Antibiotics are one of the most important medicinal products of the past century. Many such as erythromycin, apramycin, and geldanamycin contain multiple stereocenters which make them difficult targets for total synthesis. Polyketide Synthases (PKSs) are how these antibiotics are typically synthesized in nature and as such are valuable targets for novel drug discovery and development. The ketoreductase module of a PKS is of specific interest as they are able to set the stereochemistry of two atoms in a polyketide product. This research focuses on the second ketoreductase module of the amphotericin PKS (AmpKR2) as it is a model system for type I PKSs. Specifically, this research focuses on elucidating the stereochemically active amino acids present near the active site. Determination of these active residues will give insight into how many PKS ketoreductases set stereochemistry as well as show how certain mutations can affect the stereochemistry of a molecule. Another aspect of this project is using stereochemical activities already demonstrated in the literature as a basis for a machine learning method. This machine learning method would be able to look at a given ketoreductase and provide stereochemically active residues with high probability. This project is still ongoing and no final results have been obtained.

Modeling amino acid stereoselectivity by use of a type I polyketide synthase ketoreductase

ACS Spring Meeting 2021

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