Peptides Mimicking CD Receptors Are A Leap Forward in Antiviral Microbicides
Protein structure of a human CD4 receptor. Source: European Bioinformatics Institute.
While the ultimate cure or prevention strategy for HIV is still in the works, researchers continue to develop partial solutions to different aspects of the disease. These partial solutions include post exposure prophylaxis (PEP) and highly active antiretroviral therapy (HAART), but all are imperfect for various reasons.
In a bid to improve infection prevention, federal guidelines suggest pre-exposure prophylaxis (PrEP), which requires administration of the PEP drug cocktail to before exposure to HIV.1 PrEP shares side effect profiles with PEP and HAART, meaning that uninfected patients experience negative side effects as part of their prevention routine. New methods are needed, and recent research which describes a novel topical antiviral microbicide gel implemented via CD-receptor mimicking peptides is especially exciting, as topical gels can avoid many of the system-wide side effects of current PrEP cocktails.2
The mimic peptide’s in vivo ability to prevent infection after an HIV challenge proves that mimic peptides will be popular avenues for antiviral investigation in the near future. If a virus has a characterized point of human cellular entry, it’s possible to develop a peptide which mimics the entry epitope. Implementing mimetic peptides as decoys for viral binding is a microbicidal concept that can also be generalized to viruses other than HIV, assuming there’s a software suite to handle the task of simulating the binding across variations of the peptide’s sequence—a traditional problem in computational immunology.3
In order to produce mimic peptides, researchers first picked a starting peptide to base their mimic on. The CD4 peptide was chosen due to its well-characterized binding with the HIV viral particle’s gp120 protein, whose binding to cellular epitopes is necessary for establishing infection.4 The basic CD4 peptide was then modified by linking it to anionic compounds to change its binding characteristics, allowing it to mimic multiple other cellular epitopes that would normally be bound by gp120. Thus, the modified CD4 peptide is preferentially bound by gp120, preventing gp120 from initiating infection at endogenous CD4 expressed on healthy cells. The modified peptide is then suspended into a hydroxyethyl-cellulose gel for application on the tissue that is most likely to encounter HIV viral particles.
Generalizing this process for arbitrary viruses will look similar to the process pioneered by the original research group:
- Determine the cellular and viral peptides necessary for infection
- Characterize binding between the identified cellular and viral peptides during infection
- Design mimic peptide variants
- Generate mimic peptide variants and viral peptides
- Run a binding study to determine if mimic peptide variants actually bind viral peptides
- Transfer the mimic peptide variants which passed the binding study into a cell culture friendly format
- Assess in vitro if in-solution mimic peptide variants confer infection resistance to cultured cells
- Assess in vivo if in-gel mimic peptide variants confer infection resistance to animal model
Easing the In Vitro to In Vivo Gap
The troubles with developing antiviral peptides for in vivo use are numerous. Aside from the pre-research required to determine the correct peptides to mimic, the conjugates picked for addition to the mimics must be characterized and checked for their biochemical feasibility. As is typical with synthetic biologics, the ability for a peptide to be conjugated with another molecule does not guarantee that either will remain biologically active after the conjugation is complete. Binding sites may be blocked or conformationally deformed to the point of lower affinity.
After the design phase comes in vitro testing, where chemically compatible cell culture media must be chosen to conduct the experiment, lest the mimic peptide deform or degrade due to differences in pH. This problem occurs again when formulating the gel for in vivo use, and a final time when applied to the physiology of the target tissue on the animal model.
The research path required to fully test the efficacy of mimic peptides in preventing infection is quite daunting under the best of conditions. The task of generating peptides which vary by one or more amino acids is possible without sophisticated software, but adding different chemical conjugates and multiple amino acid variations per peptide requires a much more serious informatics infrastructure. Though there are many software tools that focus on developing overlapping peptide libraries or biologics, few are integrated with experimental planning and molecular design tools, not to mention collaborative workspaces.5
Many of the pain points of peptide mimic design and implementation can be eased by abundant predictive analysis before entering the laboratory:
- Simulate the original peptide to be mimicked
- Simulate the binding of the viral peptide with the original peptide
- Simulate the binding of the viral peptide with other peptides that are relevant for establishing infection
- Simulate the original peptide conjugated to an anionic compound
- Simulate mutations within the original peptide, creating variants with are different from the original by one amino acid in theoretically advantageous positions
- Simulate the viral peptide’s binding to the mimic peptide and other peptides of interest
- Simulate the mimic peptide conjugated to an anionic compound
- Simulate the viral peptide’s binding to the mimic peptide conjugate
- Combine all of the previous simulations into a simulation to test whether the mimic peptide conjugates successfully outcompete the original peptides and other peptides of interest when viral peptides are introduced
- Simulate the peptide conjugates with the greatest affinity for the viral peptides in the cell culture environment, the therapeutic gel formulation, and in the physiological target of the gel
- Simulate the likely pathway of biodegradation for the mimic peptide conjugate
- Determine the bioactivity of any likely metabolites of the mimic peptide conjugate
- Determine the mimic peptide conjugate’s rate of biodegradation in the conditions of the gel at the physiological target
Once all of the design research simulations have been performed, moving to the laboratory and subsequent in vivo studies is as simple as selecting the mimic peptide conjugates which were the best at binding the viral peptides in the simulations. Assuming that binding activity has been confirmed experimentally, in vivo studies can proceed with the confidence of a calculated outcome. Given the hefty number of simulations required, a powerful bioinformatics system is necessary to execute the peptide mimic conjugate workflow successfully.
BIOVIA’s Designed to Cure is the bioinformatics suite that will accelerate the pipeline from peptide design to animal model challenge. Bringing robust molecular simulation to a fully featured experiment planning and collaboration platform will make the development of mimic peptide conjugates able to reach its potential as a powerful new tool for antiviral prophylaxis. Contact us today to find out how BIOVIA can help you get the most out of the latest research and help the patients of the future’s antiviral therapies.
- “What is pre-exposure prophylaxix (PrEP)?” December 30th ,2016, https://www.aids.gov/hiv-aids-basics/prevention/reduce-your-risk/pre-exposure-prophylaxis/ ↩
- “CD4-mimetic sulfopeptide conjugates display sub-nanomolar anti-HIV-1 activity and protect macaques against a SHIV162P3 vaginal challenge.” October 10th, 2016, http://www.nature.com/articles/srep34829 ↩
- “Introduction to the Peptide Binding Problem of Computational Immunology: New Results.” September 17th, 2013, http://link.springer.com/article/10.1007/s10208-013-9173-9 ↩
- “The interaction of CD4 with HIV-1 gp120.” May, 1991, https://www.ncbi.nlm.nih.gov/pubmed/1888898 ↩
- “NHLBI-AbDesigner: an online tool for design of peptide-directed antibodies.” January 1st, 2012, https://www.ncbi.nlm.nih.gov/pubmed/21956165 ↩