In Silico Cell For TB Drug Discovery

Tuberculosis remains one of the biggest killers in the world today being responsible for nearly ten million cases and one and a half million deaths each year. New strains are emerging that are resistant to all current front-line anti-tuberculous drugs so new drugs are urgently needed. However, little is known about the metabolism of the TB bacillus and, because of its slow growth, experiments take a very long time.

The Surrey group hopes to speed up the drug discovery process by building an in silico model of the agent that causes TB: a virtual TB bacillus. This model was constructed using information from the entire genome sequence of the pathogen and uses mathematical equations to model the flow of nutrients through the cell. The model is extremely complex, handling 848 different biochemical reactions and 726 genes.

The Surrey team showed that the model successfully simulates many of the peculiar properties of the TB bacillus and identifies the drug targets of known anti-tuberculous drugs. But unlike the biological organisms, the in silico TB bacillus grows in nanoseconds so experiments that would normally take months can be performed in minutes. The group hope that the in silico model may be used to identify new drug targets, particularly those capable of killing persistent bacilli.

The work is published in the high-profile journal Genome Biology and describes not only the model but, for the first time, makes an in silico model available to other researchers via an interactive website. Researchers will be able to perform experiments on the virtual TB bacillus from a beach in Bombay or a mountaintop in Malawi. It is hoped that the availability of this novel research tool will stimulate new approaches to control of this deadly pathogen.