CORE--QSAR/BIOINFORMATICS

核心--QSAR/生物信息学

• 批准号: 6103486
• 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: 1999
• 资助国家: 美国
• 起止时间: 1999-03-01 至 2000-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6103486
• 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.

这是程序的核心B 癌症代理人，“采用化学多样性的多学科努力， 高通量和智能测定法对抗肿瘤的药物发现。在这个 核心，计算化学和化学数据库管理将是 用于分析合成的结构活性关系 磷酸酶抑制剂和抗微管蛋白的组合文库 化合物，导致机械和结构见解 抗癌化学治疗活性的优化。这个策略将 允许识别和比较结构和 体外无细胞生化所需的物理化学特征 体外肿瘤细胞系和体内抗肿瘤活性。在 程序，核心B将构建和利用层次结构SAR/QSAR模型 与单个分子靶标有关，抗增殖性 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，以发现选择性，高度 抗肿瘤的有效，临床前化学治疗剂 活动。