选择(遗传算法)
药物发现
化学
工作流程
计算生物学
鉴定(生物学)
匹配(统计)
化学图书馆
吲哚试验
化学数据库
组合化学
价值(数学)
计算机科学
否定选择
特征选择
铅化合物
情报检索
作者
Yiwei Zhang,Yuqiu Lan,Rufeng Fan,Lei Feng,Guoliang Wang,Xinyuan Wu,Lulu Wen,Zhiqiang Duan,Yueyue Xia,Xudong Wang,Lingrui Zhang,Lu Zhou,Minjia Tan,Cangsong Liao,Xiaojie Lu
摘要
DNA-encoded libraries (DELs) have emerged as an effective and efficient selection strategy for lead compound discovery in academia and industry over the past few decades. Despite recent advancements in this field, DEL remains limited by sensitive DNA-based constructs, particularly with low selection success rates resulting from the random selection of targets. Here, we describe a chemoenzymatic on-DNA reaction for DEL syntheses and develop a chemoproteomic-guided DEL selection platform. This platform, termed FF tags-biocatDEL, integrates DEL technology, chemoenzymatic synthesis, and fully functionalized (FF) chemical tags to match DELs with selection targets, even with limited information about ligandable hotspots. Using two diazirine-based FF indole probes, we comprehensively surveyed binding partners in cells and identified phosphoglycerate dehydrogenase (PHGDH) as a potential target for DEL selection. DEL01 and DEL02 were designed, synthesized, and selected against PHGDH, leading to the identification of a novel enzyme-active compound with an IC50 value of 2.5 μM. Our strategy, utilizing FF tags-biocatDEL, establishes a generalizable workflow for rapid target hunting and ligand discovery. It provides an effective method for precisely matching DELs with potential targets, demonstrating its significant potential as a complementary approach to drug discovery based on DELs.
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