Finding candidate drugs for hepatitis C based on chemical-chemical and chemical-protein interactions

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 t...

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Bibliographic Details
Published in:PloS one 2014, Vol.9 (9), p.e107767
Main Authors: Chen, Lei, Lu, Jing, Huang, Tao, Yin, Jun, Wei, Lai, Cai, Yu-Dong
Format: Article
Language:English
Subjects:
Acyclovir
Algorithms
Antiviral Agents - metabolism
Antiviral Agents - pharmacology
Artificial intelligence
Biology and life sciences
Border patrol
Chemical interactions
Chemicals
Computational Biology - methods
Computer applications
Drug development
Drug Discovery
Drugs
Experimental methods
Filtration
Ganciclovir
Gene Expression Regulation, Viral - drug effects
Genotype & phenotype
Hepacivirus - drug effects
Hepacivirus - genetics
Hepatitis
Hepatitis C
Hepatology
Humans
Illnesses
Interferon
Medical treatment
Medicine and health sciences
Protein interaction
Proteins
Viruses
Websites
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Summary: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.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0107767