Prediction of Drug–Drug Interactions by Using Profile Fingerprint Vectors and Protein Similarities

Abstract

In this study, we developed a computational approach to the prediction of potential drug interactions. The performance of the similarity-based computational methods was comparatively evaluated using a comprehensive real-world DDI dataset. The evaluations showed that the drug interaction profile information is a better predictor of DDIs compared to drug adverse effects and protein similarities among DDI pairs.