(166a) Computational Protein Analysis and Design of Aldehyde and Alcohol Dehydrogenases for Enhanced Butanol Biosynthesis in Solventogenic Fermentation

Biobutanol derived from acetone-butanol-ethanol (ABE) fermentation has potential to replace gasoline as fuel for automobiles powered by internal combustion engines. The roadblocks preventing this transition are the inherent limitations of the biobutanol fermentation process, such as butanol toxicity, expensive feedstocks, and high energy input requirements for butanol recovery. The high cost of biobutanol can be lessened by increasing the product yield via increasing the selectivity of the enzymes aldehyde and alcohol dehydrogenases (ALD and ADH), which convert acetyl-CoA and butyryl-CoA to corresponding aldehydes (acetaldehyde and butyraldehyde) and alcohols (ethanol and butanol), respectively, in the fermentation. Our goal is to discover novel ALD and ADH enzymes capable of performing our reaction of interest using in-silico enzyme screening, then design these enzymes for higher selectivity towards our product of choice, butanol, using computational enzyme design. First, bioprospecting or mining protein sequence databases was performed to discover genes/enzymes capable of catalyzing the reactions. Alphafold2 is then used to generate protein structures from mined sequences passing a series of filtering criteria. Ligand Docking in Rosetta is then performed using the generated models and the reaction intermediate of the enzyme’s respective reaction. The ligand/protein interface score from these docking studies can be used to evaluate each protein’s ability for performing their respective reaction. This procedure for enzyme mining and ligand docking requires insight into the enzymatic mechanism of the reaction in question. The most promising protein sequences will then be expressed in E. coli, and their enzymatic activity will be determined via in vitro assay. The results can be used in computational protein design to improve the selectivity of the enzymes displaying the highest activity. For this procedure Rosetta enzyme design can be used to mutate residues in the active site of these enzymes to enhance enzyme selectivity.