Sharo Catherine, Zhang Jiayu, Zhai Tianhua, Bao Jingxuan, Garcia-Epelboim Andrés, Mamourian Elizabeth, Shen Li, Huang Zuyi
Department of Chemical and Biological Engineering, Villanova University, Villanova, PA 19085, USA.
Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
Targets (Basel). 2024 Dec;2(4):446-469. doi: 10.3390/targets2040025. Epub 2024 Dec 4.
Alzheimer's disease is a neurodegenerative disease that continues to have a rising number of cases. While extensive research has been conducted in the last few decades, only a few drugs have been approved by the FDA for treatment, and even fewer aim to be curative rather than manage symptoms. There remains an urgent need for understanding disease pathogenesis, as well as identifying new targets for further drug discovery. Alzheimer's disease (AD) is known to stem from a build-up of amyloid beta (Aβ) plaques as well as tangles of tau proteins. Furthermore, inflammation in the brain is known to arise from the degeneration of tissue and the build-up of insoluble material. Therefore, there is a potential link between the pathology of AD and inflammation in the brain, especially as the disease progresses to later stages where neuronal death and degeneration levels are higher. Proteins that are relevant to both brain inflammation and AD thus make ideal potential targets for therapeutics; however, the proteins need to be evaluated to determine which targets would be ideal for potential drug therapeutic treatments, or 'druggable'. Druggability analysis was conducted using two structure-based methods (i.e., Drug-Like Density analysis and SiteMap), as well as a sequence-based approach, SPIDER. The most druggable targets were then evaluated using single-nuclei sequencing data for their clinical relevance to inflammation in AD. For each of the top five targets, small molecule docking was used to evaluate which FDA approved drugs were able to bind with the chosen proteins. The top targets included DRD2 (inhibits adenylyl cyclase activity), C9 (binds with C5B8 to form the membrane attack complex), C4b (binds with C2a to form C3 convertase), C5AR1 (GPCR that binds C5a), and GABA-A-R (GPCR involved in inhibiting neurotransmission). Each target had multiple potential inhibitors from the FDA-approved drug list with decent binding infinities. Among these inhibitors, two drugs were found as top inhibitors for more than one protein target. They are C15H14N2O2 and v316 (Paracetamol), used to treat pain/inflammation originally for cataracts and relieve headaches/fever, respectively. These results provide the groundwork for further experimental investigation or clinical trials.
阿尔茨海默病是一种神经退行性疾病，其病例数量持续上升。尽管在过去几十年里进行了广泛的研究，但美国食品药品监督管理局（FDA）仅批准了少数几种药物用于治疗，而且旨在治愈而非控制症状的药物更少。目前迫切需要了解疾病的发病机制，并确定进一步药物研发的新靶点。已知阿尔茨海默病（AD）源于β淀粉样蛋白（Aβ）斑块的积累以及tau蛋白缠结。此外，已知大脑中的炎症是由组织退化和不溶性物质的积累引起的。因此，AD的病理与大脑炎症之间存在潜在联系，尤其是在疾病进展到后期，神经元死亡和退化程度更高时。因此，与大脑炎症和AD都相关的蛋白质成为理想的潜在治疗靶点；然而，需要对这些蛋白质进行评估，以确定哪些靶点对于潜在的药物治疗是理想的，即“可成药的”。使用两种基于结构的方法（即类药密度分析和SiteMap）以及一种基于序列的方法SPIDER进行了可成药分析。然后使用单核测序数据评估最具可成药潜力的靶点与AD炎症的临床相关性。对于排名前五的每个靶点，使用小分子对接来评估哪些FDA批准的药物能够与所选蛋白质结合。排名靠前的靶点包括DRD2（抑制腺苷酸环化酶活性）、C9（与C5B8结合形成膜攻击复合物）、C4b（与C2a结合形成C3转化酶）、C5ARl（结合C5a的GPCR）和GABA - A - R（参与抑制神经传递的GPCR）。每个靶点都有来自FDA批准药物列表的多种潜在抑制剂，其结合亲和力良好。在这些抑制剂中，发现有两种药物是不止一个蛋白质靶点的顶级抑制剂。它们分别是C15H14N2O2和v316（对乙酰氨基酚），最初分别用于治疗白内障的疼痛/炎症和缓解头痛/发烧。这些结果为进一步的实验研究或临床试验奠定了基础。
