Collaborative Research: Mechanism-guided enzyme engineering for fucosylated glycoconjugate synthesis

点击翻译按钮获取中文摘要

Glycosynthases are enzymes that have been engineered to make instead of break chains of complex sugars (oligosaccharides and carbohydrates). With this award, the Chemistry of Life Processes Program in the Chemistry Division is funding Dr. Heather Mayes from the University of Michigan and Dr. Shishir Chundawat from Rutgers University to uncover how glycosynthases synthesize prebiotic oligosaccharides or carbohydrates. These enzymes fill a pressing need in research and industrial biotechnology for the ability to produce designer carbohydrates, sugars that are designed for a specific purpose. There remains, however, a lack mechanistic understanding for how to better engineer glycosynthases to be highly specific and efficient in making complex sugars. This project combines computational and experimental studies to provide a mechanistic understanding of how a glycosynthase (alpha-L-fucosidase) catalyzes creation of specific oligosaccharides, which will in turn enable rational design of enzymes to make designer carbohydrates. The broader impacts include designing efficient routes for creating human milk oligosaccharides that could be included in infant formula to bring the composition closer to that of human milk. Human milk oligosaccharides can improve human health by promoting growth of beneficial gut bacteria and lowering incidences of other pathogenic infections. The software developed in this work for designing such enzymes will be made publicly available. Finally, the studies form the basis for outreach activities that use the biochemistry of carbohydrates to engage with students from under-resourced communities in Michigan and New Jersey.The overall goal of this project is to understand how alpha-L-fucosidases synthesize simple glycoconjugates (e.g., human milk oligosaccharides). The hypothesis to be tested is that a priori analysis of enzyme active and binding sites, based on sequence and structural data, can be used to predict mutations that will eliminate the hydrolysis activity of the enzyme in favor of glycosidic bond synthesis of bespoke oligosaccharides. The objectives of this project are to: 1) employ experimental and computational studies to identify key structural properties that determine whether a particular enzyme mutant will be an active glycosynthase; 2) create automated processes to predict and test which mutants of disparate enzymes will be active fucosynthases; and 3) predict and test mutations needed to alter substrate specificity. The results of this feasibility study will advance the path to production of a broad suite of oligosaccharides not currently readily available for research and/or commercial applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.