Computational Prediction of Alternative Metabolic Pathways of Plasmodium Falciparum

摘要

Plasmodium falciparum (P.f.), the malaria pathogen, has shown substantial resistance to treatment and vaccine thereby requiring urgent, holistic and broad approach to prevent an endemic. Understanding the biology of the malaria parasite has been identified as a vital approach to overcome the threat of malaria. This study reconstructed the iPfa Genome-scale metabolic model (GEM) of 3D7 strain of Plasmodium falciparum by filling gaps in the model with nineteen (19) metabolites and twenty-three (23) reactions obtained from MetaCyc database. Biomass reactions and exchange reactions were removed since they are mainly used to evaluate changes in flux which is not required in our approach. Twenty (20) currency metabolites were removed from the network because they have been identified to produce shortcuts that are biologically infeasible. The resulting modified iPfa GEM was model using reaction graph and a k-shortest path algorithm was applied to identify alternative metabolic pathways of Plasmodium falciparum. Five alternative paths were predicted in the glycolysis pathway.