CD ComputaBio is a leading computational modelling company that specializes in bioinformatics and drug discovery services. One of the key services we offer is N-glycosylation sites prediction, which plays a crucial role in understanding protein glycosylation and its impact on protein structure and function.
Introduction of N-glycosylation Sites Prediction
N-glycosylation sites prediction is a complex process that involves analyzing the protein sequence to identify potential N-glycosylation motifs and predicting the likelihood of glycosylation at specific asparagine residues. There are several computational tools and algorithms that have been developed for N-glycosylation sites prediction, each with its strengths and limitations. At CD ComputaBio, we use a combination of bioinformatics tools, machine learning algorithms, and structural modeling techniques to predict N-glycosylation sites with high accuracy and confidence.
Figure 1. N-glycosylation Sites Prediction. (She Y M, et al. 2017)
Our Service
Sequence-Based Prediction
Our sequence-based prediction service utilizes machine learning algorithms to predict N-glycosylation sites in protein sequences. We analyze the amino acid sequence of a protein and identify potential N-glycosylation sites based on sequence motifs and patterns.
Structural Modeling
Our structural modeling service involves predicting N-glycosylation sites in protein structures using structural bioinformatics tools. We analyze the 3D structure of a protein and identify potential N-glycosylation sites based on solvent accessibility, secondary structure, and spatial proximity to asparagine residues.
Comparative Genomics
Our comparative genomics service compares the protein sequences of closely related species to predict conserved N-glycosylation sites. By analyzing evolutionary conservation patterns, we can identify putative N-glycosylation sites that are likely to be functionally important.
Customized Solutions
In addition to our standard services, we offer customized solutions for clients with specific requirements or research goals. Our team can develop tailored prediction models, integrate additional features or data sources, and provide in-depth analysis and interpretation of the results.
Sample Requirements and Result Delivery
Sample Requirements
Result Delivery
For accurate N-glycosylation site prediction, we require the following sample information:
Protein sequences in FASTA format
Optionally, 3D protein structure data in PDB format for structure-based prediction
Additional information such as experimental glycosylation sites (if available) for training and validation purposes
Upon analysis and prediction, clients can expect the following deliverables:
Visual representations of predicted sites on protein sequences and structures
Interpretation and analysis of predicted sites in relation to protein function and structure
Approaches to N-glycosylation Sites Prediction
Sequence-based prediction
This method relies on the analysis of protein sequences to identify potential N-glycosylation sites based on sequence motifs and physicochemical properties of amino acids.
Structure-based prediction
Utilizing protein structural information for N-glycosylation site prediction involves analyzing the 3D structure of proteins to identify solvent-accessible asparagine residues where glycosylation is likely to occur.
Hybrid approaches
Combining sequence and structural information enhances the accuracy of N-glycosylation site prediction. Hybrid methods integrate features from both sequence and structure datasets to improve the reliability of predictions.
Advantages of Our Services
1
Expertise
Our team consists of experienced bioinformatics specialists with a proven track record in computational modeling and bioinformatics analysis.
2
State-of-the-Art Tools
We utilize cutting-edge computational tools and algorithms to ensure accurate and reliable predictions for N-glycosylation sites.
3
Customized Solutions
We understand the unique requirements of each project and offer tailored solutions to meet the specific needs of our clients.
4
Fast Turnaround
We prioritize efficiency without compromising accuracy, ensuring timely delivery of results to expedite your research projects.
Frequently Asked Questions
N-glycosylation sites prediction is a valuable tool in bioinformatics and drug discovery that can provide important insights into protein glycosylation and its impact on protein structure and function. At CD ComputaBio, we offer a comprehensive N-glycosylation sites prediction service that combines advanced computational tools, machine learning algorithms, and structural modeling techniques to predict N-glycosylation sites with high accuracy and confidence.
Reference
She Y M, Farnsworth A, Li X, et al. Topological N-glycosylation and site-specific N-glycan sulfation of influenza proteins in the highly expressed H1N1 candidate vaccines. Scientific reports, 2017, 7(1): 10232.
For research use only. Not intended for any clinical use.
Figure 1. N-glycosylation Sites Prediction. (She Y M, et al. 2017)
