2024年的BindingDB：蛋白质-小分子结合数据的可 FAIR 化知识库。
BindingDB in 2024: a FAIR knowledgebase of protein-small molecule binding data.
作者信息
Liu Tiqing, Hwang Linda, Burley Stephen K, Nitsche Carmen I, Southan Christopher, Walters W Patrick, Gilson Michael K
机构信息
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093, USA.
Research Collaboratory for Structural Bioinformatics Protein Data Bank, Institute for Quantitative Biomedicine, Rutgers. The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Rutgers Cancer Institute, Robert Wood Johnson Medical School, New Brunswick, NJ 08903, USA; Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA; Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
出版信息
Nucleic Acids Res. 2025 Jan 6;53(D1):D1633-D1644. doi: 10.1093/nar/gkae1075.
BindingDB (bindingdb.org) is a public, web-accessible database of experimentally measured binding affinities between small molecules and proteins, which supports diverse applications including medicinal chemistry, biochemical pathway annotation, training of artificial intelligence models and computational chemistry methods development. This update reports significant growth and enhancements since our last review in 2016. Of note, the database now contains 2.9 million binding measurements spanning 1.3 million compounds and thousands of protein targets. This growth is largely attributable to our unique focus on curating data from US patents, which has yielded a substantial influx of novel binding data. Recent improvements include a remake of the website following responsive web design principles, enhanced search and filtering capabilities, new data download options and webservices and establishment of a long-term data archive replicated across dispersed sites. We also discuss BindingDB's positioning relative to related resources, its open data sharing policies, insights gleaned from the dataset and plans for future growth and development.
BindingDB（bindingdb.org）是一个可通过网络公开访问的数据库，收录了小分子与蛋白质之间经实验测定的结合亲和力，支持多种应用，包括药物化学、生化途径注释、人工智能模型训练以及计算化学方法开发。本次更新报告了自我们上次在2016年进行审查以来的显著增长和改进。值得注意的是，该数据库现在包含290万个结合测量值，涵盖130万种化合物和数千个蛋白质靶点。这种增长很大程度上归因于我们对从美国专利中筛选数据的独特关注，这带来了大量新的结合数据。最近的改进包括按照响应式网页设计原则重新制作网站、增强搜索和筛选功能、新的数据下载选项和网络服务，以及建立在分散站点复制的长期数据存档。我们还讨论了BindingDB相对于相关资源的定位、其开放数据共享政策、从数据集中获得的见解以及未来增长和发展计划。
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