Abstract：
To develop a method for predicting chronic toxicity of pharmaceuticals in Daphnia, we investigated the feasibility of combining the presence of drug-target orthologs in Daphnia magna, classification based on pharmacological effects, and ecotoxicity quantitative structure-activity relationship (QSAR) prediction. We established datasets on the chronic toxicity of pharmaceuticals in Daphnia, including information on therapeutic categories, target proteins, and the presence or absence of drug-target orthologs in D. magna, using literature and databases. Chronic toxicity was predicted using ecotoxicity prediction QSAR (Ecological Structure Activity Relationship and Kashinhou Tool for Ecotoxicity), and the differences between the predicted and measured values and the presence or absence of drug-target orthologs were examined. For pharmaceuticals without drug-target orthologs in D. magna or without expected specific actions, the ecotoxicity prediction QSAR analysis yielded acceptable predictions of the chronic toxicity of pharmaceuticals. In addition, a workflow model to assess the chronic toxicity of pharmaceuticals in Daphnia was proposed based on these evaluations and verified using an additional dataset. The addition of biological aspects such as drug-target orthologs and pharmacological effects would support the use of QSARs for predicting the chronic toxicity of pharmaceuticals in Daphnia.
摘要：
建立水蚤药物慢性毒性预测方法,我们研究了在大型蚤中结合药物靶向直系同源物的可行性，根据药理作用进行分类，生态毒性定量构效关系(QSAR)预测。我们建立了药物在水蚤中的慢性毒性的数据集，包括治疗类别的信息，靶蛋白,以及D.magna中是否存在药物靶向直系同源物，使用文献和数据库。使用生态毒性预测QSAR（生态结构活动关系和Kashhou生态毒性工具）预测慢性毒性，并检查了预测值和测量值之间的差异以及是否存在药物靶标直向同源物。对于在D.magna中没有药物靶向直系同源物或没有预期的特定行动的药物，生态毒性预测QSAR分析对药物的慢性毒性产生了可接受的预测。此外,在这些评价的基础上,我们提出了一个评估药物在水蚤中的慢性毒性的工作流程模型,并使用一个额外的数据集进行了验证.添加生物学方面，例如药物靶向直向同源物和药理作用，将支持使用QSAR预测药物在水蚤中的慢性毒性。
