2009
DOI: 10.1002/jssc.200900339
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Identification of non‐zein proteins in BR473 maize protein bodies by LC‐nanoESI‐MS/MS

Abstract: The nutritional value of maize seed is limited due to its high content of storage proteins (zeins), which are deficient in essential amino acids such as lysine and tryptophan. In a previous paper, we showed that protein bodies obtained from BR473 maize variety, developed by Embrapa (Brazilian Agricultural Research Corporation), were mainly constituted by Z27 and a smaller quantity of Z50 g-zeins. Besides zein proteins, other not identified protein band in the SDS/PAGE was also observed, which could indicate th… Show more

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Cited by 5 publications
(1 citation statement)
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“…Proteomics technologies have made possible a broad survey of all the functional categories of proteins, revealing their differential expression patterns in pathological tissue from various diseases as well as response to treatment [4]. Proteomic analysis coupled with liquid chromatography-nanoelectrospray ionization tandem mass spectrometry (LC-nanoESI-MS/MS) is a well-established technique for peptide sequencing analysis [5]. The objective of this work was to search for potential targets of RMR treatment in MCF-7 breast cancer cells through a proteomic approach using two-dimensional gel electrophoresis and LC-nanoESI-MS/MS for protein identification.…”
Section: Introductionmentioning
confidence: 99%
“…Proteomics technologies have made possible a broad survey of all the functional categories of proteins, revealing their differential expression patterns in pathological tissue from various diseases as well as response to treatment [4]. Proteomic analysis coupled with liquid chromatography-nanoelectrospray ionization tandem mass spectrometry (LC-nanoESI-MS/MS) is a well-established technique for peptide sequencing analysis [5]. The objective of this work was to search for potential targets of RMR treatment in MCF-7 breast cancer cells through a proteomic approach using two-dimensional gel electrophoresis and LC-nanoESI-MS/MS for protein identification.…”
Section: Introductionmentioning
confidence: 99%