ArticlePloS one2014
Finding candidate drugs for hepatitis C based on chemical-chemical and chemical-protein interactions.
Article in PloS one, 2014. 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, 33 citations in OpenAlex.
- Article
- Artificial Intelligence-Based Ensemble Learning Model for Prediction of Hepatitis C Disease.Frontiers in public health · 2022Article
- Identification of anticancer drug target genes using an outside competitive dynamics model on cancer signaling networks.Scientific reports · 2021Article
- CGINet: graph convolutional network-based model for identifying chemical-gene interaction in an integrated multi-relational graph.BMC bioinformatics · 2020Article
- Automated Extraction of Information From Texts of Scientific Publications: Insights Into HIV Treatment Strategies.Frontiers in genetics · 2020Article
- Impact of Aspirin Eugenol Ester on Cyclooxygenase-1, Cyclooxygenase-2, C-Reactive Protein, Prothrombin and Arachidonate 5-Lipoxygenase in Healthy Rats.Iranian journal of pharmaceutical research : IJPR · 2017Article
- A computational method for the identification of candidate drugs for non-small cell lung cancer.PloS one · 2017Article
- The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life.PloS one · 2016Article
- Discovery of new candidate genes related to brain development using protein interaction information.PloS one · 2015Article
- Identification of Chemical Toxicity Using Ontology Information of Chemicals.Computational and mathematical methods in medicine · 2015Article
- Article
- Prediction of drug indications based on chemical interactions and chemical similarities.BioMed research international · 2015Article
- Identification of novel thyroid cancer-related genes and chemicals using shortest path algorithm.BioMed research international · 2015Article
- Gene Ontology and KEGG Pathway Enrichment Analysis of a Drug Target-Based Classification System.PloS one · 2015Article
- The Use of Chemical-Chemical Interaction and Chemical Structure to Identify New Candidate Chemicals Related to Lung Cancer.PloS one · 2015Article
- Article
- Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach.Computational and mathematical methods in medicine · 2015Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatitis C virus (HCV) is an infectious virus that can cause serious illnesses. Only a few drugs have been reported to effectively treat hepatitis C. To have greater diversity in drug choice and better treatment options, it is necessary to develop more drugs to treat the infection. However, it is time-consuming and expensive to discover candidate drugs using experimental methods, and computational methods may complement experimental approaches as a preliminary filtering process. This type of approach was proposed by using known chemical-chemical interactions to extract interactive compounds with three known drug compounds of HCV, and the probabilities of these drug compounds being able to treat hepatitis C were calculated using chemical-protein interactions between the interactive compounds and HCV target genes. Moreover, the randomization test and expectation-maximization (EM) algorithm were both employed to exclude false discoveries. Analysis of the selected compounds, including acyclovir and ganciclovir, indicated that some of these compounds had potential to treat the HCV. Hopefully, this proposed method could provide new insights into the discovery of candidate drugs for the treatment of HCV and other diseases.
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