有机磷类化合物大鼠急性毒性QSAR模型构建与毒性机制研究
Development of QSAR Models for Acute Toxicity of Organophosphorus Compounds towards Rats and Study of Toxicity Mechanism
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摘要: 有机磷化合物(OPs)广泛分布在各种环境介质中，并对各类生物的健康有潜在的危害。本研究采用基于逐步算法(SW)和遗传算法(GA)的多元线性回归(MLR)方法，收集并筛选出53种OPs的数据集并建立其关于大鼠急性口服毒性(LD50)的定量结构活性关系(QSAR)模型。构建的SW-MLR模型的参数决定系数(R2)、留一法交叉验证系数(Q2LOO)、外部检验系数(Q2F1和Q2F2)分别为0.897、0.817、0.515和0.505，GA-MLR模型的参数分别为0.827、0.752、0.831和0.828。2个模型的统计参数表征了良好的预测能力。使用外部测试集对模型进行评估时，发现GA-MLR模型比SW-MLR模型具有更好的预测和泛化能力。此外，基于建立的模型预测了其他9种OPs的急性毒性，并辅以分子对接技术探究了其潜在的神经毒性。分子对接结果显示，其中8种OPs可以与人类丁酰胆碱酯酶结合。模型机理解释和分子对接结果显示，OPs取代基的高烷基化程度和支链长度的增加能够降低毒性。因此，建立的模型可以从OPs的分子结构上探索与毒性相关的信息，并为监管和筛选新的OPs提供基础数据。Abstract: Organophosphorus compounds (OPs) are widely distributed in various environmental media and are potentially harmful to various organisms. In this study, quantitative structure-activity relationship (QSAR) models were developed to predict the acute oral toxicity (LD50) based on the collected data of 53 OPs towards rats by using a multiple linear regression method on the basis of stepwise algorithm (SW-MLR) and genetic algorithm (GA-MLR). Coefficients of determination (R2), leave-one-out cross-validation (Q2LOO), external validation coefficients (Q2F1, and Q2F2) of the constructed SW-MLR model were 0.897, 0.817, 0.515, and 0.505, respectively, whereas those parameters of the GA-MLR model were 0.827, 0.752, 0.831, and 0.828, respectively. The statistical parameters of both models characterized good predictive power. When the models were evaluated using an external test set, the GA-MLR model was found to have better prediction and generalization capabilities than the SW-MLR model. In addition, the acute toxicity of 9 other OPs was predicted based on the established models and their potential neurotoxicity were explored with the aid of molecular docking techniques. Molecular docking results showed that 8 OPs could bind to human butyrylcholinesterase. The model mechanism explanation and docking results revealed that chain elongation and alkyl substitution can decrease the toxicity of OPs. Therefore, the developed models can explore the information related to toxicity from the molecular structure of OPs and provide basic data for regulation and screening of new OPs.
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