Detecting Drug-Drug Interactions using Protein Sequence-Structure Similarity Networks
Saminur Islam, Ahmed Abbasi, Nitin Agarwal, Wanhong Zheng, Gianfranco Doretto, Donald Adjeroh · 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · 2021
Adverse drug events represent a key challenge in public health, especially with respect to drug safety profiling and drug surveillance. Drug-drug interactions represent one of the most popular types of adverse drug events. Most computational approaches to this problem have used different types of data, such as drug chemical structure, information about protein targets, side effects, pathways, etc to predict potential interactions between drugs. In this work, we study the question of whether using just genetic information about the drugs can provide significant information about the potential safety profile for a given drug. We propose a novel neural network model to predict adverse drug events using only data about the protein sequence and protein structure associated with the drug targets. We compare the results with those from the state-of-the-art methods on this problem. Our results show that the proposed method is quite competitive, at times outperforming the state-of-the-art.