Prioritizing Genomic Drug Targets in Pathogens:
Application to Mycobacterium tuberculosis
PLoS Computational Biology, 2 (6):
e61 (June 2006)DOI: doi:10.1371/journal.pcbi.0020061
Abstract
We have developed a software program that weights and
integrates specific properties on the genes in a
pathogen so that they may be ranked as drug targets. We
applied this software to produce three prioritised drug
target lists for Mycobacterium tuberculosis, the
causative agent of tuberculosis, a disease for which a
new drug is desperately needed. Each list is based on
an individual criterion. The first list prioritises
metabolic drug targets by the uniqueness of their roles
in the M. tuberculosis metabolome (metabolic choke
points) and their similarity to known druggable protein
classes (i.e., classes whose activity has previously
been shown to be modulated by binding a small
molecule). The second list prioritizes targets that
would specifically impair M. tuberculosis, by weighting
heavily those that are closely conserved within the
Actinobacteria class but lack close homology to the
host and gut flora. M. tuberculosis can survive
asymptomatically in its host for many years by adapting
to a dormant state referred to as persistence. The
final list aims to prioritise potential targets
involved in maintaining persistence in M. tuberculosis.
The rankings of current, candidate, and proposed drug
targets are highlighted with respect to these lists.
Some features were found to be more accurate than
others in prioritising studied targets. It can also be
shown that targets can be prioritised by using
evolutionary programming to optimise the weights of
each desired property. We demonstrate this approach in
prioritizing persistence targets.
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