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Cathelicidins such as the human 37-amino acid peptide (LL-37) are peptides that not only potently kill microbes but also trigger inflammation by enabling immune recognition of endogenous nucleic acids. Here, a detailed structure-function analysis of LL-37 was performed to understand the details of this process. Alanine scanning of 34-amino acid peptide (LL-34) showed that some variants displayed increased antimicrobial activity against Staphylococcus aureus and group A Streptococcus. In contrast, different substitutions clustered on the hydrophobic face of the LL-34 alpha helix inhibited the ability of those variants to promote type 1 interferon expression in response to U1 RNA or to present U1 to the scavenger receptor (SR) B1 on the keratinocyte cell surface. Small-angle X-ray scattering experiments of the LL-34 variants LL-34, F5A, I24A, and L31A demonstrated that these peptides form cognate supramolecular structures with U1 characterized by inter-dsRNA spacings of approximately 3.5 nm, a range that has been previously shown to activate toll-like receptor 3 by the parent peptide LL-37. Therefore, while alanine substitutions on the hydrophobic face of LL-34 led to loss of binding to SRs and the complete loss of autoinflammatory responses in epithelial and endothelial cells, they did not inhibit the ability to organize with U1 RNA in solution to associate with toll-like receptor 3. These observations advance our understanding of how cathelicidin mediates the process of innate immune self-recognition to enable inert nucleic acids to trigger inflammation. We introduce the term "innate immune vetting" to describe the capacity of peptides such as LL-37 to enable certain nucleic acids to become an inflammatory stimulus through SR binding prior to cell internalization., Competing Interests: Conflict of interest R. L. G. is a cofounder, scientific advisor, consultant, and has equity in MatriSys Biosciences and is a consultant, receives income, and has equity in Sente, Inc., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

All antibiotics have to engage bacterial amphiphilic barriers such as the lipopolysaccharide-rich outer membrane or the phospholipid-based inner membrane in some manner, either by disrupting them outright and/or permeating them and thereby allow the antibiotic to get into bacteria. There is a growing class of cyclic antibiotics, many of which are of bacterial origin, that exhibit activity against Gram-negative bacteria, which constitute an urgent problem in human health. We examine a diverse collection of these cyclic antibiotics, both natural and synthetic, which include bactenecin, polymyxin B, octapeptin, capreomycin, and Kirshenbaum peptoids, in order to identify what they have in common when they interact with bacterial lipid membranes. We find that they virtually all have the ability to induce negative Gaussian curvature (NGC) in bacterial membranes, the type of curvature geometrically required for permeation mechanisms such as pore formation, blebbing, and budding. This is interesting since permeation of membranes is a function usually ascribed to antimicrobial peptides (AMPs) from innate immunity. As prototypical test cases of cyclic antibiotics, we analyzed amino acid sequences of bactenecin, polymyxin B, and capreomycin using our recently developed machine-learning classifier trained on α-helical AMP sequences. Although the original classifier was not trained on cyclic antibiotics, a modified classifier approach correctly predicted that bactenecin and polymyxin B have the ability to induce NGC in membranes, while capreomycin does not. Moreover, the classifier was able to recapitulate empirical structure-activity relationships from alanine scans in polymyxin B surprisingly well. These results suggest that there exists some common ground in the sequence design of hybrid cyclic antibiotics and linear AMPs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier B.V.)

Amphiphilicity in ɑ-helical antimicrobial peptides (AMPs) is recognized as a signature of potential membrane activity. Some AMPs are also strongly immunomodulatory: LL37-DNA complexes potently amplify Toll-like receptor 9 (TLR9) activation in immune cells and exacerbate autoimmune diseases. The rules governing this proinflammatory activity of AMPs are unknown. Here we examine the supramolecular structures formed between DNA and three prototypical AMPs using small angle X-ray scattering and molecular modeling. We correlate these structures to their ability to activate TLR9 and show that a key criterion is the AMP's ability to assemble into superhelical protofibril scaffolds. These structures enforce spatially-periodic DNA organization in nanocrystalline immunocomplexes that trigger strong recognition by TLR9, which is conventionally known to bind single DNA ligands. We demonstrate that we can "knock in" this ability for TLR9 amplification in membrane-active AMP mutants, which suggests the existence of tradeoffs between membrane permeating activity and immunomodulatory activity in AMP sequences.

Antimicrobial peptides are a class of membrane-active peptides that form a critical component of innate host immunity and possess a diversity of sequence and structure. Machine learning approaches have been profitably employed to efficiently screen sequence space and guide experiment towards promising candidates with high putative activity. In this mini-review, we provide an introduction to antimicrobial peptides and summarize recent advances in machine learning-enabled antimicrobial peptide discovery and design with a focus on a recent work Lee et al. Proc. Natl. Acad. Sci. USA 2016;113(48):13588-13593. This study reports the development of a support vector machine classifier to aid in the design of membrane active peptides. We use this model to discover membrane activity as a multiplexed function in diverse peptide families and provide interpretable understanding of the physicochemical properties and mechanisms governing membrane activity. Experimental validation of the classifier reveals it to have learned membrane activity as a unifying signature of antimicrobial peptides with diverse modes of action. Some of the discriminating rules by which it performs classification are in line with existing "human learned" understanding, but it also unveils new previously unknown determinants and multidimensional couplings governing membrane activity. Integrating machine learning with targeted experimentation can guide both antimicrobial peptide discovery and design and new understanding of the properties and mechanisms underpinning their modes of action., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Under homeostatic conditions the release of self-RNA from dying cells does not promote inflammation. However, following injury or inflammatory skin diseases such as psoriasis and rosacea, expression of the cathelicidin antimicrobial peptide LL37 breaks tolerance to self-nucleic acids and triggers inflammation. Here we report that LL37 enables keratinocytes and macrophages to recognize self-non-coding U1 RNA by facilitating binding to cell surface scavenger receptors that enable recognition by nucleic acid pattern recognition receptors within the cell. The interaction of LL37 with scavenger receptors was confirmed in human psoriatic skin, and the ability of LL37 to stimulate expression of interleukin-6 and interferon-β1 was dependent on a 3-way binding interaction with scavenger receptors and subsequent clathrin-mediated endocytosis. These results demonstrate that the inflammatory activity of LL37 is mediated by a cell-surface-dependent interaction and provides important new insight into mechanisms that drive auto-inflammatory responses in the skin.

Double-stranded RNA (dsRNA) induces production of pro-inflammatory cytokines in normal human epidermal keratinocytes (NHEK) by specific binding to endosomal Toll-like receptor-3 (TLR3). Recently, it has been shown that hyperactivation of TLR3 in psoriatic keratinocytes by dsRNA can occur in the presence of human antimicrobial peptide (AMP) LL37. Here, we combine synchrotron X-ray scattering, microscopy, computer simulations, and measurements of NHEK cytokine production to elucidate a previously unanticipated form of specific molecular pattern recognition. LL37 and similar α-helical AMPs can form pro-inflammatory nanocrystalline complexes with dsRNA that are recognized by TLR3 differently than dsRNA alone. dsRNA complexes that activate IL-6 production in NHEK and those that do not are both able to enter cells and co-localize with TLR3. However, the crystallinity of these AMP-dsRNA complexes, specifically the geometric spacing between parallel dsRNA and the repeat number of ordered dsRNA, strongly influences the level of TLR3 activation. Crystalline complexes that present dsRNA at a spacing that matches with the steric size of TLR3 can recruit and engage multiple TLR3 receptors, driving receptor clustering and immune amplification, whereas crystalline complexes that exhibit poor steric matching do not. Reverse-transcription quantitative PCR of IL-6 during siRNA knockdown of TLR3 confirms that cytokine production is due to TLR3: High levels of IL-6 transcription are observed for sterically matched complexes without TLR3 knockdown, whereas such activity is abrogated with TLR3 knockdown.