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Model Membrane Platforms for Biomedicine: Case Study on Antiviral Drug Development

Overview of attention for article published in Biointerphases, February 2012
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Title
Model Membrane Platforms for Biomedicine: Case Study on Antiviral Drug Development
Published in
Biointerphases, February 2012
DOI 10.1007/s13758-011-0018-2
Pubmed ID
Authors

Joshua A. Jackman, Nam-Joon Cho

Abstract

As one of the most important interfaces in cellular systems, biological membranes have essential functions in many activities such as cellular protection and signaling. Beyond their direct functions, they also serve as scaffolds to support the association of proteins involved in structural support, adhesion, and transport. Unfortunately, biological processes sometimes malfunction and require therapeutic intervention. For those processes which occur within or upon membranes, it is oftentimes difficult to study the mechanism in a biologically relevant, membranous environment. Therefore, the identification of direct therapeutic targets is challenging. In order to overcome this barrier, engineering strategies offer a new approach to interrogate biological activities at membrane interfaces by analyzing them through the principles of the interfacial sciences. Since membranes are complex biological interfaces, the development of simplified model systems which mimic important properties of membranes can enable fundamental characterization of interaction parameters for such processes. We have selected the hepatitis C virus (HCV) as a model viral pathogen to demonstrate how model membrane platforms can aid antiviral drug discovery and development. Responsible for generating the genomic diversity that makes treating HCV infection so difficult, viral replication represents an ideal step in the virus life cycle for therapeutic intervention. To target HCV genome replication, the interaction of viral proteins with model membrane platforms has served as a useful strategy for target identification and characterization. In this review article, we demonstrate how engineering approaches have led to the discovery of a new functional activity encoded within the HCV nonstructural 5A protein. Specifically, its N-terminal amphipathic, α-helix (AH) can rupture lipid vesicles in a size-dependent manner. While this activity has a number of exciting biotechnology and biomedical applications, arguably the most promising one is in antiviral medicine. Based on the similarities between lipid vesicles and the lipid envelopes of virus particles, experimental findings from model membrane platforms led to the prediction that a range of medically important viruses might be susceptible to rupturing treatment with synthetic AH peptide. This hypothesis was tested and validated by molecular virology studies. Broad-spectrum antiviral activity of the AH peptide has been identified against HCV, HIV, herpes simplex virus, and dengue virus, and many more deadly pathogens. As a result, the AH peptide is the first in class of broad-spectrum, lipid envelope-rupturing antiviral agents, and has entered the drug pipeline. In summary, engineering strategies break down complex biological systems into simplified biomimetic models that recapitulate the most important parameters. This approach is particularly advantageous for membrane-associated biological processes because model membrane platforms provide more direct characterization of target interactions than is possible with other methods. Consequently, model membrane platforms hold great promise for solving important biomedical problems and speeding up the translation of biological knowledge into clinical applications.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 2%
France 1 2%
Singapore 1 2%
Unknown 59 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 23%
Researcher 13 21%
Student > Master 11 18%
Student > Bachelor 5 8%
Professor 5 8%
Other 9 15%
Unknown 5 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 23%
Medicine and Dentistry 9 15%
Biochemistry, Genetics and Molecular Biology 7 11%
Chemistry 6 10%
Social Sciences 4 6%
Other 15 24%
Unknown 7 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 May 2012.
All research outputs
#19,472,725
of 23,947,846 outputs
Outputs from Biointerphases
#481
of 544 outputs
Outputs of similar age
#204,605
of 255,371 outputs
Outputs of similar age from Biointerphases
#4
of 5 outputs
Altmetric has tracked 23,947,846 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 544 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 255,371 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.