The estimate that more lives may have been lost in 2009 due to tuberculosis (TB) than in any year in history is alarming. Approximately 9.2 million new cases and 1.8 million deaths due to TB were reported in 2008. The widespread prevalence of Mycobacterium tuberculosis strains that are resistant to drugs currently used to treat TB means that new drugs are urgently needed to treat these infections. Authors from Johns Hopkins University, Texas A&M and CDD have identified pathways for the biosynthesis of essential metabolites and associated enzymes in M. tuberculosis using a genetics-based approach. Small molecules that mimic these essential metabolites were identified using computational approaches including CDD, and some of them were shown to inhibit the growth of M. tuberculosis. This illustrates an approach based on genetics and computational methods to develop inhibitors that have the potential to be advanced as candidate drugs for treating TB.
A review co-authored by CDD, SRI, NIH and Texas A&M describes how computational databases, pathway and cheminformatics techniques have been leveraged for TB over the last 5 years. Gaps were found in their integration which if remedied and optimally integrated within a workflow with experimental approaches could accelerate TB drug discovery.
This blog is authored by members of the CDD Vault community. CDD Vault is a hosted drug discovery informatics platform that securely manages both private and external biological and chemical data. It provides core functionality including chemical registration, structure activity relationship, chemical inventory, and electronic lab notebook capabilities!
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