Viral Membrane Fusion Proteins and RNA Sorting Mechanisms for the Molecular Delivery by Exosomes

The advancement of precision medicine critically depends on the robustness and specificity of the carriers used for the targeted delivery of effector molecules in the human body. Numerous nanocarriers have been explored in vivo, to ensure the precise delivery of molecular cargos via tissue-specific targeting, including the endocrine part of the pancreas, thyroid, and adrenal glands. However, even after reaching the target organ, the cargo-carrying vehicle needs to enter the cell and then escape lysosomal destruction. Most artificial nanocarriers suffer from intrinsic limitations that prevent them from completing the specific delivery of the cargo. In this respect, extracellular vesicles (EVs) seem to be the natural tool for payload delivery due to their versatility and low toxicity. However, EV-mediated delivery is not selective and is usually short-ranged. By inserting the viral membrane fusion proteins into exosomes, it is possible to increase the efficiency of membrane recognition and also ease the process of membrane fusion. This review describes the molecular details of the viral-assisted interaction between the target cell and EVs. We also discuss the question of the usability of viral fusion proteins in developing extracellular vesicle-based nanocarriers with a higher efficacy of payload delivery. Finally, this review specifically highlights the role of Gag and RNA binding proteins in RNA sorting into EVs.

Automated summary

The development of precision medicine relies on robust and specific carriers for targeted delivery of effector molecules. While nanocarriers have been explored for tissue-specific targeting, most artificial nanocarriers face limitations in specific cargo delivery. In contrast, extracellular vesicles (EVs) show versatility and low toxicity, but their delivery is not selective and is typically short-ranged. By incorporating viral fusion proteins into EVs, researchers aim to increase membrane recognition efficiency and improve payload delivery efficacy.