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Discovery of selective menaquinone biosynthesis inhibitors against Mycobacterium tuberculosis.

ABSTRACT: Aurachin RE (1) is a strong antibiotic that was recently found to possess 1,4-dihydroxy-2-naphthoate prenyltransferase (MenA) and bacterial electron transport inhibitory activities. Aurachin RE is the only molecule in a series of aurachin natural products that has the chiral center in the alkyl side chain at C9'-position. To identify selective MenA inhibitors against Mycobacterium tuberculosis , a series of chiral molecules were designed based on the structures of previously identified MenA inhibitors and 1. The synthesized molecules were evaluated in in vitro assays, including MenA enzyme and bacterial growth inhibitory assays. We could identify novel MenA inhibitors that showed significant increase in potency of killing nonreplicating M. tuberculosis in the low oxygen recovery assay (LORA) without inhibiting other Gram-positive bacterial growth even at high concentrations. The MenA inhibitors reported here are useful new pharmacophores for the development of selective antimycobacterial agents with strong activity against nonreplicating M. tuberculosis.

SUBMITTER: Debnath J

PROVIDER: S-EPMC3375340 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Discovery of selective menaquinone biosynthesis inhibitors against Mycobacterium tuberculosis.

Debnath Joy J Siricilla Shajila S Wan Bajoie B Crick Dean C DC Lenaerts Anne J AJ Franzblau Scott G SG Kurosu Michio M

Journal of medicinal chemistry 20120406 8

Aurachin RE (1) is a strong antibiotic that was recently found to possess 1,4-dihydroxy-2-naphthoate prenyltransferase (MenA) and bacterial electron transport inhibitory activities. Aurachin RE is the only molecule in a series of aurachin natural products that has the chiral center in the alkyl side chain at C9'-position. To identify selective MenA inhibitors against Mycobacterium tuberculosis , a series of chiral molecules were designed based on the structures of previously identified MenA inhi ...[more]

PMID: 22449052

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Project description:BackgroundMycobacterium tuberculosis (M.tb) is the causative agent of tuberculosis, killing ~1.7 million people annually. The remarkable capacity of this pathogen to escape the host immune system for decades and then to cause active tuberculosis disease, makes M.tb a successful pathogen. Currently available anti-mycobacterial therapy has poor compliance due to requirement of prolonged treatment resulting in accelerated emergence of drug resistant strains. Hence, there is an urgent need to identify new chemical entities with novel mechanism of action and potent activity against the drug resistant strains.ResultsThis study describes novel computational models developed for predicting inhibitors against both replicative and non-replicative phase of drug-tolerant M.tb under carbon starvation stage. These models were trained on highly diverse dataset of 2135 compounds using four classes of binary fingerprint namely PubChem, MACCS, EState, SubStructure. We achieved the best performance Matthews correlation coefficient (MCC) of 0.45 using the model based on MACCS fingerprints for replicative phase inhibitor dataset. In case of non-replicative phase, Hybrid model based on PubChem, MACCS, EState, SubStructure fingerprints performed better with maximum MCC value of 0.28. In this study, we have shown that molecular weight, polar surface area and rotatable bond count of inhibitors (replicating and non-replicating phase) are significantly different from non-inhibitors. The fragment analysis suggests that substructures like hetero_N_nonbasic, heterocyclic, carboxylic_ester, and hetero_N_basic_no_H are predominant in replicating phase inhibitors while hetero_O, ketone, secondary_mixed_amine are preferred in the non-replicative phase inhibitors. It was observed that nitro, alkyne, and enamine are important for the molecules inhibiting bacilli residing in both the phases. In this study, we introduced a new algorithm based on Matthews correlation coefficient called MCCA for feature selection and found that this algorithm is better or comparable to frequency based approach.ConclusionIn this study, we have developed computational models to predict phase specific inhibitors against drug resistant strains of M.tb grown under carbon starvation. Based on simple molecular properties, we have derived some rules, which would be useful in robust identification of tuberculosis inhibitors. Based on these observations, we have developed a webserver for predicting inhibitors against drug tolerant M.tb H37Rv available at http://crdd.osdd.net/oscadd/mdri/.

Dataset Information

Discovery of selective menaquinone biosynthesis inhibitors against Mycobacterium tuberculosis.

Publications

Discovery of selective menaquinone biosynthesis inhibitors against Mycobacterium tuberculosis.

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