Deep Mutational Scanning (DMS) Guided Therapeutic Enzyme Engineering

Phenylalanine ammonia-lyases (PALs) non-oxidatively deaminate L-phenylalanine to trans-cinnamic acid (tCA) and are widely found associated with secondary metabolism in plants, bacteria, and fungi. Biocatalytic applications for natural product and fine chemical synthesis has driven the discovery, expression, characterization, and engineering of PALs. More recently, development of PALs for phenylketonuria (PKU) management and cancer therapy has further increased interest in engineering this class of enzymes. While there is a general understanding of how residues in the substrate-binding pocket contribute to specificity and turnover, led by rational mutagenesis studies, there is poor understanding of how distal residues affect function. Deep mutational scanning (DMS) can provide a comprehensive map of sequence–function relationships to explore the protein fitness landscapes, uncover functionally relevant sites, and improve molecular energy functions. Yet, DMS has not been widely coupled with directed evolution to accelerate engineering campaigns (although there are few exceptions).

Previously, we developed a growth-coupled enrichment for rapid screening of high-activity variants of AvPAL* (used to formulate the PKU drug Pegvaliase®) in E. coli. Here, we first obtained the detailed sequence-function landscape of PAL, to date, using DMS, identifying >60 mutational hotspots. Next, we picked seven sites for comprehensive single and multi-site saturation mutagenesis and we identified multi-site mutations with improved activtiy. We then explored the epistatic effect of these mutations, uncovering positive, neutral, and negative interactions among distal and proximal sites. Finally, to understand the mechanistic role of key mutations in hyperactive variants, we performed modelling studies (quantum mechanics, molecular dynamics, including metadynamics) and concluded that there are multiple pathways to enhance PAL catalytic activity. In summary, this study demonstrates that DMS can guide and expedite enzyme directed evolution and campaigns as well as mechanistic studies.