超高吞吐量技术的进步通过并列质谱编码图书馆的发现
J Miguel Mata1, Edith van der Nol1, Sebastian J Pomplun1
1Leiden University, 2333 CC Leiden, The Netherlands.
Journal of the American Chemical Society
|August 9, 2023
概括
研究人员开发了一种用于药物发现的新方法, 这项技术可以迅速识别潜在的药物化合物, 加快新药的研发.
科学领域:
- 生物化学
- 药物发现
- 分析化学
背景情况:
- 发现新的生物活性分子对于推进药物开发至关重要.
- 传统药物发现需要对数以百万计的化合物进行选,
- 通过快速选大型复合库来加速命中发现.
研究的目的:
- 描述最近在选超大合成模图书馆的技术进步.
- 为了突出一种无条码的双重质谱解码策略.
- 展示这种技术在识别各种药物点的高亲和结合剂中的应用.
主要方法:
- 超大合成模图书馆的组合合成.
- 用于分离目标结合化合物的亲和性选择技术.
- 无条码的双重质谱测量用于自动化 de novo 测序.
- 在质谱仪器的进步.
主要成果:
- 成功选了超过1亿名会员的合成图书馆.
- 发现各种药物点的高亲和结合剂,包括蛋白质,核酸和细胞类型.
- 识别具有特定功能和反应性的合成模剂.
结论:
- 结合亲和性选择,质谱和自动化新解码提供了一种强大的发现方法.
- 这项技术可以快速识别来自超大合成库的毒品线索.
- 预计该方法将成为广泛采用的药物发现技术.
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