华南理工大学学报（自然科学版）2025，Vol.53Issue(5)：109-117,9.DOI:10.12141/j.issn.1000-565X.240242
基于图神经网络的IL-6诱导肽预测方法
Prediction Method of IL-6 Inducing Peptides Based on Graph Neural Network
摘要
Abstract
Interleukin-6(IL-6)is a highly multifunctional glycoprotein factor that can regulate both innate and adaptive immunity as well as various aspects of metabolism,including glycolysis,fatty acid oxidation and oxidative phosphorylation.Many studies have shown that the expression and release of IL-6 in patients infected with viruses significantly increase,and are positively correlated with the severity of the disease.Therefore,identifying IL-6 in-ducing peptides and exploring their action mechanisms are very important for developing immune therapies and dia-gnostic biomarker for the severity of diseases.Currently,the identification methods of IL-6 inducing peptides mostly use traditional machine learning,in which feature selection and extraction are rather complex,and field ex-pert knowledge are required.In view of this problem,this paper proposes a novel graph neural network-based pre-diction method of IL-6 inducing peptides named SFGNN-IL6.In this method,the predicted structural characteris-tics of IL-6 inducing peptides are used to construct the adjacency matrix by screening the distance information ac-cording to the threshold,and the node features of amino acids are extracted using One-hot encoding,position encod-ing and BLOSUM62 encoding,and are then graph-represented.Moreover,graph attention mechanism layers and graph convolutional neural network layers are used as dual channels to separately extract features,considering both the update of node weights and the update of node information.Finally,the two types of features are fused for the classification of IL-6 inducing peptides.Experimental results validate that the proposed method is effective.关键词
IL-6诱导肽/图神经网络/结构特征/图注意力机制/图卷积神经网络Key words
IL-6 inducing peptide/graph neural network/structural feature/graph attention mechanism/graph convolutional neural network分类
信息技术与安全科学引用本文复制引用
曹瑞芬,胡维玲,李强生,宾艳南,郑春厚..基于图神经网络的IL-6诱导肽预测方法[J].华南理工大学学报（自然科学版）,2025,53(5):109-117,9.基金项目
国家自然科学基金项目(62373001,62272004) （62373001,62272004）
国家重点研发计划项目(2020YFA0908700) （2020YFA0908700）
安徽省高校协同创新项目(GXXT-2021-030) Supported by the National Natural Science Foundation of China(62373001,62272004)and the National Key Research and Development Program of China(2020YFA0908700) （GXXT-2021-030）
