药物发现中的化学库的设计和多样性分析
Dionisio A Olmedo1,2, Armando A Durant-Archibold3,4, José Luis López-Pérez5,6
1Centro de Investigaciones Farmacognósticas de la Flora Panameña (CIFLORPAN), Facultad de Farmacia, Universidad de Panamá, Ciudad de Panamá, Apartado, 0824-00178, Panamá.
Combinatorial chemistry & high throughput screening
|July 6, 2023
概括
药物发现依赖于化学库和计算方法. 将人工智能与这些工具相结合,正在加速新药的开发和批准.
科学领域:
- 计算化学和药物发现.
- 生物信息学和化学信息学.
- 药学研究中的人工智能.
背景情况:
- 化学图书馆和化合物数据是学术界和工业界药物发现的关键投入.
- 复合图书馆的设计,信息内容和结构表示对研究成果产生重大影响.
- 关键的研究领域包括化学信息学,食品信息学,in silico药理动力学,计算毒理学,生物信息学和分子建模.
研究的目的:
- 突出化学信息和结构表示在药物发现中的基本作用.
- 讨论计算工具和人工智能在现代药品开发中的整合.
- 预测这些进展对药物批准率的未来影响.
主要方法:
- 利用化学库和复合数据集进行计算研究.
- 应用化学信息学,生物信息学和分子建模技术.
- 整合人工智能方法与计算药物发现工具.
主要成果:
- 计算方法为药物候选人优化产生"命中".
- 人工智能的整合正在推动药物发现和开发的增长.
- 预计这些进展将增加监管机构批准的药物数量.
结论:
- 化学图书馆的战略设计和表示对于有效的药物发现至关重要.
- 计算方法和人工智能之间的协同作用正在彻底改变制药研发.
- 预计将加速药物开发管道,导致更多批准的治疗方法.
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