Creating bottom-up RNA transfer vehicles from synthetic protein assemblies

Abstract

Abstract Evolution guides biological systems to populate ecological niches, with viruses being one of the most successful examples of that principle. Viruses evolved over billions of years for the efficient transfer of nucleic acids. Although highly diverse, most viruses converged toward a remarkable similarity in the size and shape of their capsids. In contrast, generative models for protein design enable the creation of protein architectures that are absent in nature. Here, we investigate whether AI-designed protein assemblies can be functionalized to construct nucleic acid transport vehicles that are independent of evolutionary trajectories. By combining natural protein domains with synthetic protein assemblies, we create more than a hundred bottom-up RNA transfer vehicles with unique sizes and shapes. These novel vehicles surpass the RNA transfer efficiency of widely used delivery vehicles by several orders of magnitude. Additionally, we demonstrate that their tropism can be programmed by incorporating computationally designed peptide binders and apply them to deliver various therapeutically relevant cargo RNAs, such as Gene Editors, into a wide range of cellular models. We show the in vivo biodistribution of one of these vehicles in a mouse with close to single-cell resolution and use it to perform a gene editing strategy for Duchenne muscular dystrophy in a pig. Our work demonstrates how proteins created by generative AI can be harnessed for the rational engineering of biological systems with desired properties by overcoming the limitations of natural protein diversity.