Machine Learning Analysis of α-amylase Inhibitors

In this work we report a Machine Learning study of a dataset involving the α-amylase inhibitors. The prediction of α-amylase inhibitory activity as anti-diabetic is carried out using LDA and classification trees (CT). A large data set of 640 compounds for α-amylase was selected to developing the ML models. In the case of CT-J48 have the better classification model performances with values above 80- 90% for the training and prediction sets, correspondingly. The best model shows an accuracy higher than 95% for training set; the model was also validated using 10-fold cross-validation procedure and through a test set achieving accuracies values of 85.32% and 86.80%, correspondingly. The full paper was published in Chem Biol Drug Des. 2019;00:1–8. DOI: 10.1111/cbdd.13518