A pro-nociceptive phenotype unmasked in mice lacking fatty-acid amide hydrolase.

Fatty-acid amide hydrolase (FAAH) is the major enzyme responsible for degradation of anandamide, an endocannabinoid. Pharmacological inhibition or genetic deletion of FAAH (FAAH KO) produces antinociception in preclinical pain models that is largely attributed to anandamide-induced activation of cannabinoid receptors. However, FAAH metabolizes a wide range of structurally related, biologically active lipid signaling molecules whose functions remain largely unknown. Some of these endogenous lipids, including anandamide itself, may exert pro-nociceptive effects under certain conditions. In our study, FAAH KO mice exhibited a characteristic analgesic phenotype in the tail flick test and in both formalin and carrageenan models of inflammatory nociception. Nonetheless, intradermal injection of the transient receptor potential channel V1 (TRPV1) agonist capsaicin increased nocifensive behavior as well as mechanical and heat hypersensitivity in FAAH KO relative to wild-type mice. This pro-nociceptive phenotype was accompanied by increases in capsaicin-evoked Fos-like immunoreactive (FLI) cells in spinal dorsal horn regions implicated in nociceptive processing and was attenuated by CB1 (AM251) and TRPV1 (AMG9810) antagonists. When central sensitization was established, FAAH KO mice displayed elevated levels of anandamide, other fatty-acid amides, and endogenous TRPV1 agonists in both paw skin and lumbar spinal cord relative to wild-type mice. Capsaicin decreased spinal cord 2-AG levels and increased arachidonic acid and prostaglandin E2 levels in both spinal cord and paw skin irrespective of genotype. Our studies identify a previously unrecognized pro-nociceptive phenotype in FAAH KO mice that was unmasked by capsaicin challenge. The heightened nociceptive response was mediated by CB1 and TRPV1 receptors and accompanied by enhanced spinal neuronal activation. Moreover, genetic deletion of FAAH has a profound impact on the peripheral and central lipidome. Thus, genetic deletion of FAAH may predispose animals to increased sensitivity to certain types of pain. More work is necessary to determine whether such changes could explain the lack of efficacy of FAAH inhibitors in clinical trials.

Broad impact of deleting endogenous cannabinoid hydrolyzing enzymes and the CB1 cannabinoid receptor on the endogenous cannabinoid-related lipidome in eight regions of the mouse brain.

BACKGROUND AND PURPOSE: The enzymes fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL) hydrolyze endogenous cannabinoids (eCBs), N-arachidonoyl ethanolamine (AEA) and 2-arachidonoyl glycerol (2-AG), respectively. These enzymes also metabolize eCB analogs such as lipoamines and 2-acyl glycerols, most of which are not ligands at CB1. To test the hypothesis that deleting eCB hydrolyzing enzymes and CB1 shifts lipid metabolism more broadly and impacts more families of eCB structural analogs, targeted lipidomics analyses were performed on FAAH KO, MAGL KO, and CB1 KO mice and compared to WT controls in 8 brain regions. EXPERIMENTAL APPROACH: Methanolic extracts of discrete brain regions (brainstem, cerebellum, cortex, hippocampus, hypothalamus, midbrain, striatum and thalamus) were partially purified on C-18 solid-phase extraction columns. Over 70 lipids per sample were then analyzed with HPLC/MS/MS. KEY RESULTS: AEA and 2-AG were unaffected throughout the brain in CB1 KO mice; however, there was an increase in the arachidonic acid (AA) metabolite, PGE2 in the majority of brain areas. By contrast, PGE2 and AA levels were significantly reduced throughout the brain in the MAGL KO corresponding to significant increases in 2-AG. No changes in AA or PGE2 were seen throughout in the FAAH KO brain, despite significant increases in AEA, suggesting AA liberated by FAAH does not contribute to steady state levels of AA or PGE2. Changes in the lipidome were not confined to the AA derivatives and showed regional variation in each of the eCB KO models. CONCLUSIONS AND IMPLICATIONS: AEA and 2-AG hydrolyzing enzymes and the CB1 receptor link the eCB system to broader lipid signaling networks in contrasting ways, potentially altering neurotransmission and behavior independently of cannabinoid receptor signaling.

The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens.

Screens using high-throughput, information-rich technologies such as microarrays, high-content screening (HCS), and next-generation sequencing (NGS) have become increasingly widespread. Compared with single-readout assays, these methods produce a more comprehensive picture of the effects of screened treatments. However, interpreting such multidimensional readouts is challenging. Univariate statistics such as t-tests and Z-factors cannot easily be applied to multidimensional profiles, leaving no obvious way to answer common screening questions such as "Is treatment X active in this assay?" and "Is treatment X different from (or equivalent to) treatment Y?" We have developed a simple, straightforward metric, the multidimensional perturbation value (mp-value), which can be used to answer these questions. Here, we demonstrate application of the mp-value to three data sets: a multiplexed gene expression screen of compounds and genomic reagents, a microarray-based gene expression screen of compounds, and an HCS compound screen. In all data sets, active treatments were successfully identified using the mp-value, and simulations and follow-up analyses supported the mp-value's statistical and biological validity. We believe the mp-value represents a promising way to simplify the analysis of multidimensional data while taking full advantage of its richness.

Determination of minimal transcriptional signatures of compounds for target prediction.

The identification of molecular target and mechanism of action of compounds is a key hurdle in drug discovery. Multiplexed techniques for bead-based expression profiling allow the measurement of transcriptional signatures of compound-treated cells in high-throughput mode. Such profiles can be used to gain insight into compounds' mode of action and the protein targets they are modulating. Through the proxy of target prediction from such gene signatures we explored important aspects of the use of transcriptional profiles to capture biological variability of perturbed cellular assays. We found that signatures derived from expression data and signatures derived from biological interaction networks performed equally well, and we showed that gene signatures can be optimised using a genetic algorithm. Gene signatures of approximately 128 genes seemed to be most generic, capturing a maximum of the perturbation inflicted on cells through compound treatment. Moreover, we found evidence for oxidative phosphorylation to be one of the most general ways to capture compound perturbation.

Computational methods for early predictive safety assessment from biological and chemical data.

INTRODUCTION: The goal of early predictive safety assessment (PSA) is to keep compounds with detectable liabilities from progressing further in the pipeline. Such compounds jeopardize the core of pharmaceutical research and development and limit the timely delivery of innovative therapeutics to the patient. Computational methods are increasingly used to help understand observed data, generate new testable hypotheses of relevance to safety pharmacology, and supplement and replace costly and time-consuming experimental procedures. AREAS COVERED: The authors survey methods operating on different scales of both physical extension and complexity. After discussing methods used to predict liabilities associated with structures of individual compounds, the article reviews the use of adverse event data and safety profiling panels. Finally, the authors examine the complexities of toxicology data from animal experiments and how these data can be mined. EXPERT OPINION: A significant obstacle for data-driven safety assessment is the absence of integrated data sets due to a lack of sharing of data and of using standard ontologies for data relevant to safety assessment. Informed decisions to derive focused sets of compounds can help to avoid compound liabilities in screening campaigns, and improved hit assessment of such campaigns can benefit the early termination of undesirable compounds.

The discodermolide hairpin structure flows from conformationally stable modular motifs.

(+)-Discodermolide (DDM), a polyketide macrolide from marine sponge, is a potent microtubule assembly promoter. Reported solid-state, solution, and protein-bound DDM conformations reveal the unusual result that a common hairpin conformational motif exists in all three microenvironments. No other flexible microtubule binding agent exhibits such constancy of conformation. In the present study, we combine force-field conformational searches with NMR deconvolution in different solvents to compare DDM conformers with those observed in other environments. While several conformational families are perceived, the hairpin form dominates. The stability of this motif is dictated primarily by steric factors arising from repeated modular segments in DDM composed of the C(Me)-CHX-C(Me) fragment. Furthermore, docking protocols were utilized to probe the DDM binding mode in beta-tubulin. A previously suggested pose is substantiated (Pose-1), while an alternative (Pose-2) has been identified. SAR analysis for DDM analogues differentiates the two poses and suggests that Pose-2 is better able to accommodate the biodata.

Conformations of laulimalide in DMSO-d6.

Laulimalide is one of the newest naturally occurring macrolides known to act as a microtubule stabilizing agent with properties similar to Taxol. It also stands as being one of the most flexible with 18 rotatable bonds. This large number of rotatable bonds allows for approximately 3(18) potential conformers. To examine the conformational energy surface of laulimalide, we have performed an NAMFIS deconvolution analysis for laulimalide in DMSO-d6. The latter has been supplemented with a post-NAMFIS energy analysis at the Becke3LYP/6-31G level that examines the opposing effects of internal hydrogen bonding and syn-pentane interactions. In this way, we have identified 15 laulimalide conformations that can be classified into 5 different families: Supine, Convex, Cobra, Stretch, and Concave motifs.

The binding mode of epothilone A on alpha,beta-tubulin by electron crystallography.

The structure of epothilone A, bound to alpha,beta-tubulin in zinc-stabilized sheets, was determined by a combination of electron crystallography at 2.89 angstrom resolution and nuclear magnetic resonance-based conformational analysis. The complex explains both the broad-based epothilone structure-activity relationship and the known mutational resistance profile. Comparison with Taxol shows that the longstanding expectation of a common pharmacophore is not met, because each ligand exploits the tubulin-binding pocket in a unique and independent manner.