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Rhodopsin and the others: A historical perspective on structural studies of G protein-coupled receptors

机译：罗地甙和其他：关于G蛋白偶联受体的结构研究的历史视角

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摘要

The role of rhodopsin as a structural prototype for the study of the whole superfamily of G protein-coupled receptors (GPCRs) is reviewed in an historical perspective. Discovered at the end of the nineteenth century, fully sequenced since the early 1980s, and with direct three-dimensional information available since the 1990s, rhodopsin has served as a platform to gather indirect information on the structure of the other superfamily members. Recent breakthroughs have elicited the solution of the structures of additional receptors, namely the β1- and β2-adrenergic receptors and the A2A adenosine receptor, now providing an opportunity to gauge the accuracy of homology modeling and molecular docking techniques and to perfect the computational protocol. Notably, in coordination with the solution of the structure of the A2A adenosine receptor, the first "critical assessment of GPCR structural modeling and docking" has been organized, the results of which highlighted that the construction of accurate models, although challenging, is certainly achievable. The docking of the ligands and the scoring of the poses clearly emerged as the most difficult components. A further goal in the field is certainly to derive the structure of receptors in their signaling state, possibly in complex with agonists. These advances, coupled with the introduction of more sophisticated modeling algorithms and the increase in computer power, raise the expectation for a substantial boost of the robustness and accuracy of computer-aided drug discovery techniques in the coming years.
机译：罗地脂作为研究G蛋白偶联受体（GPCR）全部超家族的结构原型的作用是以历史的观点审查的。在十九世纪末发现，自20世纪80年代初自9世纪80年代初完全测序，并以自20世纪90年代以来可用的直接三维信息，罗地甙曾作为一个平台，以收集关于其他超家族成员的结构的间接信息。最近的突破引发了额外受体的结构的溶液，即β1和β2-肾上腺素能受体和A2A腺苷受体，现在提供机会来衡量同源性建模和分子对接技术的准确性，并完善计算协议。值得注意的是，在与A2A腺苷受体的结构的解决方案协调中，已经组织了第一个“GPCR结构建模和对接的关键评估”，结果突出显示准确模型的建设虽然具有挑战性，但肯定是可实现的。配体的对接和姿势的得分清晰地成为最困难的组件。该领域的另一个目标肯定是在其信号传导状态下导出受体的结构，可能是与激动剂复合物。这些进步与引进更复杂的建模算法和计算机电量的增加，提高了未来几年计算机辅助药物发现技术的鲁棒性和准确性的预期。

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