| Literature DB >> 30877253 |
Nannette Y Yount1,2,3, David C Weaver4, Ernest Y Lee5, Michelle W Lee5, Huiyuan Wang1,2,3, Liana C Chan1,2,3, Gerard C L Wong5,6,7, Michael R Yeaman8,2,3,9.
Abstract
Diversity of α-helical host defense peptides (αHDPs) contributes to immunity against a broad spectrum of pathogens via multiple functions. Thus, resolving common structure-function relationships among αHDPs is inherently difficult, even for artificial-intelligence-based methods that seek multifactorial trends rather than foundational principles. Here, bioinformatic and pattern recognition methods were applied to identify a unifying signature of eukaryotic αHDPs derived from amino acid sequence, biochemical, and three-dimensional properties of known αHDPs. The signature formula contains a helical domain of 12 residues with a mean hydrophobic moment of 0.50 and favoring aliphatic over aromatic hydrophobes in 18-aa windows of peptides or proteins matching its semantic definition. The holistic α-core signature subsumes existing physicochemical properties of αHDPs, and converged strongly with predictions of an independent machine-learning-based classifier recognizing sequences inducing negative Gaussian curvature in target membranes. Queries using the α-core formula identified 93% of all annotated αHDPs in proteomic databases and retrieved all major αHDP families. Synthesis and antimicrobial assays confirmed efficacies of predicted sequences having no previously known antimicrobial activity. The unifying α-core signature establishes a foundational framework for discovering and understanding αHDPs encompassing diverse structural and mechanistic variations, and affords possibilities for deterministic design of antiinfectives.Keywords: amphipathic; antiinfective; antimicrobial; bioinformatics; host defense
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Year: 2019 PMID: 30877253 PMCID: PMC6452647 DOI: 10.1073/pnas.1819250116
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205