(672a) Computational and Experimental Exploration of Sequence-Structure-Function Relationships of a Medium-Chain Acyl-ACP Thioesterase

Enzymes which perform industrially relevant chemistry can provide selectivity otherwise difficult to achieve from chemical synthesis or agriculture. Engineering the acyl-ACP thioesterase in fatty acid biosynthesis has proven an effective approach to tailor the fatty acid distribution toward C₈, C₁₀, and C₁₂ products. To date, engineering of acyl-ACP thioesterases with a preference for the corresponding medium-chain substrates has been successful with directed evolution and rational mutagenesis techniques. However, fundamental understanding of the factors driving thioesterase chain-length selectivity remains elusive. Here, we apply a computational method to tune substrate binding and explore the sequence-structure-function relationships of an acyl-ACP thioesterase from Umbellularia californica. We used the Iterative Protein Redesign and Optimziation (IPRO) algorithm to computationally design thioesterase variants with improved in silico binding to C₈, C₁₀, and C₁₂ substrates. The pre-screened thioesterase variants were transformed in an Escherichia coli fatty acid production strain to test for changes in fatty acid chain-length distribution from the wild type thioesterase. In this talk, I will describe how we navigated through the design, build, and test cycle to enhance the learnings from each round of mutagenesis.