Deng Yin-Hua, Wang Ning-Ning, Zou Zhen-Xing, Zhang Lin, Xu Kang-Ping, Chen Alex F, Cao Dong-Sheng, Tan Gui-Shan
Xiangya School of Pharmaceutical Sciences, Central South UniversityChangsha, China.
Pharmacy Department, Xiangya Hospital, Central South UniversityChangsha, China.
Front Pharmacol. 2017 Aug 25;8:539. doi: 10.3389/fphar.2017.00539. eCollection 2017.
Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disorder which is considered to be the most common cause of dementia. It has a greater impact not only on the learning and memory disturbances but also on social and economy. Currently, there are mainly single-target drugs for AD treatment but the complexity and multiple etiologies of AD make them difficult to obtain desirable therapeutic effects. Therefore, the choice of multi-target drugs will be a potential effective strategy inAD treatment. To find multi-target active ingredients for AD treatment from plants, we firstly explored the behaviors effects on AD mice of total extracts (TE) from on by Morris water maze test and found that TE has a remarkable improvement on learning and memory function for AD mice. And then, multi-target SAR models associated with AD-related proteins were built based on Random Forest (RF) and different descriptors to preliminarily screen potential active ingredients from . Considering the prediction outputs and the quantity of existing compounds in our laboratory, 13 compounds were chosen to carry out the enzyme inhibitory experiments and 4 compounds with BACE1/MAO-B dual inhibitory activity were determined. Finally, the molecular docking was applied to verify the prediction results and enzyme inhibitory experiments. Based on these study and validation processes, we explored a new strategy to improve the efficiency of active ingredients screening based on trace amount of natural product and numbers of targets and found some multi-target compounds with biological activity for the development of novel drugs for AD treatment.
阿尔茨海默病(AD)是一种进行性且不可逆的神经退行性疾病,被认为是痴呆症最常见的病因。它不仅对学习和记忆障碍有较大影响,还对社会和经济产生影响。目前,AD治疗主要使用单靶点药物,但AD的复杂性和多种病因使得这些药物难以获得理想的治疗效果。因此,选择多靶点药物将是AD治疗中一种潜在的有效策略。为了从植物中寻找用于AD治疗的多靶点活性成分,我们首先通过莫里斯水迷宫试验探究了[植物名称]总提取物(TE)对AD小鼠行为的影响,发现TE对AD小鼠的学习和记忆功能有显著改善。然后,基于随机森林(RF)和不同描述符建立了与AD相关蛋白的多靶点构效关系模型,以从[植物名称]中初步筛选潜在的活性成分。考虑到预测结果和我们实验室现有化合物的数量,选择了13种化合物进行酶抑制实验,确定了4种具有β-分泌酶1/单胺氧化酶B双重抑制活性的化合物。最后,应用分子对接来验证预测结果和酶抑制实验。基于这些研究和验证过程,我们探索了一种基于微量天然产物和靶点数量来提高活性成分筛选效率的新策略,并发现了一些具有生物活性的多靶点化合物,用于开发AD治疗的新型药物。