CORE--QSAR/BIOINFORMATICS

核心--QSAR/生物信息学

• 批准号: 6300631
• 负责人: OREST T MACINA
• 金额: $ 19.38万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-03-01 至 2001-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6300631
• 关键词: antineoplastics; biomedical facility; cell line; chemical information system; chemical registry /resource; chemical structure function; chemical synthesis; computer data analysis; data management; drug design /synthesis /production; phosphoprotein phosphatase; tubulin

This is Core B of the Program "Combinatorial Approaches for Novel Anti- cancer Agents," a multidisciplinary effort to employ chemical diversity, high throughput and smart assays to anti-tumor drug discovery. In this Core, computational chemistry and chemical data base management will be used to analyze the structure-activity relationships of synthetic combinatorial libraries of phosphatase inhibitors and anti-tubulin compounds, leading to both mechanistic and structural insights for the optimization of anti-cancer chemotherapeutic activity. This strategy will allow for the identification and comparison of the structural and physicochemical features required for in vitro cell-free biochemical, in vitro tumor cell line, and in vivo anti-tumor activity. During the Program, Core B will build and utilize hierarchical SAR/QSAR models pertaining to the individual molecular targets, anti-proliferative activity towards cancer cell lines, and activity towards solid tumors. These activities will be optimized in order to discover selective, highly efficacious, pre-clinical chemotherapeutic agents with anti-tumor activity.

这是“新型抗病毒组合方法”计划的核心 B 癌症代理”，利用化学多样性的多学科努力， 抗肿瘤药物发现的高通量和智能分析。在这个 核心、计算化学和化学数据库管理将是 用于分析合成物的构效关系 磷酸酶抑制剂和抗微管蛋白的组合文库 化合物，从而获得机械和结构方面的见解 优化抗癌化疗活性。这一战略将 允许识别和比较结构和 体外无细胞生化所需的理化特征， 体外肿瘤细胞系和体内抗肿瘤活性。期间 计划，核心 B 将构建和利用分层 SAR/QSAR 模型 与单个分子靶点有关，抗增殖 对癌细胞系的活性和对实体瘤的活性。 这些活动将得到优化，以便发现有选择性的、高度 有效的临床前抗肿瘤化疗药物 活动。