ReviewBiointerphases2012
Model membrane platforms for biomedicine: case study on antiviral drug development.
Review in Biointerphases, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Structure and composition of supported lipid bilayers: a comparison between solvent-assisted lipid bilayer and vesicle fusion methods.Journal of applied crystallography · 2026Article
- Unraveling How Antimicrobial Lipid Mixtures Disrupt Virus-Mimicking Lipid Vesicles: A QCM-D Study.Biomimetics (Basel, Switzerland) · 2024Article
- Probing the Ion Transport Properties of Ultrashort Carbon Nanotubes Integrated with Supported Lipid Bilayers via Electrochemical Analysis.The journal of physical chemistry. B · 2023Article
- Biophysical Characterization of LTX-315 Anticancer Peptide Interactions with Model Membrane Platforms: Effect of Membrane Surface Charge.International journal of molecular sciences · 2022Article
- Nanoarchitectured air-stable supported lipid bilayer incorporating sucrose-bicelle complex system.Nano convergence · 2022Article
- Biologically interfaced nanoplasmonic sensors.Nanoscale advances · 2020Review
- Peptide-induced formation of a tethered lipid bilayer membrane on mesoporous silica.European biophysics journal : EBJ · 2015Article
- Membrainy: a 'smart', unified membrane analysis tool.Source code for biology and medicine · 2015Article
- Model cell membranes: Techniques to form complex biomimetic supported lipid bilayers via vesicle fusion.Current opinion in colloid & interface science · 2013Article
- Comparison of Extruded and Sonicated Vesicles for Planar Bilayer Self-Assembly.Materials (Basel, Switzerland) · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.