In Vivo Drug Discovery From Compound Mixtures

从化合物混合物中发现体内药物

• 批准号: 7081426
• 负责人: Emer Leahy
• 金额: $ 23.59万
• 依托单位: PSYCHOGENICS, INC.
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2007-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7081426
• 关键词: antipsychotic agents; behavior test; combinatorial chemistry; dosage; drug discovery /isolation; drug receptors; high throughput technology; laboratory mouse; molecular site; psychopharmacology; tranquilizer

DESCRIPTION (PROVIDED BY APPLICANT): Neuropsychiatric disorders are complex and involve multiple neuronal circuits. It is not surprising therefore that many of the most efficacious drugs in psychiatry have exceedingly complex pharmacology and were often discovered by observing how an animal's and human's behavior were altered in response to these drugs. For this reason, we believe that, to the extent possible, animal's behavior-based drug discovery and lead optimization should provide novel avenues to the treatment of psychiatric disorders. The aim of this proposal is a large-scale, automated in vivo screening of libraries of compounds to discover novel compounds for the treatment of psychiatric disorders. We will combine two novel technologies that have the potential to substantially change how drug discovery is carried out. PsychoGenics will utilize its proprietary, high throughput broad-based behavioral assay for mice known as SmartCube(tm) to screen and optimize compounds selected from proprietary collections of compound mixtures provided by Mixture Sciences. SmartCube is an automated test for mice that allows us to determine the antidepressant, anxiolytic and antipsychotic potential of a test compound in only one test of 90 minutes. Compounds will be initially administered as mixture instead of single chemical entity and screen for their behavioral-activity. Two mixtures containing 64,0000 thousands compounds each will be tested. These compounds will be related to a common pharmacophore, which will imply a deconvolution process to define the active compounds. Mixture Sciences' algorithms will be utilized to identify active individual compounds from the mixtures that exhibit behavioral activity in mice and we will synthesize and test these individual compounds to confirm their level of activity in vivo. At that stage, active compounds will be further tested in more traditional behavioral assays to confirm that they are true positive and to further evaluate their level of activity and spectrum of therapeutic application. We will generate data for approximately 128,000 compounds and reduce the screening time from many years to several months. From this process we hope to select at least one compound for which further pre-clinical evaluation and likely clinical development will be warranted.

描述（由申请人提供）：神经精神疾病很复杂，涉及多个神经元回路。因此，毫不奇怪，精神病学中许多最有效的药物具有极其复杂的药理学，并且通常是通过观察动物和人类的行为如何响应这些药物而改变而发现的。因此，我们相信，在可能的范围内，基于动物行为的药物发现和先导化合物优化应该为精神疾病的治疗提供新的途径。 该提案的目的是对化合物库进行大规模、自动化的体内筛选，以发现用于治疗精神疾病的新化合物。我们将结合两种新技术，它们有可能大大改变药物发现的方式。 PsychoGenics 将利用其专有的、高通量、广泛的小鼠行为分析（称为 SmartCube(tm)）来筛选和优化从 Mixture Sciences 提供的专有化合物混合物集合中选出的化合物。 SmartCube 是一种针对小鼠的自动化测试，使我们能够在 90 分钟的一次测试中确定测试化合物的抗抑郁、抗焦虑和抗精神病潜力。化合物最初将作为混合物而不是单一化学实体施用，并筛选其行为活性。将测试两种混合物，每种混合物含有 64,000 万种化合物。这些化合物将与共同的药效团相关，这意味着需要进行反卷积过程来定义活性化合物。 Mixture Sciences 的算法将用于从混合物中识别出在小鼠中表现出行为活性的活性单个化合物，我们将合成和测试这些单个化合物以确认它们在体内的活性水平。在此阶段，活性化合物将在更传统的行为测定中进行进一步测试，以确认它们是真正的阳性，并进一步评估它们的活性水平和治疗应用范围。我们将生成大约 128,000 种化合物的数据，并将筛选时间从多年缩短到几个月。从这个过程中，我们希望选择至少一种需要进一步临床前评估和可能的临床开发的化合物。