Predicting unintended effects of drugs based on off-target tissue effects

Abstract

Unintended effects of drugs can be caused by various mechanisms. Conventional analysis of unintended effects has focused on the target proteins of drugs. However, an interaction with off-target tissues of a drug might be one of the unintended effect-related mechanisms. We propose two processes to predict a drug's unintended effects by off-target tissue effects: 1) identification of a drug's off-target tissue and; 2) tissue protein – symptom relation identification (tissue protein – symptom matrix). Using this method, we predicted that 1,177 (10.7%) side-effects were related to off-target tissue effects in 11,041 known side-effects. Off-target tissues and unintended effects of successful repositioning drugs were also predicted. The effectiveness of relations of the proposed tissue protein – symptom matrix were evaluated by using the literature mining method. We predicted unintended effects of drugs as well as those effect-related off-target tissues. By using our prediction, we are able to reduce drug side-effects on off-target tissues and provide a chance to identify new indications of drugs of interest.