表征GPCR蛋白亚家族配体的共同亚结构。

Bekir Erguner, M. Hattori, S. Goto, M. Kanehisa
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引用次数: 2

摘要

g蛋白偶联受体(GPCR)超家族是最大的一类具有治疗价值的蛋白质。目前超过40%的处方药是GPCR配体。GPCR蛋白的高治疗价值和虚拟筛选方法的最新进展,引起了许多GPCR配体的虚拟筛选研究。然而,尽管对其功能和特性进行了大量的研究,但大多数gpcr的三维结构仍然未知。这使得基于靶标的GPCR配体虚拟筛选非常困难,而成功的虚拟筛选技术在很大程度上依赖于配体信息。这些虚拟筛选方法侧重于配体在GPCR蛋白水平上的特异性特征,配体在更高水平GPCR分类上的共性特征尚待研究。本文提取了GPCR蛋白亚家族中GPCR配体的共同亚结构。我们使用SIMCOMP(一个基于图的化学结构比较程序)和分层聚类来揭示共同的子结构。我们将该方法应用于850个GPCR配体,发现53个共同亚结构覆盖439个配体。这些亚结构有助于更深入地了解GPCR配体的结构特征,可用于新药物发现方法。
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Characterizing common substructures of ligands for GPCR protein subfamilies.
The G-protein coupled receptor (GPCR) superfamily is the largest class of proteins with therapeutic value. More than 40% of present prescription drugs are GPCR ligands. The high therapeutic value of GPCR proteins and recent advancements in virtual screening methods gave rise to many virtual screening studies for GPCR ligands. However, in spite of vast amounts of research studying their functions and characteristics, 3D structures of most GPCRs are still unknown. This makes target-based virtual screenings of GPCR ligands extremely difficult, and successful virtual screening techniques rely heavily on ligand information. These virtual screening methods focus on specific features of ligands on GPCR protein level, and common features of ligands on higher levels of GPCR classification are yet to be studied. Here we extracted common substructures of GPCR ligands of GPCR protein subfamilies. We used the SIMCOMP, a graph-based chemical structure comparison program, and hierarchical clustering to reveal common substructures. We applied our method to 850 GPCR ligands and we found 53 common substructures covering 439 ligands. These substructures contribute to deeper understanding of structural features of GPCR ligands which can be used in new drug discovery methods.
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