虚拟筛选
化学
药物发现
配体效率
计算生物学
生物信息学
小分子
组合化学
代谢组学
质谱法
化学空间
高通量筛选
配体(生物化学)
化学生物学
铅化合物
生物化学
生物
体外
色谱法
受体
基因
作者
Zhihua Wang,Hao Liang,Haijie Cao,Bingjie Zhang,Jun Li,Wen-Qiong Wang,Shanshan Qin,Yuefei Wang,Li‐Jiang Xuan,Luhua Lai,Wenqing Shui
出处
期刊:Analyst
[Royal Society of Chemistry]
日期:2019-01-01
卷期号:144 (9): 2881-2890
被引量:29
摘要
Although natural herbs have been a rich source of compounds for drug discovery, identification of bioactive components from natural herbs suffers from low efficiency and prohibitive cost of the conventional bioassay-based screening platforms. Here we develop a new strategy that integrates virtual screening, affinity mass spectrometry (MS) and targeted metabolomics for efficient discovery of herb-derived ligands towards a specific protein target site. Herb-based virtual screening conveniently selects herbs of potential bioactivity whereas affinity MS combined with targeted metabolomics readily screens candidate compounds in a high-throughput manner. This new integrated approach was benchmarked on screening chemical ligands that target the hydrophobic pocket of the nucleoprotein (NP) of Ebola viruses for which no small molecule ligands have been reported. Seven compounds identified by this approach from the crude extracts of three natural herbs were all validated to bind to the NP target in pure ligand binding assays. Among them, three compounds isolated from Piper nigrum (HJ-1, HJ-4 and HJ-6) strongly promoted the formation of large NP oligomers and reduced the protein thermal stability. In addition, cooperative binding between these chemical ligands and an endogenous peptide ligand was observed, and molecular docking was employed to propose a possible mechanism. Taken together, we established a platform integrating in silico and experimental screening approaches for efficient discovery of herb-derived bioactive ligands especially towards non-enzyme protein targets.
科研通智能强力驱动
Strongly Powered by AbleSci AI