Virtual fragment screening for novel inhibitors of 6-phosphogluconate dehydrogenase

Structure of Leishmania donovani 6-Phosphogluconate Dehydrogenase and Inhibition by Phosphine Gold(I) Complexes: A Potential Approach to Leishmaniasis Treatment

As unicellular parasites are highly dependent on NADPH as a source for reducing equivalents, the main NADPH-producing enzymes glucose 6-phosphate dehydrogenase (G6PD) and 6-phosphogluconate dehydrogenase (6PGD) of the pentose phosphate pathway are considered promising antitrypanosomatid drug targets. Here we present the biochemical characterization and crystal structure of Leishmania donovani 6PGD (Ld6PGD) in complex with NADP(H). Most interestingly, a previously unknown conformation of NADPH is visible in this structure. In addition, we identified auranofin and other gold(I)-containing compounds as efficient Ld6PGD inhibitors, although it has so far been assumed that trypanothione reductase is the sole target of auranofin in Kinetoplastida. Interestingly, 6PGD from Plasmodium falciparum is also inhibited at lower micromolar concentrations, whereas human 6PGD is not. Mode-of-inhibition studies indicate that auranofin competes with 6PG for its binding site followed by a rapid irreversible inhibition. By analogy with other enzymes, this suggests that the gold moiety is responsible for the observed inhibition. Taken together, we identified gold(I)-containing compounds as an interesting class of inhibitors against 6PGDs from Leishmania and possibly from other protozoan parasites. Together with the three-dimensional crystal structure, this provides a valid basis for further drug discovery approaches.

6-Phosphogluconate dehydrogenase and its crystal structures

6-Phosphogluconate dehydrogenase (6PGDH; EC 1.1.1.44) catalyses the oxidative decarboxylation of 6-phosphogluconate to ribulose 5-phosphate in the context of the oxidative part of the pentose phosphate pathway. Depending on the species, it can be a homodimer or a homotetramer. Oligomerization plays a functional role not only because the active site is at the interface between subunits but also due to the interlocking tail-modulating activity, similar to that of isocitrate dehydrogenase and malic enzyme, which catalyse a similar type of reaction. Since the pioneering crystal structure of sheep liver 6PGDH, which allowed motifs common to the β-hydroxyacid dehydrogenase superfamily to be recognized, several other 6PGDH crystal structures have been solved, including those of ternary complexes. These showed that more than one conformation exists, as had been suggested for many years from enzyme studies in solution. It is inferred that an asymmetrical conformation with a rearrangement of one of the two subunits underlies the homotropic cooperativity. There has been particular interest in the presence or absence of sulfate during crystallization. This might be related to the fact that this ion, which is a competitive inhibitor that binds in the active site, can induce the same 6PGDH configuration as in the complexes with physiological ligands. Mutagenesis, inhibitors, kinetic and binding studies, post-translational modifications and research on the enzyme in cancer cells have been complementary to the crystallographic studies. Computational modelling and new structural studies will probably help to refine the understanding of the functioning of this enzyme, which represents a promising therapeutic target in immunity, cancer and infective diseases. 6PGDH also has applied-science potential as a biosensor or a biobattery. To this end, the enzyme has been efficiently immobilized on specific polymers and nanoparticles. This review spans the 6PGDH literature and all of the 6PGDH crystal structure data files held by the Protein Data Bank.

Computational approaches for drug discovery against trypanosomatid-caused diseases

During three decades, only about 20 new drugs have been developed for malaria, tuberculosis and all neglected tropical diseases (NTDs). This critical situation was reached because NTDs represent only 10% of health research investments; however, they comprise about 90% of the global disease burden. Computational simulations applied in virtual screening (VS) strategies are very efficient tools to identify pharmacologically active compounds or new indications for drugs already administered for other diseases. One of the advantages of this approach is the low time-consuming and low-budget first stage, which filters for testing experimentally a group of candidate compounds with high chances of binding to the target and present trypanocidal activity. In this work, we review the most common VS strategies that have been used for the identification of new drugs with special emphasis on those applied to trypanosomiasis and leishmaniasis. Computational simulations based on the selected protein targets or their ligands are explained, including the method selection criteria, examples of successful VS campaigns applied to NTDs, a list of validated molecular targets for drug development and repositioned drugs for trypanosomatid-caused diseases. Thereby, here we present the state-of-the-art of VS and drug repurposing to conclude pointing out the future perspectives in the field.

NADPH Producing Enzymes as Promising Drug Targets for Chagas Disease

Reduced Nicotinamide Adenine Dinucleotide Phosphate (NADPH) is a cofactor used in different anabolic reactions, such as lipid and nucleic acid synthesis, and for oxidative stress defense. NADPH is essential for parasite growth and viability. In trypanosomatid parasites, NADPH is supplied by the oxidative branch of the pentose phosphate pathway and by enzymes associated with the citric acid cycle. The present article will review recent achievements that suggest glucose-6-phosphate dehydrogenase and the cytosolic isoform of the malic enzyme as promising drug targets for the discovery of new drugs against Trypanosoma cruzi and T. brucei. Topics involving an alternative strategy in accelerating T. cruzi drug-target validation and the concept of drug-target classification will also be revisited.

Fragment-based drug discovery as alternative strategy to the drug development for neglected diseases

Neglected diseases (NDs) affect large populations and almost whole continents, representing 12% of the global health burden. In contrast, the treatment available today is limited and sometimes ineffective. Under this scenery, the Fragment-Based Drug Discovery emerged as one of the most promising alternatives to the traditional methods of drug development. This method allows achieving new lead compounds with smaller size of fragment libraries. Even with the wide Fragment-Based Drug Discovery success resulting in new effective therapeutic agents against different diseases, until this moment few studies have been applied this approach for NDs area. In this article, we discuss the basic Fragment-Based Drug Discovery process, brief successful ideas of general applications and show a landscape of its use in NDs, encouraging the implementation of this strategy as an interesting way to optimize the development of new drugs to NDs.

Evaluation of Antigens for Development of a Serological Test for Human African Trypanosomiasis

Background

Control and elimination of human African trypanosomiasis (HAT) can be accelerated through the use of diagnostic tests that are more accurate and easier to deploy. The goal of this work was to evaluate the immuno-reactivity of antigens and identify candidates to be considered for development of a simple serological test for the detection of Trypanosoma brucei gambiense or T. b. rhodesiense infections, ideally both.

Methodology/Principal Findings

The reactivity of 35 antigens was independently evaluated by slot blot and ELISA against sera from both T. b. gambiense and T. b. rhodesiense infected patients and controls. The antigens that were most reactive by both tests to T. b. gambiense sera were the membrane proteins VSG LiTat 1.3, VSG LiTat 1.5 and ISG64. Reactivity to T. b. rhodesiense sera was highest with VSG LiTat 1.3, VSG LiTat 1.5 and SRA, although much lower than with T. b. gambiense samples. The reactivity of all possible combinations of antigens was also calculated. When the slot blot results of 2 antigens were paired, a VSG LiTat 1.3- ISG75 combination performed best on T. b. gambiense sera, while a VSG LiTat 1.3-VSG LiTat 1.5 combination was the most reactive using ELISA. A combination of SRA and either VSG LiTat 1.3 or VSG LiTat 1.5 had the highest reactivity on T. b. rhodesiense sera according to slot blot, while in ELISA, pairing SRA with either GM6 or VSG LiTat 1.3 yielded the best results.

Conclusions

This study identified antigens that were highly reactive to T. b. gambiense sera, which could be considered for developing a serological test for gambiense HAT, either individually or in combination. Antigens with potential for inclusion in a test for T. b. rhodesiense HAT were also identified, but because their reactivity was comparatively lower, a search for additional antigens would be required before developing a test for this form of the disease.

Proteome scale comparative modeling for conserved drug and vaccine targets identification in Corynebacterium pseudotuberculosis

Corynebacterium pseudotuberculosis (Cp) is a pathogenic bacterium that causes caseous lymphadenitis (CLA), ulcerative lymphangitis, mastitis, and edematous to a broad spectrum of hosts, including ruminants, thereby threatening economic and dairy industries worldwide. Currently there is no effective drug or vaccine available against Cp. To identify new targets, we adopted a novel integrative strategy, which began with the prediction of the modelome (tridimensional protein structures for the proteome of an organism, generated through comparative modeling) for 15 previously sequenced C. pseudotuberculosis strains. This pan-modelomics approach identified a set of 331 conserved proteins having 95-100% intra-species sequence similarity. Next, we combined subtractive proteomics and modelomics to reveal a set of 10 Cp proteins, which may be essential for the bacteria. Of these, 4 proteins (tcsR, mtrA, nrdI, and ispH) were essential and non-host homologs (considering man, horse, cow and sheep as hosts) and satisfied all criteria of being putative targets. Additionally, we subjected these 4 proteins to virtual screening of a drug-like compound library. In all cases, molecules predicted to form favorable interactions and which showed high complementarity to the target were found among the top ranking compounds. The remaining 6 essential proteins (adk, gapA, glyA, fumC, gnd, and aspA) have homologs in the host proteomes. Their active site cavities were compared to the respective cavities in host proteins. We propose that some of these proteins can be selectively targeted using structure-based drug design approaches (SBDD). Our results facilitate the selection of C. pseudotuberculosis putative proteins for developing broad-spectrum novel drugs and vaccines. A few of the targets identified here have been validated in other microorganisms, suggesting that our modelome strategy is effective and can also be applicable to other pathogens.

Structure- and ligand-based drug design approaches for neglected tropical diseases

Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein–ligand interactions. Structure- (SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.

IspE inhibitors identified by a combination of in silico and in vitro high-throughput screening

CDP-ME kinase (IspE) contributes to the non-mevalonate or deoxy-xylulose phosphate (DOXP) pathway for isoprenoid precursor biosynthesis found in many species of bacteria and apicomplexan parasites. IspE has been shown to be essential by genetic methods and since it is absent from humans it constitutes a promising target for antimicrobial drug development. Using in silico screening directed against the substrate binding site and in vitro high-throughput screening directed against both, the substrate and co-factor binding sites, non-substrate-like IspE inhibitors have been discovered and structure-activity relationships were derived. The best inhibitors in each series have high ligand efficiencies and favourable physico-chemical properties rendering them promising starting points for drug discovery. Putative binding modes of the ligands were suggested which are consistent with established structure-activity relationships. The applied screening methods were complementary in discovering hit compounds, and a comparison of both approaches highlights their strengths and weaknesses. It is noteworthy that compounds identified by virtual screening methods provided the controls for the biochemical screens.

Discovery of novel histamine H4 and serotonin transporter ligands using the topological feature tree descriptor

Ligand-based approaches are particularly important in the hit identification process of drug discovery when no structural information on the target is available. Pharmacophore descriptors that use a topological representation of the ligands are usually fast enough to screen large compound libraries effectively when seeking novel lead candidates. One example of this kind is the Feature Tree descriptor, a reduced graph representation implemented in the FTrees software. In this study, we tested the screening efficiency of FTrees by both retrospective and prospective screens using known histamine H4 antagonists and serotonin transporter (SERT) inhibitors as query molecules. Our results demonstrate that FTrees can effectively find actives. Particularly when combined with a subsequent 2D fingerprint-based diversity selection, FTrees was found to be extremely effective at discovering a diverse set of scaffolds. Prospective screening of our in-house compound deck provided several novel H4 and SERT ligands that could serve as suitable starting points for further optimization.

Novel lipophilic acetohydroxamic acid derivatives based on conformationally constrained spiro carbocyclic 2,6-diketopiperazine scaffolds with potent trypanocidal activity

We describe novel acetohydroxamic acid derivatives with potent activity against cultured bloodstream-form Trypanosoma brucei and selectivity indices of >1000. These analogues were derived from conformationally constrained, lipophilic, spiro carbocyclic 2,6-diketopiperazine (2,6-DKP) scaffolds by attaching acetohydroxamic acid moieties to the imidic nitrogen. Optimal activity was achieved by placing benzyl groups adjacent to the basic nitrogen of the 2,6-DKP core. S-Enantiomer 7d was the most active derivative against T. brucei (IC(50) = 6.8 nM) and T. cruzi (IC(50) = 0.21 μM).

Fragment-based approaches and computer-aided drug discovery

Fragment-based design has significantly modified drug discovery strategies and paradigms in the last decade. Besides technological advances and novel therapeutic avenues, one of the most significant changes brought by this new discipline has occurred in the minds of drug designers. Fragment-based approaches have markedly impacted rational computer-aided design both in method development and in applications. The present review illustrates the importance of molecular fragments in many aspects of rational ligand design, and discusses how thinking in "fragment space" has boosted computational biology and chemistry.