Technologies to Predict and Probe Glycosyl Transfer PROJECT SUMMARY Glycosylation is fundamental to all life. Glycans add an additional layer of information to biomolecules, affect both conformation and dynamics, have diverse modulatory roles, such as stabilizing protein folds and signaling stem-cell fate, and feature prominently in disease. As our knowledge of glycosylation's mechanistic role continues to grow, so do the opportunities for therapeutic exploitation. Emerging technologies have opened the door to facile, scalable biosynthesis of defined glycoconjugates whose glycan moieties can be tailored for different applications. At the same time, a set of tools has emerged to predict the 3D structures of biomolecules rapidly and accurately and to design new biomolecules and variants. Structure prediction and design tools have the potential to transform glycobiology by providing structural insights into the effects of glycans and additionally by enabling design of altered and novel glycoconjugates to create new functions. Our overarching goal is to develop complementary computational and experimental methods to probe the structural and environmental contexts that affect glycosylation and elongation. Our research will address the technical barriers needed to achieve these tools, namely developing methods to sample and score diverse glycoconjugate structures and to scan alternate glycoforms in experiment. Our work will create computational algorithms to predict glycosylation sites and elongation products and experimental tools to probe protein-wide glycoforms in specific targets. A computational tool to design and predict favorable candidates for experimentation would reduce costs and speed the advance of glycoscience. Experimental approaches to synthesize diverse glycoforms will enable functional testing of alternate glycoforms. To develop our technologies, we will computationally predict and experimentally generate constructs with oligosaccharyl transfer to all possible sites in the Im7 and RNase A model proteins. We will then proceed to computationally predict and experimentally test alternate elongation schemes, which result in different glycan structures, for these constructs. Together, our tool set will test how three-dimensional structure alters glycosylation, elongation, and glycoprotein function. When complete, these technologies will enable biologists to probe and design alternate glycoforms both computationally and experimentally for (1) research on the biology of glycosylation and glycosylated molecules and (2) applications to vaccines and therapeutic biomolecule design.

Public Health Relevance

This project will provide predictive computational technologies and experimental technologies to enable study and control of glycans in diverse biological contexts. This project will create (1) computational tools to predict and design oligosaccharide transfer and elongation and (2) experimental tools to create diverse protein glycoforms. The work will test how glycosylation is driven by the three-dimensional structures of the glycans, the glyco-enzymes, and the target protein toward the goal of enabling scientists to design custom functional glycovariants.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM127578-01
Application #
9496651
Study Section
Macromolecular Structure and Function B Study Section (MSFB)
Program Officer
Smith, Ward
Project Start
2018-08-01
Project End
2022-07-31
Budget Start
2018-08-01
Budget End
2019-07-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21205