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Structural studies of phosphoglucose isomerase from Mycobacterium tuberculosis H37Rv.

ABSTRACT: Phosphoglucose isomerase (PGI) plays a key role in both glycolysis and gluconeogenesis inside the cell, whereas outside the cell it exhibits cytokine properties. PGI is also known to act as an autocrine motility factor, a neuroleukin agent and a differentiation and maturation mediator. Here, the first crystal structure of PGI from Mycobacterium tuberculosis H37Rv (Mtb) is reported. The structure was refined at 2.25 A resolution and revealed the presence of one molecule in the asymmetric unit with two globular domains. As known previously, the active site of Mtb PGI contains conserved residues including Glu356, Glu216 and His387 (where His387 is from the neighbouring molecule). The crystal structure of Mtb PGI was observed to be rather more similar to human PGI than other nonbacterial PGIs, with only a few differences being detected in the loops, arm and hook regions of the human and Mtb PGIs, suggesting that the M. tuberculosis enzyme uses the same enzyme mechanism.

SUBMITTER: Anand K

PROVIDER: S-EPMC2864675 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

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Structural studies of phosphoglucose isomerase from Mycobacterium tuberculosis H37Rv.

Anand Kanchan K Mathur Divya D Anant Avishek A Garg Lalit C LC

Acta crystallographica. Section F, Structural biology and crystallization communications 20100429 Pt 5

Phosphoglucose isomerase (PGI) plays a key role in both glycolysis and gluconeogenesis inside the cell, whereas outside the cell it exhibits cytokine properties. PGI is also known to act as an autocrine motility factor, a neuroleukin agent and a differentiation and maturation mediator. Here, the first crystal structure of PGI from Mycobacterium tuberculosis H37Rv (Mtb) is reported. The structure was refined at 2.25 A resolution and revealed the presence of one molecule in the asymmetric unit wit ...[more]

PMID: 20445242

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Project description:BACKGROUND: Mycobacterium 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. RESULTS: This 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. CONCLUSION: In 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/.

Project description:The ability to adapt to different conditions is key for Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), to successfully infect human hosts. Adaptations allow the organism to evade the host immune responses during acute infections and persist for an extended period of time during the latent infectious stage. In latently infected individuals, estimated to include one-third of the human population, the organism exists in a variety of metabolic states, which impedes the development of a simple strategy for controlling or eradicating this disease. Direct knowledge of the metabolic states of M. tuberculosis in patients would aid in the management of the disease as well as in forming the basis for developing new drugs and designing more efficacious drug cocktails. Here, we propose an in silico approach to create state-specific models based on readily available gene expression data. The coupling of differential gene expression data with a metabolic network model allowed us to characterize the metabolic adaptations of M. tuberculosis H37Rv to hypoxia. Given the microarray data for the alterations in gene expression, our model predicted reduced oxygen uptake, ATP production changes, and a global change from an oxidative to a reductive tricarboxylic acid (TCA) program. Alterations in the biomass composition indicated an increase in the cell wall metabolites required for cell-wall growth, as well as heightened accumulation of triacylglycerol in preparation for a low-nutrient, low metabolic activity life style. In contrast, the gene expression program in the deletion mutant of dosR, which encodes the immediate hypoxic response regulator, failed to adapt to low-oxygen stress. Our predictions were compatible with recent experimental observations of M. tuberculosis activity under hypoxic and anaerobic conditions. Importantly, alterations in the flow and accumulation of a particular metabolite were not necessarily directly linked to differential gene expression of the enzymes catalyzing the related metabolic reactions.

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Structural studies of phosphoglucose isomerase from Mycobacterium tuberculosis H37Rv.

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Structural studies of phosphoglucose isomerase from Mycobacterium tuberculosis H37Rv.

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