Self-Assembled Multienzyme Nanostructures on Synthetic Protein Scaffolds

Sequential enzymes in a biosynthetic pathway often self-assemble to form nanomachineries known as multienzyme complexes inside cells. Enzyme self-assembly insulates toxic intermediates, increases the efficiency of intermediate transfer, minimizes metabolic crosstalk, streamlines flux, and improves the product yield. Artful structures and superior catalytic functions of these natural nano-machines inspired the development of synthetic multienzyme complexes to expedite biosynthesis. Here we present a versatile self-assembly strategy to construct multienzyme nanostructures based on synthetic protein scaffolds. The protein scaffolds were formed using the spontaneous protein reaction of SpyCatcher and SpyTag. Two types of protein scaffolds were generated: two skeleton proteins cross-linked and hierarchically assembled into heterogeneous nanostructures (the cross-linked scaffold), and head-to-tail cyclization of a dual-reactive skeleton protein gave a homogeneous cyclic scaffold. Sequential enzymes from the menaquinone biosynthetic pathway were assembled on both scaffolds through the docking domain interactions derived from polyketide synthases. Both scaffolded assemblies effectively increased the yield of the final product of the cascade catalytic reaction in menaquinone biosynthesis. Surprisingly, the rate enhancements were driven by different mechanisms: the cross-linked scaffold assembly streamlined the overall flow of the reactants, whereas the cyclic scaffold assembly accelerated the catalytic efficiency of the rate-limiting enzyme. Altogether, self-assembly of sequential enzymes by combining the SpyCatcher/SpyTag reaction and the docking domain interactions yielded protein-based nanostructures with special architecture, exceptional catalytic activity, and unexpected catalytic mechanisms. This work demonstrates a versatile strategy of gaining more powerful biocatalysts by protein self-assembly for efficient bioconversion of valuable chemicals.