Current Research

Engineering of Acyl-CoA Reductase Enzymes Using Machine Learning

Fatty alcohols made in microbial cells are promising alternatives for petrochemicals in synthesis of a variety of compounds, such as fuels, cosmetics, and surfactants. Acyl-CoA reductase (ACR) enzymes are important for microbial fatty alcohol production. Because ACRs catalyze the final reduction of acyl-CoA and acyl-ACP thioesters to aldehydes and alcohols, these enzymes are a promising target for engineering. However, ACRs are difficult to engineer by traditional protein engineering methods due to the lack of a high-resolution crystal structure or suitable high-throughput screen. I am using machine learning methods to solve challenges in engineering these enzymes and applying algorithms to develop ACR enzymes with improved activities.