title: Finding candidate drugs for hepatitis C based on chemical-chemical and chemical-protein interactions.
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.
authors.affiliation: College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China.
authors.forename: Lei
authors.initials: L
authors.lastname: Chen
authors.affiliation: Department of Medicinal Chemistry, School of Pharmacy, Yantai University, Shandong, Yantai, People's Republic of China.
authors.forename: Jing
authors.initials: J
authors.lastname: Lu
authors.affiliation: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
authors.forename: Tao
authors.initials: T
authors.lastname: Huang
authors.affiliation: College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China.
authors.forename: Jun
authors.initials: J
authors.lastname: Yin
authors.affiliation: College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China.
authors.forename: Lai
authors.initials: L
authors.lastname: Wei
authors.affiliation: Institute of Systems Biology, Shanghai University, Shanghai, People's Republic of China.
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
mesh_terms: D000465:Algorithms; D000998:Antiviral Agents / Q000378:metabolism* / Q000494:pharmacology*; D019295:Computational Biology / Q000379:methods; D055808:Drug Discovery; D015967:Gene Expression Regulation, Viral / Q000187:drug effects; D016174:Hepacivirus / Q000187:drug effects* / Q000235:genetics; D006801:Humans
chemical_list: D000998:Antiviral Agents