MODELLING AND FLUX BALANCE ANALYSIS OF THE HUMAN APOPTOTIC PATHWAY

Udayakumar Mani; Ajithavalli C; Vignesh K; Sai Mukund R

Authors

Udayakumar Mani Department of Bioinformatics, bDepartment of Biotechnology, Sastra University, Thanjavur 613401, Tamil Nadu, India
Ajithavalli C Sastra University
Vignesh K Sastra University
Sai Mukund R Sastra University

Keywords:

Apoptosis, Metabolic pathway modelling, Flux Profile, KEGG, System Biology Markup Language

Abstract

Objective: Flux balance analysis is one method to analyse genome-scale models for metabolism and transcriptional regulation. Her we use the apoptotic pathway, the most widely used FBA to perform a mathematical model also analyses the flux balance to study the relationship between the flux and the genes involved in the extrinsic pathway.

Methods: KEGG was used to obtain information of pathways and related ligands and genes. Biocyc was considered for its intricacy in explanation of the mechanisms of pathways. A specific wing of Biocyc called humancyc was used for human related pathways. SBML was used to sort the several pathways.

Results: The pathway was modelled using SBML version 2 level 1 specifications which are the most commonly used version making FBA one of the best methods for studying this process. Based on FBA, the genes like bid and cyc were classified as essential and non-essential. All these details suggest that our model is sensible scientifically. This technique can satisfy researchers to uncover several biologically complex pathways computationally. This is a more efficient and less time consuming process.

Conclusion: With the availability of experimental biochemical data, like the concentration or the ratio of these caspases in a cell, the accuracy of this method can be improved. In our method, the entire model is considered to be present in a single compartment. Separate compartments for the inclusion of inhibitors and activators can be added to represent the pathway more effectively. A more complex model including the entire apoptotic pathway can be modelled to determine all possible ways of inhibiting apoptosis.

Â

Downloads

Download data is not yet available.

Author Biographies

Udayakumar Mani, Department of Bioinformatics, bDepartment of Biotechnology, Sastra University, Thanjavur 613401, Tamil Nadu, India

Dept. of Bioinformatics and Assistant Professor

Ajithavalli C, Sastra University

Dept. of Bioinformatics

Sai Mukund R, Sastra University

Dept. of Bioinformatics and B.Tech Student

References

Christophe HS, Stefan S, Bernhard OP, Reinhart H. Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era. Biotechnol Prog 1999;15:296-303.

Eberhard OV, Jonas A. Decoupling dynamical systems for pathway identification from metabolic profiles. Bioinformatics 2003;20:1670â€“81.

Ivan VM. Systems Biology. In: Methods in Molecular Biology. 1sted. New York: Humana Press; 2009.

Vanya IR, Pedro M. Cellular responses to endoplasmic reticulum stress and apoptosis. New York: Domingos Springer; 2009.

Potten CS, James WW. Apoptosis: the life and death of cells. New York: Cambridge University Press; 2004.

Markus WC, Christophe HS, Iman F, Jeremy SE, Igor IG, Evgeni S, et al. Metabolic modeling of microbial strains in silico. Trends Biochem Sci 2001;26:179-86.

Minoru K, Susumu G. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000;28:27-30.

Peter DK, Christos AO, Caroline MK, Leon G, Pallavi K, Dag A, et al. Expansion of the BioCyc collection of pathway/genome databases to 160 genomes. Nucleic Acids Res 2005;33:6083â€“9.

Karthik R, Preethi R, Nagasuma C. Flux balance analysis of mycolic acid pathway: targets for anti-tubercular drugs. PLoS Comput Biol 2005;5:349-58.

Dantzig GB, Orden A, Wolfe P. Generalized simplex method for minimizing a linear from under linear inequality constraints. Pacific J Mathematics 1955;5:183â€“95.