[2Xin5] インタラクティブ1

[2Xin5-07] Interaction Analysis between Glycoproteins and Drugs by Mutual Attention Neural Networks

〇Eiji Shinkawa¹, Koichi Nagatsuka¹, Yuki Murata¹, Tamiko Ono¹, Masae Hosoda¹, Kiyoko Flora Kinoshita¹, Masayasu Atsumi¹ (1.Soka University)

Keywords:Glycan, Glycoprotein, Attention, Neural network

This paper proposes an attention neural network model which aims to predict and analyze interactions between drugs and glycoproteins by focusing on functions of glycans. This model firstly receives drug information, amino acid sequence information, and glycan information as input. Next, it extracts feature vectors via their respective encoders. Then, those features are weighted through mutual attention mechanism, and finally concatenated to detect interaction. The model represents the process by which a glycan mediates the interaction between glycoproteins and drugs through the attention from the glycan to the drug and the attention from the drug to the amino acid sequence. The experimental results show that the proposed mutual attention neural network predicts interactions well and attention analysis suggests candidate interactions between glycans and drugs and between drugs and amino acids.