ArticlePloS one2013
Identifying chemicals with potential therapy of HIV based on protein-protein and protein-chemical interaction network.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 19 citations in OpenAlex.
- 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
- Network-Based Analysis of OMICs Data to Understand the HIV-Host Interaction.Frontiers in microbiology · 2020Review
- HIV-1, human interaction database: current status and new features.Nucleic acids research · 2015Article
- A graphic method for identification of novel glioma related genes.BioMed research international · 2014Article
- Identifying gastric cancer related genes using the shortest path algorithm and protein-protein interaction network.BioMed research international · 2014Article
- Identification of age-related macular degeneration related genes by applying shortest path algorithm in protein-protein interaction network.BioMed research international · 2013Article
Corrections and comments
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Authors and funding
10 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acquired immune deficiency syndrome (AIDS) is a severe infectious disease that causes a large number of deaths every year. Traditional anti-AIDS drugs directly targeting the HIV-1 encoded enzymes including reverse transcriptase (RT), protease (PR) and integrase (IN) usually suffer from drug resistance after a period of treatment and serious side effects. In recent years, the emergence of numerous useful information of protein-protein interactions (PPI) in the HIV life cycle and related inhibitors makes PPI a new way for antiviral drug intervention. In this study, we identified 26 core human proteins involved in PPI between HIV-1 and host, that have great potential for HIV therapy. In addition, 280 chemicals that interact with three HIV drugs targeting human proteins can also interact with these 26 core proteins. All these indicate that our method as presented in this paper is quite promising. The method may become a useful tool, or at least plays a complementary role to the existing method, for identifying novel anti-HIV drugs.
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