Literature DB >> 26323856

Computational evaluation of phytocompounds for combating drug resistant tuberculosis by multi-targeted therapy.

Sudharsana Sundarrajan1, Sajitha Lulu, Mohanapriya Arumugam.   

Abstract

The cell wall of Mycobacterium tuberculosis interacts with the host counterpart during the pathogenesis of tuberculosis. L-rhamnosyl (L-Rha) residue, a linker connects the arabinogalactan and peptidoglycan moieties in the bacterial cell wall. The biosynthesis of L-rhamnose utilizes four successive enzymes RmlA, RmlB, RmlC and RmlD. Neither rhamnose nor the genes responsible for its synthesis are observed in humans. Thus, drugs inhibiting enzymes of this pathway are unlikely to interfere with metabolic pathways in humans. The adverse drug effects of first and second line drugs along with the development of multi-drug resistance tuberculosis have stimulated the research in search of new therapeutic drugs. Thus, it is attractive to hypothesize that inhibition of the biosynthesis of L-Rha would be lethal to the mycobacteria. Nature provides innumerable secondary metabolites with novel structural architectures with reported activity against M. tuberculosis. Combination of structure based virtual screening with physicochemical and pharmacokinetic studies against rhamnose pathway enzymes identified potential leads. The crucial screening studies recognized four phytocompounds butein, diospyrin, indicanine, and rumexneposide A with good binding affinity towards the rhamnose pathway proteins. Furthermore, the high throughput screening methods recognized butein, a secondary metabolite from Butea monosperma with strong anti-tubercular bioactive spectrum. Butein displayed promising anti-mycobacterial activity which is validated by Microplate alamar blue assay (MABA). The focus on novel agents like these phytocompounds which exhibit preference toward the successive enzymes of a single pathway can prevent the development of bacterial resistance.

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Year:  2015        PMID: 26323856     DOI: 10.1007/s00894-015-2785-z

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  34 in total

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