Engineering novel nanomaterials through de novo design of hydrophobic scaffold proteins

Abstract

Computationally designed protein nanoparticles leverage de novo designed protein subunits to build large oligomers which can be used for multivalent antigen display and cargo loading in the delivery of vaccines. Advancements in computational methods and design of membrane proteins increases the breadth of materials which can be used as subunit building blocks in these large oligomeric complexes. In this dissertation I describe engineering a protein scaffold with a hydrophobic pore and the rational design of a novel two-component nanoparticle utilizing a de novo designed transmembrane protein. Using machine learning and AI-guided approaches with two-component RPX Docking, AlphaFold 2 and RosettaFold Diffusion, I structurally characterized a novel two component transmembrane nanoparticle and to 4.16 Å by Cryo-EM. This technology marks the first generation of novel hydrophobic nanoparticles that is a step towards generating in vitro hybrid lipid-protein nanomaterials for the display of unique membrane proteins and lipid-conjugated moieties previously inaccessible through current designed nanoparticles.