Curvature-Sensing Peptides for Virus and Extracellular Vesicle Applications

Abstract

Membrane curvature is a key biophysical feature that regulates diverse biological processes. A wide range of natural proteins have distinct structural motifs that can sense membrane curvature and function independently as curvature-sensing peptides. In recent years, such peptides have demonstrated excellent potential for selectively capturing and disrupting enveloped viruses and extracellular vesicles (EVs), which are in the ∼30–300 nm size range and possess highly curved membranes. Despite extensive progress, there is an outstanding need to categorize different curvature-sensing motifs and link them to tailored peptide designs for specific applications. Herein, we introduce membrane curvature sensing as a unifying selectivity principle to target enveloped viruses and EVs, and critically evaluate the structural and mechanistic features of curvature-sensing motifs to develop a four-type classification framework that spans membrane binding and disruption. These efforts are supported by foundational studies and the latest insights obtained from experimental, theoretical, and simulation approaches as well as machine learning-aided thermodynamic modeling. According to this framework, we analyze recent advances to engineer curvature-sensing peptides for emerging applications such as one-step diagnostic capture, rapid virus quantification, antiviral and anti-EV therapies, and genome-wide screening of bacterial EV regulators. In turn, we illustrate how design parameters such as amino acid composition, conformational dynamics, and interfacial force balancing (e.g., electrostatics vs hydrophobicity) guide functional performance. These insights lead us to propose future directions for curvature-sensing peptide engineering and highlight outstanding scientific questions and translational opportunities.