Computer models combat malaria

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As one of the world’s deadliest pathogens, Plasmodium spreads relentlessly from host to host. But a computer model created by KAUST scientists may reveal and help exploit the parasite’s unknown weaknesses to uncover new options for treating malaria.

The Plasmodium parasite needs both a mosquito and vertebrate host to reproduce and complete its life cycle. Through what would otherwise be harmless insect bites, Plasmodium rapidly multiplies and spreads from mosquitoes to human hosts, where it causes malaria and kills nearly half a million people worldwide each year.

As Plasmodium infects red blood cells, transmits between hosts and reproduces, the single-celled parasite takes different forms. A key limitation of current malaria drugs is that they only treat the form of Plasmodium that actively causes malaria symptoms. Yet, treatments that target the pathogen’s transmitting form may nip the disease in the bud.

Searching for potential malaria drug targets, KAUST Ph.D. student Alyaa Abdel-Haleem and her colleagues investigated the Plasmodium genetic blueprint. They focused on the genes involved in metabolism—the chemical reactions that allow the parasite to grow, reproduce and respond to its environment. 

“Our aim in this study was to provide a model that catalogues metabolic differences between species and life-cycle stages to explore novel treatment strategies and targets,” explains Abdel-Haleem. 

First, the scientists created computer models that combined the genetic blueprint of Plasmodium with information on how metabolic genes turned on and off in five different species and at five different stages of its life cycle. They then deleted genes in their models and ran simulations to test which genes were integral to the parasite’s survival.

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