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Prioritizing Multiple Therapeutic Targets in Parallel Using Automated DNA-encoded Library Screening

Nature communications(2017)SCI 1区

GlaxoSmithKline | University of Birmingham

Cited 64|Views69
Abstract
The identification and prioritization of chemically tractable therapeutic targets is a significant challenge in the discovery of new medicines. We have developed a novel method that rapidly screens multiple proteins in parallel using DNA-encoded library technology (ELT). Initial efforts were focused on the efficient discovery of antibacterial leads against 119 targets from Acinetobacter baumannii and Staphylococcus aureus. The success of this effort led to the hypothesis that the relative number of ELT binders alone could be used to assess the ligandability of large sets of proteins. This concept was further explored by screening 42 targets from Mycobacterium tuberculosis. Active chemical series for six targets from our initial effort as well as three chemotypes for DHFR from M. tuberculosis are reported. The findings demonstrate that parallel ELT selections can be used to assess ligandability and highlight opportunities for successful lead and tool discovery.
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Combinatorial libraries,Target identification,Science,Humanities and Social Sciences,multidisciplinary
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要点】:本研究提出了一种利用自动化DNA编码库筛选技术(ELT)并行筛选多个治疗靶点的新方法,并证明了该技术能高效评估蛋白质的配体性,从而指导新药的发现。

方法】:研究采用DNA编码库技术,通过特定的化学反应将小分子与DNA编码的蛋白质结合,实现高通量的靶点筛选。

实验】:研究者在实验中首先针对119个来自Acinetobacter baumannii和Staphylococcus aureus的蛋白靶点进行筛选,并进一步对42个Mycobacterium tuberculosis的蛋白靶点进行了研究。实验成功发现了针对六个初始靶点的活性化学系列以及针对M. tuberculosis的二氢叶酸还原酶(DHFR)的三个化学类型。