Rapid Selection and Evaluation of Cyclic Peptides in Parkinson's Disease Models

帕金森病模型中环肽的快速筛选和评价

• 批准号: 7340583
• 负责人: Susan L. Lindquist
• 金额: $ 25.59万
• 依托单位: WHITEHEAD INSTITUTE FOR BIOMEDICAL RES
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-03-01 至 2010-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7340583
• 关键词: Acute; Affect; Alzheimer' s Disease; American; Animal Model; Attention; Biological; Biological Assay; Biological Models; Cell Death; Cell physiology; Cells; Cellular Structures; Class; Classification; Cyclic Peptides; Cystic Fibrosis; Data; Defect; Disease; Disease Pathway; Disease model; Elderly; Evaluation; Functional disorder; Genes; Genetic; Human; Huntington Disease; Inherited; Intervention; Laboratories; Lead; Libraries; Measures; Methods; Modeling; Molecular; Molecular Weight; Nematoda; Neurodegenerative Disorders; Neurons; Numbers; Organelles; Organism; Parkinson Disease; Pathology; Peptide Library; Pharmaceutical Chemistry; Pharmaceutical Preparations; Procedures; Property; Protein Overexpression; Proteins; Purpose; Rat Nematode; Rattus; Reagent; Score; Screening procedure; Sorting - Cell Movement; Source; Specificity; Speed; Structure-Activity Relationship; System; Techniques; Testing; Therapeutic; Therapeutic Intervention; Time; Toxic effect; Validation; Yeast Model System; Yeasts; alpha synuclein; base; cellular targeting; cost; dalton; dopaminergic neuron; drug development; human disease; in vivo; novel; prevent; protein folding; protein misfolding; restoration; scaffold; size; success; synuclein; synuclein, alpha (non A4 component of amyloid precursor) protein, human; therapeutic protein

DESCRIPTION (provided by applicant): Our laboratory has developed models of human disease in yeast that have uncovered specific cellular defects underlying hereditary and sporadic protein misfolding diseases. We wish to make use of these models for the identification of molecules with therapeutic potential. Cyclic peptides are a proven class of cellular effector that is largely unexplored as a source of molecular therapeutics. Recently, we have developed a novel high throughput method of screening libraries of small, genetically encoded cyclic peptides for molecules that prevent cell death in our yeast models. The genetic encoding of the cyclic peptides allows orders of magnitude more compounds to be screened faster, at lower cost, and with less need for mechanization than with existing procedures. We have applied this method to our model of Parkinson's disease, in which overexpressed human alpha-synuclein aggregates and causes toxicity in yeast. Two promising hits from a library of octamer cyclic peptides have resulted. In this proposal, we seek initially to identify more hits by constructing and screening libraries of cyclic peptides of several different ring sizes. We will characterize the molecular mechanisms of the hits that result by examining their effects on alpha-synuclein aggregation and the structure of cellular organelles, and by determining their protein targets. We will also test representatives of each class of hit in worm and rat models of Parkinson's disease, and begin to optimize their activity through SAR analysis. The rapid selection procedure made possible by genetically encoding cyclic peptides, and the inherent advantages of the cyclic peptide scaffold make this a powerful method for identifying new compounds that can lead to therapeutics for protein misfolding diseases. Parkinson's Disease is a devastating neurodegenerative disorder that affects more than 2% of Americans over the age of 65, making the need acute to accelerate ways of finding drugs to treat it. We have recreated much of the disease in yeast, a very small organism that grows much faster and is much more manipulable than any of the model systems now in use. These significant advantages will allow us to search through many more potential drugs and do it much faster than is now possible, as well as to examine types of potentially promising drugs that so far have received little attention.

描述(由申请人提供)：我们的实验室已经在酵母中开发出人类疾病的模型，发现了遗传性和散发性蛋白质错误折叠疾病背后的特定细胞缺陷。我们希望利用这些模型来鉴定具有治疗潜力的分子。环肽是一类已被证实的细胞效应器，作为分子疗法的来源在很大程度上是未知的。最近，我们开发了一种新的高通量方法，在我们的酵母模型中筛选小的、遗传编码的环肽文库，用于防止细胞死亡的分子。环肽的基因编码使更多的化合物可以更快、更低的成本被筛选出来，而且与现有的程序相比，对机械化的需要更少。我们已经将这种方法应用于我们的帕金森氏病模型，在该模型中，过度表达人类α-突触核蛋白聚集体并在酵母中引起毒性。从八聚体环肽文库中获得了两个有希望的结果。在这个建议中，我们最初寻求通过构建和筛选几个不同环大小的环肽文库来识别更多的命中。我们将通过检测它们对α-突触核蛋白聚集和细胞器结构的影响，并通过确定它们的蛋白质靶标，来表征这些HITS的分子机制。我们还将在帕金森病的蠕虫和大鼠模型中测试每一类HIT的代表性，并开始通过SAR分析优化它们的活性。通过基因编码环肽实现的快速选择程序，以及环肽支架的固有优势，使其成为鉴定新化合物的有效方法，这些化合物可能导致蛋白质错误折叠疾病的治疗。帕金森氏症是一种毁灭性的神经退行性疾病，影响着超过2%的65岁以上的美国人，因此迫切需要加快寻找治疗这种疾病的药物。我们已经在酵母中重现了许多疾病，这是一种非常小的有机体，生长得更快，比现在使用的任何模型系统都更易于操作。这些显著的优势将使我们能够搜索更多的潜在药物，并以比现在可能的速度更快的速度搜索，以及检查到目前为止几乎没有受到关注的潜在有前景的药物的类型。