对结构-活动关系转移的模拟序列的上下文依赖相似性分析,基于自然语言处理的概念
Atsushi Yoshimori1, Jürgen Bajorath2,3
1Institute for Theoretical Medicine, Inc., 26-1 Muraoka-Higashi 2-chome, Fujisawa, Kanagawa, 251-0012, Japan.
Journal of cheminformatics
|January 15, 2025
概括
本研究引入了一种新的计算方法,通过对比模拟序列来识别结构活动关系 (SAR) 转移事件. 该方法使用上下文依赖的相似性评估,这是化学信息学的新概念,用于增强的替代物分析.
科学领域:
- 药用化学 医学化学
- 计算化学的计算化学
- 化学信息学 化学信息学
背景情况:
- 模拟序列 (AS) 对于药物化学中的结构-活性关系 (SAR) 信息至关重要.
- 识别跨目标的SAR转移事件对于药物发现至关重要.
研究的目的:
- 开发一种计算方法,以系统地搜索和对准具有SAR传输潜力的模拟序列.
- 引入一种新的取决于上下文的替代剂相似性评估.
主要方法:
- 结合了模拟序列对齐算法与上下文依赖的相似性评估.
- 利用了从自然语言处理中适应的向量嵌入,以获得替代物相似性.
- 开发了一种方法来解释替代物相似性,识别生物异构体,并捕获替代物-属性关系.
主要成果:
- 生成精确的模拟系列对齐.
- 成功识别了SAR传输事件.
- 证明了替代品相似性和财产关系的全面会计.
结论:
- 报告的计算方法使SAR传输序列的系统识别成为可能.
- 情境依赖相似性评估是计算药物化学和其他应用的新和有价值的概念.
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