a Institute of Pharmacy, Division of Pharmaceutical and Medicinal Chemistry , Paracelsus Medical Private University Salzburg , Salzburg , Austria.
b Planta Naturstoffe , Vienna , Austria.
J Enzyme Inhib Med Chem. 2018 Dec;33(1):1529-1536. doi: 10.1080/14756366.2018.1512598.
There is an increasing interest in developing novel eosinophil peroxidase (EPO) inhibitors, in order to provide new treatment strategies against chronic inflammatory and neurodegenerative diseases caused by eosinophilic disorder. Within this study, a ligand-based pharmacophore model for EPO inhibitors was generated and used for in silico screening of large 3 D molecular structure databases, containing more than 4 million compounds. Hits obtained were clustered and a total of 277 compounds were selected for biological assessment. A class of 2-(phenyl)amino-aceto-hydrazides with different substitution pattern on the aromatic ring was found to contain the most potent EPO inhibitors, exhibiting IC values down to 10 nM. The generated pharmacophore model therefore, represents a valuable tool for the selection of compounds for biological testing. The compounds identified as potent EPO inhibitors will serve to initiate a hit to lead and lead optimisation program for the development of new therapeutics against eosinophilic disorders.
人们越来越感兴趣的是开发新型的嗜酸性粒细胞过氧化物酶(EPO)抑制剂,以提供新的治疗策略,用于治疗由嗜酸性粒细胞紊乱引起的慢性炎症和神经退行性疾病。在这项研究中,生成了用于 EPO 抑制剂的基于配体的药效团模型,并用于对包含超过 400 万个化合物的大型 3D 分子结构数据库进行计算筛选。获得的命中化合物进行聚类,共选择了 277 种化合物进行生物学评估。结果发现,具有不同芳香环取代模式的 2-(苯基)氨基乙酰基酰肼类化合物包含最有效的 EPO 抑制剂,其 IC 值低至 10 nM。因此,所生成的药效团模型代表了用于选择化合物进行生物学测试的有价值的工具。鉴定为有效 EPO 抑制剂的化合物将用于启动针对嗜酸性粒细胞紊乱的新型治疗药物的命中到先导化合物优化计划。