability domains. In silico predictions were performed considering ten endpoints: (i) Molecular weight (MW); (ii) “STP total removal”: Sewage Treatment Plant; (iii) Octanol-water partition coefficient (KOW); (iv) Predicted ready biodegradability; (v) Soil organic adsorption coefficient (KOC); (vi) “Short-term and long-term ecological assessments”; (vii) “Carcinogenicity”; (viii) “Mutagenicity”; (ix) “Estrogen receptor binding”; (x) “Cramer decision tree”. The main results showed that: (a) These 115 pharmaceuticals cover a wide range of so-called small molecules (range from 100 to 600 MW); (b) In STP, a predicted removal lower than 10 % was found for 76 pharmaceuticals; (c) Additionally, 101 chemicals has low (Log KOW <2.5), or medium sorption potential (2.5< log KOW <4.0); (d) Ultimately, 36 PPCPs were considered “persistent” after a weight-of-evidence assessment. In addiction, 17 among these 36 persistent chemicals, were classified as “very mobile” in water (log KOC <3). Finally, only three among 17 PPCPs, namely ciprofibrate, fluconazole and metoclopramide, exhibited one or more toxic characteristics (described in items vi – x). These results it will be possible to alert about the potential risks arising from the indiscriminate disposal of these PPCPs along the water sources of this Brazilian mega metropolis.</p></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468111322000421\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TOXICOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468111322000421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
In silico prediction of persistent, mobile, and toxic pharmaceuticals (PMT): A case study in São Paulo Metropolitan Region, Brazil
Computational modelling (in silico) methods based on quantitative structure-activity relationship ((Q)SAR) models, are powerful tools for the assessment of the potential “persistency, mobility, and toxicity” (PMT) of pharmaceuticals compounds. Moreover, the use of (Q)SAR models, is recommended by European Union’s REACH Regulation. In this context, the aims of this research were estimating, for the first time and based by REACH guidelines, the PMT potentials of 115 most sold pharmaceuticals in São Paulo Metropolitan Region (a megacity with 21 million of Brazilian), through five (Q)SAR updated models, namely: the OPERA QSAR; the VEGA QSAR (Version 1.1.5); the EPI Suite (Version 4.11); the ECOSAR (Version, 2.0); and the QSAR Toolbox (Version 4.5). This study prioritized the in-silico predictions from the OPERA and the VEGA, because both QSARs can generate reliable predictions, i.e., they have detailed information about the applicability domains. In silico predictions were performed considering ten endpoints: (i) Molecular weight (MW); (ii) “STP total removal”: Sewage Treatment Plant; (iii) Octanol-water partition coefficient (KOW); (iv) Predicted ready biodegradability; (v) Soil organic adsorption coefficient (KOC); (vi) “Short-term and long-term ecological assessments”; (vii) “Carcinogenicity”; (viii) “Mutagenicity”; (ix) “Estrogen receptor binding”; (x) “Cramer decision tree”. The main results showed that: (a) These 115 pharmaceuticals cover a wide range of so-called small molecules (range from 100 to 600 MW); (b) In STP, a predicted removal lower than 10 % was found for 76 pharmaceuticals; (c) Additionally, 101 chemicals has low (Log KOW <2.5), or medium sorption potential (2.5< log KOW <4.0); (d) Ultimately, 36 PPCPs were considered “persistent” after a weight-of-evidence assessment. In addiction, 17 among these 36 persistent chemicals, were classified as “very mobile” in water (log KOC <3). Finally, only three among 17 PPCPs, namely ciprofibrate, fluconazole and metoclopramide, exhibited one or more toxic characteristics (described in items vi – x). These results it will be possible to alert about the potential risks arising from the indiscriminate disposal of these PPCPs along the water sources of this Brazilian mega metropolis.
期刊介绍:
Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs