Prediction of Protein–Protein Interaction Sites Based on Stratified Attentional Mechanisms - Tang, Minli; Wu, Longxin; Yu, Xinyu; Chu, Zhaoqi; Jin, Shuting; Liu, Juan (Frontiers in Genetics, 2021)
Proteins are the basic substances that undertake human life activities, and they often perform their biological functions through interaction with other biological macromolecules, such as cell transmission and signal transduction. Predicting the interaction sites between proteins can deepen the understanding of the principle of protein interaction, but traditional experimental methods are time-consuming and labor-intensive. In this study, a new Hierarchical Attention Networks network structure, named HANPPIS, through adding six effective features of protein sequence feature, position-specific scoring matrix (PSSM), secondary structure feature, pre-training vector feature, hydrophilic feature and amino acid position feature, is proposed to predict Protein-protein interaction sites. The experimental results proved that our model has obtained very effective results, which was better than the existing advanced calculation methods. More importantly, we used the double-layer attention mechanism to improve the interpretability of the model, and to a certain extent solved the problem of the "black box" of deep neural networks, which can be used as a reference for location positioning on the biological level.