虚拟筛选
化学空间
药物发现
化学图书馆
计算生物学
组合化学
高通量筛选
配体效率
化学型
配体(生物化学)
化学
计算机科学
生化工程
纳米技术
受体
生物
小分子
生物化学
材料科学
工程类
色谱法
精油
作者
Katharina Grotsch,Anastasiia Sadybekov,Sydney Hiller,Saheem A. Zaidi,Dmitry B. Eremin,Austen D Le,Yongfeng Liu,Evan Carlton Smith,Christos Illiopoulis-Tsoutsouvas,Joice Thomas,Shubhangi Aggarwal,Julie E. Pickett,César Reyes,Elias Picazo,Bryan L. Roth,Alexandros Makriyannis,Vsevolod Katritch,Valery V. Fokin
标识
DOI:10.1021/acschembio.3c00602
摘要
The advent of ultra-large libraries of drug-like compounds has significantly broadened the possibilities in structure-based virtual screening, accelerating the discovery and optimization of high-quality lead chemotypes for diverse clinical targets. Compared to traditional high-throughput screening, which is constrained to libraries of approximately one million compounds, the ultra-large virtual screening approach offers substantial advantages in both cost and time efficiency. By expanding the chemical space with compounds synthesized from easily accessible and reproducible reactions and utilizing a large, diverse set of building blocks, we can enhance both the diversity and quality of the discovered lead chemotypes. In this study, we explore new chemical spaces using reactions of sulfur(VI) fluorides to create a combinatorial library consisting of several hundred million compounds. We screened this virtual library for cannabinoid type II receptor (CB
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