首页> 美国卫生研究院文献>Wiley-Blackwell Online Open >Three-Dimensional Pharmacophore Design and Biochemical Screening Identifies Substituted 124-Triazoles as Inhibitors of the Annexin A2–S100A10 Protein Interaction
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Three-Dimensional Pharmacophore Design and Biochemical Screening Identifies Substituted 124-Triazoles as Inhibitors of the Annexin A2–S100A10 Protein Interaction

机译:三维药理学设计和生化筛选确定取代的124-三唑类是膜联蛋白A2-S100A10蛋白相互作用的抑制剂

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摘要

AbstractProtein interactions are increasingly appreciated as targets in small-molecule drug discovery. The interaction between the adapter protein S100A10 and its binding partner annexin A2 is a potentially important drug target. To obtain small-molecule starting points for inhibitors of this interaction, a three-dimensional pharmacophore model was constructed from the X-ray crystal structure of the complex between S100A10 and annexin A2. The pharmacophore model represents the favourable hydrophobic and hydrogen bond interactions between the two partners, as well as spatial and receptor site constraints (excluded volume spheres). Using this pharmacophore model, UNITY flex searches were carried out on a 3D library of 0.7 million commercially available compounds. This resulted in 568 hit compounds. Subsequently, GOLD docking studies were performed on these hits, and a set of 190 compounds were purchased and tested biochemically for inhibition of the protein interaction. Three compounds of similar chemical structure were identified as genuine inhibitors of the binding of annexin A2 to S100A10. The binding modes predicted by GOLD were in good agreement with their UNITY-generated conformations. We synthesised a series of analogues revealing areas critical for binding. Thus computational predictions and biochemical screening can be used successfully to derive novel chemical classes of protein–protein interaction blockers.
机译:摘要蛋白质相互作用日益被视为小分子药物发现的靶标。衔接蛋白S100A10及其结合伴侣膜联蛋白A2之间的相互作用是潜在的重要药物靶标。为了获得这种相互作用的抑制剂的小分子起点,从S100A10和膜联蛋白A2之间的复合物的X射线晶体结构构建了三维药效团模型。药效团模型代表了两个伙伴之间有利的疏水键和氢键相互作用,以及空间和受体位点的限制(体积球除外)。使用这种药效团模型,在包含70万种市售化合物的3D库中进行了UNITY flex搜索。这产生了568种命中化合物。随后,对这些命中进行了GOLD对接研究,购买了190种化合物并进行了生化测试以抑制蛋白质相互作用。鉴定出三种化学结构相似的化合物为膜联蛋白A2与S100A10结合的真正抑制剂。 GOLD预测的结合模式与UNITY生成的构象非常吻合。我们合成了一系列类似物,揭示了对结合至关重要的区域。因此,计算预测和生化筛选可以成功地用于推导蛋白质-蛋白质相互作用阻滞剂的新化学类别。

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