Automated Molecular Identity Disambiguator (AutoMID)

项目总结 小分子是最重要的一类治疗方法，可以减轻痛苦，在许多情况下 全球数亿人的死亡。小分子也是研究的无价工具。 生物学，通常以验证未来治疗药物开发的新靶点为目标。 实验结果的重复性以及结果数据集的互操作性和可重用性取决于 对相关研究对象的准确描述，以及最关键的是对小的 在生物检测中被测试的分子。例如，不可能开发出预测模型 蛋白质靶标-小分子相互作用，如果它们的化学结构表示不正确。许多 小分子筛选和组学参考文献中化学结构错误的因素 数据库、科学出版物和许多其他基于Web的资源和文档。因为 表示小分子化学结构图的复杂性以及缺乏彻底的精选，错误 经常由非专家介绍，并且在不同的数字研究资产之间传播错误是一种 普遍存在的问题。为了通过可扩展的方法解决这一具有挑战性的问题，我们提出了自动化 分子同一性消歧器(AutoMID)。AutoMID将通过API在批处理模式下大规模使用，用于 举例以协助数字研究资产的维护人员进行化学结构标准化和注册， 还可以通过交互(UI)模式让日常研究人员快速、轻松地验证或更正他们的 分子表示法。AutoMID将利用广泛的高度标准化的化学品链接数据库 结构和相关信息，包括名称、同义词、生物活性和物理特性 以及它们的来源/来源，并利用专家规则和人工智能来可靠地消除化学物质的歧义 在规模上构建身份。

PROJECT SUMMARY Small molecules are one of the most important classes of therapeutics alleviating suffering and in many cases death for hundreds of millions of people worldwide. Small molecules also serve as invaluable tools to study biology, often with the goal to validate novel targets for the development of future therapeutic drugs. Reproducibility of experimental results and the interoperability and reusability of resulting datasets depend on accurate descriptions of associated research objects, and most critically on correct representations of small molecules that are tested in biological assays. For example, it is not possible to develop predictive models of protein target - small molecule interactions if their chemical structure representations are not correct. Many factors contribute to errors in reported chemical structures in small molecule screening and omics reference databases, scientific publications, and many other web-based resources and documents. Because of the complexity of representing small molecules chemical structure graphs and the lack of thorough curation, errors are frequently introduced by non-experts and error propagation across different digital research assets is a pervasive problem. To address this challenging problem via a scalable approach, we propose the Automated Molecular Identity Disambiguator (AutoMID). AutoMID will be usable in batch mode at scale via an API, for example to assist chemical structure standardization and registration by maintainers of digital research assets, and also via interactive (UI) mode for everyday researchers to quickly and easily validate or correct their small molecule representations. AutoMID will leverage extensive highly standardized linked databases of chemical structures and associated information including names, synonyms, biological activity and physical properties and their sources / provenance and leverage expert rules and AI to enable reliable disambiguation of chemical structure identities at scale.