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基于结构的 G 蛋白偶联受体配体功能预测:β-肾上腺素能受体案例研究。

Structure-Based Prediction of G-Protein-Coupled Receptor Ligand Function: A β-Adrenoceptor Case Study.

机构信息

Amsterdam Institute for Molecules, Medicines and Systems (AIMMS), Division of Medicinal Chemistry, Faculty of Science, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands.

出版信息

J Chem Inf Model. 2015 May 26;55(5):1045-61. doi: 10.1021/acs.jcim.5b00066. Epub 2015 May 1.

Abstract

The spectacular advances in G-protein-coupled receptor (GPCR) structure determination have opened up new possibilities for structure-based GPCR ligand discovery. The structure-based prediction of whether a ligand stimulates (full/partial agonist), blocks (antagonist), or reduces (inverse agonist) GPCR signaling activity is, however, still challenging. A total of 31 β1 (β1R) and β2 (β2R) adrenoceptor crystal structures, including antagonist, inverse agonist, and partial/full agonist-bound structures, allowed us to explore the possibilities and limitations of structure-based prediction of GPCR ligand function. We used all unique protein-ligand interaction fingerprints (IFPs) derived from all ligand-bound β-adrenergic crystal structure monomers to post-process the docking poses of known β1R/β2R partial/full agonists, antagonists/inverse agonists, and physicochemically similar decoys in each of the β1R/β2R structures. The systematic analysis of these 1920 unique IFP-structure combinations offered new insights into the relative impact of protein conformation and IFP scoring on selective virtual screening (VS) for ligands with a specific functional effect. Our studies show that ligands with the same function can be efficiently classified on the basis of their protein-ligand interaction profile. Small differences between the receptor conformation (used for docking) and reference IFP (used for scoring of the docking poses) determine, however, the enrichment of specific ligand types in VS hit lists. Interestingly, the selective enrichment of partial/full agonists can be achieved by using agonist IFPs to post-process docking poses in agonist-bound as well as antagonist-bound structures. We have identified optimal structure-IFP combinations for the identification and discrimination of antagonists/inverse agonist and partial/full agonists, and defined a predicted IFP for the small full agonist norepinephrine that gave the highest retrieval rate of agonists over antagonists for all structures (with an enrichment factor of 46 for agonists and 8 for antagonists on average at a 1% false-positive rate). This β-adrenoceptor case study provides new insights into the opportunities for selective structure-based discovery of GPCR ligands with a desired function and emphasizes the importance of IFPs in scoring docking poses.

摘要

G 蛋白偶联受体 (GPCR) 结构测定的惊人进展为基于结构的 GPCR 配体发现开辟了新的可能性。然而,基于结构预测配体是否刺激 (完全/部分激动剂)、阻断 (拮抗剂) 或减少 (反向激动剂) GPCR 信号活性仍然具有挑战性。总共 31 个β1(β1R)和β2(β2R)肾上腺素能受体晶体结构,包括拮抗剂、反向激动剂和部分/完全激动剂结合结构,使我们能够探索基于结构预测 GPCR 配体功能的可能性和局限性。我们使用源自所有配体结合β-肾上腺素能晶体结构单体的所有独特的蛋白-配体相互作用指纹 (IFP),在后处理已知的β1R/β2R 部分/完全激动剂、拮抗剂/反向激动剂以及在每个β1R/β2R 结构中的物理化学相似的诱饵的对接构象。对这些 1920 个独特 IFP-结构组合的系统分析为相对影响提供了新的见解,即蛋白构象和 IFP 评分对具有特定功能效应的配体的选择性虚拟筛选 (VS) 的影响。我们的研究表明,可以根据其蛋白-配体相互作用谱有效地对具有相同功能的配体进行分类。然而,受体构象(用于对接)和参考 IFP(用于对接构象评分)之间的微小差异决定了特定配体类型在 VS 命中列表中的富集。有趣的是,通过使用激动剂 IFP 在后处理激动剂结合和拮抗剂结合结构中的对接构象,可以选择性地富集部分/完全激动剂。我们已经确定了用于识别和区分拮抗剂/反向激动剂和部分/完全激动剂的最佳结构-IFP 组合,并为小的完全激动剂去甲肾上腺素定义了一个预测 IFP,该 IFP在所有结构中提供了最高的激动剂检索率,而拮抗剂的检索率为所有结构(平均激动剂的富集因子为 46,拮抗剂为 8,假阳性率为 1%)。这个β-肾上腺素能受体案例研究为具有所需功能的 GPCR 配体的选择性基于结构的发现提供了新的见解,并强调了 IFP 在对接构象评分中的重要性。

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