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Abstract
Complex carbohydrates (glycans) have long been known to play a role in immune response, regulation of cellular activity, and cell-cell interactions, to name a few. Thus the ability to model glycan structure and their interactions with other biomolecules (i.e. biorecognition) is essential to understanding and exploiting glycan functionality in the design of pharmaceutical glycomimetics, or molecules with similar properties to glycans. Over several decades, computational methods have become essential to characterizing glycan structure and bioactivity when only sparse experimental data is available. This work expands on those efforts by improving on the GLYCAM molecular mechanics force field to include a wider range of glycan structures including glycolipids and glycosaminoglycans. The GLYCAM force field was used in molecular dynamics (MD) simulations to predict the three-dimensional (3D) structures of glycans and glycoconjugates. Then, utilizing the three-dimensional glycan structure data from glycan simulations and experimental data, a virtual glycan 3D structure library was generated. In this case, the virtual library was employed to establish the first computational prediction of bulk carbohydrate-protein specificity using a method called Computational Carbohydrate Grafting (CCG). This method has been shown to be useful in augmenting the results of experimental specificity screening and it can be used to test the specificity of glycans which are not included on the experimental arrays while providing 3D structures of protein-carbohydrate complexes. The CCG method was used to predict the binding specificity restrictions of the anti-tumor antibody JAA-F11 and provided a 3D structural rational for its binding specificity. The development of the force field and CCG method are all part of an effort to better understand how the 3D structure of glycans impact biorecognition so as to guide the development of novel therapeutic or diagnostic glycomimetics.