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Vilcheze, C. et al. Transfer of a point mutation in Mycobacterium tuberculosis inhA resolves the target of isoniazid. Nature Med. 12, 1027-1029

Albert Einstein College of Medicine, New York, New York, United States
Nature Medicine (Impact Factor: 28.05). 10/2006; 12(9):1027-9. DOI: 10.1038/nm1466
Source: PubMed

ABSTRACT Isoniazid is one of the most effective antituberculosis drugs, yet its precise mechanism of action is still controversial. Using specialized linkage transduction, a single point mutation allele (S94A) within the putative target gene inhA was transferred in Mycobacterium tuberculosis. The inhA(S94A) allele was sufficient to confer clinically relevant levels of resistance to isoniazid killing and inhibition of mycolic acid biosynthesis. This resistance correlated with the decreased binding of the INH-NAD inhibitor to InhA, as shown by enzymatic and X-ray crystallographic analyses, and establishes InhA as the primary target of isoniazid action in M. tuberculosis.

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Available from: Catherine Vilcheze, Nov 26, 2014
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    • "In fact, the most accepted action mechanism of this prodrug requires a conversion of the INH into an acyl radical promoted by the KatG enzyme (Lei et al., 2000). This radical is able to link with NAD + and form a covalent adduct (Vilcheze et al., 2006) potentially capable of inhibiting the FASII enoyl-ACP reductase InhA (Lei et al., 2000; Nguyen et al., 2002; Rawat et al., 2003; Vilcheze et al., 2006). Despite this, the mechanism of action of INH has been related to occurs by other pathways, as the inhibition of nucleic acids (Gangadharam et al., 1963), phospholipids (Brennan et al., 1970) synthesis and NAD + metabolism (Bekierkunst, 1966; Zatman et al., 1954). "
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    ABSTRACT: Despite the resistance developed by the Mycobacterium tuberculosis (MTb) strains, isoniazid (INH) has been recognized as one of the best drug for treatment of Tuberculosis (Tb). The coordination of INH to ruthenium metal centers was investigated as a strategy to enhance the activity of this drug against the sensitive and resistant strains of MTb. The complexes trans-[Ru(NH3)4(L)(INH)](2+) (L = SO2 or NH3) were isolated and their chemical and antituberculosis properties studied. The minimal inhibitory concentration (MIC) data show that [Ru(NH3)5(INH)](2+) was active in both resistant and sensitive strains, whereas free INH (non-coordinated) showed to be active only against the sensitive strain. The coordination of INH to the metal center in both [Ru(NH3)5(INH)](2+) and trans-[Ru(NH3)4(SO2)(INH)](2+) complexes led to a shift in the INH oxidation potential to less positive values compared to free INH. Despite, the ease of oxidation of INH did not lead to an increase in the in vitro INH activity against MTb, it might have provided sensitivity toward resistant strains. Furthermore, ruthenium complexes with chemical structures analogous to those described above were synthesized using the oxidation products of INH as ligands (namely, isonicotinic acid and isonicotinamide). These last compounds were not active against any strains of MTb. Moreover, according to DFT calculations the formation of the acyl radical, a proposed intermediate in the INH oxidation, is favored in the [Ru(NH3)5(INH)](2+) complex by 50.7 kcal.mol(-1) with respect to the free INH. This result suggests that the stabilization of the acyl radical promoted by the metal center would be a more important feature than the oxidation potential of the INH for the antituberculosis activity against resistant strains. Copyright © 2015. Published by Elsevier B.V.
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    • "), (b) INH-NAD from PDB ID: 2NV6 (Vilchèze et al., 2006). The atoms are colored by name: carbon (gray), nitrogen (blue), oxygen (red), hydrogen (white), phosphorus (orange) and chlorine (green). "
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    ABSTRACT: Molecular docking simulations are commonly used to identify and optimize drug candidates by examining the interactions between the target protein and small chemical ligands. This procedure is computationally expensive, especially when the receptor is treated as an ensemble of molecular dynamic conformations, namely the Fully-Flexible Receptor (FFR) model. An FFR model can vary from thousands to millions of conformations. Handling molecular docking experiments on FFR models with flexible ligands still constitutes a big challenge, since it may take hours, days, or even months to be completely executed for a single ligand. Moreover, thousands of molecular docking results are quite hard to be analyzed by a domain expert, who typically explores results starting with FEB and RMSD values. This paper addresses the high computational demand to exhaustively execute molecular docking simulations on FFR models, as well as the problem of accurately selecting a small set of representative docking results to be analyzed by a domain expert. Our approach is twofold: (1) we make use of the wFReDoW environment to decrease the dimension of the FFR model during docking experiments, trying to maintain the quality in the resulting reduced models, and (2) we perform careful analyses on docking results to select a set of representative candidate poses. Our simulation results show that the proposed method is able to achieve a trade-off between accuracy and computational cost. This is evidenced from the accuracy in wFReDoW results, which contain 96% of the snapshots within the set of the 100 best FEB values when only 67% of snapshots from the FFR model were docked.
    Expert Systems with Applications 06/2014; 41(16):7608-7620. DOI:10.1016/j.eswa.2014.05.038 · 1.97 Impact Factor
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    • "Combination therapy became standard and was expanded with the inclusion of isoniazid (INH) in 1952 (BMRC, 1952). The target of isoniazid is InhA, which catalyzes a critical step in the synthesis of mycolic acids that comprise the Mtb cell wall (Vilchèze et al., 2006). Mutations in inhA and the gene encoding the activator of INH, katG, as well as ndh and mshB, cause resistance (Vilchèze et al., 2006; Vilchèze and Jacobs, 2007). "
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    ABSTRACT: Although caused by vastly different pathogens, the world's three most serious infectious diseases, tuberculosis, malaria, and HIV-1 infection, share the common problem of drug resistance. The pace of drug development has been very slow for tuberculosis and malaria and rapid for HIV-1. But for each disease, resistance to most drugs has appeared quickly after the introduction of the drug. Learning how to manage and prevent resistance is a major medical challenge that requires an understanding of the evolutionary dynamics of each pathogen. This Review summarizes the similarities and differences in the evolution of drug resistance for these three pathogens.
    Cell 03/2012; 148(6):1271-83. DOI:10.1016/j.cell.2012.02.021 · 33.12 Impact Factor
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