Engineered Tissue Based Phenotypic Screening of Mixture based Libraries

 描述（由申请人提供）：我们建议证明我们的工程组织为基础的药物筛选方法和系统组织的混合物为基础的化学库相结合的实力。这种方法可能成为开发复杂疾病（如心脏纤维化）治疗方法的最终工具，最初没有已知的药物靶点。心力衰竭是65岁以上美国人住院治疗的最常见原因。射血分数保留性心力衰竭（HFPEF）在美国老年人群中日益流行。从成纤维细胞、内皮细胞和非肌细胞分化而来的活化成纤维细胞（即肌成纤维细胞）的存在是HFPEF心肌的标志，并且它们促使心肌进展HFPEF。我们建立了一个人类心脏纤维化的疾病模型，使用含有肌纤维母细胞的工程组织构建物，重现了纤维化心肌的结缔组织。使用我们的表型筛选系统，我们在分析了42个支架的支架排序库（每个支架样品包含化合物的混合物）后鉴定了TPI-2049（17，340种化合物混合物），这相当于筛选了> 3000万种化合物。虽然我们的最终目标是确定一种治疗心脏纤维化的新药，但拟议的I期项目将专注于对化学支架中的化合物混合物进行二次样品筛选，并确定50种单独的化合物，以挑选15种命中化合物进行II期研究的测试和优化。在一项平行研究中，我们将分析TPI-2049在纤维化缓解表型中的作用机制，并通过进行无亲和力靶点鉴定方法，用单个命中化合物稳定靶分子，鉴定潜在的药物靶点。将基于组织工程的药物发现系统和支架排序库与位置扫描技术相结合的成功示范将扩展到其他年龄相关疾病（如骨关节炎）的药物发现项目。

 DESCRIPTION (provided by applicant): We propose to demonstrate the strength of combining our engineered tissue-based drug screening approach and a systematically organized mixture-based chemical library. This approach could become an ultimate tool to develop treatments for complex diseases, such as cardiac fibrosis, without known drug targets initially. Heart failure is the most common cause of hospitalization among Americans 65 or older. The heart failure with preserved ejection fraction (HFPEF) is becoming an epidemic among increasing population of aging Americans. Existence of activated fibroblasts, i.e. myofibroblasts, differentiated from fibroblasts, endothelial cells, and non-muscle cell is a hallmark of myocardium with HFPEF, and they stiffen myocardium to progress HFPEF. We developed a disease model for the human cardiac fibrosis using myofibroblast-containing engineered tissue constructs that recapitulate connective tissues of myocardium with fibrosis. Using our phenotypic screening system, we identified TPI-2049 (17,340 compound mixture) after analyzing a 42-scaffold scaffold ranking library (each scaffold sample contains mixtures of compounds), which is equivalent to screening >30 million compounds. While our final goal is to identify a novel drug for treating cardiac fibrosis, the proposed Phase I project will focus on performing a secondary sample screening of a compound mixture in the chemical scaffolds and identifying 50 individual compounds to pick 15 hit compounds to be tested and optimized in Phase II study. In a parallel study, we will analyze mechanisms of action of TPI-2049 in fibrosis relieving phenotypes and identify potential drug targets by performing affinity-free target identification method, stabilizing target molecules with individual hit compounds. Successful demonstration of combing engineered tissue based drug discovery system and scaffold ranking library with positional scanning technology will be extended to other drug discovery projects for age-related dieses such as osteoarthritis.