利用 "灰色化学物质"(Gray Chemical Matter)--高通量筛选图谱中具有新机制的化合物,拓展已知化学基因组学库之外的小规模可筛选生物空间

IF 3.5 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY ACS Chemical Biology Pub Date : 2024-04-02 DOI:10.1021/acschembio.3c00737
Jason R. Thomas*, Claude Shelton IV, Jason Murphy, Scott Brittain, Mark-Anthony Bray, Peter Aspesi, John Concannon, Frederick J. King, Robert J. Ihry, Daniel J. Ho, Martin Henault, Andrea Hadjikyriacou, Marilisa Neri, Frederic D. Sigoillot, Helen T. Pham, Matthew Shum, Louise Barys, Michael D. Jones, Eric J. Martin, Anke Blechschmidt, Sébastien Rieffel, Thomas J. Troxler, Felipa A. Mapa, Jeremy L. Jenkins, Rishi K. Jain, Peter S. Kutchukian, Markus Schirle and Steffen Renner*, 
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引用次数: 0

摘要

表型检测已成为药物发现的一种既定方法。通过复杂性更高的细胞模型和更详细的读数(如基因表达或高级成像),通常可以实现更强的疾病相关性。然而,这些检测方法的复杂性和成本限制了它们的筛选能力,往往将筛选限制在表征良好的小化合物集上,如化学基因组学文库。在这里,我们概述了一种化学信息学方法,该方法可鉴定出一小批可能具有新作用机制(MoA)的化合物,从而为通量有限的表型测定拓展了MoA搜索空间。我们的方法基于对现有大规模表型高通量筛选(HTS)数据的挖掘。它能识别在多种基于细胞的实验中表现出选择性的化学型,这些化学型具有持久而广泛的结构活性关系(SAR)。我们在广泛的细胞分析测试(细胞绘制、DRUG-seq 和 Promotor Signature Profiling)和化学蛋白质组学实验中验证了这种方法的有效性。这些实验表明,这些化合物的表现与已知的化学基因库相似,但明显偏向于新的蛋白质靶标。为了促进合作并推动这一领域的研究,我们在 PubChem 生物分析数据集的基础上策划了一套此类化合物的公共集,供科学界使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Enhancing the Small-Scale Screenable Biological Space beyond Known Chemogenomics Libraries with Gray Chemical Matter─Compounds with Novel Mechanisms from High-Throughput Screening Profiles

Phenotypic assays have become an established approach to drug discovery. Greater disease relevance is often achieved through cellular models with increased complexity and more detailed readouts, such as gene expression or advanced imaging. However, the intricate nature and cost of these assays impose limitations on their screening capacity, often restricting screens to well-characterized small compound sets such as chemogenomics libraries. Here, we outline a cheminformatics approach to identify a small set of compounds with likely novel mechanisms of action (MoAs), expanding the MoA search space for throughput limited phenotypic assays. Our approach is based on mining existing large-scale, phenotypic high-throughput screening (HTS) data. It enables the identification of chemotypes that exhibit selectivity across multiple cell-based assays, which are characterized by persistent and broad structure activity relationships (SAR). We validate the effectiveness of our approach in broad cellular profiling assays (Cell Painting, DRUG-seq, and Promotor Signature Profiling) and chemical proteomics experiments. These experiments revealed that the compounds behave similarly to known chemogenetic libraries, but with a notable bias toward novel protein targets. To foster collaboration and advance research in this area, we have curated a public set of such compounds based on the PubChem BioAssay dataset and made it available for use by the scientific community.

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来源期刊
ACS Chemical Biology
ACS Chemical Biology 生物-生化与分子生物学
CiteScore
7.50
自引率
5.00%
发文量
353
审稿时长
3.3 months
期刊介绍: ACS Chemical Biology provides an international forum for the rapid communication of research that broadly embraces the interface between chemistry and biology. The journal also serves as a forum to facilitate the communication between biologists and chemists that will translate into new research opportunities and discoveries. Results will be published in which molecular reasoning has been used to probe questions through in vitro investigations, cell biological methods, or organismic studies. We welcome mechanistic studies on proteins, nucleic acids, sugars, lipids, and nonbiological polymers. The journal serves a large scientific community, exploring cellular function from both chemical and biological perspectives. It is understood that submitted work is based upon original results and has not been published previously.
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