Chemical Fingerprinting

描述（由申请人提供）：目前化合物发现方法存在三个问题。首先，如果已知化合物靶点，合理的化合物设计可以用于治疗性地修饰现有化合物。然而，对于大多数疾病，人们对其潜在的生物学知之甚少。其次，化合物的选择也基于它们抑制或逆转特定疾病相关表型的能力（例如蛋白质蛋白水解、聚集）。然而，为化合物发育预先选择这些表型可能是一种猜测，因为可观察到的表型通常不代表主要缺陷或可能是疾病的后果。第三，组合库筛选不依赖于知道复合目标。然而，这些传统的筛查本质上是经验性的，筛查需要数年时间，往往没有成功。即使在传统的筛选中发现了化合物先导物，实际的化合物目标通常也是未知的。因此，在随后的迭代中增加导联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。在这个建议中，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。表达疾病的细胞与20,000个sirna一起孵育，以敲除所有哺乳动物基因。被敲除的基因分为两类。那些对毒性没有影响的基因和那些失去表达mhttt细胞的基因。失去能增强细胞存活的一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是毒性抑制剂，因为它们去除与毒性相关的基因通路。如果化合物也作为mhtt毒性抑制剂，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。基因指纹可以“翻译”为蛋白质相互作用，以预测抑制剂活性的实际目标，并且在疾病模型中测试途径和目标。作为内部控制，指纹识别方法（目标2）与常规筛选一起进行测试，以选择已知致病蛋白的抑制剂（目标1）。通过常规方法选择的抑制剂预计与从全局筛选中确定的抑制剂重叠。

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.