ArticleBMC bioinformatics2016
Resistance related metabolic pathways for drug target identification in Mycobacterium tuberculosis.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Prioritization of chemical scaffolds using the TDR Targets database: An integrative workflow for Trypanosoma cruzi drug discovery.PLoS neglected tropical diseases · 2026Article
- The implication of Mycobacterium tuberculosis-mediated metabolism of targeted xenobiotics.Nature reviews. Chemistry · 2023Review
- Progress Report: Antimicrobial Drug Discovery in the Resistance Era.Pharmaceuticals (Basel, Switzerland) · 2022Review
- Article
- Article
- Metabolite Profiling: A Tool for the Biochemical Characterisation ofMicroorganisms · 2019Review
- Designing novel possible kinase inhibitor derivatives as therapeutics against Mycobacterium tuberculosis: An in silico study.Scientific reports · 2019Article
- An integrative, multi-omics approach towards the prioritization of Klebsiella pneumoniae drug targets.Scientific reports · 2018Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIncreasing resistance to anti-tuberculosis drugs has driven the need for developing new drugs. Resources such as the tropical disease research (TDR) target database and AssessDrugTarget can help to prioritize putative drug targets. Hower, these resources do not necessarily map to metabolic pathways and the targets are not involved in dormancy. In this study, we specifically identify drug resistance pathways to allow known drug resistant mutations in one target to be offset by inhibiting another enzyme of the same metabolic pathway. One of the putative targets, Rv1712, was analysed by modelling its three dimensional structure and docking potential inhibitors.
resultsWe mapped 18 TB drug resistance gene products to 15 metabolic pathways critical for mycobacterial growth and latent TB by screening publicly available microarray data. Nine putative targets, Rv1712, Rv2984, Rv2194, Rv1311, Rv1305, Rv2195, Rv1622c, Rv1456c and Rv2421c, were found to be essential, to lack a close human homolog, and to share >67 % sequence identity and >87 % query coverage with mycobacterial orthologs. A structural model was generated for Rv1712, subjected to molecular dynamic simulation, and identified 10 compounds with affinities better than that for the ligand cytidine-5'-monophosphate (C5P). Each compound formed more interactions with the protein than C5P.
conclusionsWe focused on metabolic pathways associated with bacterial drug resistance and proteins unique to pathogenic bacteria to identify novel putative drug targets. The ten compounds identified in this study should be considered for experimental studies to validate their potential as inhibitors of Rv1712.
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