Amaranth and quinoa are nutritious grains rich in essential amino acids, vitamins, and phytochemicals. The use of these emergent functional foods is still limited because their proteins are poorly characterized. Here, we compared amaranth and quinoa seeds by profiling their proteins using Osborne and polarity-based extraction methods and evaluating their relative protein content. The Osborne fractions and the two fractions generated by the polarity-based method (hydrophilic and hydrophobic) were quantified and analyzed by 1D-SDS-PAGE in the absence and presence of a reducing agent, as well as by diagonal electrophoresis. In addition, hydrophilic and hydrophobic proteins were analyzed by 2-DE, and the representative spots for each species were identified by LC-MS/MS. Both methods yield similar total protein amounts. The electrophoretic profiles showed differentiated patterns between the two seeds. All the extracts reflect the formation of high-molecular-mass aggregates because of interchain disulfide bonds. Intrachain disulfide bonds were also detected in 2S albumins. A differential behavior in the solubility of 11S globulins was observed across both species, and molecular modelling and molecular dynamics simulations were performed to explain this phenomenon. This study provides valuable insights into the structural differences between amaranth and quinoa proteins, which could help inform decisions about potential food applications. SIGNIFICANCE: This work addresses two main topics: the implementation of alternative methods for characterizing plant proteins and the detailed comparison of the protein profiles of amaranth and quinoa seeds using different electrophoretic approaches. The polarity-based method we propose represents an alternative to reduce sample handling and the number of extracts required for proteome characterization without sacrificing the protein yield. This study generated relevant information on the storage proteins of the two seeds analyzed, primarily 2S albumins, prolamins, and 11S globulins, to inform decision-making on their application in food technology.
Bojórquez-Velázquez et al. (2026) studied this question.