使用基于图形的变压器模型探索新型芬太尼类比物
Guangle Zhang1, Yuan Zhang2, Ling Li3
1College of Science, Wuxi University, 214105, Wuxi, China.
Interdisciplinary sciences, computational life sciences
|April 29, 2024
概括
这项研究引入了一种基于分子图的新型变压器模型,用于产生新的芬太尼类似物. 该模型成功地创造了许多新型化合物,有助于探索芬太尼分子结构和分布.
科学领域:
- 计算化学计算化学
- 药物发现 药物发现 药物发现
- 人工智能的人工智能
背景情况:
- 芬太尼及其类似物很容易被修改,由于数据库条目有限,这给监管监管带来了挑战.
- 犯罪分子利用芬太尼类似物的结构变化来逃避检测.
研究的目的:
- 开发一种新的分子生成模型,用于制造新的芬太尼类 analogue.
- 为了加强芬太尼分子结构的探索,并了解它们的分布模式.
主要方法:
- 采用了基于分子图的变压器模型.
- 集成了一个使用子结构替换的数据增强技术.
- 生成的分子被选,并计算了它们的特性.
主要成果:
- 产生了14万种潜在的芬太尼类似物,在查后发现了36799种.
- 该模型展示了学习原始芬太尼分子特性的能力.
- 与其他深度学习模型相比,拟议的模型产生了更多的新型芬太尼类型.
结论:
- 基于分子图的变压器模型有效地产生了新的芬太尼类型.
- 这种方法有助于探索潜在芬太尼分子的结构格局.
- 这些发现有助于了解芬太尼类似物的分布.
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