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Quantitatively integrating molecular structure and bioactivity profile evidence into drug-target relationship analysis

机译:将分子结构和生物活性谱证据定量整合到药物-靶标关系分析中

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摘要

BackgroundPublic resources of chemical compound are in a rapid growth both in quantity and the types of data-representation. To comprehensively understand the relationship between the intrinsic features of chemical compounds and protein targets is an essential task to evaluate potential protein-binding function for virtual drug screening. In previous studies, correlations were proposed between bioactivity profiles and target networks, especially when chemical structures were similar. With the lack of effective quantitative methods to uncover such correlation, it is demanding and necessary for us to integrate the information from multiple data sources to produce an comprehensive assessment of the similarity between small molecules, as well as quantitatively uncover the relationship between compounds and their targets by such integrated schema.
机译:背景技术化合物的公共资源的数量和数据表示类型都在快速增长。全面了解化合物的内在特征与蛋白质靶标之间的关系是评估虚拟药物筛选潜在的蛋白质结合功能的一项基本任务。在以前的研究中,特别是在化学结构相似的情况下,提出了生物活性谱与目标网络之间的相关性。由于缺乏有效的定量方法来揭示这种相关性,因此我们需要并有必要整合来自多个数据源的信息以对小分子之间的相似性进行全面评估,并定量地揭示化合物与其化合物之间的关系。这样的集成模式确定目标。

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