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首页> 外文期刊>Behavioural processes >Discovery of high affinity ligands for beta_2-adrenergic receptor through pharmacophore-based high-throughput virtual screening and docking
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Discovery of high affinity ligands for beta_2-adrenergic receptor through pharmacophore-based high-throughput virtual screening and docking

机译:通过基于Phara_2-肾上腺素能受体的高亲和力配体发现高亲和力配体通过药物的高通量虚拟筛选和对接

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摘要

Novel high affinity compounds for human beta_2-adrenergic receptor (beta_2-AR) were searched among the clean drug-like subset of ZINC database consisting of 9,928,465 molecules that satisfy the Lipinski's rule of five. The screening protocol consisted of a high-throughput pharmacophore screening followed by an extensive amount of docking and rescoring. The pharmacophore model was composed of key features shared by all five inactive states of beta_2-AR in complex with inverse agonists and antagonists. To test the discriminatory power of the pharmacophore model, a small-scale screening was initially performed on a database consisting of 117 compounds of which 53 antagonists were taken as active inhibitors and 64 agonists as inactive inhibitors. Accordingly, 7.3% of the ZINC database subset (729,413 compounds) satisfied the pharmacophore requirements, along with 44 antagonists and 17 agonists. Afterwards, all these hit compounds were docked to the inactive apo form of the receptor using various docking and scoring protocols. Following each docking experiment, the best pose was further evaluated based on the existence of key residues for antagonist binding in its vicinity. After final evaluations based on the human intestinal absorption (HIA) and the blood brain barrier (BBB) penetration properties, 62 hit compounds have been clustered based on their structural similarity and as a result four scaffolds were revealed. Two of these scaffolds were also observed in three high affinity compounds with experimentally known K_i values. Moreover, novel chemical compounds with distinct structures have been determined as potential beta_2-AR drug candidates.
机译:在锌数据库的清洁药物状子集中搜查了人β_2-肾上腺素能受体(Beta_2-AR)的新型高亲和力化合物,其中包含9,928,465分子,这些分子满足Lipinski的五个。筛选方案由高通量的药物筛选组成,然后是广泛的对接和重新扫描。药效线模型由所有五种非活动状态共享的β_2-AR的关键特征组成,其复杂于反向激动剂和拮抗剂。为了测试药效线模型的鉴别力,最初对由117种化合物组成的数据库中的小规模筛选,其中将53个拮抗剂作为活性抑制剂和64个激动剂作为无活性抑制剂。因此,7.3%的锌数据库子集(729,413种化合物)满足药效线要求,以及44个拮抗剂和17位激动剂。然后,使用各种对接和评分方案,将所有这些击中化合物对接到受体的无惰性APO形式。在每个对接实验之后,进一步评估最佳姿势,基于其附近的拮抗剂结合的关键残留物的存在。在基于人肠道吸收(Hia)和血脑屏障(BBB)渗透性的最终评估之后,基于其结构相似性,并因此揭示了42个麦芽化合物。其中两种支架中还在三种高亲和力化合物中观察到具有实验已知的K_I值。此外,具有不同结构的新型化学化合物已被确定为潜在的β2-AR药物候选物。

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