Brain-specific aminopeptidase: from enkephalinase to protector against neurodegeneration.
ABSTRACT The major breakthrough discovery of enkephalins as endogenous opiates led our attempts to determine their inactivation mechanisms. Because the NH2-terminal tyrosine is absolutely necessary for the neuropeptides to exert analgesic effects, and aminopeptidase activities are extraordinarily high in the brain, a specific "amino-enkephalinase" should exist. Several aminopeptidases were identified in the central nervous system during the search. In fact, our laboratory found two novel neuron-specific aminopeptidases: NAP and NAP-2. NAP is the only functionally active brain-specific enzyme known. Its synaptic location coupled with its limited substrate specificity could constitute a "functional" specificity and contribute to enkephalin-specific functions. In addition, NAP was found to be essential for neuron growth, differentiation, and death. Thus, aminopeptidases are likely important for mental health and neurological diseases. Recently, puromycin-sensitive aminopeptidase (PSA) was identified as a modifier of tau-induced neurodegeneration. Because the enzymatic similarity between PSA and NAP, we believe that the depletion of NAP in Alzheimer's disease (AD) brains plays a causal role in the development of AD pathology. Therefore, use of the puromycin-sensitive neuron-aminopeptidase NAP could provide neuroprotective mechanisms in AD and similar neurodegenerative diseases.
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ABSTRACT: Aminopeptidases represent a class of (zinc) metalloenzymes that catalyze the cleavage of amino acids nearby the N-terminus of polypeptides, resulting in hydrolysis of peptide bonds. Aminopeptidases operate downstream of the ubiquitin-proteasome pathway and are implicated in the final step of intracellular protein degradation either by trimming proteasome-generated peptides for antigen presentation or full hydrolysis into free amino acids for recycling in renewed protein synthesis. This review focuses on the function and subcellular location of five key aminopeptidases (aminopeptidase N, leucine aminopeptidase, puromycin-sensitive aminopeptidase, leukotriene A4 hydrolase and endoplasmic reticulum aminopeptidase 1/2) and their association with different diseases, in particular cancer and their current position as target for therapeutic intervention by aminopeptidase inhibitors. Historically, bestatin was the first prototypical aminopeptidase inhibitor that entered the clinic 35 years ago and is still used for the treatment of lung cancer. More recently, new generation aminopeptidase inhibitors became available, including the aminopeptidase inhibitor prodrug tosedostat, which is currently tested in phase II clinical trials for acute myeloid leukemia. Beyond bestatin and tosedostat, medicinal chemistry has emerged with additional series of potential aminopeptidases inhibitors which are still in an early phase of (pre)clinical investigations. The expanded knowledge of the unique mechanism of action of aminopeptidases has revived interest in aminopeptidase inhibitors for drug combination regimens in anti-cancer treatment. In this context, this review will discuss relevant features and mechanisms of action of aminopeptidases and will also elaborate on factors contributing to aminopeptidase inhibitor efficacy and/or loss of efficacy due to drug resistance-related phenomena. Together, a growing body of data point to aminopeptidase inhibitors as attractive tools for combination chemotherapy, hence their implementation may be a step forward in a new era of personalized treatment of cancer patients.Amino Acids 01/2014; 46(4). · 3.65 Impact Factor
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ABSTRACT: The accumulation of β-amyloid (Aβ) peptide in the brain is one of the pathological hallmarks of Alzheimer's disease and is thought to be of primary aetiological significance. In an unbiased genetic screen, we identified puromycin-sensitive aminopeptidase (PSA) as a potent suppressor of Aβ toxicity in a Drosophila model system. We established that coexpression of Drosophila PSA (dPSA) in the flies' brains improved their lifespan, protected against locomotor deficits, and reduced brain Aβ levels by clearing the Aβ plaque-like deposits. However, confocal microscopy and subcellular fractionation of amyloid-expressing 7PA2 cells demonstrated that PSA localizes to the cytoplasm. Therefore, PSA and Aβ are unlikely to be in the same cellular compartment; moreover, when we artificially placed them in the same compartment in flies, we could not detect a direct epistatic interaction. The consequent hypothesis that PSA's suppression of Aβ toxicity is indirect was supported by the finding that Aβ is not a proteolytic substrate for PSA in vitro. Furthermore, we showed that the enzymatic activity of PSA is not required for rescuing Aβ toxicity in neuronal SH-SY5Y cells. We investigated whether the stimulation of autophagy by PSA was responsible for these protective effects. We found however that PSA's promotion of autophagosome fusion with lysosomes required proteolytic activity and so its effect on autophagy could not be identical to its protection against Aβ toxicity.Biochimica et Biophysica Acta 08/2013; · 4.66 Impact Factor
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ABSTRACT: High-spatial resolution imaging datasets of mammalian brains have recently become available in unprecedented amounts. Images now reveal highly complex patterns of gene expression varying on multiple scales. The challenge in analyzing these images is both in extracting the patterns that are most relevant functionally and in providing a meaningful representation that allows neuroscientists to interpret the extracted patterns. Here, we present FuncISH-a method to learn functional representations of neural in situ hybridization (ISH) images. We represent images using a histogram of local descriptors in several scales, and we use this representation to learn detectors of functional (GO) categories for every image. As a result, each image is represented as a point in a low-dimensional space whose axes correspond to meaningful functional annotations. The resulting representations define similarities between ISH images that can be easily explained by functional categories. We applied our method to the genomic set of mouse neural ISH images available at the Allen Brain Atlas, finding that most neural biological processes can be inferred from spatial expression patterns with high accuracy. Using functional representations, we predict several gene interaction properties, such as protein-protein interactions and cell-type specificity, more accurately than competing methods based on global correlations. We used FuncISH to identify similar expression patterns of GABAergic neuronal markers that were not previously identified and to infer new gene function based on image-image similarities. firstname.lastname@example.org Supplementary data are available at Bioinformatics online.Bioinformatics 07/2013; 29(13):i36-i43. · 4.62 Impact Factor