• Bulletin of the Korean Chemical Society
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• v.28 no.6
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• pp.947-952
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• 2007

Mycobacterium tuberculosis is a pathogen responsible for 2-3 million deaths every year worldwide. The emergence of drug-resistant and multidrug-resistant tuberculosis has increased the need to identify new antituberculosis targets. Acetohydroxy acid synthase, (AHAS, EC 2.2.1.6), an enzyme involved in branched-chain amino acid synthesis, has recently been identified as a potential anti-tuberculosis target. To assist in the search for new inhibitors and “receptor-based” design of effective inhibitors of tubercular AHAS (TbAHAS), we constructed four different structural models of TbAHAS and used one of the models as a target for virtual screening of potential inhibitors. The quality of each model was assessed stereochemically by PROCHECK and found to be reliable. Up to 89% of the amino acid residues in the structural models were located in the most favored regions of the Ramachandran plot, which indicates that the conformation of each residue in the models is good. In the models, residues at the herbicide-binding site were highly conserved across 39 AHAS sequences. The binding mode of TbAHAS with a sulfonylurea herbicide was characterized by 32 hydrophobic interactions, the majority of which were contributed by residue Trp516. The model based on the highest resolution X-ray structure of yeast AHAS was used as the target for virtual screening of a chemical database containing 8300 molecules with a heterocyclic ring. We developed a short list of molecules that were predicted to bind with high scores to TbAHAS in a conformation similar to that of sulfonylurea derivatives. Five sulfonylurea herbicides that were calculated to efficiently bind TbAHAS were experimentally verified and found to inhibit enzyme activity at micromolar concentrations. The data suggest that this time-saving and costeffective computational approach can be used to discover new TbAHAS inhibitors. The list of chemicals studied in this work is supplied to facilitate independent experimental verification of the computational approach.