Integrating DNA-encoded chemical libraries with virtual combinatorial library screening: Optimizing a PARP10 inhibitor
作者:Mike Lemke、Hannah Ravenscroft、Nicole J. Rueb、Dmitri Kireev、Dana Ferraris、Raphael M. Franzini
DOI:10.1016/j.bmcl.2020.127464
日期:2020.10
Two critical steps in drug development are 1) the discovery of molecules that have the desired effects on a target, and 2) the optimization of such molecules into lead compounds with the required potency and pharmacokinetic properties for translation. DNA-encoded chemical libraries (DECLs) can nowadays yield hits with unprecedented ease, and lead-optimization is becoming the limiting step. Here we
药物开发的两个关键步骤是 1) 发现对靶标具有所需作用的分子,以及 2) 将此类分子优化为具有所需效力和药代动力学特性的先导化合物以进行翻译。DNA 编码的化学文库 (DECL) 现在可以前所未有地轻松产生命中,而铅优化正在成为限制步骤。在这里,我们将 DECL 筛选与基于结构的计算方法相结合,以简化先导化合物的开发。提出的工作流程包括枚举源自 DECL 筛选命中的虚拟组合库 (VCL),并使用计算结合预测来识别相对于原始 DECL 命中具有增强特性的分子。作为概念验证演示,