以语法为导向的SMILES标准化使用了TokenSMILES
Luis Armando Gonzalez-Ortiz1, Lisset Noriega1, Filiberto Ortiz-Chi2
1Departamento de Física Aplicada, Centro de Investigación y de Estudios Avanzados Unidad Mérida, km 6 Antigua Carretera a Progreso, Apdo. Postal 73, Cordemex 97310 Mérida Yucatán Mexico.
Chemical science
|November 28, 2025
概括
标记SMILES通过创建简化分子输入线输入系统 (SMILES) 字符串的语法框架来标准化化学符号. 这种方法显著减少了冗余,并提高了化学信息学应用的机器解释性.
科学领域:
- 计算化学计算化学
- 化学信息学 化学信息学
- 语言学原则 语言学原则
背景情况:
- 简化分子输入线输入系统 (SMILES) 符号提出了冗余性挑战,其中多个字符串可以表示相同的分子.
- 这种冗余性使计算化学和化学信息学任务复杂化,阻碍了高效的数据处理和分析.
研究的目的:
- 引入TokenSMILES,这是一个新的语法框架,旨在标准化SMILES标记.
- 通过将字符串转换为结构化,无上下文的句子来减轻SMILES冗余.
- 为了实现可控生成和操作有效的SMILES字符串,增强语法和语义一致性.
主要方法:
- 开发了TokenSMILES,一个框架,将五个语法约束 (例如,分支限制,平衡括号) 应用于SMILES字符串.
- 利用语义解析规则来确保价值和八位合规性.
- 在开源的 SmilX 工具中实现了 TokenSMILES,用于生成标准化的 SMILES.
主要成果:
- 在保持化学有效性的同时,TokenSMILES 显著减少了 SMILES 对基的冗余.
- 结合TokenSMILES的SmilX工具生成有效的SMILES,其准确度与现有的低缺水分子 (HDI ≤ 4) 的方法相美.
- 该框架通过诸如键插入,循环化和异构原子替代等修改,证明了超出基的适用性.
结论:
- 标记SMILES将SMILES语法正式化为标准化,机器可解释的形式,解决化学信息学中的一个关键挑战.
- 该框架为药物发现,材料设计和机器学习中的应用提供了系统的化学空间探索.
- 对于高度不和的系统,需要进一步开发,强调动态可行性检查的重要性.
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