Computers find vulnerable targets in the race to fight malaria
Researchers at Leeds have developed a first-of-its-kind computer model that successfully predicts new drug targets for malaria.
The research, published in a paper of the American Society for Microbiology, is a collaboration between infectious disease specialist Dr Glenn McConkey, who has been working in malaria drug targeting for more than 25 years, and computational biology expert Professor David Westhead.
“Malaria is one of the world’s deadliest diseases and kills more than half a million people every year”, explains McConkey. “Resistance to the drug is on the rise and there is currently no fully effective vaccine available. This makes the need to understand and treat the disease extremely urgent, and it is where our research comes in.”
The team used a computer model of the parasite that causes malaria to simulate how it grows and survives. The model predicted drug targets, pinpointing ‘weak spots’, or metabolic reactions essential for its survival.
How the computer model works
The computer model maps out the parasite’s internal chemistry, linking genes to the chemical reactions they control. By ‘deleting’ each reaction one at a time, researchers could identify which ones were essential for growth of the disease.
“The model was originally generated based on a flow diagram connecting reactions of metabolites - an intermediate or end-product of the chemical reactions in an organism- in the microbe with all the genes in the organism. The net was limited by inputs such as nutrients and the output of growth.”
“This process of deleting genes individually would be a monumental task in the laboratory and take several years, but once we had developed the model, all of the genes were tested in silico overnight,” explained Glenn.
Many of the predicted targets matched those already used in current antimalarial drugs, but crucially the model also identified new novel targets. One of these was shown to be to be a viable option for future drug development genetically and chemically. The development of a screening assay and an initial inhibitor paves the way to what may be the first in a series of new antimalarial drugs.
Dr Glenn McConkey says:
This is the first time a computer model has been used to integrate large amounts of information to successfully predict and validate a new drug target for malaria. This provides proof of the utility of genome-scale computer models opening the door to faster, more efficient drug discovery, not just for malaria, but potentially for other infectious diseases too.”
Further info
Validated antimalarial drug target discovery using genome-scale metabolic modeling is authored by Supannee Taweechai, Francis Isidore Garcia Totañes, David Westhead, Clara Herrera-Arozamena, Richard Foster, Glenn A. McConkey
Top image: Microscopy images of human blood, Dr Glenn McConkey. Image shows necessity of UMP-CMP synthase for P. falciparum malaria parasite growth, with left panel microscopic image of red cells (grey) with induced-gene knockout parasites (purple, with arrows) and right panel control human blood culture with healthy parasites (purple). Note aberrant morphology for knockout parasites.
