Optimizing self-assembly kinetics for biomolecules and complex nanostructures
In a heterogeneous system, such as a large biomolecule or complex nanostructure, there is no guarantee that the lowest-free-energy state will form via self-assembly. Defects and mis-interactions among subunits often arise during a self-assembly reaction, particularly when these systems comprise many distinct components. As a result, if we wish to assemble complex nanostructures reliably, we need to design robust kinetic pathways to the target structures. I shall describe a theoretical approach for predicting self-assembly pathways in both engineered nanostructures and natural biomolecules. First, I shall discuss design principles that can be used to tune the nucleation and growth rates of colloidal nanostructures, with implications for achieving low-defect self-assembly and designing time-dependent experimental protocols. Then, turning to biological examples of kinetic optimization, I shall discuss how analogous principles have shaped the evolution of variable ribosome translation rates in order to optimize the folding of nascent proteins.