Graph Convolutional Neural Networks for Predicting Drug-Target Interactions

Cited by (365)

Items 101–200 of 365

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4. Decoding the protein–ligand interactions using parallel graph neural networks
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6. DSGAT: predicting frequencies of drug side effects by graph attention networks
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7. Trends in Deep Learning for Property-driven Drug Design
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8. Advances in machine intelligence‐driven virtual screening approaches for big‐data
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9. Unveiling Dynamic Hotspots in Protein–Ligand Binding: Accelerating Target and Drug Discovery Approaches
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10. Prediction of protein-ligand binding affinity with deep learning
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11. Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach
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13. DeepBindGCN: Integrating Molecular Vector Representation with Graph Convolutional Neural Networks for Protein–Ligand Interaction Prediction
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14. Bridging the Worlds of Pharmacometrics and Machine Learning
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15. A survey on graph embedding techniques for biomedical data: Methods and applications
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16. GDilatedDTA: Graph dilation convolution strategy for drug target binding affinity prediction
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17. Improved drug–target interaction prediction with intermolecular graph transformer
    Siyuan Liu, Yusong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie‐Yan Liu, Tong Wang · 2022 · Briefings in Bioinformatics
18. Graph Neural Networks as a Potential Tool in Improving Virtual Screening Programs
    Luiz Anastácio Alves, Natiele Carla da Silva Ferreira, Victor Maricato, Anael Viana Pinto Alberto, Evellyn Araújo Dias, Nt Jose Aguiar Coelho · 2022 · Frontiers in Chemistry
19. Latent Biases in Machine Learning Models for Predicting Binding Affinities Using Popular Data Sets
    Ganesh Chandan Kanakala, Rishal Aggarwal, Divya Nayar, U. Deva Priyakumar · 2023 · ACS Omega
20. Hierarchical multimodal self-attention-based graph neural network for DTI prediction
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21. Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer
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22. Protein–ligand binding affinity prediction with edge awareness and supervised attention
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23. DENVIS: Scalable and High-Throughput Virtual Screening Using Graph Neural Networks with Atomic and Surface Protein Pocket Features
    Agamemnon Krasoulis, Nick Antonopoulos, Vassilis Pitsikalis, Stavros Theodorakis · 2022 · Journal of Chemical Information and Modeling
24. Exploring protein–ligand binding affinity prediction with electron density-based geometric deep learning
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25. G-K BertDTA: A graph representation learning and semantic embedding-based framework for drug-target affinity prediction
    Xihe Qiu, Haoyu Wang, Xiaoyu Tan, Zhijun Fang · 2024 · Computers in Biology and Medicine
26. An end-to-end method for predicting compound-protein interactions based on simplified homogeneous graph convolutional network and pre-trained language model
    Yufang Zhang, Jiayi Li, Shenggeng Lin, Jianwei Zhao, Yi Xiong, Dong-Qing Wei · 2024 · Journal of Cheminformatics
27. Influenza-like symptom recognition using mobile sensing and graph neural networks
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28. Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction
    Jiahua Rao, Shuangjia Zheng, Sijie Mai, Yuedong Yang · 2022 · International Joint Conference on Artificial Intelligence
29. Graph pooling in graph neural networks: methods and their applications in omics studies
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30. CRNNTL: Convolutional Recurrent Neural Network and Transfer Learning for QSAR Modeling in Organic Drug and Material Discovery
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31. EMBER—Embedding Multiple Molecular Fingerprints for Virtual Screening
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32. Explaining Black Box Drug Target Prediction Through Model Agnostic Counterfactual Samples
    Tri Minh Nguyen, Thomas P Quinn, Thin Nguyen, Truyen Tran · 2022 · IEEE Transactions on Computational Biology and Bioinformatics
33. Learnable Hypergraph Laplacian for Hypergraph Learning
    Jiying Zhang, Yuzhao Chen, Xi Xiao, Runiu Lu, Shu‐Tao Xia · 2022 · IEEE International Conference on Acoustics Speech and Signal Processing
34. Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model
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35. DTI-BERT: Identifying Drug-Target Interactions in Cellular Networking Based on BERT and Deep Learning Method
    Jie Zheng, Xuan Xiao, Wang‐Ren Qiu · 2022 · Frontiers in Genetics
36. TGOpt
    Yufeng Wang, Charith Mendis · 2023 · ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
37. GraphsformerCPI: Graph Transformer for Compound–Protein Interaction Prediction
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38. Integrating multi-scale neighbouring topologies and cross-modal similarities for drug–protein interaction prediction
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39. Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Protein Structures and Interaction Networks
    Arian R. Jamasb, Ramón Viñas, Eric J. Ma, Charlie Harris, Kexin Huang, Dominic Hall, Píetro Lió, Tom L. Blundell · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
40. A Novel Graph Neural Network Methodology to Investigate Dihydroorotate Dehydrogenase Inhibitors in Small Cell Lung Cancer
    Hong-Yi Zhi, Lu Zhao, Cheng-Chun Lee, Calvin Yu‐Chian Chen · 2021 · Biomolecules
41. Deep Scoring Neural Network Replacing the Scoring Function Components to Improve the Performance of Structure-Based Molecular Docking
    Lijuan Yang, Guanghui Yang, Xiaolong Chen, Qiong Yang, Xiaojun Yao, Zhitong Bing, Yuzhen Niu, Liang Huang, Lei Yang · 2021 · ACS Chemical Neuroscience
42. Drug-Target Interaction Prediction via Graph Auto-Encoder and Multi-Subspace Deep Neural Networks
    Qing Ye, Xiaolong Zhang, Xiaoli Lin · 2022 · IEEE Transactions on Computational Biology and Bioinformatics
43. ColdstartCPI: Induced-fit theory-guided DTI predictive model with improved generalization performance
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44. HyperPCM: Robust Task-Conditioned Modeling of Drug–Target Interactions
    Emma Svensson, Pieter-Jan Hoedt, Sepp Hochreiter, Günter Klambauer · 2024 · Journal of Chemical Information and Modeling
45. An efficient curriculum learning-based strategy for molecular graph learning
    Yaowen Gu, Si Zheng, Zidu Xu, Qijin Yin, Liang Li, Jiao Li · 2022 · Briefings in Bioinformatics
46. MolNet: A Chemically Intuitive Graph Neural Network for Prediction of Molecular Properties
    Yeji Kim, Yoonho Jeong, Jihoo Kim, Eok Kyun Lee, Won June Kim, Insung S. Choi · 2022 · Chemistry - An Asian Journal
47. ICAN: Interpretable cross-attention network for identifying drug and target protein interactions
    2022
48. Prediction of Chromatography Conditions for Purification in Organic Synthesis Using Deep Learning
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49. Super High-Throughput Screening of Enzyme Variants by Spectral Graph Convolutional Neural Networks
    Carlos Ramírez-Palacios, ‪Siewert J. Marrink · 2023 · Journal of Chemical Theory and Computation
50. LigBind: Identifying Binding Residues for Over 1000 Ligands with Relation-Aware Graph Neural Networks
    Ying Xia, Xiaoyong Pan, Hong‐Bin Shen · 2023 · Journal of Molecular Biology
51. Ligand binding affinity prediction with fusion of graph neural networks and 3D structure-based complex graph
    Lina Dong, Shuai Shi, Xiaoyang Qu, Ding Luo, Binju Wang · 2023 · Physical Chemistry Chemical Physics
52. Comprehensive Review on Drug-target Interaction Prediction - Latest Developments and Overview
    Ali K. Abdul Raheem, Ban Nadeem Dhannoon · 2023 · Current Drug Discovery Technologies
53. A graph-convolutional neural network for addressing small-scale reaction prediction
    Yejian Wu, Chengyun Zhang, Ling Wang, Hongliang Duan · 2021 · Chemical Communications
54. Predicting target–ligand interactions with graph convolutional networks for interpretable pharmaceutical discovery
    Paola Ruiz Puentes, Laura Rueda-Gensini, Natalia Valderrama, Isabela Hernández, Cristina González, Laura Alexandra Daza, Carolina Muñoz-Camargo, Juan C. Cruz, Pablo Arbeláez · 2022 · Scientific Reports
55. Binding Thermodynamics of Fourth-Generation EGFR Inhibitors Revealed by Absolute Binding Free Energy Calculations
    Huaxin Zhou, Haohao Fu, Xueguang Shao, Wensheng Cai · 2023 · Journal of Chemical Information and Modeling
56. An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models
    Conor D. Parks, Zied Gaieb, Rommie E. Amaro · 2020 · Frontiers in Molecular Biosciences
57. Deep Learning for Protein–Protein Interaction Site Prediction
    Arian R. Jamasb, Ben Day, Cătălina Cangea, Píetro Lió, Tom L. Blundell · 2021 · Methods in molecular biology
58. Graph Transformer-based Heterogeneous Graph Neural Networks enhanced by multiple meta-path adjacency matrices decomposition
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59. A Hybrid Structure-Based Machine Learning Approach for Predicting Kinase Inhibition by Small Molecules
    Changchang Liu, Peter S. Kutchukian, Nhan Duc Nguyen, Mohammed AlQuraishi, Peter Karl Sorger · 2023 · Journal of Chemical Information and Modeling
60. FOTF-CPI: A compound-protein interaction prediction transformer based on the fusion of optimal transport fragments
    Zeyu Yin, Yu Chen, Yajie Hao, Sanjeevi Pandiyan, Jinsong Shao, Li Wang · 2023 · iScience
61. Interface-aware molecular generative framework for protein–protein interaction modulators
    Jianmin Wang, Jiashun Mao, Chunyan Li, Hongxin Xiang, Xun Wang, Shuang Wang, Zixu Wang, Yangyang Chen, Yuquan Li, Kyoung Tai No et al. · 2024 · Journal of Cheminformatics
62. A Deep Graph Network–Enhanced Sampling Approach to Efficiently Explore the Space of Reduced Representations of Proteins
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63. Deep fusion learning facilitates anatomical therapeutic chemical recognition in drug repurposing and discovery
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64. TranScreen: Transfer Learning on Graph-Based Anti-Cancer Virtual Screening Model
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65. COLLAPSE : A representation learning framework for identification and characterization of protein structural sites
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66. Edge-Gated Graph Neural Network for Predicting Protein-Ligand Binding Affinities
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67. TGLite: A Lightweight Programming Framework for Continuous-Time Temporal Graph Neural Networks
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68. Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks
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69. SPP-CPI: Predicting Compound–Protein Interactions Based On Neural Networks
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70. Deep Learning Based Methods for Molecular Similarity Searching: A Systematic Review
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71. Machine Learning for Cancer Drug Combination
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72. Recent Applications of Artificial Intelligence in the Detection of Gastrointestinal, Hepatic and Pancreatic Diseases
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73. Proteome‐Scale Drug‐Target Interaction Predictions: Approaches and Applications
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74. REDIRECTION: Generating drug repurposing hypotheses using link prediction with DISNET data
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75. Self-supervised graph representation learning integrates multiple molecular networks and decodes gene-disease relationships
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80. A bidirectional interpretable compound-protein interaction prediction framework based on cross attention
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81. Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning
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84. MFF-DTA: Multi-scale feature fusion for drug-target affinity prediction
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85. Intelligence on the graph: Graph neural networks for mechanistic drug target discovery
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