The work provides a new model for the prediction of the MAO-A and -B inhibitor activity by the use of combined complex networks and QSAR methodologies. On the basis of the obtained model, we prepared and assayed 33 coumarin derivatives, and the theoretical prediction was compared with the experimental activity data. The model correctly predicted 27 compounds, and most of the active derivatives showed
这项工作通过使用复杂的网络和Q
SAR方法,为预测MAO-A和-B
抑制剂的活性提供了一个新模型。在获得的模型的基础上,我们制备并测定了33种
香豆素衍
生物,并将理论预测值与实验活性数据进行了比较。该模型可以正确预测27种化合物,并且大多数活性衍
生物对MAO-A和MAO-B同种型的IC 50值均在muM-nM范围内。化合物14显示出与用作参照
抑制剂的
盐酸高粱碱相同的MAO-A抑制活性(IC 50 = 7.2 nM),并且具有最高的MAO-A特异性(比MAO-B高1000倍)。另一方面,化合物24(IC 50 = 1.2 nM)和28(IC 50 = 1.5 nM)的活性高于
司来吉兰(IC 50 = 19)。