应用神经网络方法研究3-甲基芬太尼类似物的定量构-效关系(英文)

QSAR of 3-methylfentanyl derivatives studied with neural networks method

目的:应用神经网络这种新型的信息处理系统研究定量构-效关系.方法:应用自编的逆传播神经网络算法,结合偏最小二乘法,研究了25个3-甲基芬太尼类似物的量子化学指数和镇痛活性之间的定量关系.结果:得到了良好的QSAR模型,3-甲基芬太尼类似物的量子化学指数即N_1和O_(16)上净电荷、C_(10)-C_9-N_8-C_4二面角、C_7-PhA中心的距离与镇痛活性之间具有很好的相关性,并根据计算结果,提出了芬太尼类似物与阿片受体的结合模式.结论:神经网络方法研究结果优于单纯偏最小二乘法的结果,且能对化合物活性进行准确的预测.

AIM:To use neural networks, which simulate the functions of living nervous systems, in QSAR studies; METHODS: Using the back-propagation neural networks program devised by us, combining with partial least squares (PLS) method, we studied the relationships of quantum chemical indices and analgesic activities of 25 3-methylfentanyl derivatives; RESULTS: Through learning process, a good QSAR model was established, and the activities of these compounds were predicted; the correlation between the activities and quantum chemical indices; the net charge of the atom N1,the net charge of the atom O16, the torsional angle of atoms C10-C9-N8-C4, the interatomic distance between atom C7 and the center of phenyl plane C9-14 (PhA) , is quite well-matched. Based on these results, an interactive pattern between 3-methylfentanyl derivatives and opioid receptors was suggested; CONCLUSION: Not only are the results of neural networks superior to those of PLS method but they also provide accurate predictions of the activity of the compounds and also combine the PLS method with neural networks.