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通过高通量再合成 DNA 缀合物和亲和选择质谱对 DNA 编码文库选择结果进行分类。

Triaging of DNA-Encoded Library Selection Results by High-Throughput Resynthesis of DNA-Conjugate and Affinity Selection Mass Spectrometry.

机构信息

WuXi AppTec (Shanghai) Co., Ltd., 240 Hedan Road, Shanghai 200131, China.

出版信息

Bioconjug Chem. 2021 May 19;32(5):1001-1007. doi: 10.1021/acs.bioconjchem.1c00170. Epub 2021 Apr 29.

DOI:10.1021/acs.bioconjchem.1c00170
PMID:33914520
Abstract

DNA encoded library (DEL) technology allows for rapid identification of novel small-molecule ligands and thus enables early-stage drug discovery. DEL technology is well-established, numerous cases of discovered hit molecules have been published, and the technology is widely employed throughout the pharmaceutical industry. Nonetheless, DEL selection results can be difficult to interpret, as library member enrichment may derive from not only desired products, but also DNA-conjugated byproducts and starting materials. Note that DELs are generally produced using split-and-pool combinatorial chemistry, and DNA-conjugated byproducts and starting materials cannot be removed from the library mixture. Herein, we describe a method for high-throughput parallel resynthesis of DNA-conjugated molecules such that byproducts, starting materials, and desired products are produced in a single pot, using the same chemical reactions and reagents as during library production. The low-complexity mixtures of DNA-conjugate are then assessed for protein binding by affinity selection mass spectrometry and the molecular weights of the binding ligands ascertained. This workflow is demonstrated to be a practical tool to triage and validate potential hits from DEL selection data.

摘要

DNA 编码文库 (DEL) 技术可快速鉴定新型小分子配体,从而实现药物研发的早期阶段。DEL 技术已经成熟,已经有许多发现的命中分子的案例被发表,并且该技术在整个制药行业得到广泛应用。尽管如此,DEL 选择结果可能难以解释,因为文库成员的富集可能不仅来自于所需产物,还来自于 DNA 偶联的副产物和起始材料。请注意,DEL 通常使用分而治之的组合化学方法生产,而 DNA 偶联的副产物和起始材料不能从文库混合物中去除。本文中,我们描述了一种高通量平行再合成 DNA 偶联分子的方法,使得副产物、起始材料和所需产物在一个锅中生成,使用与文库生产相同的化学反应和试剂。然后通过亲和选择质谱法评估 DNA 偶联物的低复杂度混合物的蛋白结合情况,并确定结合配体的分子量。该工作流程被证明是一种实用的工具,可用于从 DEL 选择数据中筛选和验证潜在的命中。

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