In silico soil degradation and ecotoxicity analysis of veterinary pharmaceuticals on terrestrial species: first report.

IF 2.2 4区 医学 Q3 TOXICOLOGY Toxicology Research Pub Date : 2024-02-26 eCollection Date: 2024-02-01 DOI:10.1093/toxres/tfae020
Purusottam Banjare, Rekha Singh, Nilesh Kumar Pandey, Balaji Wamanrao Matore, Anjali Murmu, Jagadish Singh, Partha Pratim Roy
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Abstract

With the aim of persistence property analysis and ecotoxicological impact of veterinary pharmaceuticals on different terrestrial species, different classes of veterinary pharmaceuticals (n = 37) with soil degradation property (DT50) were gathered and subjected to QSAR and q-RASAR model development. The models were developed from 2D descriptors under organization for economic cooperation and development guidelines with the application of multiple linear regressions along with genetic algorithm. All developed QSAR and q-RASAR were statistically significant (Internal = R2adj: 0.721-0.861, Q2LOO: 0.609-0.757, and external = Q2Fn = 0.597-0.933, MAEext = 0.174-0.260). Further, the leverage approach of applicability domain assured the model's reliability. The veterinary pharmaceuticals with no experimental values were classified based on their persistence level. Further, the terrestrial toxicity analysis of persistent veterinary pharmaceuticals was done using toxicity prediction by computer assisted technology and in-house built quantitative structure toxicity relationship models to prioritize the toxic and persistent veterinary pharmaceuticals. This study will be helpful in estimation of persistence and toxicity of existing and upcoming veterinary pharmaceuticals.

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兽药对陆生物种的土壤降解和生态毒性硅学分析:首次报告。
为了分析兽药的持久性和对不同陆生物种的生态毒理影响,收集了具有土壤退化特性(DT50)的不同类别兽药(n = 37),并对其进行了 QSAR 和 q-RASAR 模型开发。这些模型是根据经济合作与发展组织的指导方针,应用多重线性回归和遗传算法,从二维描述符中建立的。所有开发的 QSAR 和 q-RASAR 都具有显著的统计学意义(内部 = R2adj:0.721-0.861,Q2LOO:0.609-0.757,外部 = Q2Fn = 0.597-0.933,MAEext = 0.174-0.260)。此外,适用性领域的杠杆方法确保了模型的可靠性。根据持久性水平对无实验值的兽药进行了分类。此外,通过计算机辅助毒性预测技术和内部建立的定量结构毒性关系模型,对持久性兽药进行了陆地毒性分析,以确定有毒持久性兽药的优先级。这项研究将有助于估算现有和未来兽药的持久性和毒性。
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来源期刊
Toxicology Research
Toxicology Research TOXICOLOGY-
CiteScore
3.60
自引率
0.00%
发文量
82
期刊介绍: A multi-disciplinary journal covering the best research in both fundamental and applied aspects of toxicology
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