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小分子生物活性注释的形态亚谱分析。

Morphological subprofile analysis for bioactivity annotation of small molecules.

机构信息

Max Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany.

Max Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany.

出版信息

Cell Chem Biol. 2023 Jul 20;30(7):839-853.e7. doi: 10.1016/j.chembiol.2023.06.003. Epub 2023 Jun 28.

Abstract

Fast prediction of the mode of action (MoA) for bioactive compounds would immensely foster bioactivity annotation in compound collections and may early on reveal off-targets in chemical biology research and drug discovery. Morphological profiling, e.g., using the Cell Painting assay, offers a fast, unbiased assessment of compound activity on various targets in one experiment. However, due to incomplete bioactivity annotation and unknown activities of reference compounds, prediction of bioactivity is not straightforward. Here we introduce the concept of subprofile analysis to map the MoA for both, reference and unexplored compounds. We defined MoA clusters and extracted cluster subprofiles that contain only a subset of morphological features. Subprofile analysis allows for the assignment of compounds to, currently, twelve targets or MoA. This approach enables rapid bioactivity annotation of compounds and will be extended to further clusters in the future.

摘要

快速预测生物活性化合物的作用模式(MoA)将极大地促进化合物库中的生物活性注释,并可能尽早揭示化学生物学研究和药物发现中的非靶标。形态分析,例如使用细胞染色分析,可以在一个实验中快速、无偏地评估化合物对各种靶标的活性。然而,由于生物活性注释不完整和参考化合物的未知活性,因此预测生物活性并不简单。在这里,我们引入子谱分析的概念,以映射参考化合物和未探索化合物的 MoA。我们定义了 MoA 簇,并提取仅包含形态特征子集的簇子谱。子谱分析允许将化合物分配给目前的 12 个靶标或 MoA。这种方法可以快速注释化合物的生物活性,并将在未来扩展到更多的簇。

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