MODEL SYSTEMS FOR BETA AMYLOID FORMATION AND INHIBITION

该研究的目的是开发新的模型 用于研究β-淀粉样结构的系统，以及 确定新的先导化合物的战略 阿尔茨海默病的潜在治疗方法老年痴呆症是一 进行性神经退行性疾病影响了大约一半 85岁以上的老年人。杰出的神经病理学家 阿尔茨海默病的特征是淀粉样纤维沉积在 大脑是由大脑中的 淀粉样β蛋白（Abeta）。创新的药理学方法 尚未被广泛研究用于治疗 阿尔茨海默氏症是开发化合物，抑制形成 淀粉样纤维研究不溶于水的 β-折叠基序如Abeta强调了水溶性的需要。 可溶的、模拟β-折叠大分子复合物。最近， 基于聚丙氨酸的肽（Ac-KYAn K-NH 2，n大于或等于11） 由主要研究者设计， “天然”单体α-螺旋构象状态转化为极端 稳定、水溶性、大分子β-折叠片 宏观结构特别地，发现Ac-KYA 13 K-NH 2形成Abeta-。 像纤维一样这些基于聚丙氨酸的 肽的A β样结构，和潜在的神经毒性， 模型肽将被进一步研究。模型系统将 用于β折叠抑制剂的鉴定 宏观组织形成这将通过筛选来实现 合成组合文库（SCL）由数千个 数以百万计的杂环化合物、肽模拟物或肽。的 SCL方法允许快速鉴定高活性化合物 从单个化合物的大池中。在初始步骤中，测定 将被开发，这将允许大量的样本， 同时检测。两种生物物理技术（例如，大小 排阻色谱法、圆二色谱法和荧光法）， 比色技术（例如，MTT还原试验）进行评价。 然后将鉴定出的抑制性化合物的活性 相对于A β的短导数（即，beta1-39）， 以确认该方法的实用性和通用性。的结果 预计这些研究将具有重要价值， 预防β-淀粉样蛋白形成的策略。

The objective of the proposed research is to develop novel model systems for the study of beta-amyloid liked structures, as well as strategies for the identification of new lead compounds for the potential treatment of Alzheimer's disease. Alzheimer's disease is a progressive neurodegenerative disorder that affects approximately half of the elderly population over age 85. The preeminent neuropathological feature of Alzheimer's disease is the deposition of amyloid fibrils in the brain that result from the self-aggregative polymerization of the amyloid beta-protein (Abeta). An innovative pharmacological approach that has not yet been studied extensively for the treatment of Alzheimer's disease is to develop compounds that inhibit the formation of amyloid fibrils. The difficulties inherent to the study of insoluble beta-sheet motifs such as Abeta underscore the need for aqueous soluble, model beta-sheet macromolecular complexes. Recently, polyalanine-based peptides (Ac-KYAn K-NH2, n greater or equal to 11) have been designed by the Principal Investigator that change from "native" monomeric alpha-helical conformational states into extremely stable, aqueous soluble, macromolecular beta-pleated-sheet macrostructures. In particular, Ac-KYA13K-NH2 was found to form Abeta- like fibrils. The conformational resemblance of these polyalanine-based peptides to Abeta-like structures, and the potential neurotoxicity of the model peptides will be further studied. The model systems will then be used for the identification of inhibitors of beta-sheet macrostructure formation. This will be accomplished by screening synthetic combinatorial libraries (SCLs) made up of thousands to millions of heterocyclic compounds, peptidomimetics, or peptides. The SCL approach allows the rapid identification of highly active compounds from large pools of individual compounds. In an initial step, an assay will be developed that will allow large numbers of samples to be assayed simultaneously. Both biophysical techniques (e.g., size exclusion chromatography, circular dichroism, and fluorescence) and colorimetric techniques (e.g., MTT reduction assay) will be evaluated. The activity of the identified inhibitory compounds will then be determined against short derivatives of Abeta (i.e., beta1-39) in order to confirm the utility and generality of the approach. The results of these studies are anticipated to have significant value as a potential strategy for the prevention of beta-amyloid formation.