Guo Xin, Wang Jie, Fan Hongyang, Tao Wanying, Ren Zijing, Li Xingyue, Liu Suyu, Zhou Peiyang, Chen Yingzhu
Department of Geriatric Neurology, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou, Jiangsu, China.
Department of Neurology, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, China.
Front Pharmacol. 2025 Apr 8;16:1539032. doi: 10.3389/fphar.2025.1539032. eCollection 2025.
Parkinson's disease (PD), a prevalent and progressive neurodegenerative disorder, currently lacks effective and satisfactory pharmacological treatments. Computational drug repurposing represents a promising and efficient strategy for drug discovery, aiming to identify new therapeutic indications for existing pharmaceuticals. We employed a drug-target network approach to computationally repurpose FDA-approved drugs from databases such as DrugBank. A literature review was conducted to select candidates not previously reported as pharmacoprotective against PD. Subsequent in vitro evaluation utilized Cell Counting Kit-8 (CCK8) assays to assess the neuroprotective effects of the selected compounds in the SH-SY5Y cell model of Parkinson's disease induced by 1-methyl-4-phenylpyridinium (MPP+). Furthermore, an in vivo mouse model of Parkinson's disease induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) was developed to investigate the mechanisms of action and therapeutic potential of the identified drug candidates. Our approach identified 176 drug candidates, with 28 selected for their potential anti-Parkinsonian effects and lack of prior PD-related reporting. CCK8 assays showed significant neuroprotection in SH-SY5Y cells for Omaveloxolone and Cyproheptadine. In the MPTP-induced mouse model, Cyproheptadine inhibited interleukin-6 (IL-6) expression and prevented Tyrosine Hydroxylase (TH) downregulation via the MAPK/NFκB pathway, while Omaveloxolone alleviated TH downregulation, potentially through the Kelch-like ECH-associated protein 1 (KEAP1)-NF-E2-related factor 2 (Nrf2)/antioxidant response element (ARE) pathway. Both drugs preserved dopaminergic neurons and improved neurological deficits in the PD model. This study elucidates potential drug candidates for the treatment of Parkinson's disease through the application of computational repurposing, thereby underscoring its efficacy as a drug discovery strategy.
帕金森病（PD）是一种常见的进行性神经退行性疾病，目前缺乏有效且令人满意的药物治疗方法。计算药物重新定位是一种有前景且高效的药物发现策略，旨在为现有药物确定新的治疗适应症。我们采用药物-靶点网络方法，从DrugBank等数据库中对美国食品药品监督管理局（FDA）批准的药物进行计算重新定位。通过文献综述筛选出先前未报道具有抗帕金森病药物保护作用的候选药物。随后的体外评估利用细胞计数试剂盒-8（CCK8）测定法，评估所选化合物在1-甲基-4-苯基吡啶鎓（MPP+）诱导的帕金森病SH-SY5Y细胞模型中的神经保护作用。此外，还建立了由1-甲基-4-苯基-1,2,3,6-四氢吡啶（MPTP）诱导的帕金森病小鼠体内模型，以研究已鉴定的候选药物的作用机制和治疗潜力。我们的方法确定了176种候选药物，其中28种因其潜在的抗帕金森病作用且此前未与帕金森病相关报道而被选中。CCK8测定法显示，奥马韦罗酮和赛庚啶对SH-SY5Y细胞具有显著的神经保护作用。在MPTP诱导的小鼠模型中，赛庚啶通过丝裂原活化蛋白激酶/核因子κB（MAPK/NFκB）途径抑制白细胞介素-6（IL-6）表达并防止酪氨酸羟化酶（TH）下调，而奥马韦罗酮可能通过 Kelch样ECH相关蛋白1（KEAP1）-核因子E2相关因子2（Nrf2）/抗氧化反应元件（ARE）途径减轻TH下调。两种药物在帕金森病模型中均保留了多巴胺能神经元并改善了神经功能缺损。本研究通过应用计算重新定位阐明了治疗帕金森病的潜在候选药物，从而强调了其作为药物发现策略的有效性。
