Investigation of mechanism of action of drug induced agranulocytosis.

描述（由申请人提供）：亨廷顿氏病（HD）是一种毁灭性的神经退行性疾病，由亨廷顿蛋白（Htt）中的多聚谷氨酰胺束扩展引起，导致其聚集成富含β折叠的原纤维。有证据表明，Htt的17个氨基酸的头部片段（N17）强烈调节其聚集。本研究的目的之一是通过分子动力学模拟预测N17的结构和在低聚反应中的作用，并进行实验验证。另一个目标是利用这种结构信息和实验数据来设计Htt聚集的抑制剂。对Htt蛋白聚集的早期步骤的更好的结构理解对于设计亨廷顿氏病的治疗方法将是非常宝贵的。具体目标是：1.研究N17头部片段在亨廷顿蛋白聚集中的结构作用。!以前的MD模拟孤立的N17头段表明，它是高度螺旋，并采用两个高度填充的构象组成的一个和两个两亲性螺旋。我们将：a.使用Markov状态模型在Folding@home上进行N17-polyQ聚集的分子动力学模拟。我们将研究我们的假设，即埋葬多个N17疏水表面启动聚集的polyQ道正确定位它们相对于彼此。基于模拟，将提出N17中预期抑制Htt聚集的突变。B.通过与斯坦福大学的朱迪思·弗里德曼实验室的合作，计算预测的N17突变将破坏聚集，并将得到实验验证。2.通过模拟N17头片段的结构，计算设计和模拟肽聚集抑制剂，并通过实验验证有前途的抑制肽。!我将设计针对Htt聚集的“钉合肽”抑制剂，特别是通过调节N17在寡聚化过程中的假设作用。最近由哈佛的Greg Verdine实验室开创的一项技术“钉合肽”，将肽“斯台普斯”成α螺旋构象。我们将：a.使用“钉合肽”来检验关于亨廷顿蛋白寡聚体结构的假设。将设计钉合肽以模拟上述MD模拟中聚集核中N17的拟定螺旋结构，并使用钉合肽重新运行模拟。B.设计亨廷顿蛋白聚集的钉合肽抑制剂，通过并入实验显示阻断聚集的N17突变，同时保持N17区域之间的结合界面。C. Frydman实验室将采购有前景的肽，并在体外和体内进行实验测试。“钉合肽”在抑制Htt聚集中具有作为“纳米医学治疗剂”的潜在应用。 公共卫生相关性：说明：！!亨廷顿氏病是一种由亨廷顿蛋白的错误折叠和聚集引起的破坏性神经退行性疾病。有证据表明，亨廷顿蛋白的前17个氨基酸（N17）强烈刺激其聚集。本研究的目标是通过计算预测N17<s在该聚集过程中的结构和作用，并通过实验验证，然后利用这些结构信息和实验数据来设计和测试亨廷顿聚集抑制剂。

DESCRIPTION (provided by applicant): Huntington<s Disease (HD) is a devastating neurodegenerative disease caused by an expanded polyglutamine tract in the huntingtin (Htt) protein, leading to its aggregation into beta-sheet-rich fibrils. Evidence suggests the 17 amino acid headpiece (N17) of Htt strongly modulates its aggregation. One goal of this research is to predict N17;s structure and role in oligomerization via molecular dynamics simulations, with experimental verification. Another goal is to leverage this structural information and experimental data to design inhibitors of Htt aggregation. Better structural understanding of the early steps of aggregation of the Htt protein would be invaluable for designing therapeutics for Huntington<s Disease. The specific aims are: 1. To investigate the structural role of the N17 headpiece in huntingtin aggregation. ! Previous MD simulations of the isolated N17 headpiece suggest that it is highly helical, and adopts two highly populated conformations consisting of one and two amphipathic helices. We will: a. Perform molecular dynamics simulations of N17-polyQ aggregation on Folding@home using Markov state models. We will investigate our hypothesis that burial of multiple N17 hydrophobic surfaces initiates aggregation of the polyQ tracts by positioning them correctly relative to each other. Based on the simulations, mutations in N17 will be proposed that would be expected to inhibit Htt aggregation. b. N17 mutations computationally predicted to disrupt aggregation will be experimentally verified, via a collaboration with Judith Frydman<s lab at Stanford. 2. To computationally design and simulate peptide inhibitors of aggregation by mimicking the structure adopted by the N17 headpiece, and verify promising inhibitory peptides experimentally. ! I will design "stapled peptide" inhibitors against Htt aggregation, specifically by modulating N17<s hypothesized role in the oligomerization process. "Stapled peptides", a recent technique pioneered by Greg Verdine<s lab at Harvard, "staples" peptides into an alpha-helical conformation. We will: a. Use "stapled peptides" to test hypotheses about the huntingtin oligomeric structure. Stapled peptides will be designed to mimic the proposed helical structure(s) of N17 in the aggregation nucleus in the MD simulations above, and simulations will be re-run with the stapled peptides. b. Design stapled peptide inhibitors of huntingtin aggregation, by incorporating N17 mutations shown experimentally to block aggregation, while maintaining the binding interface between N17 regions. c. Promising peptides will be procured and experimentally tested both in vitro and in vivo by the Frydman Lab. "Stapled peptides" have potential applications as "nanomedicine therapeutics" in inhibiting Htt aggregation. PUBLIC HEALTH RELEVANCE: Lay description:! ! Huntington<s Disease is a devastating neurodegenerative disease caused by misfolding and aggregation of the huntingtin protein. Evidence suggests the first 17 amino acids (N17) of the huntingtin protein strongly stimulate its aggregation. The goals of this research are to predict N17<s structure and role in this aggregation process computationally, with experimental verification, and then to leverage this structural information and experimental data to design and test inhibitors of huntingtin aggregation.