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DNA编码文库筛选后从活性分子到先导化合物优化的趋势

Trends in Hit-to-Lead Optimization Following DNA-Encoded Library Screens.

作者信息

Reiher Christopher A, Schuman David P, Simmons Nicholas, Wolkenberg Scott E

机构信息

Discovery Chemistry, Janssen Research & Development, LLC, Welsh & McKean Roads, Spring House, Pennsylvania 19477, United States.

Discovery Chemistry, Janssen Research & Development, LLC, 3210 Merryfield Row, San Diego, California 92121, United States.

出版信息

ACS Med Chem Lett. 2021 Feb 11;12(3):343-350. doi: 10.1021/acsmedchemlett.0c00615. eCollection 2021 Mar 11.

Abstract

DNA-encoded library (DEL) screens have emerged as a powerful hit-finding tool for a number of biological targets. In this Innovations article, we review published hit-to-lead optimization studies following DEL screens. Trends in molecular property changes from hit to lead are identified, and specific optimization tactics are exemplified in case studies. Across the studies, physicochemical property and structural changes post-DEL screening are similar to those which occur during hit-to-lead optimization following high throughputscreens (HTS). However, unique aspects of DEL-the combinatorial synthetic methods which enable DEL synthesis and the linker effects at the DNA attachment point-impact the strategies and outcomes of hit-to-lead optimizations.

摘要

DNA编码文库(DEL)筛选已成为一种针对多种生物学靶点的强大的命中发现工具。在这篇创新文章中,我们回顾了DEL筛选后已发表的从命中物到先导物的优化研究。确定了从命中物到先导物分子性质变化的趋势,并在案例研究中举例说明了具体的优化策略。在各项研究中,DEL筛选后的物理化学性质和结构变化与高通量筛选(HTS)后从命中物到先导物优化过程中发生的变化相似。然而,DEL的独特之处——实现DEL合成的组合合成方法以及DNA连接点处的连接子效应——影响了从命中物到先导物优化的策略和结果。

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本文引用的文献

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Denoising DNA Encoded Library Screens with Sparse Learning.基于稀疏学习的 DNA 编码文库筛选降噪。
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