关键词: 血管紧张素转换酶抑制剂（ACEI）, 分子对接, 机器学习, 支持向量机

Abstract: Angiotensin Converting Enzyme Inhibitor（ACEI） plays an important role in the treatment of hypertension. Candidate small molecular data sets are constructed from the database of complex compounds and the sample sets obtained from the data set using molecular docking techniques are used to construct the classification model. The classification model of angiotensin converting enzyme inhibitors and non inhibitors is established by using support vector machine, [K] nearest neighbor, decision tree, random forest and Naive Bayes method, respectively. The support vector machine has higher prediction rate compared with other methods and the overall prediction and correlation coefficients of the model are 82. 4% and 0. 653, respectively. The results show that the support vector machine method has a good effect on the virtual screening of angiotensin converting enzyme inhibitors.

Key words: Angiotensin Converting Enzyme Inhibitor（ACEI）, molecular docking, machine learning, support vector machine