对接(动物)
激酶
化学
虚拟筛选
生物信息学
计算生物学
化学图书馆
高通量筛选
药物发现
生物化学
组合化学
小分子
生物
医学
基因
护理部
作者
Rafael Gozalbes,Laurence Simon,Nicolas Froloff,Eric Sartori,Claude Monteils,Romuald Baudelle
摘要
A high-throughput docking strategy for the filtering of in silico compounds and the generation of kinase-targeted libraries is described. Systematic docking and scoring in three kinase crystal 3D structures of 123 structurally diverse kinase ligands led to the determination of six thresholds for each kinase. These thresholds were used as filters for the virtual screening of two collections of compounds: a collection of more than 2500 drugs and drug-like compounds (negative control) and a kinase-targeted library of 1440 compounds. This strategy was then experimentally validated by testing 60 compounds from the kinase-targeted library on 41 kinases from five different families. The 60 compounds were split into those passing all the thresholds and the others (30 compounds in each group). The overall hit enrichment was 6.70-fold higher in the first group, validating our approach for the generation of kinase-targeted libraries and the identification of scaffolds with high kinase inhibitory potential.
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