Doctoral Degree Program in Toxicology, College of Pharmacy, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes, Miaoli County, 35053, Taiwan.
Arch Toxicol. 2022 Dec;96(12):3305-3314. doi: 10.1007/s00204-022-03376-1. Epub 2022 Sep 29.
Exposure to neurotoxicants has been associated with Parkinson's disease (PD). Limited by the clinical variation in the signs and symptoms as well as the slow disease progression, the identification of parkinsonian neurotoxicants relies on animal models. Here, we propose an innovative in silico model for the prediction of parkinsonian neurotoxicants. The model was designed based on a validated adverse outcome pathway (AOP) for parkinsonian motor deficits initiated from the inhibition of mitochondrial complex I. The model consists of a molecular docking model for mitochondrial complex I protein to predict the molecular initiating event and a neuronal cytotoxicity Quantitative Structure-Activity Relationships (QSAR) model to predict the cellular outcome of the AOP. Four known PD-related complex I inhibitors and four non-neurotoxic chemicals were utilized to develop the threshold of the models and to validate the model, respectively. The integrated model showed 100% specificity in ruling out the non-neurotoxic chemicals. The screening of 41 neurotoxicants and complex I inhibitors with the model resulted in 16 chemicals predicted to induce parkinsonian disorder through the molecular initiating event of mitochondrial complex I inhibition. Five of them, namely cyhalothrin, deguelin, deltamethrin, diazepam, and permethrin, are cases with direct evidence linking them to parkinsonian motor deficit-related signs and symptoms. The neurotoxicant prediction model for parkinsonian motor deficits based on the AOP concept may be useful in prioritizing chemicals for further evaluations on PD potential.
接触神经毒素与帕金森病（PD）有关。由于帕金森病的体征和症状存在临床差异，且疾病进展缓慢，因此帕金森病神经毒素的识别依赖于动物模型。在这里，我们提出了一种用于预测帕金森病神经毒素的创新计算模型。该模型基于帕金森病运动障碍的已验证不良结局途径（AOP）设计，该途径由线粒体复合物 I 的抑制引发。该模型由用于预测分子起始事件的线粒体复合物 I 蛋白的分子对接模型和用于预测 AOP 的细胞结果的神经毒性定量构效关系（QSAR）模型组成。利用四个已知的与 PD 相关的复合物 I 抑制剂和四个非神经毒性化学物质来开发模型的阈值并验证模型，分别。综合模型在排除非神经毒性化学物质方面具有 100％的特异性。使用该模型对 41 种神经毒素和复合物 I 抑制剂进行筛选，结果预测有 16 种化学物质通过线粒体复合物 I 抑制的分子起始事件诱导帕金森病。其中有 5 种，即氯氟氰菊酯、去氧鬼臼毒素、溴氰菊酯、地西泮和氯菊酯，它们与帕金森病运动障碍相关的体征和症状直接相关。基于 AOP 概念的帕金森病运动障碍神经毒素预测模型可能有助于优先考虑化学物质以进一步评估 PD 潜力。
