At CD BioGlyco, we are constantly exploring the frontiers of glycobiology research. We are proud to provide Glycoinformatics-assisted Analysis/Prediction Services, which integrate advanced bioinformatics techniques to accurate predictions of glycan structures and functions. Within this service framework, our Glycoinformatics-assisted Structure Modeling Service is a highlight, which focuses on building the three-dimensional structure of biomolecules through computational simulation. In particular, our glycoinformatics-assisted glycopeptide structure modeling service brings unprecedented accuracy and depth to glycopeptide structure research.
Understanding glycopeptide structure is vital for biomedical research, drug development, and therapeutic interventions. However, the complexity and diversity of glycan structures pose significant challenges. Our glycoinformatics-assisted approach leverages computational techniques to provide detailed and reliable glycopeptide structural models.
The starting point involves acquiring high-quality experimental data, which we typically obtain through mass spectrometry (MS), nuclear magnetic resonance (NMR), or X-ray crystallography. These methods provide key insights into the peptide backbone sequence and glycosylation sites.
MS data analysis: We use deconvolution of MS spectra to identify glycan components associated with the peptide chain.
NMR data interpretation: We use resonance assignments and distance restraints to elucidate the three-dimensional structure in detail.
Crystallographic data refinement: We use electron density maps to refine the initial model.
Sequence alignment: We align the peptide sequence with known databases to make preliminary structure predictions.
Glycan structure prediction: We use glycoinformatics tools to predict potential glycan conformations.
Homology modeling: We use known glycoprotein structures as templates to model the peptide backbone.
Glycan docking: We use carbohydrate docking algorithms to predict the interactions and binding conformations of glycans on the peptide chain.
Molecular dynamics (MD) simulations: We use MD to obtain a dynamic view of glycopeptide stability and conformational changes, validate and optimize the predicted structures.
Energy minimization: Computational protocols to minimize steric clashes and optimize hydrogen bond networks.
Cross-validation: We compare the modeled structures with the original experimental data to detect and correct discrepancies.
Glycosylation site analysis: We examine the glycosylation sites in detail to obtain the correct connectivity and branching patterns.
Journal: Nature methods
IF: 36.1
Published: 2021
Results: This research, carried out by a group of experts in glycoproteomics software, sought to assess methodologies for comprehensive glycopeptide analysis. Through their detailed examination of the data, the authors identified critical search parameters linked to performance and offered suggestions for enhancing glycoproteomics search solutions. The findings indicated that multiple software options are available for thorough glycopeptide data analysis, highlighted several effective search strategies, and pinpointed essential factors that will steer future software advancements and aid in decision-making within glycoproteomics informatics.
Fig.1 Glycopeptides reported across teams. (Kawahara, et al., 2021)
At CD BioGlyco, we are dedicated to empowering researchers with state-of-the-art tools and expertise in glycopeptide structural modeling. Our glycoinformatics-assisted approach bridges the gap between complex biological data and actionable scientific insights. Please feel free to contact us if you are interested in our glycoinformatics-assisted glycopeptide structure modeling service.
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We envision a future where the intricate world of carbohydrate is no longer shrouded in mystery, but rather illuminated by the power of cutting-edge computational tools.