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Updated: Mar 26, 2026
System for Efficacy and Cytotoxicity Screening of Inhibitors Targeting Intracellular Mycobacterium tuberculosis
Published on: April 5, 2017
Resistance related metabolic pathways for drug target identification in Mycobacterium tuberculosis
Ruben Cloete1, Ekow Oppon2, Edwin Murungi3,4
1South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa. ruben@sanbi.ac.za.
Background:
Increasing 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.
Results:
We 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.
Conclusions:
We 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.
Insights
New drug targets were identified by mapping tuberculosis drug resistance pathways to essential metabolic pathways. Ten novel compounds show potential as Rv1712 inhibitors, offering new avenues for anti-TB drug development.
Area of Science:
- Microbiology
- Drug Discovery
- Bioinformatics
Background:
- Rising anti-tuberculosis drug resistance necessitates novel therapeutic strategies.
- Existing drug target databases lack pathway mapping and dormancy involvement.
- This study focuses on identifying drug resistance pathways to overcome resistance through metabolic pathway inhibition.
Purpose of the Study:
- To identify novel drug targets in tuberculosis by analyzing drug resistance pathways.
- To find potential inhibitors for Rv1712, a key target in mycobacterial metabolism.
- To offset drug resistance by targeting alternative enzymes within the same metabolic pathway.
Main Methods:
- Screening publicly available microarray data to map 18 TB drug resistance gene products to 15 metabolic pathways.
- Identifying essential genes lacking human homologs and exhibiting high sequence identity with mycobacterial orthologs.
- Generating a 3D structural model of Rv1712, performing molecular dynamic simulations, and docking potential inhibitors.
Main Results:
- Nine essential putative drug targets, including Rv1712, were identified.
- A structural model of Rv1712 was created and simulated.
- Ten compounds demonstrated superior binding affinities to Rv1712 compared to cytidine-5'-monophosphate (C5P).
Conclusions:
- Novel drug targets were identified by focusing on metabolic pathways linked to drug resistance and proteins unique to pathogenic bacteria.
- The ten identified compounds warrant experimental validation as potential inhibitors of Rv1712.
- This approach offers a strategy to combat drug-resistant tuberculosis.
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