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Mapping the Druggable Allosteric Space of G-Protein Coupled Receptors: a Fragment-Based Molecular Dynamics Approach

机译:映射的G蛋白偶联受体的药物变构空间:基于片段的分子动力学方法。

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摘要

To address the problem of specificity in G-protein coupled receptor (GPCR) drug discovery, there has been tremendous recent interest in allosteric drugs that bind at sites topographically distinct from the orthosteric site. Unfortunately, structure-based drug design of allosteric GPCR ligands has been frustrated by the paucity of structural data for allosteric binding sites, making a strong case for predictive computational methods. In this work, we map the surfaces of the β1 (β1AR) and β2 (β2AR) adrenergic receptor structures to detect a series of five potentially druggable allosteric sites. We employ the FTMAP algorithm to identify ‘hot spots’ with affinity for a variety of organic probe molecules corresponding to drug fragments. Our work is distinguished by an ensemble-based approach, whereby we map diverse receptor conformations taken from molecular dynamics (MD) simulations totaling approximately 0.5 μs. Our results reveal distinct pockets formed at both solvent-exposed and lipid-exposed cavities, which we interpret in light of experimental data and which may constitute novel targets for GPCR drug discovery. This mapping data can now serve to drive a combination of fragment-based and virtual screening approaches for the discovery of small molecules that bind at these sites and which may offer highly selective therapies.
机译:为了解决G蛋白偶联受体(GPCR)药物发现中的特异性问题,最近人们对在与正构位点在地形学上不同的位点结合的变构药物产生了极大的兴趣。不幸的是,变构GPCR配体的基于结构的药物设计因变构结合位点的结构数据不足而受挫,这为预测计算方法提供了有力依据。在这项工作中,我们绘制了β1(β1AR)和β2(β2AR)肾上腺素能受体结构的表面图,以检测一系列五个潜在可药物化的变构位点。我们采用FTMAP算法来识别对与药物片段相对应的各种有机探针分子具有亲和力的“热点”。我们的工作以基于整体的方法而著称,该方法可绘制从分子动力学(MD)模拟中获取的各种受体构象,总计约0.5μs。我们的结果揭示了在暴露于溶剂的腔室和暴露于脂质的腔室上都形成了明显的囊袋,我们根据实验数据对其进行了解释,这可能构成GPCR药物发现的新靶标。现在,该映射数据可用于驱动基于片段的筛选方法和虚拟筛选方法的组合,以发现在这些位点结合并可能提供高度选择性疗法的小分子。

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