Research graph
References from Machine learning for drug-target interaction prediction: A comprehensive review of models, challenges, and computational strategies. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1038/nrd3078
10.1038/nrd3078 · External reference
10.1038/nrd3681
10.1038/nrd3681 · External reference
Unresolved reference
External reference
10.1038/nbt.2786
10.1038/nbt.2786 · External reference
10.1016/j.jhealeco.2016.01.012
10.1016/j.jhealeco.2016.01.012 · External reference
10.1016/j.drudis.2018.11.014
10.1016/j.drudis.2018.11.014 · External reference
10.1038/s41573-019-0024-5
10.1038/s41573-019-0024-5 · External reference
10.1016/j.drudis.2018.01.039
10.1016/j.drudis.2018.01.039 · External reference
10.1038/nrd.2017.232
10.1038/nrd.2017.232 · External reference
Unresolved reference
External reference
Generative artificial intelligence empowers digital twins in drug discovery and clinical trials
10.1080/17460441.2023.2273839 · 2024 · External reference
Drug-target interaction prediction using ensemble learning and dimensionality reduction
10.1016/j.ymeth.2017.05.016 · 2017 · External reference
10.1038/nrd.2016.230
10.1038/nrd.2016.230 · External reference
10.1111/j.1476-5381.2010.01127.x
10.1111/j.1476-5381.2010.01127.x · External reference
Unresolved reference
2018 · External reference
A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information
10.1038/s41467-017-00680-8 · 2017 · External reference
Surface plasmon resonance: a versatile technique for biosensor applications
10.3390/s150510481 · 2015 · External reference
Application of isothermal titration calorimetry as a tool to study natural product interactions
10.1039/c5np00094g · 2016 · External reference
10.1001/jama.2017.18391
10.1001/jama.2017.18391 · External reference
Nanotechnology in preclinical pharmacokinetics
10.1007/978-981-15-2195-9_30 · 2020 · External reference
Unresolved reference
External reference
10.1038/s41591-018-0300-7
10.1038/s41591-018-0300-7 · External reference
A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning
10.3389/fphar.2024.1375522 · 2024 · External reference
10.3390/ijms20184331
10.3390/ijms20184331 · External reference
Drug–target interaction prediction by integrating heterogeneous information with mutual attention network
10.1186/s12859-024-05976-3 · 2024 · External reference
Relationship between the inhibition constant (KI) and the concentration of inhibitor which causes 50 per cent inhibition (ic50) of an enzymatic reaction
10.1016/0006-2952(73)90196-2 · 1973 · External reference
π-σ-ρ analysis. A method for the correlation of biological activity and chemical structure
10.1021/ja01062a035 · 1964 · External reference
10.1021/jm4004285
10.1021/jm4004285 · External reference
10.1039/d0cs00098a
10.1039/d0cs00098a · External reference
Simplified molecular input line entry system (smiles) as an alternative for constructing quantitative structure-property relationships (qspr)
2005 · External reference
10.1016/b978-0-12-801505-6.00011-9
10.1016/b978-0-12-801505-6.00011-9 · External reference
10.1124/pr.112.007336
10.1124/pr.112.007336 · External reference
In silico prediction of the inhibition of new molecules on sars-cov-2 3cl protease using QSAR modeling and molecular docking
2024 · External reference
Machine learning models identify inhibitors of sars-cov-2 main protease
10.1021/acs.jcim.1c00683 · 2021 · External reference
Proteochemometric models using multiple sequence alignments and a subword-based tokenization scheme improve kinase affinity prediction
2021 · External reference
The importance of good practices and false hits for qsar-driven virtual screening: a real application against sars-cov-2
2023 · External reference
Qsar without borders
2020 · External reference
10.1146/annurev-biochem-030222-120000
10.1146/annurev-biochem-030222-120000 · External reference
10.1021/jm050362n
10.1021/jm050362n · External reference
10.1021/jm0306430
10.1021/jm0306430 · External reference
10.1002/jcc.21334
10.1002/jcc.21334 · External reference
10.1038/s41586-019-0917-9
10.1038/s41586-019-0917-9 · External reference
An open-source drug discovery platform enables ultra-large virtual screens
10.1038/s41586-020-2117-z · 2020 · External reference
Rapid identification of potential inhibitors of SARS-Cov-2 main protease by deep docking of 1.3 billion compounds
10.1002/minf.202000028 · 2020 · External reference
10.1021/acs.jcim.0c01010
10.1021/acs.jcim.0c01010 · External reference
Gnina 1.0: molecular docking with deep learning
10.1186/s13321-021-00522-2 · 2021 · External reference
Deep generative models for 3D compound design
2021 · External reference
10.1038/nsb0902-646
10.1038/nsb0902-646 · External reference
10.1016/j.neuron.2018.08.011
10.1016/j.neuron.2018.08.011 · External reference
10.1021/ja512751q
10.1021/ja512751q · External reference
10.1126/science.1208351
10.1126/science.1208351 · External reference
10.1016/j.neuron.2018.08.011
10.1016/j.neuron.2018.08.011 · External reference
Gromacs 4.5: a high-throughput and highly parallel open source molecular simulation toolkit
2013 · External reference
10.1002/jcc.20289
10.1002/jcc.20289 · External reference
Free energy calculations by the mm-pbsa method: recent advances and issues
10.1002/minf.201100135 · 2012 · External reference
10.1021/acs.jcim.7b00564
10.1021/acs.jcim.7b00564 · External reference
Open science discovery of potent noncovalent sars-cov-2 main protease inhibitors
2023 · External reference
Molecular basis for biased agonism at the cannabinoid cb1 receptor
2023 · External reference
10.1038/s41586-025-08618-7
10.1038/s41586-025-08618-7 · External reference
Large-scale assessment of binding free energy calculations in active drug discovery projects
10.1021/acs.jcim.0c00900 · 2020 · External reference
10.1016/j.compbiomed.2025.110438
10.1016/j.compbiomed.2025.110438 · External reference
10.1145/3386052.3386062
10.1145/3386052.3386062 · 2020 · External reference
10.1021/acs.jcim.3c01841
10.1021/acs.jcim.3c01841 · External reference
10.1016/j.ymeth.2021.10.007
10.1016/j.ymeth.2021.10.007 · External reference
Attentiondta: drug–target binding affinity prediction by sequence-based deep learning with attention mechanism
10.1109/tcbb.2022.3170365 · 2022 · External reference
Sequence-based drug-target affinity prediction using weighted graph neural networks
10.1186/s12864-022-08648-9 · 2022 · External reference
Deepfusion: a deep learning based multi-scale feature fusion method for predicting drug-target interactions
10.1016/j.ymeth.2022.02.007 · 2022 · External reference
Hyperattentiondti: improving drug–protein interaction prediction by sequence-based deep learning with attention mechanism
10.1093/bioinformatics/btab715 · 2022 · External reference
Gifdti: prediction of drug-target interactions based on global molecular and intermolecular interaction representation learning
10.1109/tcbb.2022.3225423 · 2022 · External reference
Superpred 3.0: drug classification and target prediction—a machine learning approach
10.1093/nar/gkac297 · 2022 · External reference
Dtiam: a unified framework for predicting drug-target interactions, binding affinities and drug mechanisms
10.1038/s41467-025-57828-0 · 2025 · External reference
Kg-dti: a knowledge graph based deep learning method for drug-target interaction predictions and alzheimer’s disease drug repositions
10.1007/s10489-021-02454-8 · 2022 · External reference
Predicting drug-target interactions via dual-stream graph neural network
2022 · External reference
Mindg: a drug–target interaction prediction method based on an integrated learning algorithm
10.1093/bioinformatics/btae147 · 2024 · External reference
Admetlab 3.0: an updated comprehensive online admet prediction platform enhanced with broader coverage, improved performance, API functionality and decision support
10.1093/nar/gkae236 · 2024 · External reference
Graphormerdti: a graph transformer-based approach for drug-target interaction prediction
10.1016/j.compbiomed.2024.108339 · 2024 · External reference
10.3390/toxics13070525
10.3390/toxics13070525 · External reference
Transformer-based models for chemical smiles representation: a comprehensive literature review
10.1016/j.heliyon.2024.e39038 · 2024 · External reference
A review of molecular representation in the age of machine learning
10.1002/wcms.1603 · 2022 · External reference
Comparative analysis of molecular fingerprints in prediction of drug combination effects
10.1093/bib/bbab291 · 2021 · External reference
Graphdrug: a multimodal graph learning for predicting bioactivity and pharmacokinetics of drug candidates
10.64252/dvme6f15 · 2025 · External reference
Graphsformercpi: graph transformer for compound–protein interaction prediction
10.1007/s12539-024-00609-y · 2024 · External reference
A point cloud-based deep learning strategy for protein–ligand binding affinity prediction
2022 · External reference
Transvae-dta: transformer and variational autoencoder network for drug-target binding affinity prediction
10.1016/j.cmpb.2023.108003 · 2024 · External reference
10.26434/chemrxiv-2022-jjm0j-v4
10.26434/chemrxiv-2022-jjm0j-v4 · External reference
10.1126/science.ade2574
10.1126/science.ade2574 · External reference
Deepconv-dti: prediction of drug-target interactions via deep learning with convolution on protein sequences
10.1371/journal.pcbi.1007129 · 2019 · External reference
Leveraging alphafold 3 for structural modeling of neurological disorder-associated proteins: a pathway to precision medicine
2024 · External reference
Alphafold-aware prediction of protein-dna binding sites using graph transformer
2021 · External reference
Attention-based knowledge graph representation learning for predicting drug-drug interactions
2022 · External reference
10.1016/j.csbj.2021.03.004 · Admitted local publication
Multi-hop graph structural modeling for cancer-related circrna-mirna interaction prediction
10.1016/j.patcog.2025.112078 · 2026 · External reference
Integrating transformer and graph attention network for circrna-mirna interaction prediction
2025 · External reference
Unresolved reference
2006 · External reference
Principal component analysis: a review and recent developments
10.1098/rsta.2015.0202 · 2016 · External reference
Visualizing data using t-sne
2008 · External reference
Molgraph: a python package for the implementation of molecular graphs and graph neural networks with Tensorflow and keras
10.1007/s10822-024-00578-w · 2025 · External reference
Evaluating self-supervised learning for molecular graph embeddings
2023 · External reference
Molecular contrastive learning of representations via graph neural networks
10.1038/s42256-022-00447-x · 2022 · External reference
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
10.1073/pnas.2016239118 · 2021 · External reference
Prottrans: toward understanding the language of life through self-supervised learning
10.1109/tpami.2021.3095381 · 2021 · External reference
10.1038/s41586-021-03819-2
10.1038/s41586-021-03819-2 · External reference
Prediction of protein–protein interaction using graph neural networks
10.1038/s41598-022-12201-9 · 2022 · External reference
Predicting circrna–disease associations through multisource domain-aware embeddings and feature projection networks
10.1021/acs.jcim.4c02250 · 2025 · External reference
Mpsm-dti: prediction of drug–target interaction via machine learning based on the chemical structure and protein sequence
10.1039/d1dd00011j · 2022 · External reference
Predtis: prediction of drug–target interactions based on multiple feature information using gradient boosting framework with data balancing and feature selection techniques
10.1093/bib/bbab046 · 2021 · External reference
Dti2vec: drug–target interaction prediction using network embedding and ensemble learning
10.1186/s13321-021-00552-w · 2021 · External reference
A machine learning-based biological drug–target interaction prediction method for a tripartite heterogeneous network
10.1021/acsomega.0c05377 · 2021 · External reference
Unresolved reference
2022 · External reference
Predicting drug-target interaction via self-supervised learning
10.1109/tcbb.2022.3153963 · 2022 · External reference
Semi-supervised meta-learning elucidates understudied molecular interactions
10.1038/s42003-024-06797-z · 2024 · External reference
Gsrf-dti: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph
10.1186/s12915-024-01949-3 · 2024 · External reference
Algorithmic graph theory, reinforcement learning and game theory in MD simulations: from 3D structures to topological 2D-molecular graphs (2D-molgraphs) and vice versa
10.3390/molecules28072892 · 2023 · External reference
A novel method to predict drug-target interactions based on large-scale graph representation learning
10.3390/cancers13092111 · 2021 · External reference
Novel drug-target interactions via link prediction and network embedding
10.1186/s12859-022-04650-w · 2022 · External reference
A novel method for drug-target interaction prediction based on graph transformers model
10.1186/s12859-022-04812-w · 2022 · External reference
10.1109/icbcb52223.2021.9459231
10.1109/icbcb52223.2021.9459231 · 2021 · External reference
10.15302/j-qb-022-0320
10.15302/j-qb-022-0320 · External reference
Effective prediction of drug–target interaction on Hiv using deep graph neural networks
10.1016/j.chemolab.2022.104676 · 2022 · External reference
Drug-target interaction prediction: end-to-end deep learning approach
10.1109/tcbb.2020.2977335 · 2020 · External reference
10.1007/s12539-023-00557-z
10.1007/s12539-023-00557-z · External reference
A novel deep neural network technique for drug–target interaction
10.3390/pharmaceutics14030625 · 2022 · External reference
Lds-cnn: a deep learning framework for drug-target interactions prediction based on large-scale drug screening
10.1007/s13755-023-00243-w · 2023 · External reference
Identifying drug–target interactions based on graph convolutional network and deep neural network
10.1093/bib/bbaa044 · 2021 · External reference
10.1016/j.neucom.2020.12.068
10.1016/j.neucom.2020.12.068 · External reference
Drug target prediction through deep learning functional representation of gene signatures
10.1038/s41467-024-46089-y · 2024 · External reference
Identifying potential drug-target interactions based on ensemble deep learning
10.3389/fnagi.2023.1176400 · 2023 · External reference
Predicting drug-target interaction network using deep learning model
10.1016/j.compbiolchem.2019.03.016 · 2019 · External reference
A deep learning-based method for drug-target interaction prediction based on long short-term memory neural network
2020 · External reference
10.1093/bioinformatics/btab548
10.1093/bioinformatics/btab548 · External reference
Gcardti: drug–target interaction prediction based on a hybrid mechanism in drug selfies
10.1002/qub2.39 · 2024 · External reference
Daspfind: new efficient method to predict drug–target interactions
10.1186/s13321-016-0128-4 · 2016 · External reference
10.1016/j.compbiomed.2021.104676
10.1016/j.compbiomed.2021.104676 · External reference
10.1007/978-3-030-01418-6_11
10.1007/978-3-030-01418-6_11 · 2018 · External reference
Deepfusiondta: drug-target binding affinity prediction with information fusion and hybrid Deep-learning ensemble model
10.1109/tcbb.2021.3103966 · 2021 · External reference
Deepaptamer: advancing high-affinity aptamer discovery with a hybrid deep learning model
10.1016/j.omtn.2024.102436 · 2025 · External reference
10.1016/j.chemolab.2025.105337
10.1016/j.chemolab.2025.105337 · External reference
Qsar analysis of vegfr-2 inhibitors based on machine learning, topomer comfa and molecule docking
10.1186/s13065-024-01165-8 · 2024 · External reference
10.1021/acs.jcim.3c01417
10.1021/acs.jcim.3c01417 · External reference
Small molecule inhibitors of il-1r1/il-1β interaction identified via transfer machine learning qsar modelling
10.1016/j.ijbiomac.2024.137295 · 2024 · External reference
Integration of molecular docking and molecular dynamics simulations with subtractive proteomics approach to identify the novel drug targets and their inhibitors in Streptococcus Gallolyticus
10.1038/s41598-024-64769-z · 2024 · External reference
10.1021/acs.jcim.4c00055
10.1021/acs.jcim.4c00055 · External reference
Structure-based drug-development study against fibroblast growth factor receptor 2: molecular docking and molecular dynamics simulation approaches
10.1038/s41598-024-69850-1 · 2024 · External reference
Structure-based screening of fda-approved drugs and molecular dynamics simulation to identify potential leukocyte antigen related protein (ptp-lar) inhibitors
10.1016/j.compbiolchem.2024.108264 · 2024 · External reference
Drug-like screening, molecular docking, molecular dynamics simulations, and binding free energies on the interaction of pyrazole derivatives as inhibitors of lysosomal storage disorders and anticancer activity
10.1007/s44371-024-00025-7 · 2024 · External reference
Explainable artificial intelligence for drug discovery and development: a comprehensive survey
10.1109/access.2024.3373195 · 2024 · External reference
The emergent role of explainable artificial intelligence in the materials sciences
2023 · External reference
Higher-order explanations of graph neural networks via relevant walks
10.1109/tpami.2021.3115452 · 2021 · External reference
Shapley-based graph explanation in embedding space
10.1016/j.knosys.2024.112244 · 2024 · External reference
Unresolved reference
2025 · External reference
10.1145/3447548.3467154
10.1145/3447548.3467154 · 2021 · External reference
Unresolved reference
2023 · External reference
10.1016/j.cels.2020.09.007
10.1016/j.cels.2020.09.007 · External reference
10.1016/j.cell.2023.04.010
10.1016/j.cell.2023.04.010 · External reference
Ai-driven drug discovery: exploring abaucin as a promising treatment against multidrug-resistant acinetobacter baumannii
10.1002/hsr2.2150 · 2024 · External reference
10.4155/fmc.15.50
10.4155/fmc.15.50 · External reference
10.1021/acschembio.5c00213
10.1021/acschembio.5c00213 · External reference
Using tr-fret to investigate protein–protein interactions: a case study of pxr-coregulator interaction
10.1016/bs.apcsb.2017.06.001 · 2018 · External reference
Causal discovery from temporal data: an overview and new perspectives
10.1145/3705297 · 2024 · External reference
Causal enhanced drug–target interaction prediction based on graph generation and multi-source information fusion
10.1093/bioinformatics/btae570 · 2024 · External reference
10.1038/s41596-021-00659-2
10.1038/s41596-021-00659-2 · External reference
Rapid traversal of vast chemical space using machine learning-guided docking screens
2025 · External reference
A Bayesian machine learning approach for drug target identification using diverse data types
10.1038/s41467-019-12928-6 · 2019 · External reference
Off-targetp ML: an open source machine learning framework for off-target panel safety assessment of small molecules
10.1186/s13321-022-00603-w · 2022 · External reference
Covid-19: combining antiviral and anti-inflammatory treatments
10.1016/s1473-3099(20)30132-8 · 2020 · External reference
10.1093/bioinformatics/bty294
10.1093/bioinformatics/bty294 · External reference
Deep learning identifies synergistic drug combinations for treating Covid-19
10.1073/pnas.2105070118 · 2021 · External reference
Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs
10.1038/s41467-021-22170-8 · 2021 · External reference
Prior knowledge-guided multilevel graph neural network for tumor risk prediction and interpretation via multi-omics data integration
10.1093/bib/bbae184 · 2024 · External reference
Unresolved reference
2023 · External reference
10.1016/j.cell.2017.10.049
10.1016/j.cell.2017.10.049 · External reference
10.1145/3744237
10.1145/3744237 · External reference
10.1016/j.sbi.2023.102771
10.1016/j.sbi.2023.102771 · External reference
10.1038/s41589-023-01349-8
10.1038/s41589-023-01349-8 · External reference
The comprehensive in vitro proarrhythmia assay (cipa) initiative—update on progress
10.1016/j.vascn.2016.06.002 · 2016 · External reference
10.1152/physrev.00017.2023
10.1152/physrev.00017.2023 · External reference
Advancing bioactivity prediction through molecular docking and self-attention
10.1109/jbhi.2024.3448455 · 2024 · External reference
10.1145/2939672.2939754
10.1145/2939672.2939754 · 2016 · External reference
