Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan.
Mol Divers. 2012 Nov;16(4):771-85. doi: 10.1007/s11030-012-9395-9. Epub 2012 Oct 4.
B-RAF is a member of the RAF protein kinase family involved in the regulation of cell growth, differentiation, and proliferation. It forms a part of conserved apoptosis signals through the RAS-RAF-MAPK pathway. (V600E)B-RAF protein has much potential for scientific research as therapeutic target due to its involvement in human melanoma cancer. In this work, a molecular modeling study was carried out for the first time with 3D-QSAR studies by following the docking protocol on three different data sets of (V600E)B-RAF inhibitors. Based on the co-crystallized compound (PDB ID: 1UWJ), a receptor-guided alignment method was utilized to derive reliable CoMFA and CoMSIA models. The selected CoMFA model gives the best statistical values (q(2) = 0.753, r(2) = 0.962). With the same alignment protocol, a statistically reliable CoMSIA model out of fourteen different combinations was also derived (q(2) = 0.807, r(2) = 0.961). The actual predictive powers of both models were rigorously validated with an external test set, which gave satisfactory predictive r(2) values for CoMFA and CoMSIA models, 0.89 and 0.88, respectively. In addition, y-randomization test was also performed to validate our 3D-QSAR models. Contour maps from CoMFA and CoMSIA models supported statistical results, revealed important structural features responsible for biological activity within the active site and explained the correlation between biological activity and receptor-ligand interactions. Based on the developed models few new structures were designed. The newly predicted structure (IIIa) showed higher inhibitory potency (pIC(50) 6.826) than that of the most active compound of the series.
B-RAF 是 RAF 蛋白激酶家族的成员,参与细胞生长、分化和增殖的调节。它通过 RAS-RAF-MAPK 途径形成凋亡信号的一部分。(V600E)B-RAF 蛋白由于参与人类黑色素瘤癌症,因此作为治疗靶标具有很大的科研潜力。在这项工作中,首次通过遵循对接方案在三个不同的(V600E)B-RAF 抑制剂数据集上进行了 3D-QSAR 研究的分子建模研究。基于共晶化合物(PDB ID:1UWJ),使用受体导向的对齐方法得出可靠的 CoMFA 和 CoMSIA 模型。所选的 CoMFA 模型给出了最佳的统计值(q(2) = 0.753,r(2) = 0.962)。使用相同的对齐协议,还从十四个不同的组合中得出了统计学上可靠的 CoMSIA 模型(q(2) = 0.807,r(2) = 0.961)。通过外部测试集严格验证了这两个模型的实际预测能力,CoMFA 和 CoMSIA 模型的预测 r(2)值分别为 0.89 和 0.88,令人满意。此外,还进行了 y 随机化测试以验证我们的 3D-QSAR 模型。CoMFA 和 CoMSIA 模型的轮廓图支持统计结果,揭示了负责活性部位内生物活性的重要结构特征,并解释了生物活性与受体 - 配体相互作用之间的相关性。基于开发的模型,设计了一些新的结构。新预测的结构(IIIa)显示出比系列中最活跃的化合物更高的抑制效力(pIC(50) 6.826)。