Research graph
References from AI based target-ligand binding methods. Local targets link to admitted publications; unresolved targets remain external evidence.
Studying protein-protein interactions: latest and most popular approaches
10.1016/j.jsb.2024.108118 · 2024 · External reference
A multiscale in silico approach to impede the interaction between Dengue NS1 and Human RPL18, aiming to suppress the Dengue viral translation and proliferation
10.1080/08927022.2024.2426587 · 2024 · External reference
The protein data bank
10.1093/nar/28.1.235 · 2000 · External reference
The role of AI in drug discovery: challenges, opportunities, and strategies
10.3390/ph16060891 · 2023 · External reference
Identification of drug-drug interactions using chemical interactions
10.2174/1574893611666160618094219 · 2017 · External reference
Artificial intelligence-driven prediction of multiple drug interaction
10.1093/bib/bbac427 · 2022 · External reference
An effective framework for predicting drug-drug interactions based on molecular substructures and knowledge graph neural network
10.1016/j.compbiomed.2023.107900 · 2024 · External reference
Research and development costs of new drugs
10.1001/jama.2020.8645 · 2020 · External reference
Insights into protein-ligand interactions: mechanisms, models, and methods
10.3390/ijms17020144 · 2016 · External reference
AutoDock Vina 1.2. 0: new docking methods, expanded force field, and python bindings
10.1021/acs.jcim.1c00203 · 2021 · External reference
Computational prediction of drug-drug interactions based on drugs functional similarities
10.1016/j.jbi.2017.04.021 · 2017 · External reference
AI-driven drug discovery: a comprehensive review
10.1021/acsomega.5c00549 · 2025 · External reference
Knowledge-based scoring function to predict protein-ligand interactions
10.1006/jmbi.1999.3371 · 2000 · External reference
Benchmarking AI-powered docking methods from the perspective of virtual screening
10.1038/s42256-025-00993-0 · 2025 · External reference
New machine learning and physics-based scoring functions for drug discovery
10.1038/s41598-021-82410-1 · 2021 · External reference
Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges
10.3389/fphar.2018.01089 · 2018 · External reference
Accelerating therapeutics for opportunities in medicine: a paradigm shifts in drug discovery
10.3389/fphar.2020.00770 · 2020 · External reference
Predicting drug-drug interactions using deep neural network
2019 · External reference
Principles of early drug discovery
10.1111/j.1476-5381.2010.01127.x · 2011 · External reference
A hybrid approach based on pattern recognition and BioNLP for investigating drug-drug interaction
10.2174/157489361003150723135136 · 2015 · External reference
Detection of clinically significant drug-drug interactions in fatal torsades de pointes: disproportionally analysis of the food and drug administration adverse event reporting system
10.2196/65872 · 2025 · External reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · 2021 · External reference
Atom-based 3D-QSAR and DFT analysis of 5‐substituted 2‐acylaminothiazole derivatives as HIV-1 latency-reversing agents
10.1080/07391102.2022.2112078 · 2023 · External reference
A review of CYP-mediated drug interactions: mechanisms and in vitro drug-drug interaction assessment
10.3390/biom14010099 · 2024 · External reference
Drug-drug interaction extraction based on transfer weight matrix and memory network
10.1109/access.2019.2930641 · 2019 · External reference
Drug-drug interaction extraction via convolutional neural networks
2016 · External reference
Enhancing drug-drug interaction prediction using deep attention neural networks
10.1109/tcbb.2022.3172421 · 2023 · External reference
Modeling polypharmacy effects with heterogeneous signed graph convolutional networks
10.1007/s10489-021-02296-4 · 2021 · External reference
Prediction of active drug molecule using back propagation neural network
2019 · External reference
GNINA 1.0: molecular docking with deep learning
10.1186/s13321-021-00522-2 · 2021 · External reference
Automated radiotherapy treatment planning
10.1016/j.semradonc.2019.02.003 · 2019 · External reference
An evaluation of the completeness of drug-drug interaction-related information in package inserts
10.1007/s00228-016-2151-9 · 2017 · External reference
Pharmacokinetic drug-drug interaction and their implication in clinical management
2013 · External reference
Identification of potent inhibitors targeting the pre-fusion DENV envelope protein: A consensus physics-and AI-based in silico multi-tier screening approach
10.1016/j.bbrc.2026.153722 · 2026 · External reference
Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation
10.1016/j.ijantimicag.2024.107122 · 2024 · External reference
AI in drug discovery and its clinical relevance
10.1016/j.heliyon.2023.e17575 · 2023 · External reference
Drug interactions: mechanisms, assessment and management strategies
10.5530/jyp.2024.16.58 · 2024 · External reference
Advances in QSAR through artificial intelligence and machine learning methods
2023 · External reference
Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors
10.1016/j.ymeth.2023.09.010 · 2023 · External reference
Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures
10.1371/journal.pone.0219796 · 2019 · External reference
An in-depth examination of drug-drug interaction databases: enhancing patient safety through advanced predictive models and artificial intelligence techniques
10.21608/jmals.2024.410645 · 2024 · External reference
Drug-drug interaction extraction via recurrent hybrid convolutional neural networks with an improved focal loss
10.3390/e21010037 · 2019 · External reference
A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports
10.1136/amiajnl-2011-000214 · 2012 · External reference
On the road to explainable AI in drug-drug interactions prediction: a systematic review
10.1016/j.csbj.2022.04.021 · 2022 · External reference
Prediction of protein–ligand binding affinity via deep learning models
10.1093/bib/bbae081 · 2024 · External reference
GoGNN: graph of graphs neural network for predicting structured entity interactions
2020 · External reference
The prevalence of the potential drug-drug interactions involving anticancer drugs in China: a retrospective study
2019 · External reference
drug-drug interaction extraction via hybrid neural networks on biomedical literature
10.1016/j.jbi.2020.103432 · 2020 · External reference
The role of artificial intelligence in predicting drug-drug interaction: a new frontier in patient safety
2025 · External reference
Pharmacophore modeling and applications in drug discovery: challenges and recent advances
10.1016/j.drudis.2010.03.013 · 2010 · External reference
Unresolved reference
External reference
Application of artificial intelligence in drug-drug interactions prediction: a review
2023 · External reference
A review of biophysical strategies to investigate protein-ligand binding: what have we employed?
10.1016/j.ijbiomac.2024.133973 · 2024 · External reference
TTD: therapeutic target database describing target druggability information
10.1093/nar/gkad751 · 2024 · External reference
SSF-DDI: a deep learning method utilizing drug sequence and substructure features for drug-drug interaction prediction
10.1186/s12859-024-05654-4 · 2024 · External reference
Research and development costs of new drugs
10.1001/jama.2020.8645 · ExternalCitation · doi-reference
Knowledge-based scoring function to predict protein-ligand interactions
10.1006/jmbi.1999.3371 · ExternalCitation · doi-reference
An evaluation of the completeness of drug-drug interaction-related information in package inserts
10.1007/s00228-016-2151-9 · ExternalCitation · doi-reference
Modeling polypharmacy effects with heterogeneous signed graph convolutional networks
10.1007/s10489-021-02296-4 · ExternalCitation · doi-reference
Identification of potent inhibitors targeting the pre-fusion DENV envelope protein: A consensus physics-and AI-based in silico multi-tier screening approach
10.1016/j.bbrc.2026.153722 · ExternalCitation · doi-reference
An effective framework for predicting drug-drug interactions based on molecular substructures and knowledge graph neural network
10.1016/j.compbiomed.2023.107900 · ExternalCitation · doi-reference
On the road to explainable AI in drug-drug interactions prediction: a systematic review
10.1016/j.csbj.2022.04.021 · ExternalCitation · doi-reference
Pharmacophore modeling and applications in drug discovery: challenges and recent advances
10.1016/j.drudis.2010.03.013 · ExternalCitation · doi-reference
AI in drug discovery and its clinical relevance
10.1016/j.heliyon.2023.e17575 · ExternalCitation · doi-reference
Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation
10.1016/j.ijantimicag.2024.107122 · ExternalCitation · doi-reference
A review of biophysical strategies to investigate protein-ligand binding: what have we employed?
10.1016/j.ijbiomac.2024.133973 · ExternalCitation · doi-reference
Computational prediction of drug-drug interactions based on drugs functional similarities
10.1016/j.jbi.2017.04.021 · ExternalCitation · doi-reference
drug-drug interaction extraction via hybrid neural networks on biomedical literature
10.1016/j.jbi.2020.103432 · ExternalCitation · doi-reference
Studying protein-protein interactions: latest and most popular approaches
10.1016/j.jsb.2024.108118 · ExternalCitation · doi-reference
Automated radiotherapy treatment planning
10.1016/j.semradonc.2019.02.003 · ExternalCitation · doi-reference
Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors
10.1016/j.ymeth.2023.09.010 · ExternalCitation · doi-reference
AutoDock Vina 1.2. 0: new docking methods, expanded force field, and python bindings
10.1021/acs.jcim.1c00203 · ExternalCitation · doi-reference
AI-driven drug discovery: a comprehensive review
10.1021/acsomega.5c00549 · ExternalCitation · doi-reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · ExternalCitation · doi-reference
New machine learning and physics-based scoring functions for drug discovery
10.1038/s41598-021-82410-1 · ExternalCitation · doi-reference
Benchmarking AI-powered docking methods from the perspective of virtual screening
10.1038/s42256-025-00993-0 · ExternalCitation · doi-reference
Atom-based 3D-QSAR and DFT analysis of 5‐substituted 2‐acylaminothiazole derivatives as HIV-1 latency-reversing agents
10.1080/07391102.2022.2112078 · ExternalCitation · doi-reference
A multiscale in silico approach to impede the interaction between Dengue NS1 and Human RPL18, aiming to suppress the Dengue viral translation and proliferation
10.1080/08927022.2024.2426587 · ExternalCitation · doi-reference
Artificial intelligence-driven prediction of multiple drug interaction
10.1093/bib/bbac427 · ExternalCitation · doi-reference
Prediction of protein–ligand binding affinity via deep learning models
10.1093/bib/bbae081 · ExternalCitation · doi-reference
The protein data bank
10.1093/nar/28.1.235 · ExternalCitation · doi-reference
TTD: therapeutic target database describing target druggability information
10.1093/nar/gkad751 · ExternalCitation · doi-reference
Drug-drug interaction extraction based on transfer weight matrix and memory network
10.1109/access.2019.2930641 · ExternalCitation · doi-reference
Enhancing drug-drug interaction prediction using deep attention neural networks
10.1109/tcbb.2022.3172421 · ExternalCitation · doi-reference
Principles of early drug discovery
10.1111/j.1476-5381.2010.01127.x · ExternalCitation · doi-reference
A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports
10.1136/amiajnl-2011-000214 · ExternalCitation · doi-reference
SSF-DDI: a deep learning method utilizing drug sequence and substructure features for drug-drug interaction prediction
10.1186/s12859-024-05654-4 · ExternalCitation · doi-reference
GNINA 1.0: molecular docking with deep learning
10.1186/s13321-021-00522-2 · ExternalCitation · doi-reference
Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures
10.1371/journal.pone.0219796 · ExternalCitation · doi-reference
An in-depth examination of drug-drug interaction databases: enhancing patient safety through advanced predictive models and artificial intelligence techniques
10.21608/jmals.2024.410645 · ExternalCitation · doi-reference
A hybrid approach based on pattern recognition and BioNLP for investigating drug-drug interaction
10.2174/157489361003150723135136 · ExternalCitation · doi-reference
Identification of drug-drug interactions using chemical interactions
10.2174/1574893611666160618094219 · ExternalCitation · doi-reference
Detection of clinically significant drug-drug interactions in fatal torsades de pointes: disproportionally analysis of the food and drug administration adverse event reporting system
10.2196/65872 · ExternalCitation · doi-reference
Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges
10.3389/fphar.2018.01089 · ExternalCitation · doi-reference
Accelerating therapeutics for opportunities in medicine: a paradigm shifts in drug discovery
10.3389/fphar.2020.00770 · ExternalCitation · doi-reference
A review of CYP-mediated drug interactions: mechanisms and in vitro drug-drug interaction assessment
10.3390/biom14010099 · ExternalCitation · doi-reference
Drug-drug interaction extraction via recurrent hybrid convolutional neural networks with an improved focal loss
10.3390/e21010037 · ExternalCitation · doi-reference
Insights into protein-ligand interactions: mechanisms, models, and methods
10.3390/ijms17020144 · ExternalCitation · doi-reference
The role of AI in drug discovery: challenges, opportunities, and strategies
10.3390/ph16060891 · ExternalCitation · doi-reference
Drug interactions: mechanisms, assessment and management strategies
10.5530/jyp.2024.16.58 · ExternalCitation · doi-reference
