ArticlePLoS computational biology2012
Prediction of drug-target interactions and drug repositioning via network-based inference.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 302 papers.
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Who cites it
302 citing papers in PubMed.
- A Node-Adaptive Feature Fusion Network for Drug-Target Interaction Prediction Based on Multi-View Graphs.Biomolecules · 2026Article
- Machine Learning Approaches for Compound-Target Interaction Prediction: A Review.Foods (Basel, Switzerland) · 2026Review
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- ARKbase: Antimicrobial Resistance Knowledgebase1.0.Nucleic acids research · 2026Article
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- In silico drug sensitivity predicts subgroup-specific therapeutics in medulloblastoma patients.Scientific reports · 2025Article
- Graph convolution network based on meta-paths and mutual information for drug-target interaction prediction.BMC bioinformatics · 2025Article
- A fused deep learning approach to transform drug repositioning.Communications chemistry · 2025Article
- DeepTarget predicts anti-cancer mechanisms of action of small molecules by integrating drug and genetic screens.NPJ precision oncology · 2025Article
- Computational Investigation of the Potential Antileishmanial Mechanism of the Nitroindazole Derivative VATR131.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Drug-disease networks and drug repurposing.PLoS computational biology · 2025Article
- DHGT-DTI: Advancing drug-target interaction prediction through a dual-view heterogeneous network with GraphSAGE and Graph Transformer.Journal of pharmaceutical analysis · 2025Article
- Improving computational drug repositioning through multi-source disease similarity networks.Scientific reports · 2025Article
- Repurposing FDA approved drugs for psoriasis indications through integrated molecular docking, one-SVM algorithm, and molecular dynamics simulation approaches.Scientific reports · 2025Article
- DrugReX: an explainable drug repurposing system powered by large language models and literature-based knowledge graph.Research square · 2025Article
- Labels as a feature: Network homophily for systematically annotating human GPCR drug-target interactions.Nature communications · 2025Article
- DTIAM: a unified framework for predicting drug-target interactions, binding affinities and drug mechanisms.Nature communications · 2025Article
- Improving drug repositioning accuracy using non-negative matrix tri-factorization.Scientific reports · 2025Article
- MFCADTI: improving drug-target interaction prediction by integrating multiple feature through cross attention mechanism.BMC bioinformatics · 2025Article
242 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming and costly to determine DTI experimentally. Hence, it is necessary to develop computational methods for the prediction of potential DTI. Based on complex network theory, three supervised inference methods were developed here to predict DTI and used for drug repositioning, namely drug-based similarity inference (DBSI), target-based similarity inference (TBSI) and network-based inference (NBI). Among them, NBI performed best on four benchmark data sets. Then a drug-target network was created with NBI based on 12,483 FDA-approved and experimental drug-target binary links, and some new DTIs were further predicted. In vitro assays confirmed that five old drugs, namely montelukast, diclofenac, simvastatin, ketoconazole, and itraconazole, showed polypharmacological features on estrogen receptors or dipeptidyl peptidase-IV with half maximal inhibitory or effective concentration ranged from 0.2 to 10 µM. Moreover, simvastatin and ketoconazole showed potent antiproliferative activities on human MDA-MB-231 breast cancer cell line in MTT assays. The results indicated that these methods could be powerful tools in prediction of DTIs and drug repositioning.
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Registered trials
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.