N-Glycan biosynthesis

Introduction

N-Linked glycans are attached in the endoplasmic reticulum to the nitrogen (N) in the side chain of asparagine in the sequon. The sequon is an Asn-X-Ser or Asn-X-Thr sequence, where X is any amino acid except proline and the glycan may be composed of N-acetyl galactosamine, galactose, neuraminic acid, N-acetylglucosamine, fructose, mannose, fucose, and other monosaccharides.

The first version of the model, made in the system BioUML. (The first stage of the modeling)

Model of the first Golgi compartment. (The second stage of the modeling)

Optimization results for the first three patients from Korcula population. (The third stage of the modeling)

N-linked glycans are extremely important in proper protein folding in eukaryotic cells, in cell-cell interactions and in personalized medicine.

Mathematical model of N-Glycan biosynthesis

Model realization

Because of an important role of N-Glycans in personalized medicine it was decided to work out a mathematical model of its biosynthesis in BioUML. The research was begun with Reference pathway from KEGG database implementation .

Reaction rate equations were generated by KEGGtranslator, a number of necessary parameters, such as Michaelis-Menten constants, were taken from BRENDA Enzyme Database.

To give more intuitive representation Glycan structures property was used and to achieve the optimum accuracy we supposed that the distribution of the N-glycans in each Golgi compartment is modeled as a well-mixed reactor.

Despite of the simplicity of the reaction mechanisms and reactions' parameters availability, the process of the building of the computer model of glycosylation split into several stages.

Model optimization

The next step was the model reduction: the decrease in the number of model parameters and materials, which allowed to significantly simplify the model, speed up the Simulation and compare the model results with the experiment.

We use the expiremental data for Korcula population and made the Optimization of model parameters was performed for every individual patient.

Results

We carry out parameters optimization for patients from Korcula population. The objective functions, which is calculated as the sum of squared differences between model and experimental concenration, have the order of 0,0000001-0,00000001.

For every patient his/her individual parameters correlate with each other and with age poorly. Random forest analysis can rpedict only about 15% of results.