COMBINATORIAL SYNTHESIS OF ANTICANCER LIBRARIES

抗癌文库的组合合成

• 批准号: 6928830
• 负责人: Peter Wipf
• 金额: $ 18.85万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-01 至 2010-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6928830
• 关键词: antimitotics; antineoplastics; biological products; combinatorial chemistry; drug discovery /isolation; peptide analog; phosphatase inhibitor; phosphates

The overall goal of the combinatorial chemistry section (Project 1) of this Program Project grant application is the demonstration of new strategies for mechanism-based anticancer drug discovery using solid-phase and solution-phase combinatorial synthesis as well as phase-switching methods. Lead structure identification is mainly derived from natural products and target-based array design. High quality, defined-compound libraries will provide the broad structure-activity relationship necessary for rational lead optimization. Specifically, we have four major strategic goals: 1. to develop solution-phase and solid-phase parallel synthesis protocols for the preparation of a focused library of ca. 200 peptide mimetics based on rational design and the co-crystal of human Cdc25B and a peptide ligand, 2. the design of novel phosphate group mimics with the goal of identifying new scaffolds for highly selective protein phosphatase inhibitors, 3. to prepare a library of ca. 500 analogs of the femtomolar antimitotic agent tubulysin A with the goal to develop selective anticancer agents that target microtubule assembly, 4. to explore new synthetic methods for the preparation and analysis of novel dynamic libraries for phosphatase inhibition and the discovery of new classes of antiproliferative agents. The proposed program represents a multi-dimensional effort to improve current methodologies for the combinatorial synthesis of organic molecules, establish new strategies for the use of natural products as lead structures for drug discovery, and identify novel mechanism-based anticancer agents.

该计划项目授予应用的组合化学部分（项目1）的总体目标是使用固相和溶液相结合合成以及相位开关方法的基于机制的抗癌药物发现的新策略。铅结构识别主要来自天然产品和基于目标的阵列设计。高质量的定义化合物库将提供合理铅优化所需的广泛结构活性关系。具体而言，我们有四个主要的战略目标：1。开发解决方案相和固相并行合成协议，以制备CA的重点库。 200基于理性设计和人类Cdc25b和肽配体的共晶的肽模拟物，2。新型磷酸盐群模拟的设计，目的是识别高度选择性蛋白质磷酸酶抑制剂的新脚手架，3。制备CA的库。 500个具有靶向微管组装的选择性抗癌剂的femtolol抗抗毒剂小管胞蛋白A的类似物，4。探索新的合成方法，以制备和分析新型动力学库的新型合成方法 磷酸酶抑制和发现新类抗增殖剂的发现。提出的计划代表了一项多维的努力，以改善当前方法论 有机分子的组合合成，为使用天然产物作为药物发现的铅结构建立新的策略，并确定基于机制的新型抗癌剂。