Godad Angel, Sawant Richa, Pahelkar Akshata R, Pereira Galvina, Sathaye Sadhana
Department of Pharmaceutical Sciences and Technology, Institute of Chemical Technology, Mumbai (Maharashtra), India.
SVKM's Dr, Bhanuben Nanavati College of Pharmacy, Mumbai (Maharashtra), India.
Mol Neurobiol. 2025 Jun 24. doi: 10.1007/s12035-025-05145-4.
Parkinson's disease is the second-most prevalent neurological disease globally, affecting about 8.5 million people. Ursolic acid (UA) is a widely distributed pentacyclic triterpenoid compound with various health benefits, including anti-inflammatory, antioxidant, antiviral and anti-tumor properties. Although its anti-Parkinson's activity has been confirmed previously, related mechanisms and pathways of drug action have been studied limited. This study explored possible pathways and used network pharmacology to create a network map of drugs and disease targets. The ADMET profiling was performed to assess the suitability of UA prior to target identification. All the targets were collected and screened through database searches and literature mining. Targeted molecules data were entered into the Cytoscape platform to create a PPI network. Additionally, functional annotation analysis and pathway enrichment were performed. After screening 1520 PD targets and 27 ursolic acid targets, nine targets were identified as overlapping. Through bioinformatics annotation of these overlapping genes, a KEGG pathway gene ontology involving GO biological processes, cellular processes and molecular functions were obtained. From the results, it was observed that UA may exert its effects via the sphingolipid signaling pathway or by activating the cannabinoid receptor, both of which play significant roles in Parkinson's disease. These mechanisms were further supported by molecular docking and dynamics studies. Docking analysis revealed strong binding of UA to the selected target proteins, with ADAM10 exhibiting the highest binding affinity (- 8.4 kcal/mol), surpassing that of the native ligand, levodopa. To evaluate the stability and interaction profile, a 100-ns molecular dynamics simulation was conducted using MOE software, confirming the efficient binding of UA to the Parkinson's disease target ADAM10.
帕金森病是全球第二常见的神经疾病,影响着约850万人。熊果酸(UA)是一种广泛分布的五环三萜类化合物,具有多种健康益处,包括抗炎、抗氧化、抗病毒和抗肿瘤特性。尽管其抗帕金森病活性此前已得到证实,但药物作用的相关机制和途径研究有限。本研究探索了可能的途径,并利用网络药理学创建了药物与疾病靶点的网络图。在进行靶点识别之前,进行了ADMET分析以评估UA的适用性。通过数据库搜索和文献挖掘收集并筛选所有靶点。将靶向分子数据输入Cytoscape平台以创建蛋白质-蛋白质相互作用(PPI)网络。此外,还进行了功能注释分析和通路富集分析。在筛选出1520个帕金森病靶点和27个熊果酸靶点后,确定了9个重叠靶点。通过对这些重叠基因的生物信息学注释,获得了一个涉及基因本体论(GO)生物学过程、细胞过程和分子功能的京都基因与基因组百科全书(KEGG)通路。从结果中观察到,UA可能通过鞘脂信号通路或激活大麻素受体发挥作用,这两者在帕金森病中都起着重要作用。分子对接和动力学研究进一步支持了这些机制。对接分析显示UA与所选靶蛋白有强烈结合,其中ADAM10表现出最高的结合亲和力(-8.4千卡/摩尔),超过了天然配体左旋多巴。为了评估稳定性和相互作用概况,使用MOE软件进行了100纳秒的分子动力学模拟,证实了UA与帕金森病靶点ADAM10的有效结合。