AIMC Topic: Drug Repositioning

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Comparing a knowledge-driven approach to a supervised machine learning approach in large-scale extraction of drug-side effect relationships from free-text biomedical literature.

BMC bioinformatics Mar 18, 2015
BACKGROUND: Systems approaches to studying drug-side-effect (drug-SE) associations are emerging as an active research area for both drug target discovery and drug repositioning. However, a comprehensive drug-SE association knowledge base does not exi...
MEDLINE Search Engine Databases, Pharmaceutical Pharmaceutical Preparations Phenotype Humans Knowledge Bases Periodicals as Topic Artificial Intelligence Data Mining Drug Discovery Drug-Related Side Effects and Adverse Reactions Biological Ontologies Drug Repositioning
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Prediction of drug gene associations via ontological profile similarity with application to drug repositioning.

Methods (San Diego, Calif.) Dec 8, 2014
The amount of biomedical literature has been increasing rapidly during the last decade. Text mining techniques can harness this large-scale data, shed light onto complex drug mechanisms, and extract relation information that can support computational...
Humans Genetic Association Studies Data Mining Forecasting Drug Repositioning Pharmacogenetics Gene Ontology Pharmaceutical Preparations
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Adaptive debiasing learning for drug repositioning.

Journal of biomedical informatics Jul 1, 2025
Drug repositioning, pivotal in current pharmaceutical development, aims to find new uses for existing drugs, offering an efficient and cost-effective path to drug discovery. In recent years, graph neural network-based deep learning methods have achie...
Humans Drug Discovery Deep Learning Drug Repositioning Neural Networks, Computer Algorithms Databases, Factual
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Heterogeneous Graph Contrastive Learning with Graph Diffusion for Drug Repositioning.

Journal of chemical information and modeling Jun 9, 2025
Drug repositioning, which identifies novel therapeutic applications for existing drugs, offers a cost-effective alternative to traditional drug development. However, effectively capturing the complex relationships between drugs and diseases remains c...
Drug Repositioning Alzheimer Disease Humans Machine Learning
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MiRAGE-DTI: A novel approach for drug-target interaction prediction by integrating drug and target similarity metrics.

Computers in biology and medicine Jun 1, 2025
MOTIVATION: Accurately predicting drug-target interactions (DTIs) is critical for accelerating drug discovery, repositioning, and development. Traditional experimental methods are often expensive and time-consuming, emphasizing the need for efficient...
Drug Discovery Humans Machine Learning Computational Biology Algorithms Drug Repositioning
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Drug repurposing targeting COVID-19 3CL protease using molecular docking and machine learning regression approaches.

Scientific reports May 28, 2025
The COVID-19 pandemic has initiated a global health emergency, with an exigent need for an effective cure. Progressively, drug repurposing is emerging as a promising solution for saving time, cost, and labor. However, the number of drug candidates th...
Antiviral Agents Protein Binding Drug Repositioning Cysteine Endopeptidases Humans COVID-19 COVID-19 Drug Treatment Betacoronavirus Machine Learning SARS-CoV-2 Quantitative Structure-Activity Relationship Coronavirus 3C Proteases Pandemics Molecular Docking Simulation Viral Nonstructural Proteins
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A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Scientific reports May 12, 2025
Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae family and Henipavirus genus is transmitted by Pteropus bats. Climate-induced changes in bat migration pa...
Humans Animals RNA-Dependent RNA Polymerase Molecular Dynamics Simulation Molecular Docking Simulation Adenosine Monophosphate Alanine Deep Learning Henipavirus Infections Nipah Virus Antiviral Agents Drug Repositioning Models, Molecular
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A Multi-Modal Graph Neural Network Framework for Parkinson's Disease Therapeutic Discovery.

International journal of molecular sciences May 7, 2025
Parkinson's disease (PD) is a complex neurodegenerative disorder lacking effective disease-modifying treatments. In this study, we integrated large-scale protein-protein interaction networks with a multi-modal graph neural network (GNN) to identify a...
Graph Neural Networks Humans Neural Networks, Computer Drug Discovery Protein Interaction Maps Parkinson Disease Drug Repositioning
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Repurposing FDA-approved drugs as NLRP3 inhibitors against inflammatory diseases: machine learning and molecular simulation approaches.

Journal of biomolecular structure & dynamics May 1, 2025
Activation of NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) has been associated with multiple chronic pathologies, including diabetes, atherosclerosis, and rheumatoid arthritis. Moreover, histone deacetylases (HDACs), specifical...
NLR Family, Pyrin Domain-Containing 3 Protein Molecular Dynamics Simulation Inflammasomes United States Food and Drug Administration Drug Approval Inflammation United States Drug Repositioning Machine Learning Molecular Docking Simulation Humans Protein Binding
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H2GnnDTI: hierarchical heterogeneous graph neural networks for drug-target interaction prediction.

Bioinformatics (Oxford, England) Mar 29, 2025
MOTIVATION: Identifying drug-target interactions (DTIs) is a crucial step in drug repurposing and drug discovery. The significant increase in demand and the expensive nature for experimentally identifying DTIs necessitate computational tools for auto...
Neural Networks, Computer Pharmaceutical Preparations Graph Neural Networks Computational Biology Software Proteins Algorithms Drug Repositioning Drug Discovery
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