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Self-Assembling Enveloped Virus-Mimicking Particle for Extrahepatic Targeting mRNA Delivery
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DOI：10.1021/acsnano.5c21254.png)
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Abstract
En 中文
Precise and efficient delivery of messenger RNA (mRNA) to extrahepatic tissues remains a major challenge in advancing mRNA-based therapeutics. Although enveloped viruses and virus-like particles (VLPs) serve as natural RNA delivery systems with varied extrahepatic targeting capabilities, their clinical translation is often hampered by bottlenecks in tunability, safety, immunogenicity, and scalability. Here, we developed a bottom-up self-assembling enveloped virus-mimicking particle (EVMP) composed of highly simplified yet high-performance virus-mimicking peptide (VMP) and tissue-targeting envelope phospholipids. By employing virtual screening via molecular dynamics simulation, directed evolution via key assembling domain mutation, strategic N-terminal fatty acylation modifications, and precise adjustments to envelope phospholipid composition, we achieved high-efficiency delivery of mRNA to organs such as the lungs and spleen. Notably, the optimized lung-targeted EVMP achieved transfection in 37% of total lung cells, including 73% of endothelial cells and 28% of immune cells. In a metastatic lung tumor model, the lead EVMP loaded with IL-12 mRNA effectively suppressed tumor progression. Notably, EVMP demonstrated excellent long-term biosafety and the capacity for repeated administration, owing to their minimal immunogenic profile. This biomimetic virus-mimicking nanoplatform represents a transformative advance in mRNA delivery technologies, enabling effective and safe mRNA-based therapy for extrahepatic diseases. Furthermore, it establishes a generalizable strategy for bottom-up engineering of biomimetic materials with programmable tissue tropism and modular functionality.
Keywords:
Anatomy
Cells
Lipids
Peptides and proteins
Rodent models
extrahepatic mRNA delivery
bottom up
enveloped virus-mimicking particle
self-assembling domain
virus-mimicking peptide
directed evolution
Journal
IF:
16
Papers:
2.6W
Citations:
25.6W
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