Aggregation and binding: a fundamental study of amyloid and antimicrobial peptides

Murray, Brian
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Belfort, Georges
Tessier, Peter M.
Karande, Pankaj
Fabris, Daniele
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Chemical engineering
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Attribution-NonCommercial-NoDerivs 3.0 United States
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
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For amyloidogenic peptides, their adverse health effects are primarily derived from their ability to aggregate into small oligomers and subsequently large fibrils. Here, an aggrega-tion reaction model is developed in order to understand how modifications to both the amyloid’s sequence and its surrounding environment affect the rates of individual reactions in the aggregation pathway. Notably, point mutations to the N-terminus of amyloid beta 1-42 (Aβ1-42) alter the rate of monomer rearrangement into an aggregation-prone conformation, rather than the rate of small oligomer nucleation or the rate of fibrillation (Chapter 2). Meanwhile modifications to the amyloid’s surrounding envi-ronment, by the addition of osmolytes or hydrophilic polymers to solution, affect either the monomer rearrangement rate (osmolytes) or the nucleation rate in conjunction with fibrillation rate, (hydrophilic polymers, Chapter 3).
Finally, a framework to develop the design algorithm and the Aβ1-42 N-terminus binding peptides for therapeutic use is detailed in Chapter 7. Specific plans on how to avoid problems that have plagued peptide therapeutics in the past, including in vivo degrada-tion, weak binding, non-specificity, and poor delivery, are discussed. Continuation of the work presented in this thesis should focus on the development of the peptides and peptide design algorithm from Chapters 5 and 6 to overcome these challenges.
In a continuation of previously published research by the Belfort group, a potentially general algorithm to design novel synthetic AMPs against antibiotic resistant bacteria is developed. The peptide design algorithm generated a synthetic peptide capable of inhibiting the growth of Staphylococcus aureus and Methicillin-resistant S. aureus (MRSA) better than 85% of the peptides in two publically available databases of AMPs and with nearly the same potency as a small molecule positive control used to kill S. aureus. The algorithm also generated peptide sequences strikingly similar to peptides previously designed by the Belfort group against Mycobacterium tuberculosis. Future modifications to the design algorithm must include designs against a broader range of antibiotic resistant bacteria and reductions in the synthesized peptides’ cytotoxicity.
Antimicrobial peptides are believed to kill pathogenic bacteria primarily by destabilizing the bacterial outer membrane. Chapter 4 details the development of a straightforward method and analysis procedure to identify the membrane destabilization mechanism. Unique mechanisms of antimicrobial peptide disruption of lipid bilayers are easily discernable using the method presented here. Additionally, the role that a given AMP secondary structure has on its membrane disruption mechanism is examined. Interesting-ly, peptides with completely unique secondary structures can operate through similar mechanisms, while AMPs with nearly identical sequences and secondary structures operate through exactly the same mechanism with varying intensities depending on the peptides’ bactericidal capabilities.
Additionally, for Aβ1-42, a heretofore under-researched domain of the peptide that has considerable effects on the peptide’s stability, aggregation rate, and binding to neuronal receptors is identified. Mutations to the N-terminus of Aβ1-42, specifically A2T, a naturally occurring mutation that protects against AD development, and A2V, a muta-tion that enhances the chance of developing AD, both significantly alter the monomer folding landscape, monomer cross-sectional area, overall aggregation kinetics, the conformation of peptide aggregates, and the peptide’s ability to bind to neuronal recep-tors and inhibit hippocampal cell communication (Chapter 2). Utilizing this information, along with additional arguments outlined in Chapter 6, preliminary results from a search for peptides that bind to the N-terminus of Aβ1-42 with single to low double digit mi-cromolar affinity are presented (Chapter 6).
Two classes of diseases are rapidly emerging throughout the world, dementia and antibiotic resistant bacterial infections. 35.6 million people worldwide were estimated to be living with dementia in 2012. Among this broad class of aging diseases, Alzheimer’s disease (AD) is the most prevalent, and is the only cause of death in the top 10 in the United States that cannot be prevented, cured, or even slowed. On the other hand, the growing danger from increased antimicrobial resistance threatens to be even more severe. According to the World Health Organization, “a post-antibiotic era – in which common infections and minor injuries can kill… [is] a very real possibility for the 21st century”. Underlying these two major classes of diseases are two types of peptides: (i) amyloids, responsible for AD and other types of dementia, and (ii) antimicrobial peptides (AMPs), which kill pathogens through pathways orthogonal to the ones targeted by conventional antibiotics. Here, a mechanism-based study is performed on these two types of peptides and preliminary results are presented detailing peptides designed to treat both classes of diseases.
May 2016
School of Engineering
Dept. of Chemical and Biological Engineering
Rensselaer Polytechnic Institute, Troy, NY
Rensselaer Theses and Dissertations Online Collection
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