mlsanityData to 7 Oct 2026

DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences

arXiv 1811.02114 ↗First posted 6 Nov 2018q-bio.QM cs.LGcited by 45

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Abstract (arXiv)

Identification of drug-target interactions (DTIs) plays a key role in drug discovery. The high cost and labor-intensive nature of in vitro and in vivo experiments have highlighted the importance of in silico-based DTI prediction approaches. In several computational models, conventional protein descriptors are shown to be not informative enough to predict accurate DTIs. Thus, in this study, we employ a convolutional neural network (CNN) on raw protein sequences to capture local residue patterns participating in DTIs. With CNN on protein sequences, our model performs better than previous protein descriptor-based models. In addition, our model performs better than the previous deep learning model for massive prediction of DTIs. By examining the pooled convolution results, we found that our model can detect binding sites of proteins for DTIs. In conclusion, our prediction model for detecting local residue patterns of target proteins successfully enriches the protein features of a raw protein sequence, yielding better prediction results than previous approaches.

Key facts. Cited by 45 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Nov 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 8; 2023: 6; 2024: 8; 2025: 14; 2026: 5.

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  1. 2023BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associationscited by 100
  2. 2023Large AI Models in Health Informatics: Applications, Challenges, and the Futurecited by 61
  3. 2024BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuningcited by 54
  4. 2022Interpretable bilinear attention network with domain adaptation improves drug-target predictioncited by 39
  5. 2022Deep learning for drug repurposing: methods, databases, and applicationscited by 16
  6. 2021BridgeDPI: A Novel Graph Neural Network for Predicting Drug-Protein Interactionscited by 12
  7. 2024PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Predictioncited by 10
  8. 2022Hierarchical Graph Representation Learning for the Prediction of Drug-Target Binding Affinitycited by 7
  9. 2021Drug-Target Interaction Prediction with Graph Attention networkscited by 6
  10. 2022Predicting Protein-Ligand Binding Affinity via Joint Global-Local Interaction Modelingcited by 5
  11. 2024A Cross-Field Fusion Strategy for Drug-Target Interaction Predictioncited by 5
  12. 2025SCALAR: Self-Calibrating Adaptive Latent Attention Representation Learningcited by 5
33 more
  1. 2022Associative Learning Mechanism for Drug-Target Interaction Predictioncited by 4
  2. 2022Structure-based drug discovery with deep learningcited by 3
  3. 2023Ophiuchus: Scalable Modeling of Protein Structures through Hierarchical Coarse-graining SO(3)-Equivariant Autoencoderscited by 3
  4. 2024FusionDTI: Fine-grained Binding Discovery with Token-level Fusion for Drug-Target Interactioncited by 3
  5. 2024FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learningcited by 3
  6. 2025DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Searchcited by 3
  7. 2023FragXsiteDTI: Revealing Responsible Segments in Drug-Target Interaction with Transformer-Driven Interpretationcited by 2
  8. 2024HiGraphDTI: Hierarchical Graph Representation Learning for Drug-Target Interaction Predictioncited by 2
  9. 2024Accurate Prediction of Ligand-Protein Interaction Affinities with Fine-Tuned Small Language Modelscited by 2
  10. 2025Drug-Target Interaction/Affinity Prediction: Deep Learning Models and Advances Reviewcited by 2
  11. 2025EquiCPI: SE(3)-Equivariant Geometric Deep Learning for Structure-Aware Prediction of Compound-Protein Interactionscited by 2
  12. 2025Zero-Shot Learning with Subsequence Reordering Pretraining for Compound-Protein Interactioncited by 2
  13. 2025Multimodal Regression for Enzyme Turnover Rates Predictioncited by 2
  14. 2023PIGNet2: A Versatile Deep Learning-based Protein-Ligand Interaction Prediction Model for Binding Affinity Scoring and Virtual Screeningcited by 1
  15. 2025Inductive-Associative Meta-learning Pipeline with Human Cognitive Patterns for Unseen Drug-Target Interaction Predictioncited by 1
  16. 2025PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation modelscited by 1
  17. 2026Tensor-DTI: Enhancing Biomolecular Interaction Prediction with Contrastive Embedding Learningcited by 1
  18. 2021ParaVS: A Simple, Fast, Efficient and Flexible Graph Neural Network Framework for Structure-Based Virtual Screeningcited by 0
  19. 2021CSI: Contrastive Data Stratification for Interaction Prediction and its Application to Compound-Protein Interaction Predictioncited by 0
  20. 2022A Supervised Machine Learning Approach for Sequence Based Protein-protein Interaction (PPI) Predictioncited by 0
  21. 2022Enhanced compound-protein binding affinity prediction by representing protein multimodal information via a coevolutionary strategycited by 0
  22. 2023MCPI: Integrating Multimodal Data for Enhanced Prediction of Compound Protein Interactionscited by 0
  23. 2024Enhancing Drug-Target Interaction Prediction through Transfer Learning from Activity Cliff Prediction Taskscited by 0
  24. 2025Leveraging Large Language Models to Predict Antibody Biological Activity Against Influenza A Hemagglutinincited by 0
  25. 2025SCOPE-DTI: Semi-Inductive Dataset Construction and Framework Optimization for Practical Usability Enhancement in Deep Learning-Based Drug Target Interaction Predictioncited by 0
  26. 2025KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Predictioncited by 0
  27. 2025Structure-Aware Contrastive Learning with Fine-Grained Binding Representations for Drug Discoverycited by 0
  28. 2025Learning to Align Molecules and Proteins: A Geometry-Aware Approach to Binding Affinitycited by 0
  29. 2025Towards Precision Protein-Ligand Affinity Prediction Benchmark: A Complete and Modification-Aware DAVIS Datasetcited by 0
  30. 2026RiboSphere: Learning Unified and Efficient Representations of RNA Structurescited by 0
  31. 2026SPADE: Faster Drug Discovery by Learning from Sparse Datacited by 0
  32. 2026I-SAFE: Wasserstein Coherence Metrics for Structural Auditing of Scientific AI Modelscited by 0
  33. 2026MoTIF-X: A Multimodal Tokenized Framework for Interpretable and Extensible Molecular Representation Learningcited by 0