Integration of Experimental and Computational Methods to Characterize Glycoproteins

This chapter examines the integration of experimental and computational approaches in glycoprotein characterization. Glycans, the most information-dense biopolymers on Earth, present unique structural challenges due to their inherent flexibility and complexity. Molecular dynamics simulations have emerged as essential tools for studying glycoproteins, complementing experimental techniques such as nuclear magnetic resonance (NMR), X-ray crystallography, and cryo-electron microscopy (cryo-EM). Recent advances in computing power, specialized force fields, and enhanced sampling techniques have enabled microsecond-scale simulations of glycosylated proteins, revealing their conformational ensembles and functional roles. The SARS-CoV-2 pandemic catalyzed unprecedented computational efforts, demonstrating how glycosylation affects spike protein dynamics, receptor binding, and antibody recognition. Combined quantum mechanics/molecular mechanics (QM/MM) approaches further elucidate reaction mechanisms in glycoenzymes. This synergistic integration of experimental and computational methods provides comprehensive insights into glycoprotein structure, dynamics, and function that neither approach could achieve alone.