Evaluation of CoA biosynthesis proteins of Mycobacterium tuberculosis as potential drug targets.

Coenzyme A biosynthesis pathway proteins are potential targets for developing inhibitors against bacteria including Mycobacterium tuberculosis. We have evaluated two enzymes in this pathway: phosphopantetheine adenylyltransferase (CoaD) and dephospho CoA kinase (CoaE) for essentiality and selectivity. Based on the previous transposon mutagenesis studies, coaD had been predicted to be a non-essential gene in M. tuberculosis. Our bioinformatics analysis showed that there is no other functional homolog of this enzyme in M. tuberculosis, which suggests that coaD should be an essential gene. In order to get an unambiguous answer on the essentiality of coaD, we attempted inactivation of coaD in wild type and merodiploid backgrounds. It was found that coaD could only be inactivated in the presence of an additional gene copy, confirming it to be an essential gene. Using a similar approach we found that CoaE was also essential for the survival of M. tuberculosis. RT-PCR analysis showed that both coaD and coaE were transcribed in M. tuberculosis. Amino acids alignment and phylogenetic analysis showed CoaD to be distantly related to the human counterpart while CoaE was found to be relatively similar to the human enzyme. Analysis of CoaD and CoaE structures at molecular level allowed us to identify unique residues in the Mtb proteins, thus providing a selectivity handle. The essentiality and selectivity analysis combined with the published biochemical characterization of CoaD and CoaE makes them suitable targets for developing inhibitors against M. tuberculosis.

Kinetic modelling of GlmU reactions - prioritization of reaction for therapeutic application.

Mycobacterium tuberculosis(Mtu), a successful pathogen, has developed resistance against the existing anti-tubercular drugs necessitating discovery of drugs with novel action. Enzymes involved in peptidoglycan biosynthesis are attractive targets for antibacterial drug discovery. The bifunctional enzyme mycobacterial GlmU (Glucosamine 1-phosphate N-acetyltransferase/ N-acetylglucosamine-1-phosphate uridyltransferase) has been a target enzyme for drug discovery. Its C- and N- terminal domains catalyze acetyltransferase (rxn-1) and uridyltransferase (rxn-2) activities respectively and the final product is involved in peptidoglycan synthesis. However, the bifunctional nature of GlmU poses difficulty in deciding which function to be intervened for therapeutic advantage. Genetic analysis showed this as an essential gene but it is still unclear whether any one or both of the activities are critical for cell survival. Often enzymatic activity with suitable high-throughput assay is chosen for random screening, which may not be the appropriate biological function inhibited for maximal effect. Prediction of rate-limiting function by dynamic network analysis of reactions could be an option to identify the appropriate function. With a view to provide insights into biochemical assays with appropriate activity for inhibitor screening, kinetic modelling studies on GlmU were undertaken. Kinetic model of Mtu GlmU-catalyzed reactions was built based on the available kinetic data on Mtu and deduction from Escherichia coli data. Several model variants were constructed including coupled/decoupled, varying metabolite concentrations and presence/absence of product inhibitions. This study demonstrates that in coupled model at low metabolite concentrations, inhibition of either of the GlmU reactions cause significant decrement in the overall GlmU rate. However at higher metabolite concentrations, rxn-2 showed higher decrement. Moreover, with available intracellular concentration of the metabolites and in vivo variant of model, uncompetitive inhibition of rxn-2 caused highest decrement. Thus, at physiologically relevant metabolite concentrations, targeting uridyltranferase activity of Mtu GlmU would be a better choice for therapeutic intervention.

A kinetic platform for in silico modeling of the metabolic dynamics in Escherichia coli.

BACKGROUND: A prerequisite for a successful design and discovery of an antibacterial drug is the identification of essential targets as well as potent inhibitors that adversely affect the survival of bacteria. In order to understand how intracellular perturbations occur due to inhibition of essential metabolic pathways, we have built, through the use of ordinary differential equations, a mathematical model of 8 major Escherichia coli pathways. RESULTS: Individual in vitro enzyme kinetic parameters published in the literature were used to build the network of pathways in such a way that the flux distribution matched that reported from whole cells. Gene regulation at the transcription level as well as feedback regulation of enzyme activity was incorporated as reported in the literature. The unknown kinetic parameters were estimated by trial and error through simulations by observing network stability. Metabolites, whose biosynthetic pathways were not represented in this platform, were provided at a fixed concentration. Unutilized products were maintained at a fixed concentration by removing excess quantities from the platform. This approach enabled us to achieve steady state levels of all the metabolites in the cell. The output of various simulations correlated well with those previously published. CONCLUSION: Such a virtual platform can be exploited for target identification through assessment of their vulnerability, desirable mode of target enzyme inhibition, and metabolite profiling to ascribe mechanism of action following a specific target inhibition. Vulnerability of targets in the biosynthetic pathway of coenzyme A was evaluated using this platform. In addition, we also report the utility of this platform in understanding the impact of a physiologically relevant carbon source, glucose versus acetate, on metabolite profiles of bacterial pathogens.

A mycobacterial cyclic AMP phosphodiesterase that moonlights as a modifier of cell wall permeability.

Mycobacterium tuberculosis utilizes many mechanisms to establish itself within the macrophage, and bacterially derived cAMP is important in modulating the host cellular response. Although the genome of M. tuberculosis is endowed with a number of mammalian-like adenylyl cyclases, only a single cAMP phosphodiesterase has been identified that can decrease levels of cAMP produced by the bacterium. We present the crystal structure of the full-length and sole cAMP phosphodiesterase, Rv0805, found in M. tuberculosis, whose orthologs are present only in the genomes of slow growing and pathogenic mycobacteria. The dimeric core catalytic domain of Rv0805 adopts a metallophosphoesterase-fold, and the C-terminal region builds the active site and contributes to multiple substrate utilization. Localization of Rv0805 to the cell wall is dependent on its C terminus, and expression of either wild type or mutationally inactivated Rv0805 in M. smegmatis alters cell permeability to hydrophobic cytotoxic compounds. Rv0805 may therefore play a key role in the pathogenicity of mycobacteria, not only by hydrolyzing bacterial cAMP, but also by moonlighting as a protein that can alter cell wall functioning.

Structural models in the assessment of protein druggability based on HTS data.

Insights on the potential of target proteins to bind small molecules with high affinity can be derived from the knowledge of their three-dimensional structural details especially of their binding pockets. The present study uses high-throughput screening (HTS) results on various targets, to obtain mathematical predictive models in which a minimal set of structural parameters significantly contributing to the hit rates or the affinity of the protein binding pockets for small molecular entities, is identified. An emphasis is given to focus on target variation aspect of the data by consideration of commonly tested compounds against the HTS targets. We identify 'four-parameter' models with R (2), [Formula: see text], SEE, and LOO q (2) values of 0.70, 0.60, 0.27 and 0.50, respectively, or better. We demonstrate through cross-validation exercises that our regression models apply well on varied data sets. Thus we can use these models to estimate hit rates for HTS campaigns and thereby assign priority to drug targets before they undergo such resource intense experimental screening and follow-up.

Thermodynamics of binding of 2-methoxy-3-isopropylpyrazine and 2-methoxy-3-isobutylpyrazine to the major urinary protein.

In the present study we examine the thermodynamics of binding of two related pyrazine-derived ligands to the major urinary protein, MUP-I, using a combination of isothermal titration calorimetry (ITC), X-ray crystallography, and NMR backbone (15)N and methyl side-chain (2)H relaxation measurements. Global thermodynamics data derived from ITC indicate that binding is driven by favorable enthalpic contributions, rather than the classical entropy-driven hydrophobic effect. Unfavorable entropic contributions from the protein backbone and side-chain residues in the vicinity of the binding pocket are partially offset by favorable entropic contributions at adjacent positions, suggesting a "conformational relay" mechanism whereby increased rigidity of residues on ligand binding are accompanied by increased conformational freedom of side chains in adjacent positions. The principal driving force governing ligand affinity and specificity can be attributed to solvent-driven enthalpic effects from desolvation of the protein binding pocket.

Methyl side-chain dynamics in proteins using selective enrichment with a single isotopomer.

13C relaxation studies on side-chain methyl groups in proteins typically involve measurements on (13)CHD(2) isotopomers, where the (13)C relaxation mechanism is particularly straightforward in the presence of a single proton. While such isotopomers can be obtained in proteins overexpressed in bacteria by use of (13)C enriched and fractionally deuterated media, invariably all possible (2)H isotopomers are obtained. This results in a loss of both resolution and sensitivity, which becomes particularly severe for larger proteins. We describe an approach that overcomes this problem by chemical synthesis of amino acids containing a pure (13)CHD(2) isotopomer. We illustrate the benefits of this approach in (13)C side-chain relaxation measurements on the mouse major urinary protein selectively enriched with [gamma(1),gamma(2)-(13)C(2),alpha,beta,gamma(1),gamma(1),gamma(2),gamma(2)-(2)H(6)] valine. Relaxation measurements in the absence and presence of pyrazine-derived ligands suggest that valine side-chain dynamics do not contribute significantly to binding entropy.