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人工智能驱动的药物重定位发现依非韦伦可作为α-突触核蛋白传播的调节剂:在帕金森病中的意义。

Artificial intelligence-driven drug repositioning uncovers efavirenz as a modulator of α-synuclein propagation: Implications in Parkinson's disease.

机构信息

Department of Pharmacology, Ajou University School of Medicine, Suwon, Korea; Center for Convergence Research of Neurological Disorders, Ajou University School of Medicine, Suwon, Korea; Neuroscience Graduate Program, Department of Biomedical Sciences, Ajou University School of Medicine, Suwon, Korea.

Center for Convergence Research of Neurological Disorders, Ajou University School of Medicine, Suwon, Korea.

出版信息

Biomed Pharmacother. 2024 May;174:116442. doi: 10.1016/j.biopha.2024.116442. Epub 2024 Mar 20.

Abstract

Parkinson's disease (PD) is a complex neurodegenerative disorder with an unclear etiology. Despite significant research efforts, developing disease-modifying treatments for PD remains a major unmet medical need. Notably, drug repositioning is becoming an increasingly attractive direction in drug discovery, and computational approaches offer a relatively quick and resource-saving method for identifying testable hypotheses that promote drug repositioning. We used an artificial intelligence (AI)-based drug repositioning strategy to screen an extensive compound library and identify potential therapeutic agents for PD. Our AI-driven analysis revealed that efavirenz and nevirapine, approved for treating human immunodeficiency virus infection, had distinct profiles, suggesting their potential effects on PD pathophysiology. Among these, efavirenz attenuated α-synuclein (α-syn) propagation and associated neuroinflammation in the brain of preformed α-syn fibrils-injected A53T α-syn Tg mice and α-syn propagation and associated behavioral changes in the C. elegans BiFC model. Through in-depth molecular investigations, we found that efavirenz can modulate cholesterol metabolism and mitigate α-syn propagation, a key pathological feature implicated in PD progression by regulating CYP46A1. This study opens new avenues for further investigation into the mechanisms underlying PD pathology and the exploration of additional drug candidates using advanced computational methodologies.

摘要

帕金森病(PD)是一种复杂的神经退行性疾病,其病因尚不清楚。尽管进行了大量研究,但开发针对 PD 的疾病修饰治疗方法仍然是一个主要的未满足的医学需求。值得注意的是,药物重定位在药物发现中正成为一个越来越有吸引力的方向,而计算方法为识别可测试的假说提供了一种相对快速和节省资源的方法,这些假说可以促进药物重定位。我们使用基于人工智能(AI)的药物重定位策略来筛选广泛的化合物库,并确定治疗 PD 的潜在治疗剂。我们的 AI 驱动分析表明,依非韦伦和奈韦拉平,批准用于治疗人类免疫缺陷病毒感染,具有不同的特征,表明它们对 PD 病理生理学的潜在影响。在这些化合物中,依非韦伦在预形成的α-突触核蛋白(α-syn)纤维注射 A53T α-syn Tg 小鼠的大脑中减弱了α-syn 的传播和相关的神经炎症,在 C. elegans BiFC 模型中减弱了α-syn 的传播和相关的行为变化。通过深入的分子研究,我们发现依非韦伦可以调节胆固醇代谢,减轻α-syn 的传播,这是一种关键的病理特征,通过调节 CYP46A1 参与 PD 的进展。这项研究为进一步研究 PD 病理学的机制以及使用先进的计算方法探索其他药物候选物开辟了新的途径。

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