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Full-fledged proteomic analysis of bioactive wheat amylase inhibitors by a 3-D analytical technique: Identification of new heterodimeric aggregation states. | LitMetric

Wheat proteinaceous alpha-amylase inhibitors (alpha-AIs) are increasingly investigated for their agronomical role as natural defence molecules of plants against the attack of insects and pests, but also for their effects on human health. The wheat genomes code for several bioactive alpha-AIs that share sequence homology, but differ in their specificity against alpha-amylases from different species and for their aggregation states. Wheat alpha-AIs are traditionally classified as belonging to the three classes of tetrameric, homodimeric and monomeric forms, each class being constituted by a number of polypeptides that display different electrophoretic mobilities. Here we describe a proteomic approach for the identification of bioactive alpha-AIs from wheat and, in particular, a 3-D technique that allows to best identify and characterize the dimeric fraction. The technique takes advantage of the thermal resistance of alpha-AIs (resistant to T > 70 degrees C) and consists in the separation of protein mixtures by 2-D polyacrylamide/starch electrophoresis under nondissociating PAGE (ND-PAGE, first dimension) and dissociating (urea-PAGE or U-PAGE second dimension) conditions, followed by in-gel spontaneous reaggregation of protein complexes and identification of the alpha-amylase inhibitory activity (antizymogram, third dimension) using enzymes from human salivary glands and from the larvae of Tenebrio molitor coleopter (yellow mealworm). Dimeric alpha-AIs from Triticum aestivum (bread wheat) were observed to exist as heterodimers. The formation of heterodimeric complexes was also confirmed by in vitro reaggregation assays carried out on RP-HPLC purified wheat dimeric alpha-AIs, and their bioactivity assayed by antizymogram analysis. The present 3-D analytical technique can be exploited for fast, full-fledged identification and characterization of wheat alpha-AIs.

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http://dx.doi.org/10.1002/elps.200600348DOI Listing

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