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每个化学基因组学文库的多药药理学程度如何?

How polypharmacologic is each chemogenomics library?

作者信息

Ni Eric, Kwon Eehjoe, Young Lauren M, Felsovalyi Klara, Fuller Jennifer, Cardozo Timothy

机构信息

NYU Langone Health, Department of Biochemistry & Molecular Pharmacology, New York, NY 10016, USA.

Genecentrix Inc, New York, NY 10014, USA.

出版信息

Future Drug Discov. 2020 Feb 5;2(1):FDD26. doi: 10.4155/fdd-2019-0032.

Abstract

AIM

High-throughput phenotypic screens have emerged as a promising avenue for small-molecule drug discovery. The challenge faced in high-throughput phenotypic screens is target deconvolution once a small molecule hit is identified. Chemogenomics libraries have emerged as an important tool for meeting this challenge. Here, we investigate their target-specificity by deriving a 'polypharmacology index' for broad chemogenomics screening libraries.

METHODS

All known targets of all the compounds in each library were plotted as a histogram and fitted to a Boltzmann distribution, whose linearized slope is indicative of the overall polypharmacology of the library.

RESULTS & CONCLUSION: Comparison of libraries clearly distinguished the most target-specific library, which might be assumed to be more useful for target deconvolution in a phenotypic screen.

摘要

目的

高通量表型筛选已成为小分子药物发现的一条有前景的途径。高通量表型筛选面临的挑战是一旦鉴定出小分子活性物质,就要进行靶点反卷积。化学基因组学文库已成为应对这一挑战的重要工具。在此,我们通过为广泛的化学基因组学筛选文库推导一个“多药理学指数”来研究它们的靶点特异性。

方法

将每个文库中所有化合物的所有已知靶点绘制成直方图,并拟合到玻尔兹曼分布,其线性化斜率表明文库的整体多药理学特性。

结果与结论

文库之间的比较清楚地区分出了靶点特异性最强的文库,该文库可能被认为在表型筛选中对靶点反卷积更有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b96/7052528/91d7014bffcf/fdd-02-26-g1.jpg

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