Glycoinformatics-assisted Glycoproteomics Analysis Service
Unlock the Secrets of Glycoproteins with Glycoinformatics Analysis
Glycoproteomics analysis utilizing glycoinformatics integrates glycan and proteomics data to enhance the comprehensive understanding of glycoprotein structure, function, and interactions. CD BioGlyco has the expertise and specialists to provide clients with a comprehensive
Glycoinformatics-assisted Glycomics Analysis Service, which includes
Disease Glycomics,
Glycogenomics,
Glycolipidomics,
Glycometabolomics, and glycoproteomics. Our glycoinformatics-assisted glycoproteomics analysis service encompasses a wide range of services, including but not limited to the following:
Glycoinformatics-assisted glycosyltransferases gene and protein expression analysis
We provide glycoinformatics-based identification and analysis of gene and protein expression for glycosyltransferases. Our experts use the information provided by the glycosyltransferase database, including enzyme name, EC number, organism, nucleotide access number, expression profiles, amino acid sequences, and biochemical reactions, to understand the structure of the glycans formed by the glycosyltransferases and to infer their function and regulatory mechanisms in glycoproteomics. Meanwhile, the information provided by the glycosyltransferase database, such as nucleotide access numbers and amino acid sequences, is utilized to research the synthesis and regulatory mechanisms of glycosyltransferases.
Enhancing glycan analysis through database integration and 3D modeling
Based on various databases and tools, we provide glycan analysis, 3D structure modeling, and rapid conversion of complex glycan sequences into reliable 3D molecular models for molecular dynamics simulations. Simultaneously, we conduct investigations into compound data within databases to enable the linkage of glycomics and proteomics data, thereby enhancing our ability to offer superior glycan analysis services.
Publication
Technology: Lectin microarrays, glycan microarrays, and glycogen microarrays
Journal: International Journal of Molecular Sciences
IF: 6.208
Published: 2020
Results: This article is about glycobiology and glycoproteomics based on glycoinformatics. The study of glycobiology and glycoproteomics is more complex compared to the study of genome and proteome because the diversity and branching nature of glycans make the study more difficult. In addition, glycan expression is affected by a variety of factors, such as differences in the expression of glycosyltransferases and glucosidases in different cells and tissues, and glycan chains on the same protein are associated with cells, tissues, organisms, and physiological states. Therefore, deciphering information about glycosylation sites, attached glycan chain structures, protein scaffolds, and associated glycosyltransferases is essential for understanding the biological functions of glycosylation. With improved analytical methods, including high-performance separation techniques and mass spectrometry-based analysis, qualitative and quantitative data on glycans, glycosylation sites, glycopeptides, and glycoproteins have greatly increased. In addition, the widespread use of lectin microarrays, glycan microarrays, and glycogen microarrays has greatly increased data on sugar-protein interactions and glyco-genomes. Therefore, the development of databases and informatics tools to store, retrieve, integrate, and interpret these data is one of the most active areas in glycobiology.
Fig.1 Summary of major glycoinformatic databases using membrane glycoproteins as an illustration. (Li, et al., 2020)
Applications
- The technology of glycoinformatics-assisted glycoproteomics analysis is employed to examine the glycosylation patterns of cancer cell surface glycoproteins to identify cancer biomarkers and facilitate early disease detection.
- Glycoinformatics-assisted glycoproteomics analysis is employed for the identification of disease-associated glycoproteins, thereby revealing potential targets for drug development.
- Glycoinformatics-assisted glycoproteomics analysis is used to assess the stability and consistency of glycosylation of biopharmaceuticals during production and to optimize the manufacturing process.
Advantages
- Combined with mass spectrometry and glycoinformatics tools, glycoproteins can be analyzed simultaneously in a large number of samples, providing high-throughput data acquisition.
- Our glycoinformatics-assisted glycoproteomics analysis technology facilitates comprehensive identification of glycosylation sites, allowing for more precise determination of glycosylation sites on glycoproteins and resolution of complex glycosylation modification patterns.
- We integrate glycoproteomic data with other genomic data, such as genomic, transcriptomic, and metabolomic data, to provide you with more comprehensive information and analysis results.
Frequently Asked Questions
- What is Glycoinformatics-assisted glycoproteomics analysis?
- Glycoinformatics-assisted glycoproteomics analysis is a state-of-the-art analytical technique that combines glycobioinformatics and glycoproteomics to study and analyze the structure and function of glycoproteins and their glycosylation modification patterns.
- How is the credibility of the analyzed results ensured?
- Repeated experiments: We verify the results by several independent experiments.
- Data correction: We use standards and controls for data correction to exclude experimental errors.
- Tool validation: We utilize multiple glycoinformatics tools for cross-validation to ensure the accuracy of the results.
As a leading provider of glycoinformatics services globally, CD BioGlyco operates a technical center to support clients in their research. With years of experience in glycoinformatics-based research, we offer professional glycoinformatics-assisted glycoproteomics analysis services to clients. If you need further details, please don't hesitate to contact us.
Reference
- Li, X.; et al. Databases and bioinformatic tools for glycobiology and glycoproteomics. International Journal of Molecular Sciences. 2020, 21(18): 6727.
For research use only. Not intended for any diagnostic use.
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