Graph Convolutional Neural Networks for Predicting Drug-Target Interactions

Cited by (365)

Items 301–365 of 365

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2. CarbonAI, A Non-Docking Deep learning based small molecule virtual screening platform
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4. CBSF: A New Empirical Scoring Function for Docking Parameterized by Weights of Neural Network
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9. Protein–Protein Interactions Prediction Base on Multiple Information Fusion via Graph Representation Learning
   Yan Li, Yu-Ren Zhang, Ping Zhang, Dongxu Li, Tianlong Xiao · 2022 · Journal of Biomaterials and Tissue Engineering
10. The Role of Big Data Analytics in Drug Discovery and Vaccine Development Against COVID-19
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13. PocketAnchor: Learning Structure-Based Pocket Representations for Protein-Ligand Interaction Prediction
    Shuya Li, Tingzhong Tian, Ziting Zhang, Ziheng Zou, Dan Zhao, Jianyang Zeng · 2022 · SSRN Electronic Journal
14. APIP: Attention-based Protein Representation Learning for Protein-Ligand Interface Prediction
    Tian Xia, Bo Hui, Wei‐Shinn Ku · 2022 · IEEE International Conference on Big Data (BigData)
15. PandoraRLO: DQN and Graph convolution based method for optimized ligand pose
    Justin Jose, Ujjaini Alam A, Divye Singh, Nidhi Jatana, Pooja Arora · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
16. GcnSV: A Method Based on Deep Learning of Calling Structural Variations from the Third-Generation Sequencing Data
    Meng Huang, Han Wang, Jingyang Gao · 2023 · Communications in computer and information science
17. Drug-Target Interaction Prediction Based on Interpretable Graph Transformer Model
    Baozhong Zhu, Runhua Zhang, Tengsheng Jiang, Zhiming Cui, Hongjie Wu · 2023 · Lecture notes in computer science
18. Therapeutics and Diagnostics Discovery
    Daria Mochly‐Rosen, Kevin Grimes, Rami N. Hannoush, B. Koch, Gretchen Marie Ehrenkaufer, Daniel A. Erlanson, Julie Saiki, Jennifer L. Wilson, Shelley Force Aldred, Adriana Ann Garcia et al. · 2023 · Springer eBooks
19. PandoraRLO: Unveiling Protein-Ligand Interactions with Reinforcement Learning for Optimized Pose Prediction
    Justin Jose, Ujjaini Alam A, Divye Singh, Pooja Arora · 2023 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
20. Binding Affinity Prediction with 3D Machine Learning: Training Data and Challenging External Testing
    José Carlos Gómez-Tamayo, Lili Cao, Mazen Ahmad, Gary Tresadern · 2024 · Research Square
21. Deep Learning based Models for Drug-Target Interactions
    Ali K. Abdul Raheem, Ban Nadeem Dhannoon · 2024 · Baghdad Science Journal
22. Research and Implementation of Drug Relocation Algorithm Based on Deep Learning
    Haodong Zhang, Ren Tao, Li Yueqi, Wang Yuqing, Xiao Jiacheng, Huang Yuxuan, Lu Chen, Guan Xiangxin · 2024 · International Conference on Computer and Automation Engineering
23. Drug-Target Interaction Prediction Based on Multi-path Graph Convolution and Graph-Level Attention Mechanism
    Weiwenzheng Liu, Xiaolong Zhang, Xiaoli Lin, Jing Hu · 2024 · Lecture notes in computer science
24. Improving drug–target interaction prediction through dual-modality fusion with InteractNet
    Baozhong Zhu, Runhua Zhang, Tengsheng Jiang, Zhiming Cui, Jing Chen, Hongjie Wu · 2024 · Journal of Bioinformatics and Computational Biology
25. HeteroRepur: Efficient Modeling of Heterogeneous Disease Graph for Depression Drug Repurposing using Heterogeneous Graph Neural Networks
    Ko‐Hong Lin, Tongtong Huang, Kai Zhang, Xiaoqian Jiang, Yejin Kim · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
26. Protocol for a Graph Database of NTDs for Drug Repurposing
    André Giordani, Duncan D. Ruiz · 2025 · Lecture notes in networks and systems
27. PVEIN: A Pretrained Vertex Embedding Infer Network for Open-Domain Question Answer Scoring
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28. Application of Graph Neural Networks in Screening p38α MAPK Inhibitors in Natural Products
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29. AIRES: Accelerating Out-of-Core GCNs via Algorithm-System Co-Design
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30. TGTNet: Graph Transformer-Based Architecture for Drug-Target Interaction Prediction
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31. ECLIPSE: Exploration of Complex Ligand-Protein Interactions through Learning from Systems-level Heterogeneous Biomedical Knowledge Graphs
    Heval Ataş, Tunca Doğan · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
32. Multi-Classification of Drug–Drug interaction based on a complete graph convolutional neural network and explainable artificial intelligence
    Samar Monem, Ashraf Darwish, Aboul Ella Hassanien, Heba M. Afify · 2025 · Journal of Bioinformatics and Computational Biology
33. Research on drug molecule structure prediction and target recognition based on graph neural networks
    Wen Zhong, Bo Gui · 2025 · International Conference on Biomedicine and Intelligent Technology (ICBIT)
34. Additional file 2 of A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data
    Li, Baiqing, Shimin Su, Chan Zhu, Lin, Jie, Hu, Xinyue, Lebin Su, Zhunzhun Yu, Kuangbiao Liao, Chen, Hongming · 2024 · Figshare
35. Additional file 1 of A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data
    Li, Baiqing, Shimin Su, Chan Zhu, Lin, Jie, Hu, Xinyue, Lebin Su, Zhunzhun Yu, Kuangbiao Liao, Chen, Hongming · 2024 · Figshare
36. Additional file 1 of An end-to-end method for predicting compound-protein interactions based on simplified homogeneous graph convolutional network and pre-trained language model
    Zhang, Yufang, Li, Jiayi, Shenggeng Lin, Zhao, Jianwei, Xiong, Yi, Wei, Dong-Qing · 2024 · Figshare
37. Artificial Intelligence for Drug Target and Pathway Identification, Assessment, Validation, and Indication Expansion
    Geoffrey Ho Duen Leung, Frank W. Pun, Vladimir Naumov, David G. Gennert, Petrina R. N. Kamya, Alex Aliper, Feng Ren, Alex A. Zhavoronkov · 2026 · Springer eBooks
38. DeepHybridCPI: A hybrid deep learning framework for compound–protein interaction prediction
    Areen Rasool, Jamshaid Ul Rahman, Qasim Ali · 2026 · Journal of Molecular Graphics and Modelling
39. Equivariant Hierarchical Graph Interaction Network for Protein-Ligand Affinity Prediction
    Xiaoyu Ling, Dongxi Li · 2025 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
40. MICA-DTI: Multi-Modal Intra and Cross Attention for Drug-Target Interaction Prediction
    Zhihui Yang, Binfeng Liu, Kai Yan, Yingyu Huo, Haoliang Qi · 2025 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
41. Deep Graph Learning Approaches for Protein-Ligand Binding Site Prediction
    V Shobha Rani, S. Venu Gopal, S. Deepan, Adepu Ranjith Kumar · 2025 · International Conference for Advancement in Technology (ICONAT)
42. MSIGN: A deep learning framework based on multi-scale interaction graph neural networks for predicting binding of synthetic cannabinoids to receptors
    Zhenyong Cheng, Dinghao Liu, Yuanpeng Fu, Kewei Sheng, Yan Xing, Yanling Qiao, Shangxuan Cai, Jubo Wang, Peng Xu, Bin Di et al. · 2026 · Digital Discovery
43. Drug-Target Interaction Prediction with PIGLET
    Kristy A. Carpenter, Russ Biagio Altman · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
44. GRANII: Selection and Ordering of Primitives in GRAph Neural Networks using Input Inspection
    Damitha Lenadora, Vimarsh Sathia, Gerasimos Gerogiannis, Şerif Yeşil, Josep Torrellas, Charith Mendis · 2026 · Proceedings of the CGO/Proceedings of the ... CGO
45. A Dual-Cross Contrastive Neural Network Based on Molecular Graph with Simplified Feature for Molecular Property Prediction
    Jiandong Zhang, Zhihong Jiang, Chunyan Li · 2025 · International Conference on Data Science and Intelligent Systems (DSIS)
46. Drug repurposing: Innovative antimicrobial strategies for discovering new antibiotics
    Qing Luo, Jingjing Guo · 2026 · Elsevier eBooks
47. Design and application of deep learning methods to structure-based drug design
    Mikhail Volkov · 2023 · theses.fr (ABES)
48. Structural prediction of protein assemblies with deep learning
    Hélène Bret · 2023 · theses.fr (ABES)
49. Docking et Deep Learning : affinement de méthodologies in silico pour le développementde stratégies thérapeutiques innovantes
    Kévin Crampon · 2023
50. Integrated model for drug-target interaction prediction leveraging multiple protein language embeddings
    Shasha Tao, Jin Liu, Min Xiang, Xin Ma, Tongtong Huo, Xiaolin Ning · 2026 · Biomedical Signal Processing and Control
51. ADME‐DTI: Augmented Deep Meta Ensemble for Drug–Target Interaction Prediction
    Tariq Sha’ban, Ahmad M. Mustafa, Mostafa Z. Ali, Talal Z. Ali · 2026 · Molecular Informatics
52. Machine Learning Networks System (MLNS) A Multi-objective Machine Learning Framework for Network Structured Data
    Kranthi Kumar Singamaneni, Bomma Ramakrishna, M. Siva Ganga Prasad, Ramesh Babu Pittala, Gandham Naga Visweswara Rao, Medikonda Asha Kiran · 2026 · Lecture notes in networks and systems
53. Graph Neural Networks for Kinase–Inhibitor Affinity Prediction Using Docking Scores and Binding-Site Features
    Michael Turner, Sophia Nguyen, David Clark, Emma Wilson · 2024 · Pharmacophore
54. Equivariant Neural Networks for Protein–Ligand Pose Refinement Using Atomic Coordinates and Interaction Energies
    Ali Hassan, Noor Siddiqui, Bilal Khan, Sana Malik · 2025 · Pharmacophore
55. Sequence-based prediction of drug–target binding using machine learning, deep learning and ensemble models without 3D structural information
    Nazife Çevik, Taner Çevik, Ahmet Gürhanlı · 2026 · Scientific Reports
56. Descriptor-Aware Meta-Ensemble Learning Reveals Cross-Target Pharmacophore Recognition Patterns Across CNS-Related Therapeutic Targets
    Tangilal Dihan Chowdhury, Maisha Farzana, Md Ushama Shafoyat, Md Tobibul Islam, Arpita Shil Puja, Jafrin Sultana, Syed Rashedul Haque, Kazy Noor e Alam Siddiquee, Mizanul Chowdhury, Maruf Hasan et al. · 2026 · Research Square
57. Graph-based drug–target interaction modeling: from representation learning to output-driven drug discovery
    Thành Nguyen, Hiến Minh Tô, Duy Anh Nguyen, Duy Trieu, Giang Nguyen · 2026 · Briefings in Bioinformatics
58. Lead Optimization in Natural Product Chemical Space: A Methodological Model for Generative Design, Activity Prediction, Synthetic Feasibility, and Pharmacological Plausibility
    Peter Nilsson, Eva Johansson, Lars Andersson · 2025 · International Journal of Pharmaceutical and Phytopharmacological Research
59. Leveraging Machine Learning for Network Pharmacology
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60. DeepACPred: an integrated multistage framework for anticancer peptide discovery and activity prediction
    Bo Zhang, Ruifang Li, Kedong Yin, Yufeng Yang, Jinhua Zhang, Mengwan Jiang, Huijie Wang, Shiyu Li, Lujing Jia · 2026 · Briefings in Bioinformatics
61. Fernandez M. From Molecular Accuracy to Pharmacological Meaning: An Evidence-Constrained Theory of Interpretable Prediction in Early Drug Discovery
    Ethan Blake, Isabella Russo, Klaus Richter, Maria Fernandez · 2024 · Pharmacophore
62. Fatty acid amide hydrolase (FAAH) inhibitor design and preclinical studies: lessons learned from BIA 10–2474 and the challenges ahead
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63. Hidden Potential Unlocked: AI-Driven Exploration of Existing Drugs to Fight against Unmet Medical Needs
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64. GiGCN: a network-based framework for uncovering synthetic lethal and viable genetic interactions
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65. Motif-Attention Enhanced Graph Convolutional Networks for Drug-Target Interaction Prediction: Improved Generalization Under Cold-Start Conditions
    Muhammad Yusuf ML, Isman Kurniawan · 2026 · ARMADA Jurnal Penelitian Multidisiplin