从图书馆到景观:药物重用中复合图书馆的整合性注释工作流程
Jeanette Reinshagen1, Brinton Seashore-Ludlow2,3, Yojana Gadiya1,4
1Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Discovery Research ScreeningPort, Schnackenburgallee 114, 22525 Hamburg, Germany.
Database : the journal of biological databases and curation
|December 9, 2025
概括
自动化管道简化了化学和生物活性数据的整合,用于药物发现和重新利用. 这一框架提高了数据的可访问性和分析,以确定新的治疗候选药物.
科学领域:
- 计算化学是一种计算化学.
- 生物信息学是一种生物信息学.
- 药物发现 药物发现
背景情况:
- 对化学和生物活性数据的有效访问对于药物发现和重新利用至关重要.
- 像ChEMBL和PubChem这样的公共存储库包含有价值的,但往往不一致的数据.
研究的目的:
- 开发自动化管道,从公共存储库中提取和整合化学和生物活性数据.
- 创建交互式仪表板,用于对药物重用数据进行多层分析和可视化.
主要方法:
- 开发了基于KNIME和Python的注释管道,用于自动数据提取和集成.
- 使用ChEMBL和PubChem作为数据源,支持用户提供的复合库.
- 使用 Specs 重用集合 (>5000个化合物) 的协调子集验证框架.
- 创建了交互式仪表板,用于可视化化学性质,生物活性概况和关系数据.
主要成果:
- 管道成功实现了化学和生物活性数据的收集和协调的自动化.
- 该框架允许可重复的工作流来整合来自异质来源的数据.
- 规格子集分析揭示了批准和临床药物的代表性化学支架.
- 交互式仪表板促进了对药物重新用途至关重要的多层次分析.
结论:
- 开发的框架简化了用于药物重新定位和发现的数据收集和分析.
- 该框架具有多功能性,适用于更广泛的药物发现工作.
- 规格集合是识别药物重用候选人的宝贵资源.
- 公共可用的协议和开放式的仪表板促进了更广泛的采用和协作.
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