ArticleBMC systems biology2012
Predicting new molecular targets for rhein using network pharmacology.
Article in BMC systems biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 48 citations in OpenAlex.
- Study on the Mechanism of the Combination of Methotrexate and Leflunomide in the Treatment of Rheumatoid Arthritis Based on Network Pharmacology, Molecular Docking, andCombinatorial chemistry & high throughput screening · 2025Article
- Identify Diabetes-related Targets based on ForgeNet_GPC.Current computer-aided drug design · 2024Article
- Disease-related compound identification based on deeping learning method.Scientific reports · 2022Article
- Computer-aided drug design combined network pharmacology to explore anti-SARS-CoV-2 or anti-inflammatory targets and mechanisms of Qingfei Paidu Decoction for COVID-19.Frontiers in immunology · 2022Article
- The Ameliorative Effects of Arctiin and Arctigenin on the Oxidative Injury of Lung Induced by Silica via TLR-4/NLRP3/TGF-Oxidative medicine and cellular longevity · 2021Article
- Mechanisms of Paeonia lactiflora in Treatment of Ulcerative Colitis: A Network Pharmacological Study.Medical science monitor : international medical journal of experimental and clinical research · 2019Article
- Systems Biology - A Pivotal Research Methodology for Understanding the Mechanisms of Traditional Medicine.Journal of pharmacopuncture · 2015Review
- Rhein prevents endotoxin-induced acute kidney injury by inhibiting NF-κB activities.Scientific reports · 2015Article
- Toward more realistic drug-target interaction predictions.Briefings in bioinformatics · 2015Article
- Network pharmacological identification of active compounds and potential actions of Erxian decoction in alleviating menopause-related symptoms.Chinese medicine · 2015Article
- An analysis of chemical ingredients network of Chinese herbal formulae for the treatment of coronary heart disease.PloS one · 2015Article
- Retraction note: Predicting new molecular targets for rhein using network pharmacology.BMC systems biology · 2014Article
- Drug target mining and analysis of the Chinese tree shrew for pharmacological testing.PloS one · 2014Article
- CVDHD: a cardiovascular disease herbal database for drug discovery and network pharmacology.Journal of cheminformatics · 2013Article
- A Drug-Target Network-Based Approach to Evaluate the Efficacy of Medicinal Plants for Type II Diabetes Mellitus.Evidence-based complementary and alternative medicine : eCAM · 2013Article
- Polypharmacology: drug discovery for the future.Expert review of clinical pharmacology · 2013Review
- Navigating traditional chinese medicine network pharmacology and computational tools.Evidence-based complementary and alternative medicine : eCAM · 2013Article
- Network pharmacology: a new approach for chinese herbal medicine research.Evidence-based complementary and alternative medicine : eCAM · 2013Article
- Material basis of Chinese herbal formulas explored by combining pharmacokinetics with network pharmacology.PloS one · 2013Article
- Drug repurposing: translational pharmacology, chemistry, computers and the clinic.Current topics in medicinal chemistry · 2013Review
Corrections and comments
- Retraction · 2014-09-18Compromised Peer Review · Misconduct by Author ·
- Retracted
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDrugs can influence the whole biological system by targeting interaction reactions. The existence of interactions between drugs and network reactions suggests a potential way to discover targets. The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of drug-targets in current datasets are validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. Currently, network pharmacology has used in identifying potential drug targets to predicting the spread of drug activity and greatly contributed toward the analysis of biological systems on a much larger scale than ever before.
methodsIn this article, we present a computational method to predict targets for rhein by exploring drug-reaction interactions. We have implemented a computational platform that integrates pathway, protein-protein interaction, differentially expressed genome and literature mining data to result in comprehensive networks for drug-target interaction. We used Cytoscape software for prediction rhein-target interactions, to facilitate the drug discovery pipeline.
resultsResults showed that 3 differentially expressed genes confirmed by Cytoscape as the central nodes of the complicated interaction network (99 nodes, 153 edges). Of note, we further observed that the identified targets were found to encompass a variety of biological processes related to immunity, cellular apoptosis, transport, signal transduction, cell growth and proliferation and metabolism.
conclusionsOur findings demonstrate that network pharmacology can not only speed the wide identification of drug targets but also find new applications for the existing drugs. It also implies the significant contribution of network pharmacology to predict drug targets.
Indexed as
Identifiers
What OpenQuestion holds
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.