BindingDB: An Open Knowledgebase of Protein-Small Molecule Interactions

结合特定蛋白质的有机小分子是最有效的方法之一 医生必须治疗疾病，研究人员可以用来探测生命系统。 这种小分子，也称为配体，可以以多种方式发挥作用，例如通过阻止 蛋白质工作，通过激活蛋白质，或通过使蛋白质被 正常的细胞过程。事实上，大多数药物都是配体，研究人员在 大学、政府实验室和制药公司都在不断地寻找 作为药物和生物探针的新技术。这些持续的努力产生了源源不断的 关于什么小分子与什么蛋白质结合以及结合的紧密程度的信息。 这些信息不仅在生成它的特定项目中很有用，而且对许多人也很有用 其他应用，例如帮助研究人员识别探针分子，以帮助他们 研究，作为计算化学家创建软件的基准 预测配体-蛋白质结合，以及用于药物设计的训练和测试机器学习工具。 然而，产生这种信息的科学家通常会在科学文章或专利中公布它， 在那里它不容易被其他研究人员找到或访问。 本项目的核心目的是进一步开发BindingDB知识库， 极大地扩展了蛋白质-配体结合信息的可用性并将其连接起来 将信息提供给其他知识领域，以使其尽可能广泛地有用。这 将通过使用自动化和人工方法的组合来完成 快速、准确地从科学文章和专利中提取大量数据。这些数据 将以机器可读格式呈现，并与相关数据链接，例如关于 蛋白质结构和功能，并以开放源码格式通过 可搜索的BindingDB网站，该网站还允许大量下载离线数据 使用。 BindingDB中的信息将按照更高的社区标准进行管理 可发现性、可访问性、互操作性和可重用性(FAIR)，该项目将实现 高CoreTrustSeal标准和可靠性和长期保存认证。在……里面 此外，将采取措施最大限度地提高这些信息的可用性和集成度，例如通过 将其作为新兴云资源中的公共数据集提供，并从以下位置创建链接- 在线期刊文章和专利到BindingDB中从中提取的数据。

Small, organic molecules that bind specific proteins represent one of the most effective ways that physicians have to treat diseases and that researchers can use to probe living systems. Such small molecules, also known as ligands, can act in many ways, such as by blocking a protein from working, by activating a protein, or by causing the protein to be broken down by normal cellular processes. In fact, most medications are ligands, and researchers in universities, government labs, and pharmaceutical companies, are constantly at work seeking new ones as drugs and biological probes. These ongoing efforts generate a continuous flow of information about what small molecules bind what proteins, and how tightly. This information is useful not only within the specific project that generated it, but also for many other applications, such as helping researchers identify probe molecules to help with their research, serving as benchmarks for computational chemists creating software designed to predict ligand-protein binding, and training and testing machine-learning tools for drug design. However, scientists generating this information typically release it in scientific articles or patents, where it cannot easily be found or accessed by other researchers. The core purpose of this project is to further develop the BindingDB Knowledgebase, dramatically expanding the availability of protein-ligand binding information and connecting this information to other areas of knowledge in order to make it as broadly useful as possible. This will be accomplished by using a combination of automated and human methods to carry out fast, accurate extraction of large volumes of data from scientific articles and patents. These data will be rendered in machine readable format, linked with related data, such as information on protein structure and function, and made publicly available in open source format via the searchable BindingDB website, which also allows data to be downloaded in quantity for offline use. The information in BindingDB will be managed according to high community standards for findability, accessibility, interoperability, and reusability (FAIR), and the project will achieve the high CoreTrustSeal standards and certification for reliability and long-term preservation. In addition, steps will be taken to maximize usability and integration of this information, such as by making it available as a public dataset in emerging cloud resources and creating links from on- line journal articles and patents to the data extracted from them in BindingDB.