Schürer Stephan C, Vempati Uma, Smith Robin, Southern Mark, Lemmon Vance
Center for Computational Science, University of Miami, Miami, Florida 33136, USA.
J Biomol Screen. 2011 Apr;16(4):415-26. doi: 10.1177/1087057111400191.
High-throughput screening data repositories, such as PubChem, represent valuable resources for the development of small-molecule chemical probes and can serve as entry points for drug discovery programs. Although the loose data format offered by PubChem allows for great flexibility, important annotations, such as the assay format and technologies employed, are not explicitly indexed. The authors have previously developed a BioAssay Ontology (BAO) and curated more than 350 assays with standardized BAO terms. Here they describe the use of BAO annotations to analyze a large set of assays that employ luciferase- and β-lactamase-based technologies. They identified promiscuous chemotypes pertaining to different subcategories of assays and specific mechanisms by which these chemotypes interfere in reporter gene assays. Results show that the data in PubChem can be used to identify promiscuous compounds that interfere nonspecifically with particular technologies. Furthermore, they show that BAO is a valuable toolset for the identification of related assays and for the systematic generation of insights that are beyond the scope of individual assays or screening campaigns.
高通量筛选数据存储库，如PubChem，是开发小分子化学探针的宝贵资源，可作为药物发现计划的切入点。尽管PubChem提供的松散数据格式具有很大的灵活性，但重要的注释，如所采用的测定形式和技术，并未明确索引。作者此前开发了生物测定本体（BAO），并用标准化的BAO术语策划了350多种测定。在此，他们描述了使用BAO注释来分析大量采用基于荧光素酶和β-内酰胺酶技术的测定。他们确定了与不同测定子类别相关的混杂化学型，以及这些化学型干扰报告基因测定的具体机制。结果表明，PubChem中的数据可用于识别非特异性干扰特定技术的混杂化合物。此外，他们还表明，BAO是识别相关测定以及系统生成超出单个测定或筛选活动范围的见解的宝贵工具集。
