Combinatorial Chemical Libraries and Cancer Targets

组合化学库和癌症靶标

• 批准号: 6990226
• 负责人: PETER K VOGT
• 金额: $ 17.1万
• 依托单位: SCRIPPS RESEARCH INSTITUTE, THE
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-03-12 至 2009-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6990226
• 关键词: SCID mouse; antineoplastics; athymic mouse; cadherins; cell proliferation; combinatorial chemistry; dimer; drug discovery /isolation; genetic transcription; intermolecular interaction; neoplastic cell; protein protein interaction; small molecule; transcription factor

This project proposes the identification, optimization, and characterization of small molecules that affect protein-protein and protein-DNA interactions in the Myc and the beta-catenin-LEF networks. The project also proposes identification and development of anticancer compounds from novel combinatorial chemical libraries. The work is based on discoveries made during the past funding cycle which include the identification of the first small molecule inhibitors of Myc-Max dimerization, inhibitors of LEF-dependent transcription, and compounds that interfere with the growth of cancer cells. The project depends on strong collaboration with the laboratory of Dr. Boger in the area of chemistry and with Dr. Cheresh in the area of animal testing. The following are the specific aims: (1) Identify and characterize small molecules that inhibit Myc-Max dimerization. (2) Identify and characterize small molecules that stabilize interaction of Myc network proteins. (3) Identify and characterize small molecules that specifically inhibit LEF-dependent transcription. (4) Screen primary and analog combinatorial chemical libraries for compounds that are selectively active against cancer cells and characterize these compounds.

该项目提出了小分子的识别、优化和表征， 影响 Myc 和 β-catenin-LEF 网络中蛋白质-蛋白质和蛋白质-DNA 相互作用。 该项目还建议从新型药物中鉴定和开发抗癌化合物 组合化学库。这项工作基于过去资助期间的发现 该周期包括鉴定第一个 Myc-Max 二聚化小分子抑制剂、LEF 依赖性转录抑制剂以及干扰癌细胞生长的化合物。该项目依赖于与 Boger 博士实验室在化学领域以及与 Cheresh 博士在动物测试领域的密切合作。 具体目标如下： (1) 识别和表征抑制 Myc-Max 二聚化的小分子。 (2) 识别和表征稳定 Myc 网络蛋白相互作用的小分子。 (3) 鉴定并表征特异性抑制 LEF 依赖性转录的小分子。 (4) 筛选对癌细胞具有选择性活性的化合物的初级和模拟组合化学库，并表征这些化合物。