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Fighting malaria through mathematical analysis of parasite's metabolism

Model could accelerate development of antimalarial drugs that target parasite's metabolic processes

Date:
March 23, 2017
Source:
PLOS
Summary:
A new mathematical model, based on the deadliest malaria parasite, Plasmodium falciparum, could help develop antimalarials by identifying key metabolic targets, according to a new study.
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A new mathematical model, based on the deadliest malaria parasite, Plasmodium falciparum, could help develop antimalarials by identifying key metabolic targets, according to a study published in PLOS Computational Biology by Vassily Hatzimanikatis at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, and colleagues.

Malaria, a mosquito-borne infectious disease caused by parasites of the Plasmodium genus, is becoming increasingly difficult to treat as the parasites develop resistance to current drugs. A promising new strategy is to target the parasites' metabolism, but it has proven to be both versatile and complex, making it difficult to target. It has also been difficult to integrate existing experimental data on the metabolism with genetic data on the genome sequence, gene expression, and essential genes for growth.

To overcome these obstacles, the authors of the present study developed a model that accurately connects experimental information from both genetics and metabolomics. They looked at the thermodynamic properties of the metabolic reactions, which relate to the way the parasites use and produce energy. This focus on the energetics of the reactions allows them to analyse, for the first time, which metabolic functions are thermodynamically coupled and are essential during infection. It reveals complex interactions between the parasites' genes and metabolism, which, the authors state, could identify potential mechanisms to target with drugs.

"The model integrates all available knowledge on the genetics and metabolism of the parasites and allows the formulation of testable hypotheses behind the parasite's essential functions," says Dr. Hatzimanikatis. "Ultimately, it can accelerate the discovery toward novel antimalarial drug targets."

The EPFL scientists will now continue to calibrate and improve the predictive capabilities of the model with additional genetics and metabolomics data provided by collaborators from the MalarX.ch consortium in the University of Geneva and Bern and the Wellcome Trust Sanger Institute. They hope to reveal the mechanisms behind host-pathogen interactions and gain insight into the physiology of the parasite while it is dormant.

This press release is based on text provided by the authors.


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Journal Reference:

  1. Anush Chiappino-Pepe, Stepan Tymoshenko, Meriç Ataman, Dominique Soldati-Favre, Vassily Hatzimanikatis. Bioenergetics-based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks. PLOS Computational Biology, 2017; 13 (3): e1005397 DOI: 10.1371/journal.pcbi.1005397

Cite This Page:

PLOS. "Fighting malaria through mathematical analysis of parasite's metabolism: Model could accelerate development of antimalarial drugs that target parasite's metabolic processes." ScienceDaily. ScienceDaily, 23 March 2017. <www.sciencedaily.com/releases/2017/03/170323141421.htm>.
PLOS. (2017, March 23). Fighting malaria through mathematical analysis of parasite's metabolism: Model could accelerate development of antimalarial drugs that target parasite's metabolic processes. ScienceDaily. Retrieved May 26, 2017 from www.sciencedaily.com/releases/2017/03/170323141421.htm
PLOS. "Fighting malaria through mathematical analysis of parasite's metabolism: Model could accelerate development of antimalarial drugs that target parasite's metabolic processes." ScienceDaily. www.sciencedaily.com/releases/2017/03/170323141421.htm (accessed May 26, 2017).

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