Graph Convolutional Neural Networks for Predicting Drug-Target Interactions

Cited by (365)

Items 201–300 of 365

1. AQDnet: Deep Neural Network for Protein–Ligand Docking Simulation
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2. Reinforcement Learning Based Approach for Ligand Pose Prediction
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3. Learning RMSD to Improve Protein-Ligand Scoring and Pose Selection
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4. Graph representation learning for structural proteomics
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5. Graph neural networks for the identification of novel inhibitors of a small RNA
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6. Comprehensive Review of Graph Neural Networks: Challenges, Classification, Architectures, Applications, and Potential Utility in Bioinformatics
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7. An Efficient Modern Strategy to Screen Drug Candidates Targeting RdRp of SARS-CoV-2 With Potentially High Selectivity and Specificity
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8. Graph Convolutional Neural Network-Based Virtual Screening of Phytochemicals and In-Silico Docking Studies of Drug Compounds for Hemochromatosis
   R. Ani, O. S. Deepa · 2023 · IEEE Access
9. Investigating Graph Embedding Methods for Cross-Platform Binary Code Similarity Detection
   Victor Cochard, Damian Pfammatter, Chi Thang Duong, Mathias Humbert · 2022 · IEEE European Symposium on Security and Privacy
10. Exploring Myocardial Ischemia‐Reperfusion Injury Mechanism of Cinnamon by Network Pharmacology, Molecular Docking, and Experiment Validation
    Tao Xue, Yan Xue, Yangyue Fang, Chuanghong Lu, Yu Fu, Zefeng Lai, Xiaojun Qin, Feng Huang, Zhiyu Zeng, Jianping Huang · 2023 · Computational and Mathematical Methods in Medicine
11. Coal Wall and Roof Segmentation in the Coal Mine Working Face Based on Dynamic Graph Convolution Neural Networks
    Zhizhong Xing, Shuanfeng Zhao, Wei Guo, Xiaojun Guo, Shenquan Wang, Junjie Ma, Haitao He · 2021 · ACS Omega
12. DrugOrchestra: Jointly predicting drug response, targets, and side effects via deep multi-task learning
    Yuepeng Jiang, Stefano Rensi, Sheng Wang, Russ Biagio Altman · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
13. SEQUENCE VS. STRUCTURE: DELVING DEEP INTO DATA-DRIVEN PROTEIN FUNCTION PREDICTION
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14. RhoMax: Computational Prediction of Rhodopsin Absorption Maxima Using Geometric Deep Learning
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15. Artificial intelligence and multi-omics in drug discovery: A deep learning-powered revolution
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16. GraphEGFR : Multi‐task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family proteins on data scarcity
    Bundit Boonyarit, Nattawin Yamprasert, Pawit Kaewnuratchadasorn, Jiramet Kinchagawat, Chanatkran Prommin, Thanyada Rungrotmongkol, Sarana Y. Nutanong · 2024 · Journal of Computational Chemistry
17. Spectra-descriptor-based machine learning for predicting protein–ligand interactions
    Cheng Chen, Ledu Wang, Yi Feng, Wencheng Yao, Jiahe Liu, Zifan Jiang, Luyuan Zhao, Letian Zhang, Jun Jiang, Shuo Feng · 2025 · Chemical Science
18. DeepAden: an explainable machine learning method for predicting the substrate specificity of nonribosomal peptide synthetases
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19. Appropriate Evaluation Measurements for Regression Models
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20. Functional microRNA-targeting drug discovery by graph-based deep learning
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21. Edge-enhanced interaction graph network for protein-ligand binding affinity prediction
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22. Advancements in breast cancer therapy: Integrating AI tools for drug discovery and clinical trials
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23. Predicting variable-length ACE inhibitory peptides based on graph convolutional network
    Yating Rong, Baolong Feng, Xiao‐Shuang Cai, Hongjie Song, Lili Wang, Yehui Wang, Xinxu Yan, Yulin Sun, Jinyong Zhao, Ping Li et al. · 2024 · International Journal of Biological Macromolecules
24. Predicting Protein–Ligand Binding Affinity Using Fusion Model of Spatial-Temporal Graph Neural Network and 3D Structure-Based Complex Graph
    Gai‐Li Li, Yongna Yuan, Ruisheng Zhang · 2024 · Interdisciplinary Sciences Computational Life Sciences
25. MaskMol: knowledge-guided molecular image pre-training framework for activity cliffs with pixel masking
    Zhixiang Cheng, Hongxin Xiang, Pengsen Ma, Li Zeng, Xin Jin, Xixi Yang, Jianxin Lin, Xinxin Feng, Bosheng Song, Xinxin Feng et al. · 2025 · BMC Biology
26. Predicting Compound-Protein Interaction by Deepening the Systemic Background via Molecular Network Feature Embedding
    Han Wang, Hangxu Zhu, Wenhao Li, Ming Liu, Li Zhang, Dong He Xu · 2022 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
27. Cross-Modality Protein Embedding for Compound-Protein Affinity and Contact Prediction
    Yuning You, Yang Shen · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
28. Drug repurposing for Leishmaniasis with Hyperbolic Graph Neural Networks
    Yenson Lau, Jahir M. Gutierrez, Maksims Volkovs, Saba Zuberi · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
29. Knowledge Graph-Embedded Time-Serial-Data-Driven Bottleneck Analysis of Textile and Apparel Production Processes
    Guodong Wang, Guohua Liu, Qianqian Li · 2023 · Machines
30. Drugging the entire human proteome: Are we there yet?
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31. Graph Neural Networks and Molecular Docking as Two Complementary Approaches for Virtual Screening: A Case Study on Cruzain
    José Leonardo Gómez Chávez, Adriano M. Luchi, Roxana Noelia Villafañe, Germán Andrés Conti, Ernesto Rafael Pérez, Emilio Angelina, Nélida M. Peruchena · 2024 · ChemistrySelect
32. A beginner’s approach to deep learning applied to VS and MD techniques
    Stijn Dhondt, Jose Oramas M., Hans L. De Winter · 2025 · Journal of Cheminformatics
33. Depth-defying OOF-GNN: Sailing smoothly amidst GNN waves
    Aafaq Mohi ud din, Shaima Qureshi · 2023 · Knowledge-Based Systems
34. GATLGEMF: A graph attention model with line graph embedding multi-complex features for ncRNA-protein interactions prediction
    Jing Ying Yan, Wenyan Qu, Xiaoyi Li, Ruobing Wang, Jianjun Tan · 2023 · Computational Biology and Chemistry
35. Emerging technologies for drug repurposing: Harnessing the potential of text and graph embedding approaches
    Xialan Dong, Weifan Zheng · 2024 · Artificial Intelligence Chemistry
36. Research progress on Drug-Target Interactions in the last five years
    Yun Zuo, Xiaoting Wu, Fei Ge, Hongjin Yan, Sirui Fei, Jingwen Liang, Zhaohong Deng · 2024 · Analytical Biochemistry
37. Drug-Target Interaction Prediction via Multiple Output Graph Convolutional Networks
    Qing Ye, Xiaolong Zhang, Xiaoli Lin · 2021 · Lecture notes in computer science
38. Current Perspectives on Viral Disease Outbreaks - Epidemiology, Detection and Control
    Claborn, David · 2020 · IntechOpen eBooks
39. Directional ΔG Neural Network (DrΔG-Net): A Modular Neural Network Approach to Binding Free Energy Prediction
    Derek P. Metcalf, Zachary L. Glick, Andrea Bortolato, Andy Jiang, Daniel L. Cheney, C. David Sherrill · 2024 · Journal of Chemical Information and Modeling
40. Application of DNA‐Binding Protein Prediction Based on Graph Convolutional Network and Contact Map
    Weizhong Lu, Nan Zhou, Yijie Ding, Hongjie Wu, Yu Zhang, Qiming Fu, Haiou Li · 2022 · BioMed Research International
41. Drug-Target Interaction Prediction Based on Transformer
    Junkai Liu, Tengsheng Jiang, Yaoyao Lu, Hongjie Wu · 2022 · Lecture notes in computer science
42. Combined Molecular Graph Neural Network and Structural Docking Selects Potent Programmable Cell Death Protein 1/Programmable Death-Ligand 1 (PD-1/PD-L1) Small Molecule Inhibitors
    Prageeth R. Wijewardhane, Krupal P. Jethava, Jonathan A. Fine, Gaurav Chopra · 2020 · ChemRxiv
43. Combined Molecular Graph Neural Network and Structural Docking Selects Potent Programmable Cell Death Protein 1/Programmable Death-Ligand 1 (PD-1/PD-L1) Small Molecule Inhibitors
    Prageeth R. Wijewardhane, Krupal P. Jethava, Jonathan A. Fine, Gaurav Chopra · 2020 · ChemRxiv
44. ProteoDockNet: Novel GNN-based ligand binding affinities prediction architecture via SMILES to key liver, kidney and brain proteins using QSAR data
    Anagha Shamsundar Setlur, Vidya Niranjan, Arjun Balaji, Chandrashekar Karunakaran · 2024 · Computational and Structural Biotechnology Reports
45. IHDFN-DTI: Interpretable Hybrid Deep Feature Fusion Network for Drug–Target Interaction Prediction
    Yuanyuan Zhang, Qihao Wang, Ci’ao Zhang, Baoming Feng, Junliang Shang, Li Zhang · 2025 · Interdisciplinary Sciences Computational Life Sciences
46. Binding Affinity Prediction for Pancreatic Ductal Adenocarcinoma Using Drug-Target Descriptors and Artificial Intelligence
    Pragya, A. Amalin Prince, Jac Fredo Agastinose Ronickom · 2025 · IEEE Access
47. BiMA-DTI: a bidirectional Mamba-Attention hybrid framework for enhanced drug-target interaction prediction
    Youyuan Shui, Xuewen Ge, Chen Cao, Junjie Wang, Jie Hu, Yun Liu · 2025 · BMC Biology
48. DeepSIBA: chemical structure-based inference of biological alterations using deep learning
    Christos Fotis, Nikolaos Meimetis, Antonis Sardis, Leonidas G. Alexopoulos · 2020 · Molecular Omics
49. WAE-DTI: Ensemble-based architecture for drug–target interaction prediction using descriptors and embeddings
    Tariq Sha’ban, Ahmad M. Mustafa, Mostafa Z. Ali · 2024 · Informatics in Medicine Unlocked
50. MultiChem: predicting chemical properties using multi-view graph attention network
    Heesang Moon, Mina Rho · 2025 · BioData Mining
51. Prediction of drug–protein interaction based on dual channel neural networks with attention mechanism
    Dayu Tan, Haijun Jiang, Haitao Li, Ying Xie, Yansen Su · 2023 · Briefings in Functional Genomics
52. Co-supervised Pre-training of Pocket and Ligand
    Zhangyang Gao, Cheng Tan, Jun Xia, Stan Ziqing Li · 2023 · Lecture notes in computer science
53. CSstep: Step-by-step exploration of the chemical space of drug molecules via multi-agent and multi-stage reinforcement learning
    Xinhao Che, Yujing Zhao, Qilei Liu, Fang Yu, Hanyu Gao, Lei Zhang · 2025 · Chemical Engineering Science
54. Leveraging artificial intelligence for drug development and drug discovery
    Shilpa Chatterjee, Sayantan Kundu, Nandan Sarkar · 2025 · Elsevier eBooks
55. Using machine learning in the in-silico design of selective dopamine receptor ligands: Advancements in targeted therapies for neurological and psychiatric disorders
    Melika F. Aghdam, Mahia V. Solout, Fatemeh Amini, Sogol Meknatkhah, Noushin Agha Babaie, Morteza Farnia, Jahan Bakhsh Ghasemi · 2025 · Results in Chemistry
56. SLAB: simultaneous labeling and binding affinity prediction for protein–ligand structures
    Aditya Ranganath, Hyojin Kim, Heesung Shim, Jonathan E. Allen · 2025 · Digital Discovery
57. Deep learning for small-molecule drug discovery: From molecular design to clinical translation
    Rita I. Oliveira, Tiago Pereira, Maryam Abbasi, Jorge A. R. Salvador, Joel Perdiz Arrais · 2025 · Journal of Pharmaceutical Analysis
58. Machine Learning for RNA-Targeting Drug Design
    Wissam Karroucha, Carlos Oliver, Véronique Stoven, Vincent Mallet · 2026 · Journal of Chemical Information and Modeling
59. Unsupervised Machine Learning Approach for Identifying Biomechanical Influences on Protein-Ligand Binding Affinity
    Arjun Singh · 2021 · International Journal of Advanced Computer Science and Applications
60. Quantum Graph Neural Networks Based Protein-Ligand Classification
    Srinjoy Ganguly, Vaishnavi Chandilkar, Prateek Jain, Luis Gerardo Ayala Bertel · 2024 · Communications in computer and information science
61. Drug–Target Interaction Prediction Based on Graph Neural Network and Recommendation System
    Peng Lei, Changan Yuan, Hongjie Wu, Xing‐Ming Zhao · 2022 · Lecture notes in computer science
62. Review on data-centric brain-inspired computing paradigms exploiting emerging memory devices
    Wei Juan Wang, Shahar Kvatinsky, Heidemarie Schmidt, Nan Du · 2022 · Frontiers in Electronic Materials
63. PandoraRL: DQN and Graph Convolution based ligand pose learning for SARS-COV1 Mprotease
    Justin Jose, Ujjaini Alam A, Pooja Arora, Divye Singh, Nidhi Jatana · 2022 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
64. Predicting Potent Compounds Using a Conditional Variational Autoencoder Based upon a New Structure–Potency Fingerprint
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65. Using Single Protein/Ligand Binding Models to Predict Active Ligands for Unseen Proteins
    Vikram Sundar, Lucy J. Colwell · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
66. Unsupervised learning reveals landscape of local structural motifs across protein classes
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67. RAG-msCNN: predicting protein-DNA binding sites by integration of retrieval-augmented generation (RAG) with protein language models and the multi-scale separable convolutional neural network
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68. SynerDTI: a synergistic deep learning framework for drug-target interaction prediction via global feature coordinated attention mechanism
    Yuxuan Liao, Mugang Lin, Jia Peng, Yu Peng, Jiajia Liu · 2026 · Molecular Diversity
69. Explainability Methods from Machine Learning Detect Important Drugs’ Atoms in Drug-Target Interactions
    Mrinal Mahindran, Qingyuan Liu, Vishak Madhwaraj Kadambalithaya, Olga V. Kalinina · 2026 · Journal of Chemical Information and Modeling
70. MolXProt: A Cross-Attention Transformer-Based Graph Neural Network for Protein-Ligand Binding Affinity Prediction
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71. CholBindNet as an interpretable neural network for cholesterol-binding site classification
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72. A spatial-temporal graph attention network for protein–ligand binding affinity prediction based on molecular geometry
    Gai‐Li Li, Yongna Yuan, Ruisheng Zhang · 2025 · Multimedia Systems
73. MIN: Multi-Channel Interaction Network for Drug-Target Interaction With Protein Distillation
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74. MGCN: Graph Convolutional Network for Drug Molecular Screening
    Shoujin Wang, Yongyuan Zhu, Jifei Liu · 2021 · Journal of Physics Conference Series
75. Graph machine learning in drug discovery
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76. DICCA-DTA: Diffusion and Contextualized Capsule Attention guided Factorized Cross-Pooling for Drug-Target Affinity prediction
    E. Uma, T. Mala · 2025 · Computational Biology and Chemistry
77. DSAGLSTM-DTA: Prediction of Drug-Target Affinity using Dual Self-Attention and LSTM
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78. Graph Neural Networks Bootstrapped for Synthetic Selection and Validation of Small Molecule Immunomodulators
    Prageeth R. Wijewardhane, Krupal P. Jethava, Jonathan A. Fine, Gaurav Chopra · 2021 · ChemRxiv
79. Learning RMSD to Improve Protein-Ligand Scoring and Pose Selection
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80. Structure‐Based Ultra‐Large Virtual Screenings
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81. Integrating (deep) machine learning and cheminformatics for predicting human intestinal absorption of small molecules
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82. Re-quantization based binary graph neural networks
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83. CanGRNNA: Ensembling Message Passing and Temporal Dynamics with Attention for Prediction of Structural Cancer Protein–Protein Interactions
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84. Predicting the Binding of Small Molecules to Proteins through Invariant Representation of the Molecular Structure
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85. Neural Collapse Inspired Regularization for Deep Graph Neural Networks
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86. Generalizable compound protein interaction prediction with a model incorporating protein structure aware and compound property aware language model representations
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87. Curated and Structure-Based Drug–Target Interactions Improve Underprediction of Drug Side Effects in Network Models
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88. Deep Learning and Artificial Intelligence in the Design of Angiotensin-Converting Enzyme (ACE) Inhibitory Peptides
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89. Graphs, Entities, and Step Mixture for Enriching Graph Representation
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90. WLLP: A weighted reconstruction-based linear label propagation algorithm for predicting potential therapeutic agents for COVID-19
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91. Prediction of organic molecular optical absorption energy based on deep learning using mordred descriptor features
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92. Drug-Target Interaction Prediction Based on Drug Subgraph Fingerprint Extraction Strategy and Subgraph Attention Mechanism
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93. PfgPDI: Pocket feature-enabled graph neural network for protein-drug interaction prediction
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94. Understanding and classification of innate immune response through weighted edge representation learning with dual hypergraph transformation
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95. mHMG-DTI: A Drug-Target Interaction Prediction Framework Combining Modified Hierarchical Molecular Graphs and Improved Convolutional Block Attention Module
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96. Graph Neural Networks Based Explainability of Drug-Target Interactions
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97. Machine learning strategies for identifying repurposed drugs for cancer therapy
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98. Artificial intelligence methods to repurpose and discover new drugs to fight the Coronavirus disease-2019 pandemic
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99. ParaVS: A Simple, Fast, Efficient and Flexible Graph Neural Network Framework for Structure-Based Virtual Screening
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100. Dynamic Interaction Learning and Multimodal Representation for Drug Response Prediction
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