Enzyme and metabolic engineering offer the potential to develop biocatalysts for converting natural resources to a wide range of chemicals. To broaden the scope of potential products beyond natural metabolites, methods of engineering enzymes to accept alternative substrates and/or perform novel chemistries must be developed. DNA synthesis can create large libraries of enzyme-coding sequences, but most biochemistries lack a simple assay to screen for promising enzyme variants. Our solution to this challenge is structure-guided mutagenesis, in which optimization algorithms select the best sequences from libraries based on specified criteria (i.e., binding selectivity). Here, we demonstrate this approach by identifying medium-chain (C8-C12) acyl-ACP thioesterases through structure-guided mutagenesis. Medium-chain fatty acids, which are products of thioesterase-catalyzed hydrolysis, are limited in natural abundance, compared to long-chain fatty acids; the limited supply leads to high costs of C6-C10 oleochemicals such as fatty alcohols, amines, and esters. Here, we applied computational tools to tune substrate binding of the highly active 'TesA thioesterase in Escherichia coli. We used the IPRO algorithm to design thioesterase variants with enhanced C12 or C8 specificity, while maintaining high activity. After four rounds of structure-guided mutagenesis, we identified 3 variants with enhanced production of dodecanoic acid (C12) and 27 variants with enhanced production of octanoic acid (C8). The top variants reached up to 49% C12 and 50% C8 while exceeding native levels of total free fatty acids. A comparably sized library created by random mutagenesis failed to identify promising mutants. The chain length-preference of 'TesA and the best mutant were confirmed in vitro using acyl-CoA substrates. Molecular dynamics simulations, confirmed by resolved crystal structures, of 'TesA variants suggest that hydrophobic forces govern 'TesA substrate specificity. We expect the design rules that we uncovered and the thioesterase variants that we identified will be useful to metabolic engineering projects aimed at sustainable production of medium-chain-length oleochemicals.
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