Purinergic ligands induce extracellular acidification and increased ATP turnover in HepG2 cells.

Nucleosides and nucleotides at µM concentrations stimulated a 300% increase in acid secretion in HepG2 cells, which was quantitatively accounted for as increased export of lactate generated by glycogenolysis. Agonist selectivity encompassed nucleosides and nucleotides for all 5 natural nucleobases and, along with antagonist profiles, was inconsistent with a role for purinergic receptors in mediating this activity. Agonist catabolism did not contribute significantly to either low selectivity or lactate production. Lactate production was driven by an increase in ATP turnover of as much as 56%. For some agonists, especially adenosine, ATP turnover decreased precipitously at mM concentrations, correlating with known adenosine-stimulated apoptosis. We propose that nucleoside/nucleotide agonists induce a futile energy cycle via a novel mechanism, which results in increased ATP turnover and initiates a continuum of events that for some agonists culminates in apoptosis.

Mathermycin, an anti-cancer molecule that targets cell surface phospholipids.

Mathermycin, a lantipeptide isolated from marine actinomycete Marinactinospora thermotolerans, is an antibiotic that has been shown to disrupt bacterial plasma membrane. We now provide evidences that mathermycin can also disrupt cancer, but not normal, cell plasma membranes through targeting phosphatidylethanolamine (PE), which is located only in the inner leaflet of the plasma membrane in normal cells but in both the inner and outer leaflets of the membrane in tumor cells. Our data shows that mathermycin inhibits the metabolic activity and induces mainly necrotic death of all cancer cell lines with EC50 between 4.2 and 16.9 µM, while normal cell lines have EC50 between 113 and 129 µM. The cytotoxicity of mathermycin could be inhibited by exogenous PE, but not phosphoserine and phosphocholine. The formation of mathermycin-PE complexes was confirmed by in silico analysis, HPLC and MS spectrometer. Furthermore, mathermycin exhibited similar cytotoxicity toward cancer and multidrug resistant cancer cells, which could be due to its ability to inhibit mitochondrial function, as shown by our data from the Seahorse™ metabolic analyzer. This study demonstrates that mathermycin is a potentially effective class of anti-tumor chemotherapeutics that do not easily develop resistance due to a mechanism of action targeting PE.

Oligomycin-induced proton uncoupling.

Oligomycin is a classical mitochondrial reagent that binds to the proton channel on the Fo component of ATP synthase. As a result, oligomycin blocks mitochondrial ATP synthesis, proton translocation, and O2 uptake. Here we show that oligomycin induces proton uncoupling subsequent to inhibition of ATP synthesis, as evidenced by recovery of O2 uptake to near baseline levels. Uncoupling is uniquely rapid and readily observed in HepG2 cells but is also observed at longer times in the unrelated H1299 cell line. Proton fluxes plateau at oligomycin concentrations in the region 0.25-5 µM. At the plateau, fluxes are lower than expected for the classical mitochondrial permeability transition pore, although in H1229 cells, fluxes increase to levels consistent with pore opening at higher oligomycin concentrations. Uncoupling is observed in cells metabolizing either pyruvate or lactate and reversed by addition of glucose to restore ATP synthesis. Uncoupling is not sensitive to cyclosporin A and is not reversed by the ANT inhibitor bongkrekic acid. However, bongkrekic acid inhibits uncoupling if added before oligomycin, which we interpret in terms of maintenance of mitochondrial ATP levels.

Reducing Glucokinase Activity Restores Endogenous Pulsatility and Enhances Insulin Secretion in Islets From db/db Mice.

An early sign of islet failure in type 2 diabetes (T2D) is the loss of normal patterns of pulsatile insulin release. Disruptions in pulsatility are associated with a left shift in glucose sensing that can cause excessive insulin release in low glucose (relative hyperinsulinemia, a hallmark of early T2D) and ß-cell exhaustion, leading to inadequate insulin release during hyperglycemia. Our hypothesis was that reducing excessive glucokinase activity in diabetic islets would improve their function. Isolated mouse islets were exposed to glucose and varying concentrations of the glucokinase inhibitor d-mannoheptulose (MH) to examine changes in intracellular calcium ([Ca2+]i) and insulin secretion. Acutely exposing islets from control CD-1 mice to MH in high glucose (20 mM) dose dependently reduced the size of [Ca2+]i oscillations detected by fura-2 acetoxymethyl. Glucokinase activation in low glucose (3 mM) had the opposite effect. We then treated islets from male and female db/db mice (age, 4 to 8 weeks) and heterozygous controls overnight with 0 to 10 mM MH to determine that 1 mM MH produced optimal oscillations. We then used 1 mM MH overnight to measure [Ca2+]i and insulin simultaneously in db/db islets. MH restored oscillations and increased insulin secretion. Insulin secretion rates correlated with MH-induced increases in amplitude of [Ca2+]i oscillations (R2 = 0.57, P < 0.01, n = 10) but not with mean [Ca2+]i levels in islets (R2 = 0.05, not significant). Our findings show that correcting glucose sensing can restore proper pulsatility to diabetic islets and improved pulsatility correlates with enhanced insulin secretion.

SEURAT-1 liver gold reference compounds: a mechanism-based review.

There is an urgent need for the development of alternative methods to replace animal testing for the prediction of repeat dose chemical toxicity. To address this need, the European Commission and Cosmetics Europe have jointly funded a research program for 'Safety Evaluation Ultimately Replacing Animal Testing.' The goal of this program was the development of in vitro cellular systems and associated computational capabilities for the prediction of hepatic, cardiac, renal, neuronal, muscle, and skin toxicities. An essential component of this effort is the choice of appropriate reference compounds that can be used in the development and validation of assays. In this review, we focus on the selection of reference compounds for liver pathologies in the broad categories of cytotoxicity and lipid disorders. Mitochondrial impairment, oxidative stress, and apoptosis are considered under the category of cytotoxicity, while steatosis, cholestasis, and phospholipidosis are considered under the category of lipid dysregulation. We focused on four compound classes capable of initiating such events, i.e., chemically reactive compounds, compounds with specific cellular targets, compounds that modulate lipid regulatory networks, and compounds that disrupt the plasma membrane. We describe the molecular mechanisms of these compounds and the cellular response networks which they elicit. This information will be helpful to both improve our understanding of mode of action and help in the selection of appropriate mechanistic biomarkers, allowing us to progress the development of animal-free models with improved predictivity to the human situation.

Transplant-insert-constrain-relax-assemble (TICRA): protein-ligand complex structure modeling and application to kinases.

We introduce TICRA (transplant-insert-constrain-relax-assemble), a method for modeling the structure of unknown protein-ligand complexes using the X-ray crystal structures of homologous proteins and ligands with known activity. We present results from modeling the structures of protein kinase-inhibitor complexes using p38 and Lck as examples. These examples show that the TICRA method may be used prospectively to create and refine models for protein kinase-inhibitor complexes with an overall backbone rmsd of less than 0.75 Å for the kinase domain, when compared to published X-ray crystal structures. Further refinement of the models of the kinase domains of p38 and Lck in complex with their cognate ligands from the published crystal structures was able to improve the rmsd's of the model complexes to below 0.5 Å. Our results show that TICRA is a useful approach to the problem of structure-based drug design in cases where little structural information is available for the target proteins and the binding mode of active compounds is unknown.

Fragment-based prediction of the clinical occurrence of long QT syndrome and torsade de pointes.

We present a study directly linking clinically observed adverse events to molecular structure. The method is applied to predict the long QT syndrome (LQS) and the resulting condition torsade de pointes (TdP) that can lead to sudden death. The predictive models are created by correlating biochemically significant chemical substructures, derived from a database of marketed drugs, to reports of adverse events in the FDA adverse event reporting system, which contains all events reported to the FDA since 1997. We compute the reporting ratio for each drug/event combination and perform a chi(2) test to determine whether there is a statistically significant association of each drug to reports of LQS and TdP. Linear models are then used to identify chemical substructures that are most consistently associated with the adverse event. The results for LQS and TdP are compared to models for LQS based on human ether-a-go-go-related gene binding and tested for statistical significance by comparing to models created with a randomized dependent variable. The ability to identify compounds associated with LQS and TdP is approximately five times improved in comparison to models based on randomized data, suggesting that there is a significant relationship between specific chemical structures and these adverse events.

Fragment-based computation of binding free energies by systematic sampling.

A fragment-based method for computing protein-ligand binding free energies by systematic sampling has been developed. Systematic sampling of fragment-protein interactions in translational and rotational space is followed by de novo assembly of fragments into molecules and computation of binding free energies for the molecules with statistical mechanics. The rigorous sampling provides independence from the choice of initial binding pose and assembling fragments enables evaluation of binding of a large number of molecule poses with relatively little computation. The method allows a full sampling of possible conformations and avoids the "conformational focusing" problem associated with free energy methods that sample only limited conformational and orientation changes from a starting pose. The direct computation of the entropy loss upon assembling fragments into molecules is an innovation for fragment-based methods. The computed binding free energies are compared to calorimetric data for a series of ligands for the T4 lysozyme L99A mutant and binding constants for a series of p38 MAP kinase ligands. In both cases, the standard error of prediction is close to 1 kcal/mol.

Grand canonical free-energy calculations of protein-ligand binding.

The principles behind the computation of protein-ligand binding free energies by Monte Carlo simulation in the Grand Canonical Ensemble are described in detail, and two variations of the calculation are presented. The computation can be performed by bathing a protein binding site either with ligand images that interact with each other or with ligand images that pass through each other. The second method is theoretically more rigorous, but we show that both methods lead to the same result, and there are distinct numeric advantages to using ligand images that interact with each other. The Grand Canonical simulation provides gas-phase binding free energies that can be converted to aqueous energies by generalized Born-surface area (GB/SA) solvation calculations to provide values that agree with experiment within +/-1.5 kcal/mol. However, the accuracy of these simple solvation calculations is a major limiting factor in the accuracy of the overall binding free-energy computation. The Grand Canonical simulation has several characteristics beneficial to free-energy calculations. One is that the number of parameters that must be set for the simulation is small and can be determined objectively, making the outcome more deterministic, with respect to choice of input conditions, as compared to perturbation methods. Second, the simulation is free from assumptions about the starting pose or nature of the binding site. A final benefit is that binding free energies are a direct outcome of the simulation, and little processing is required to determine them.