Kumar Pradeep, Pillay Viness, Choonara Yahya E, Modi Girish, Naidoo Dinesh, du Toit Lisa C
Department of Pharmacy and Pharmacology, University of the Witwatersrand, 7 York Road, Parktown, 2193, Johannesburg, South Africa; E-Mails:
Int J Mol Sci. 2011 Jan 19;12(1):694-724. doi: 10.3390/ijms12010694.
The aggregation of the amyloid-β-peptide (AβP) into well-ordered fibrils has been considered as the key pathological marker of Alzheimer's disease. Molecular attributes related to the specific binding interactions, covalently and non-covalently, of a library of compounds targeting of conformational scaffolds were computed employing static lattice atomistic simulations and array constructions. A combinatorial approach using isobolographic analysis was stochastically modeled employing Artificial Neural Networks and a Design of Experiments approach, namely an orthogonal Face-Centered Central Composite Design for small molecules, such as curcumin and glycosylated nornicotine exhibiting concentration-dependent behavior on modulating AβP aggregation and oligomerization. This work provides a mathematical and in silico approach that constitutes a new frontier in providing neuroscientists with a template for in vitro and in vivo experimentation. In future this could potentially allow neuroscientists to adopt this in silico approach for the development of novel therapeutic interventions in the neuroprotection and neurotherapy of Alzheimer's disease. In addition, the neuroprotective entities identified in this study may also be valuable in this regard.
淀粉样β肽（AβP）聚集成有序的纤维被认为是阿尔茨海默病的关键病理标志物。利用静态晶格原子模拟和阵列构建，计算了与靶向构象支架的化合物库的特异性结合相互作用（共价和非共价）相关的分子属性。采用人工神经网络和实验设计方法（即针对小分子的正交面心中心复合设计，如姜黄素和糖基化去甲烟碱，它们在调节AβP聚集和寡聚方面表现出浓度依赖性行为），对使用等效线图分析的组合方法进行了随机建模。这项工作提供了一种数学和计算机模拟方法，为神经科学家提供了体外和体内实验的模板，构成了一个新的前沿领域。未来，这可能会使神经科学家采用这种计算机模拟方法来开发针对阿尔茨海默病神经保护和神经治疗的新型治疗干预措施。此外，本研究中鉴定出的神经保护实体在这方面可能也很有价值。
