Abstract
Antimicrobial peptides (AMPs) are an abundant and wide class of molecules produced by many tissues and cell types in a variety of mammals, plant and animal species. Linear alpha-helical antimicrobial peptides are among the most widespread membrane-disruptive AMPs in nature, representing a particularly successful structural arrangement in innate defense. Recently, AMPs have received increasing attention as potential therapeutic agents, owing to their broad activity spectrum and their reduced tendency to induce resistance. The introduction of non-natural amino acids will be a key requisite in order to contrast host resistance and increase compound's life. In this work, the possibility to design novel AMP sequences with non-natural amino acids was achieved through a flexible computational approach, based on chemophysical profiles of peptide sequences. Quantitative structure-activity relationship (QSAR) descriptors were employed to code each peptide and train two statistical models in order to account for structural and functional properties of alpha-helical amphipathic AMPs. These models were then used as fitness functions for a multi-objective evolutional algorithm, together with a set of constraints for the design of a series of candidate AMPs. Two ab-initio natural peptides were synthesized and experimentally validated for antimicrobial activity, together with a series of control peptides. Furthermore, a well-known Cecropin-Mellitin alpha helical antimicrobial hybrid (CM18) was optimized by shortening its amino acid sequence while maintaining its activity and a peptide with non-natural amino acids was designed and tested, demonstrating the higher activity achievable with artificial residues.
Highlights
Antimicrobial peptides (AMPs) are small evolutionally conserved molecules found among all classes of life, from multicellular organisms to bacterial cells [1,2]
Some AMPs are already in clinical and commercial use, the future design of novel AMPs will need to minimize the toxicity against eukaryotic cells and enhance the resistance to proteolytic degradation, with a key opportunity being offered by the introduction of non-natural amino acids (AA) to contrast host resistance and increase compound’s life
In this work we introduce an ACC descriptor accounting for both weak and strong correlations, the Minimum and Maximum of auto and crosscovariances descriptor (Equation 1)
Summary
Antimicrobial peptides (AMPs) are small evolutionally conserved molecules found among all classes of life, from multicellular organisms to bacterial cells [1,2]. Alpha-helical AMPs are among the most abundant and widespread membrane-disruptive sequences in nature and represent a successful structural arrangement for innate defense, as it can afford peptide insertion into lipid bilayers [3]. AMP membrane perturbation activity can be explained by at least three major mechanisms, all leading to bacterial membrane’s collapse and subsequent cell’s death. Two of these models (i.e. the ‘barrel-stave’ and the ‘toroidal-pore’ models) rely on the peptide ability to form ordered transmembrane channels/pores, while the so called ‘carpet model’ implies that, at a critical threshold concentration, the peptides disrupt the bilayer in a detergent-like manner, eventually leading to the formation of micelles [6]. Some AMPs are already in clinical and commercial use (see Table S1 for a list of AMPs commercially available and in clinical trial), the future design of novel AMPs will need to minimize the toxicity against eukaryotic cells and enhance the resistance to proteolytic degradation, with a key opportunity being offered by the introduction of non-natural amino acids (AA) to contrast host resistance and increase compound’s life
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
