Gueto Carlos, Ruiz José L, Torres Juan E, Méndez Jefferson, Vivas-Reyes Ricardo
Grupo de Química Cuántica y Teórica, Universidad de Cartagena, Programa de Química, Facultad de Ciencias Exactas y Naturales Cartagena, Colombia.
Bioorg Med Chem. 2008 Mar 1;16(5):2439-47. doi: 10.1016/j.bmc.2007.11.053. Epub 2007 Nov 28.
Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of benzotriazine derivatives, as Src inhibitors. Ligand molecular superimposition on the template structure was performed by database alignment method. The statistically significant model was established of 72 molecules, which were validated by a test set of six compounds. The CoMFA model yielded a q(2)=0.526, non cross-validated R(2) of 0.781, F value of 88.132, bootstrapped R(2) of 0.831, standard error of prediction=0.587, and standard error of estimate=0.351 while the CoMSIA model yielded the best predictive model with a q(2)=0.647, non cross-validated R(2) of 0.895, F value of 115.906, bootstrapped R(2) of 0.953, standard error of prediction=0.519, and standard error of estimate=0.178. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. Results indicate that small steric volumes in the hydrophobic region, electron-withdrawing groups next to the aryl linker region, and atoms close to the solvent accessible region increase the Src inhibitory activity of the compounds. In fact, adding substituents at positions 5, 6, and 8 of the benzotriazine nucleus were generated new compounds having a higher predicted activity. The data generated from the present study will further help to design novel, potent, and selective Src inhibitors as anticancer therapeutic agents.
作为Src抑制剂,对一系列苯并三嗪衍生物进行了比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)。通过数据库比对方法将配体分子与模板结构进行叠加。建立了包含72个分子的具有统计学意义的模型,并用6种化合物的测试集进行了验证。CoMFA模型的q(2)=0.526,非交叉验证R(2)为0.781,F值为88.132,自举R(2)为0.831,预测标准误差=0.587,估计标准误差=0.351,而CoMSIA模型产生了最佳预测模型,q(2)=0.647,非交叉验证R(2)为0.895,F值为115.906,自举R(2)为0.953,预测标准误差=0.519,估计标准误差=0.178。对从3D-QSAR研究中获得的等高线图进行分析,以评估所分析分子的活性趋势。结果表明,疏水区域的小空间体积、芳基连接区域旁边的吸电子基团以及靠近溶剂可及区域的原子会增加化合物的Src抑制活性。事实上,在苯并三嗪核的5、6和8位添加取代基可生成预测活性更高的新化合物。本研究产生的数据将进一步有助于设计新型、高效和选择性的Src抑制剂作为抗癌治疗药物。