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PrePeP–用于鉴定和表征泛测定干扰化合物的工具

PrePeP – A Tool for the Identification and Characterization of Pan Assay Interference Compounds
课程网址: http://videolectures.net/kdd2018_koptelov_prepep_tool/  
主讲教师: Maksim Koptelov
开课单位: Caen Basse Normandie大学
开课时间: 2018-11-23
课程语种: 英语
中文简介:
泛分析干扰化合物(PAINS)是现代药物发现中的一个重要问题:在高通量筛选中显示出非靶向特异性活性的化合物会在命中识别过程中误导药物化学家,浪费时间和资源。最近的工作表明,现有的结构性警报无法完成识别疼痛的任务。为了解决这一短期问题,我们正在开发一种预测疼痛的工具PrePeP,并允许专家直观地探究预测的原因。在本文中,我们讨论了开发功能工具所涉及的不同方面:系统地导出结构描述符,解决数据的极端不平衡,提供药理学化学家熟悉的视觉信息。我们使用文献中的基准数据集评估方法的质量,并表明我们纠正了最近指出的现有PAINS警报的几个缺点。
课程简介: Pan Assays Interference Compounds (PAINS) are a significant problem in modern drug discovery: compounds showing non-target specific activity in high-throughput screening can mislead medicinal chemists during hit identification, wasting time and resources. Recent work has shown that existing structural alerts are not up to the task of identifying PAINS. To address this short-coming, we are in the process of developing a tool, PrePeP, that predicts PAINS, and allows experts to visually explore the reasons for the prediction. In the paper, we discuss the different aspects that are involved in developing a functional tool: systematically deriving structural descriptors, addressing the extreme imbalance of the data, offering visual information that pharmacological chemists are familiar with. We evaluate the quality of the approach using benchmark data sets from the literature and show that we correct several short-comings of existing PAINS alerts that have recently been pointed out.
关 键 词: 泛分析干扰化合物; 在高通量筛选中显示; 药理学化学家熟悉; 基准数据集评估方法
课程来源: 视频讲座网
数据采集: 2023-01-16:cyh
最后编审: 2023-01-16:cyh
阅读次数: 56