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In Silico Analysis and In Vitro Characterization of the Bioactive Profile of Three Novel Peptides Identified from 19 kDa α-Zein Sequences of Maize

In this study, we characterized three novel peptides derived from the 19 kDa α-zein, and determined their bioactive profile in vitro and developed a structural model in silico. The peptides, 19ZP1, 19ZP2 and 19ZP3, formed α-helical structures and had positive and negative electrostatic potential sur...

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Detalles Bibliográficos
Autores principales: Díaz-Gómez, Jorge L., Neundorf, Ines, López-Castillo, Laura-Margarita, Castorena-Torres, Fabiola, Serna-Saldívar, Sergio O., García-Lara, Silverio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7699256/
https://www.ncbi.nlm.nih.gov/pubmed/33227894
http://dx.doi.org/10.3390/molecules25225405
Descripción
Sumario:In this study, we characterized three novel peptides derived from the 19 kDa α-zein, and determined their bioactive profile in vitro and developed a structural model in silico. The peptides, 19ZP1, 19ZP2 and 19ZP3, formed α-helical structures and had positive and negative electrostatic potential surfaces (range of −1 to +1). According to the in silico algorithms, the peptides displayed low probabilities for cytotoxicity (≤0.05%), cell penetration (10–33%) and antioxidant activities (9–12.5%). Instead, they displayed a 40% probability for angiotensin-converting enzyme (ACE) inhibitory activity. For in vitro characterization, peptides were synthesized by solid phase synthesis and tested accordingly. We assumed α-helical structures for 19ZP1 and 19ZP2 under hydrophobic conditions. The peptides displayed antioxidant activity and ACE-inhibitory activity, with 19ZP1 being the most active. Our results highlight that the 19 kDa α-zein sequences could be explored as a source of bioactive peptides, and indicate that in silico approaches are useful to predict peptide bioactivities, but more structural analysis is necessary to obtain more accurate data.