产量(工程)
选择(遗传算法)
简单(哲学)
组合化学
DNA
信号(编程语言)
编码(内存)
生物系统
计算机科学
极限(数学)
化学图书馆
计算生物学
化学
算法
数学
数据挖掘
生化工程
生物
人工智能
工程类
生物化学
小分子
热力学
物理
哲学
程序设计语言
数学分析
认识论
作者
J. Perry Hall,Timothy L. Foley,Qiu Xia Chen,David I. Israel,Yong Xu,Kristin K. Ford,Ping Xie,Jing Fan,Jinqiao Wan
标识
DOI:10.1016/j.bbrc.2020.04.024
摘要
DNA-encoded libraries (DELs) can contain billions of unique chemical species; selecting against such large inputs, it is typical to find more candidate binders than is reasonable to pursue for follow-up synthesis and testing. Given this wealth of choices, common practice is to limit synthesis to only those compounds estimated to have the greatest chance of being high-affinity binders; of the many potential factors contributing to this estimation, the strength of the selection signal of a candidate binder is always important. We define here methods and equations which relate the theoretical selection signal of a compound to its affinity and chemical yield. Tests using known binders of BRD4 and ROCK2 support the theory backing these equations and suggest they should be of use for prospectively determining affinity and chemical yield from primary DEL selection data.
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