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A3 腺苷受体:同源建模和 3D-QSAR 研究。

A3 adenosine receptor: homology modeling and 3D-QSAR studies.

机构信息

Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche (STEBICEF) - Sezione di Chimica Farmaceutica e Biologica, Università degli Studi di Palermo, Via Archirafi 32, 90123 Palermo, Italy.

出版信息

J Mol Graph Model. 2013 May;42:60-72. doi: 10.1016/j.jmgm.2013.03.001. Epub 2013 Mar 19.

Abstract

Adenosine receptors (AR) belong to the superfamily of G-protein-coupled receptors (GPCRs). They are divided into four subtypes (A1, A2A, A2B, and A3) and can be distinguished on the basis of their distinct molecular structures, distinct tissues distribution, and selectivity for adenosine analogs. The hA3R, the most recently identified adenosine receptor, is involved in a variety of intracellular signaling pathways and physiological functions. Expression of hA3R was reported to be elevated in cancerous tissues and A3 antagonists could be proposed for therapeutic treatments of tumor. By using the crystal structure of hA2A adenosine receptor, recently published, we were able to obtain a model for A3R, further optimized using nanosecond scale molecular dynamics simulation. One hundred twenty two active and selective compounds were docked into this model and used as training set to generate pharmacophore models. These last address the prevalent features to be used for the search of new inhibitors. Therefore, it was employed as template to screen the ZINC database in the attempt to find new potent and selective human A3R antagonists. Our theoretical model of hA3 adenosine receptor was used to evaluate and quantify the structure-activity relationship of known antagonists. Moreover the obtained 3D-QSAR model allowed to identify new potential inhibitors.

摘要

腺苷受体(AR)属于 G 蛋白偶联受体(GPCR)超家族。它们分为四个亚型(A1、A2A、A2B 和 A3),可以根据其独特的分子结构、不同的组织分布以及对腺苷类似物的选择性来区分。hA3R 是最近发现的一种腺苷受体,参与多种细胞内信号通路和生理功能。研究报道 hA3R 在癌组织中表达上调,A3 拮抗剂可用于肿瘤的治疗。利用最近发表的 hA2A 腺苷受体的晶体结构,我们获得了 A3R 的模型,并进一步使用纳秒级别的分子动力学模拟对其进行了优化。将 122 种活性和选择性化合物对接入该模型中,并将其用作训练集来生成药效团模型。这些模型旨在研究新抑制剂,用于寻找新的有效且选择性的人 A3R 拮抗剂。因此,我们将该模型用作模板,对 ZINC 数据库进行筛选,试图找到新的强效和选择性的人 A3R 拮抗剂。我们使用 hA3 腺苷受体的理论模型来评估和量化已知拮抗剂的结构-活性关系。此外,获得的 3D-QSAR 模型还可以识别新的潜在抑制剂。

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