Predictions of CCR1 chemokine receptor structure and BX 471 antagonist binding followed by experimental validation
Predictions of CCR1 chemokine receptor structure and BX 471 antagonist binding followed by experimental validation
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DOI：
10.1074/jbc.m601389200
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发表时间：
2006-09-15
影响因子：
4.8
通讯作者：
Horuk, Richard
中科院分区：
文献类型：
--
作者：
Vaidehi, Nagarajan;Schlyer, Sabine;Horuk, Richard
将基于结构的药物设计方法应用于 G 蛋白偶联受体 (GPCR) 超家族的蛋白质时面临的主要挑战是结构信息的缺乏 (1)。属于 GPCR A 类家族的 19 种趋化因子受体不仅是多发性硬化症等自身免疫性疾病的重要药物靶点，而且也是阻断人类免疫缺陷病毒 1 型进入的重要药物靶点 (2)。使用MembStruk计算方法（3），我们预测了人类CCR1受体的三维结构。此外，我们还预测了小分子 CCR1 拮抗剂 BX 471 的结合位点，该药物目前正处于 II 期临床试验中 (4)。根据预测的拮抗剂结合位点，我们设计了 17 个 CCR1 点突变体来验证预测。随后对这些突变体进行的竞争性配体结合和趋化性实验与这些预测具有良好的相关性。特别是，我们发现跨膜结构域 3 上的 Tyr-113 和 Tyr-114 以及跨膜结构域 6 上的 Ile-259 对 BX 471 的结合有显着贡献。最后，我们在 Maybridge 数据库的虚拟筛选验证中使用了预测和验证的 CCR1 结构，并接种了选择性 CCR1 拮抗剂。筛选在前 5% 的点击中识别出 63% 的 CCR1 拮抗剂。我们的结果表明，针对 GPCR 靶点进行合理的药物设计是一种可行的方法。
A major challenge in the application of structure-based drug design methods to proteins belonging to the superfamily of G protein-coupled receptors (GPCRs) is the paucity of structural information (1). The 19 chemokine receptors, belonging to the Class A family of GPCRs, are important drug targets not only for autoimmune diseases like multiple sclerosis but also for the blockade of human immunodeficiency virus type 1 entry (2). Using the MembStruk computational method (3), we predicted the three-dimensional structure of the human CCR1 receptor. In addition, we predicted the binding site of the small molecule CCR1 antagonist BX 471, which is currently in Phase II clinical trials (4). Based on the predicted antagonist binding site we designed 17 point mutants of CCR1 to validate the predictions. Subsequent competitive ligand binding and chemotaxis experiments with these mutants gave an excellent correlation to these predictions. In particular, we find that Tyr-113 and Tyr-114 on transmembrane domain 3 and Ile-259 on transmembrane 6 contribute significantly to the binding of BX 471. Finally, we used the predicted and validated structure of CCR1 in a virtual screening validation of the Maybridge data base, seeded with selective CCR1 antagonists. The screen identified 63% of CCR1 antagonists in the top 5% of the hits. Our results indicate that rational drug design for GPCR targets is a feasible approach.