ArticlePharmaceutics2020
Uncovering New Drug Properties in Target-Based Drug-Drug Similarity Networks.
Article in Pharmaceutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- MHNNMDA: multi-stage hypergraph neural network for predicting miRNA-disease association types.Journal of computer-aided molecular design · 2026Article
- The Complexity of Drug Development: Translational Value and Limitations of Computational ADMET Assays Applied to Approved Anticancer Drugs.Pharmaceuticals (Basel, Switzerland) · 2026Article
- The Evolution of Machine Learning in Medicinal Chemistry: A Comprehensive Bibliometric Analysis.Current neuropharmacology · 2026Review
- Redefining Breast Cancer Care by Harnessing Computational Drug Repositioning.Medicina (Kaunas, Lithuania) · 2025Review
- Drug repositioning pipeline integrating community analysis in drug-drug similarity networks and automated ATC community labeling to foster molecular docking analysis.Frontiers in bioinformatics · 2025Article
- Combining single-cell RNA sequencing and network pharmacology to explore the target of cangfu daotan decoction in the treatment of obese polycystic ovary syndrome from an immune perspective.Frontiers in pharmacology · 2024Article
- Guiding Drug Repositioning for Cancers Based on Drug Similarity Networks.International journal of molecular sciences · 2023Article
- The curse and blessing of abundance-the evolution of drug interaction databases and their impact on drug network analysis.GigaScience · 2022Article
- Artificial Intelligence and Precision Medicine: A New Frontier for the Treatment of Brain Tumors.Life (Basel, Switzerland) · 2022Review
- Proposal to Consider Chemical/Physical Microenvironment as a New Therapeutic Off-Target Approach.Pharmaceutics · 2022Article
- GABAkines - Advances in the discovery, development, and commercialization of positive allosteric modulators of GABAPharmacology & therapeutics · 2022Review
- Integrating Network Pharmacology and Molecular Docking to Analyse the Potential Mechanism of action ofVeterinary sciences · 2021Article
- Drug Repurposing Using Modularity Clustering in Drug-Drug Similarity Networks Based on Drug-Gene Interactions.Pharmaceutics · 2021Article
- New Investigations with Lupane Type A-Ring Azepane Triterpenoids for Antimycobacterial Drug Candidate Design.International journal of molecular sciences · 2021Article
- 3D-ALMOND-QSAR Models to Predict the Antidepressant Effect of Some Natural Compounds.Pharmaceutics · 2021Article
- Topological network measures for drug repositioning.Briefings in bioinformatics · 2021Article
- Biocomputational Prediction Approach Targeting FimH by Natural SGLT2 Inhibitors: A Possible Way to Overcome the Uropathogenic Effect of SGLT2 Inhibitor Drugs.Molecules (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite recent advances in bioinformatics, systems biology, and machine learning, the accurate prediction of drug properties remains an open problem. Indeed, because the biological environment is a complex system, the traditional approach-based on knowledge about the chemical structures-can not fully explain the nature of interactions between drugs and biological targets. Consequently, in this paper, we propose an unsupervised machine learning approach that uses the information we know about drug-target interactions to infer drug properties. To this end, we define drug similarity based on drug-target interactions and build a weighted Drug-Drug Similarity Network according to the drug-drug similarity relationships. Using an energy-model network layout, we generate drug communities associated with specific, dominant drug properties. DrugBank confirms the properties of 59.52% of the drugs in these communities, and 26.98% are existing drug repositioning hints we reconstruct with our DDSN approach. The remaining 13.49% of the drugs seem not to match the dominant pharmacologic property; thus, we consider them potential drug repurposing hints. The resources required to test all these repurposing hints are considerable. Therefore we introduce a mechanism of prioritization based on the betweenness/degree node centrality. Using betweenness/degree as an indicator of drug repurposing potential, we select Azelaic acid and Meprobamate as a possible antineoplastic and antifungal, respectively. Finally, we use a test procedure based on molecular docking to analyze Azelaic acid and Meprobamate's repurposing.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.