scholarly journals Generation and Analysis of Large-Scale Data-Driven Mycobacterium tuberculosis Functional Networks for Drug Target Identification

2011 ◽  
Vol 2011 ◽  
pp. 1-14 ◽  
Author(s):  
Gaston K. Mazandu ◽  
Nicola J. Mulder
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Targets ◽  
Large Scale ◽  
Global Analysis ◽  
Interaction Network ◽  
Interaction Networks ◽  
Microbial Pathogens ◽  
Potential Drug ◽  
Functional Interaction ◽  
Potential Drug Targets

Technological developments in large-scale biological experiments, coupled with bioinformatics tools, have opened the doors to computational approaches for the global analysis of whole genomes. This has provided the opportunity to look at genes within their context in the cell. The integration of vast amounts of data generated by these technologies provides a strategy for identifying potential drug targets within microbial pathogens, the causative agents of infectious diseases. As proteins are druggable targets, functional interaction networks between proteins are used to identify proteins essential to the survival, growth, and virulence of these microbial pathogens. Here we have integrated functional genomics data to generate functional interaction networks between Mycobacterium tuberculosis proteins and carried out computational analyses to dissect the functional interaction network produced for identifying drug targets using network topological properties. This study has provided the opportunity to expand the range of potential drug targets and to move towards optimal target-based strategies.

scholarly journals Characterization of G-Quadruplex Motifs in espB, espK, and cyp51 Genes of Mycobacterium tuberculosis as Potential Drug Targets

2019 ◽  
Vol 16 ◽  
pp. 698-706 ◽  
Author(s):  
Subodh Kumar Mishra ◽  
Uma Shankar ◽  
Neha Jain ◽  
Kriti Sikri ◽  
Jaya Sivaswami Tyagi ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Targets ◽  
Potential Drug ◽  
G Quadruplex ◽  
Potential Drug Targets

Proteomic profile of Mycobacterium tuberculosis after eupomatenoid-5 induction reveals potential drug targets

2017 ◽  
Vol 12 (10) ◽  
pp. 867-879 ◽  
Author(s):  
Luciana D Ghiraldi-Lopes ◽  
Paula AZ Campanerut-Sá ◽  
Jean E Meneguello ◽  
Flávio AV Seixas ◽  
Mariana A Lopes-Ortiz ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Targets ◽  
Proteomic Profile ◽  
Potential Drug ◽  
Potential Drug Targets

scholarly journals Evaluating potential drug targets through human loss-of-function genetic variation

2019 ◽  
Author(s):  
Eric Vallabh Minikel ◽  
Konrad J Karczewski ◽  
Hilary C Martin ◽  
Beryl B Cummings ◽  
Nicola Whiffin ◽  
...  
Keyword(s):  
Drug Targets ◽  
Large Scale ◽  
Human Genetics ◽  
Positional Distribution ◽  
Model Organism ◽  
New Drugs ◽  
Potential Drug ◽  
Loss Of Function ◽  
Potential Drug Targets

AbstractHuman genetics has informed the clinical development of new drugs, and is beginning to influence the selection of new drug targets. Large-scale DNA sequencing studies have created a catalogue of naturally occurring genetic variants predicted to cause loss of function in human genes, which in principle should provide powerfulin vivomodels of human genetic “knockouts” to complement model organism knockout studies and inform drug development. Here, we consider the use of predicted loss-of-function (pLoF) variation catalogued in the Genome Aggregation Database (gnomAD) for the evaluation of genes as potential drug targets. Many drug targets, including the targets of highly successful inhibitors such as aspirin and statins, are under natural selection at least as extreme as known haploinsufficient genes, with pLoF variants almost completely depleted from the population. Thus, metrics of gene essentiality should not be used to eliminate genes from consideration as potential targets. The identification of individual humans harboring “knockouts” (biallelic gene inactivation), followed by individual recall and deep phenotyping, is highly valuable to study gene function. In most genes, pLoF alleles are sufficiently rare that ascertainment will be largely limited to heterozygous individuals in outbred populations. Sampling of diverse bottlenecked populations and consanguineous individuals will aid in identification of total “knockouts”. Careful filtering and curation of pLoF variants in a gene of interest is necessary in order to identify true LoF individuals for follow-up, and the positional distribution or frequency of true LoF variants may reveal important disease biology. Our analysis suggests that the value of pLoF variant data for drug discovery lies in deep curation informed by the nature of the drug and its indication, as well as the biology of the gene, followed by recall-by-genotype studies in targeted populations.

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