Bhargava Kiran, Seth Prahlad Kishore, Pant Kamlesh Kumar, Dixit Rakesh Kumar, Agarwal Vivek, Sawlanid Kamal Kumar, Nath Rajendra
King George's Medical University Erstwhile CSMMU, Lucknow, UP, India.
Biotech Park, Lucknow, UP, India.
Bioinformation. 2020 Sep 30;16(9):666-671. doi: 10.6026/97320630016666. eCollection 2020.
Dopamine (D2) receptors are known drug targets for various antipsychotics used in Schizophrenia. Therefore, it is of interest to analyze the binding features of D2 receptors with known olanzapine derivatives for further consideration using molecular docking and QSAR analysis. A 2D QSAR model was built using energy-based descriptors generated by docking as independent variable and known Ki value of Olanzapine derivatives with D2 Receptor as dependent variable. QSAR model provided coefficient of determination of r2 of 0.7 in multiple linear regression analysis. The predictive performance of QSAR model was assessed using different cross-validation procedures. Thus, data shows that a ligand-receptor binding interaction for D2 Receptor using a QSAR model is promising approach to design novel and potent inhibitors of D2 Receptor.
多巴胺（D2）受体是精神分裂症中使用的各种抗精神病药物已知的药物靶点。因此，分析D2受体与已知奥氮平衍生物的结合特征，以便使用分子对接和定量构效关系（QSAR）分析进行进一步研究，这一点很有意义。使用对接生成的基于能量的描述符作为自变量，以及奥氮平衍生物与D2受体的已知抑制常数（Ki）值作为因变量，建立了二维QSAR模型。在多元线性回归分析中，QSAR模型的决定系数r2为0.7。使用不同的交叉验证程序评估了QSAR模型的预测性能。因此，数据表明，使用QSAR模型研究D2受体的配体-受体结合相互作用是设计新型强效D2受体抑制剂的一种有前景的方法。
