Drug-Target Interaction Prediction Based on Multi-path Graph Convolution and Graph-Level Attention Mechanism | Advanced Intelligent Computing in Bioinformatics (2025)

Article

Authors: Weiwenzheng Liu, Xiaolong Zhang, Xiaoli Lin, Jing Hu

Advanced Intelligent Computing in Bioinformatics: 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part II

Pages 143 - 154

Published: 05 August 2024 Publication History

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Abstract

Drug-target interaction (DTIs) prediction is crucial for drug discovery and repositioning, but traditional biological experimental methods are time-consuming and expensive. Therefore, deep learning-based methods have been widely applied in the field of DTIs prediction. In recent years, methods utilizing graph convolutional neural networks to learn the features of drug-protein pairs (DPPs) and thus achieve DTI prediction have achieved certain success. However, these methods struggle to effectively integrate the topological and semantic features of DPPs and capture their interaction relationships when learning the features of DPPs. Therefore, this paper proposes a DTI prediction model named HMFGCN-DTI, which utilizes multi-path graph convolution and graph-level attention mechanism to learn features of DPPs. Experimental results indicate that compared to other state-of-the-art methods, the proposed approach demonstrates higher accuracy and generalization capability.

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Li, A., Lin, X., Yu, H.: Inferring DTIs based on similarity clustering and CaGCN-DTI model from heterogeneous network. In: 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2399–2406. IEEE, Location (2021)

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Rayhan, F., Ahmed, S., Mousavian, Z., et al.: FRnet-DTI: Deep convolutional neural network for drug-target interaction prediction. Heliyon 6(3) (2020)

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Index Terms

  1. Drug-Target Interaction Prediction Based on Multi-path Graph Convolution and Graph-Level Attention Mechanism

    1. Applied computing

      1. Life and medical sciences

        1. Bioinformatics

          1. Computational biology

            1. Biological networks

              1. Molecular structural biology

                1. Recognition of genes and regulatory elements

            2. Computing methodologies

              1. Machine learning

                1. Learning paradigms

                  1. Supervised learning

              2. Theory of computation

                1. Theory and algorithms for application domains

                  1. Machine learning theory

                    1. Structured prediction

              Index terms have been assigned to the content through auto-classification.

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              Published In

              Drug-Target Interaction Prediction Based on Multi-path Graph Convolution and Graph-Level Attention Mechanism | Advanced Intelligent Computing in Bioinformatics (1)

              Advanced Intelligent Computing in Bioinformatics: 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part II

              Aug 2024

              504 pages

              ISBN:978-981-97-5691-9

              DOI:10.1007/978-981-97-5692-6

              • Editors:
              • De-Shuang Huang

                https://ror.org/036mbz113Eastern Institute of Technology, Ningbo, China

                ,
              • Yijie Pan

                https://ror.org/036mbz113Eastern Institute of Technology, Ningbo, China

                ,
              • Qinhu Zhang

                https://ror.org/036mbz113Eastern Institute of Technology, Ningbo, China

              © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

              Publisher

              Springer-Verlag

              Berlin, Heidelberg

              Publication History

              Published: 05 August 2024

              Author Tags

              1. Drug-target Interactions
              2. Deep Learning
              3. Drug-protein Pairs (DPP)
              4. Graph Convolutional Neural Networks
              5. Graph-level Attention Mechanism

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              Drug-Target Interaction Prediction Based on Multi-path Graph Convolution and Graph-Level Attention Mechanism | Advanced Intelligent Computing in Bioinformatics (2)

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