阿尔茨海默病(AD)是一种复杂的多因素神经退行性疾病,其特征是进行性记忆丧失。该疾病的主要病理特征是淀粉样β(Aβ)斑块的细胞外沉积和由过度磷酸化tau蛋白组成的细胞内神经原纤维缠结。了解导致AD进展的因素,分子特征的数量,和治疗剂的开发在发现治疗疾病的改善疾病的药物中发挥了重要作用。生物信息学已经确立了其在许多生物学领域的意义。生物信息学在药物发现中的作用,正在显著崛起,并将继续发展。近年来,不同的生物信息学方法,viz.蛋白质信号通路,不同类别药物之间的分子特征差异,药物的相互作用及其潜在的治疗机制,已被用于确定AD的潜在治疗靶标。还发现生物信息学工具有助于发现新药,基于组学的生物标志物,和药物重新用于AD。本综述旨在探讨各种先进的生物信息学工具在靶标识别中的应用。生物标志物,通路,以及治疗这种疾病的潜在疗法。
Alzheimer\'s disease (AD) is a complex multifactorial neurodegenerative disease characterized by progressive memory loss. The main pathological features of the disease are extracellular deposition of amyloid β (Aβ) plaques and intracellular neurofibrillary tangles composed of hyperphosphorylated tau protein. Understanding factors contributing to AD progression, the number of molecular signatures, and the development of therapeutic agents played a significant role in the discovery of disease-modifying drugs to treat the disease. Bioinformatics has established its significance in many areas of biology. The role of bioinformatics in drug discovery, is emerging significantly and will continue to evolve. In recent years, different bioinformatics methodologies, viz. protein signaling pathway, molecular signature differences between different classes of drugs, interacting profiles of drugs and their potential therapeutic mechanisms, have been applied to identify potential therapeutic targets of AD. Bioinformatics tools were also found to contribute to the discovery of novel drugs, omics-based biomarkers, and drug repurposing for AD. The review aims to explore the applications of various advanced bioinformatics tools in the identification of targets, biomarkers, pathways, and potential therapeutics for the treatment of the disease.