A New Tool for the Analysis of Glycan Recognition in Lectin
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With this award, the Chemistry of Life Processes Program in the Chemistry Division is funding Drs. Hung-Jen Wu and Joseph Kwon from Texas A&M University to develop a next-generation glycoarray tool that can be used in the study of the complex interactions between glycans and lectins, both of which are biomolecules found in living systems. More specifically, lectins are proteins that recognize and bind glycans, which are carbohydrate molecules; the binding between lectins and glycans plays an important role in a wide range of physiological and pathological processes. Lectin-glycan binding has several important features. Firstly, it is not highly specific; a lectin often binds to different glycan structures with different affinities. Most lectins bind to glycans via multivalent interactions, i.e. multiple binding domains of a single lectin simultaneously interact with multiple glycan molecules. Moreover, glycans attached to lipids or membrane proteins can diffuse on two-dimensional cell membranes. These features distinguish the lectin-glycan interactions from classic bimolecular interactions such as those between antibodies and antigens. Existing methods for lectin analysis miss these essential characteristics, and thus often fail to describe some unexpected phenomena in glycobiology. The goal of this research project is to establish a next-generation glycoarray tool that fills this critical need and makes possible the discovery of the lectin-glycan recognition principles. The project also involves the development of a project-based learning program that focuses on supporting the learning by high school students of chemistry and nanoscience topics. The students participants are engaged in hands-on experiments and interactive activities. Drs. Wu and Kwon''s team is converting the educational program to an open-access web-based course for teachers with the goal of increasing the impact of their STEM outreach efforts. Drs. Wu and Kwon are developing a high-throughput nanocube sensor array to quantitatively measure lectin-glycan interactions in an environment that mimics the cell membrane. In addition, a kinetic Monte Carlo simulation is being developed for modeling complex lectin-glycan interactions. This novel glycoarray tool that integrates analytical assay and computational modeling allows one to measure fundamental microscopic binding parameters, which in turn can be used in the prediction of lectin functions on complex cellular surfaces. The tool makes possible the simultaneous examination of the influence of semi-specificity, multivalency, and ligand diffusion on lectin-glycan recognition. The analysis of the lectin-glycan recognition pattern becomes highly accessible, flexible, and inexpensive. End users can conduct measurements in their own laboratories without specialized equipment by following a step-by-step guide included in the sophisticated modeling software. The detection tool is compatible with a variety of glycan-binding species, including toxins, bacteria, viruses, and cancer cells; consequently, it can benefit a wide range of scientific communities. 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.