Chemical Fingerprinting

描述（由申请人提供）：三个问题困扰着当前的化合物发现方法。首先，如果化合物靶标已知，则可以在治疗上使用合理的化合物设计来修饰现有的化合物。然而，对于大多数疾病，对潜在的生物学几乎没有深入的了解。第二，化合物的选择也是基于其抑制或逆转特定疾病相关表型（例如蛋白质水解、聚集）的能力。然而，预先选择这些表型用于化合物开发可能是猜测，因为可观察到的表型通常不代表原发性缺陷或可能是疾病的后果。第三，组合文库筛选不依赖于知道化合物靶标。然而，这些传统的筛选本质上是经验性的，筛选需要数年时间，往往没有成功。即使在传统筛选中识别出复合先导化合物，实际的复合靶点通常也是未知的。因此，在后续迭代中增加先导化合物的效力和特异性可能是一个困难和长期的过程，并且在历史上并不成功。在这个提议中，我们开发，测试和应用一种新的“智能”方法，允许以系统和定向的方式发现。这种方法被称为指纹识别。该方法是通用的，可以应用于任何疾病基因，但在本提案中，我们将该方法应用于亨廷顿病。将表达疾病的细胞与20，000个siRNA孵育以敲低所有哺乳动物基因。被敲除的基因分为两类。那些对毒性没有影响的基因，以及那些丢失了能增强mht表达细胞存活的基因。一组基因的缺失增强了细胞的存活，这组基因被称为基因指纹，并定义了与毒性相关的遗传途径。指纹siRNA是毒性的抑制剂，因为它们去除了与毒性相关的基因通路。如果化合物也作为mhtt毒性的抑制剂，它们应该作为siRNA。因此，由siRNA定义的基因指纹应该与“好的”化学抑制剂的指纹重叠。遗传指纹可以“翻译”成蛋白质相互作用，以预测抑制剂活性的实际靶点，并在疾病模型中测试这些途径和靶点。作为内部对照，将指纹法（Aim 2）与常规筛选一起测试，以选择已知致病蛋白的抑制剂（Aim 1）。预测通过常规方法选择的抑制剂与从全局筛选鉴定的那些重叠。

DESCRIPTION (provided by applicant): Three problems plague current methods of compound discovery. First, rational compound design can be used therapeutically to modify existing compounds if the compound target is known. However, for most diseases, there is little in depth understanding of the underlying biology. Second, compounds have also been selected based on their ability to inhibit or reverse specific disease-related phenotypes (e.g. protein proteolysis, aggregation). However, pre-selecting these phenotypes for compound development can be guesswork, as observable phenotypes do not often represent the primary defect or may be consequences of disease. Third, combinatorial library screens do not depend on knowing the compound target. However, these traditional screens are empirical in nature, and screening takes years, often without success. Even if a compound lead is identified in traditional screens, the actual compound target is typically not known. Therefore, increasing the potency and specificity of a lead in subsequent iterations can be a difficult and long-term process, and has not historically been successful. In this proposal, we develop, test and apply a new "intelligent" methodology that allows discovery in a systematic and directed manner. The method is called fingerprinting. The method is general and can apply to any disease gene, but in this proposal, we apply the methodology to Huntington's Disease. Disease-expressing cells are incubated with 20,000 siRNAs to knock-down all mammalian genes. Knocked down genes fall into two classes. Those that have no effect on toxicity and those genes whose loss enhance survival of mhtt-expressing cells. The set of genes whose loss enhances cell survival is called the gene fingerprint and defines genetic pathways associated with toxicity. The fingerprint siRNAs are inhibitors of toxicity since they remove gene pathways relevant to toxicity. If compounds also act as inhibitors of mhtt toxicity, they should act as an siRNA. Thus, the gene fingerprint defined by the siRNA should overlap with the fingerprint of a "good" chemical inhibitor. The genetic fingerprint can be "translated" into protein interactions to predict the actual targets of the inhibitor activity, and the pathways and targets are tested in models for disease. As an internal control, the fingerprinting methodology (Aim 2) is tested together with conventional screens to select for inhibitors to known disease- causing proteins (Aim 1). Inhibitors selected by the conventional methods are predicted to overlap with those identified from the global screen.