In recent years, computational protein design has emerged as a promising tool to predict a broad range of protein structures from scratch with atomic accuracy. Although the creation of enzymes with tailor-made properties for biocatalytic applications would be an exciting application of this technology, the efficiencies of de novo catalysts are generally low. To bridge the gap between natural and computationally designed enzymes, we are combining in silico methods with laboratory evolution. Specifically, ultrahigh-throughput droplet-based microfluidics screening enables exploration of large regions of sequence space that are inaccessible to conventional plate assays, providing insight into protein designability and the relationships between protein sequence, structure, and function. Progress applying this approach to the functionalization of naïve de novo scaffolds will be presented.

Blueprint for de novo protein design and engineering

2019 Fall National Meeting

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