Mustyala Kiran Kumar, Chitturi Annapurna Renee, Naikal James Prameela Subhashini, Vuruputuri Uma
Department of Chemistry, Nizam College, Osmania University, Basheerbagh, Hyderabad, Andhra Pradesh, India.
J Recept Signal Transduct Res. 2012 Apr;32(2):102-13. doi: 10.3109/10799893.2012.660532. Epub 2012 Mar 2.
A(2A) adenosine receptor (AR) antagonists play an important role in neurodegenerative diseases like Parkinson's disease. A 3D-QSAR study of A(2A) AR antagonists, was taken up to design best pharmacophore model. The pharmacophoric features (ADHRR) containing a hydrogen bond acceptor (A), a hydrogen bond donor (D), a hydrophobic group (H) and two aromatic rings (R), is projected as the best predictive pharmacophore model. The QSAR model was further treated as a template for in silico search of databases to identify new scaffolds. The binding patterns of the leads with A(2A) AR are analysed using docking studies and novel potent ligands of A(2A) AR are projected.
A（2A）腺苷受体（AR）拮抗剂在帕金森病等神经退行性疾病中发挥着重要作用。开展了一项关于A（2A）AR拮抗剂的3D-QSAR研究，以设计最佳药效团模型。包含氢键受体（A）、氢键供体（D）、疏水基团（H）和两个芳香环（R）的药效特征（ADHRR）被预测为最佳预测药效团模型。该QSAR模型进一步用作数据库虚拟搜索的模板，以识别新的支架。通过对接研究分析先导化合物与A（2A）AR的结合模式，并预测A（2A）AR的新型强效配体。
