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Advancing vaccine design with IU’s Karst cluster

High performance systems Jun 21, 2019

Although the field of glycomics lags far behind proteomics and genomics, carbohydrates have many important functions in the human body, like dictating blood type, mediating protein binding, and activating immune response. Dr. Alison Vickman and her colleagues in the Pohl research group in the Department of Chemistry at Indiana University, Bloomington focus on the long-term goal of designing carbohydrate-based vaccines and adjuvants (substances within vaccines that enhance their ability to stimulate the body’s immune response). The team uses a systems approach to advance vaccine design by improving synthetic strategies, de novo structure analysis, and computation.

The Pohl research group, IU Chemistry

The Pohl group is working to clarify how small modifications to monosaccharide (single unit sugars) structures change their three-dimensional shape, which can affect synthetic reactivity and biological recognition. To do so, the team uses computational models to better understand the conformational landscape of various sugar derivatives. Vickman recognized an opportunity to spearhead the Pohl group’s first computational work in order to better understand the factors that influence carbohydrate shape using IU’s extensive high performance computing resources. Vickman and her colleagues are among the first to use these methods on a large scale, due to the complexity and number of calculations required for these highly flexible molecules.

To model the spatial arrangements of over 200 structures, the team faced the challenge of determining how to handle a high volume of calculations efficiently and accurately, but Karst, IU’s high-throughput computing resource, simplified the process. In collaboration with colleagues in the Baik lab, the Pohl group used an in-house software suite to carry out over 30,000 calculations on Karst. Their calculations provide an opportunity to formulate straightforward rules that govern carbohydrate reactivity and, thus, create faster, more efficient syntheses. Such predictions would greatly reduce the time it takes to prepare synthetic sugars, moving scientists one step closer to providing biologists with standards that are used to determine sugars’ biologicals roles. Overall, this work provides a glimpse into the advantages of a big data approach to enhance understanding of structurally complex molecules.

The computing systems available at Indiana University offer an invaluable resource for researchers. Vickman recommends Big Red II and Karst, “as these systems allow for parallel processing, high-throughput, and dynamic environment customization.” Though computational methods have made great strides within the past decade, there is still some skepticism regarding their accuracy – especially for organic chemistry applications. Vickman recognizes the need for improvement in some areas, but notes significant improvements in accuracy within recent years. As an organic chemist who branched into computational chemistry early on in her graduate studies, Vickman is an advocate for the use of computational methods to answer questions that can’t be obtained through standard analytical methods. As computational methods improve and their predictive power progresses, researchers will be able to better inform experimental outcomes before carrying out reactions at bench.  

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