The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
The HCV Life Cycle: In vitro Tissue Culture Systems and Therapeutic Targets
Open accessAbstract
Hepatitis C virus (HCV) is a highly variable plus-strand RNA virus of the family Flaviviridae. Viral strains are grouped into six epidemiologically relevant genotypes that differ from each other by more than 30% at the nucleotide level. The variability of HCV allows immune evasion and facilitates persistence. It is also a substantial challenge for the development of specific antiviral therapies effective across all HCV genotypes and for prevention of drug resistance. Novel HCV cell culture models were instrumental for identification and profiling of therapeutic strategies. Concurrently, these models revealed numerous host factors critical for HCV propagation, some of which have emerged as targets for antiviral therapy. It is generally assumed that the use of host factors is conserved among HCV isolates and genotypes. Additionally, the barrier to viral resistance is thought to be high when interfering with host factors. Therefore, current drug development includes both targeting of viral factors but also of host factors essential for virus replication. In fact, some of these host-targeting agents, for instance inhibitors of cyclophilin A, have advanced to late stage clinical trials. Here, we highlight currently available cell culture systems for HCV, review the most prominent host-targeting strategies against hepatitis C and critically discuss opportunities and risks associated with host-targeting antiviral strategies.
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Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
PHENIX : a comprehensive Python-based system for macromolecular structure solution
Adams, P. D., Afonine, P. V., Bunkóczi, G., Chen, V. B., Davis, I. W., Echols, N., Headd, J. J., Hung, L.-W., Kapral, G. J., Grosse-Kunstleve, R. W., et al. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909052925 · Cited by 23,716
Kabsch, W., & Sander, C. (1983) · Biopolymers · doi:10.1002/bip.360221211 · Cited by 15,320
Mfold web server for nucleic acid folding and hybridization prediction
Zuker, M. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg595 · Cited by 13,404
Principal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248
Erlotinib in Previously Treated Non–Small-Cell Lung Cancer
Shepherd, F. A., Rodrigues Pereira, J., Ciuleanu, T., Tan, E. H., Hirsh, V., Thongprasert, S., Campos, D., Maoleekoonpiroj, S., Smylie, M., Martins, R., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa050753 · Cited by 5,419
Mammalian microRNAs predominantly act to decrease target mRNA levels
Guo, H., Ingolia, N. T., Weissman, J. S., & Bartel, D. P. (2010) · Nature · doi:10.1038/nature09267 · Cited by 3,886
Regulation of mRNA Translation and Stability by microRNAs
Fabian, M. R., Sonenberg, N., & Filipowicz, W. (2010) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060308-103103 · Cited by 3,214
Thematic review series: Glycerolipids. DGAT enzymes and triacylglycerol biosynthesis
Yen, C.-L. E., Stone, S. J., Koliwad, S., Harris, C., & Farese, R. V. (2008) · Journal of Lipid Research · doi:10.1194/jlr.r800018-jlr200 · Cited by 1,105
Structures and mechanisms of viral membrane fusion proteins: multiple variations on a common theme
White, J. M., Delos, S. E., Brecher, M., & Schornberg, K. (2008) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.1080/10409230802058320 · Cited by 892
Specific incorporation of cyclophilin A into HIV-1 virions
Franke, E. K., Yuan, H. E. H., & Luban, J. (1994) · Nature · doi:10.1038/372359a0 · Cited by 745
Evolution of microRNA diversity and regulation in animals
Berezikov, E. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3079 · Cited by 712
Ribosome Profiling Shows That miR-430 Reduces Translation Before Causing mRNA Decay in Zebrafish
Bazzini, A. A., Lee, M. T., & Giraldez, A. J. (2012) · Science · doi:10.1126/science.1215704 · Cited by 709
The growing family of interferon regulatory factors
Nguyen, H., Hiscott, J., & Pitha, P. M. (1997) · Cytokine & Growth Factor Reviews · doi:10.1016/s1359-6101(97)00019-1 · Cited by 480
The epidermal growth factor receptor ligands at a glance
Schneider, M. R., & Wolf, E. (2009) · Journal of Cellular Physiology · doi:10.1002/jcp.21635 · Cited by 447
A cryptic sensor for HIV-1 activates antiviral innate immunity in dendritic cells
Manel, N., Hogstad, B., Wang, Y., Levy, D. E., Unutmaz, D., & Littman, D. R. (2010) · Nature · doi:10.1038/nature09337 · Cited by 427
Regulation of hepatic innate immunity by hepatitis C virus
Horner, S. M., & Gale, M. (2013) · Nature Medicine · doi:10.1038/nm.3253 · Cited by 278
Interferons: Signaling, antiviral and viral evasion
Bonjardim, C. A., Ferreira, P. C. P., & Kroon, E. G. (2009) · Immunology Letters · doi:10.1016/j.imlet.2008.11.002 · Cited by 196
Saphire, A. C. S., Gallay, P. A., & Bark, S. J. (2006) · Journal of Proteome Research · doi:10.1021/pr050276b · Cited by 77
R2D2 Organizes Small Regulatory RNA Pathways in Drosophila∇†
Okamura, K., Robine, N., Liu, Y., Liu, Q., & Lai, E. C. (2011) · Molecular and Cellular Biology · doi:10.1128/mcb.01141-10 · Cited by 70
Cited by
Bartel, D. P. (2018) · Cell · doi:10.1016/j.cell.2018.03.006 · Cited by 3,751
Type I interferons in infectious disease
McNab, F., Mayer-Barber, K., Sher, A., Wack, A., & O'Garra, A. (2015) · Nature Reviews Immunology · doi:10.1038/nri3787 · Cited by 2,780
Endogenous microRNA sponges: evidence and controversy
Thomson, D. W., & Dinger, M. E. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.20 · Cited by 2,185
Into the Eye of the Cytokine Storm
Tisoncik, J. R., Korth, M. J., Simmons, C. P., Farrar, J., Martin, T. R., & Katze, M. G. (2012) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.05015-11 · Cited by 1,940
Phosphoinositides: Tiny Lipids With Giant Impact on Cell Regulation
Balla, T. (2013) · Physiological Reviews · doi:10.1152/physrev.00028.2012 · Cited by 1,638
Metadata
- Authors
- Gerold, G., & Pietschmann, T.
- Venue
- Digestive Diseases
- Publisher
- S. Karger AG
- Published
- 2014
- Volume
- 32
- Issue
- 5
- Pages
- 525-537
- ISSN
- 0257-2753 (ISSN-L)
- 1421-9875
- OpenAlex
- W2022687771
- Cited by
- 4,854
- References
- 20
- FWCI
- 303.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
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