TY - JOUR
T1 - Clustering and cross-linking of the wheat storage protein α-gliadin
T2 - A combined experimental and theoretical approach
AU - Markgren, Joel
AU - Rasheed, Faiza
AU - Hedenqvist, Mikael S.
AU - Skepö, Marie
AU - Johansson, Eva
PY - 2022
Y1 - 2022
N2 - Our aim was to understand mechanisms for clustering and cross-linking of gliadins, a wheat seed storage protein type, monomeric in native state, but incorporated in network while processed. The mechanisms were studied utilizing spectroscopy and high-performance liquid chromatography on a gliadin-rich fraction, in vitro produced α-gliadins, and synthetic gliadin peptides, and by coarse-grained modelling, Monte Carlo simulations and prediction algorithms. In solution, gliadins with α-helix structures (dip at 205 nm in CD) were primarily present as monomeric molecules and clusters of gliadins (peaks at 650- and 700-s on SE-HPLC). At drying, large polymers (Rg 90.3 nm by DLS) were formed and β-sheets increased (14% by FTIR). Trained algorithms predicted aggregation areas at amino acids 115–140, 150–179, and 250–268, and induction of liquid-liquid phase separation at P- and Poly-Q-sequences (Score = 1). Simulations showed that gliadins formed polymers by tail-to-tail or a hydrophobic core (Kratky plots and Ree = 35 and 60 for C- and N-terminal). Thus, the N-terminal formed clusters while the C-terminal formed aggregates by disulphide and lanthionine bonds, with favoured hydrophobic clustering of similar/exact peptide sections (synthetic peptide mixtures on SE-HPLC). Mechanisms of clustering and cross-linking of the gliadins presented here, contribute ability to tailor processing results, using these proteins.
AB - Our aim was to understand mechanisms for clustering and cross-linking of gliadins, a wheat seed storage protein type, monomeric in native state, but incorporated in network while processed. The mechanisms were studied utilizing spectroscopy and high-performance liquid chromatography on a gliadin-rich fraction, in vitro produced α-gliadins, and synthetic gliadin peptides, and by coarse-grained modelling, Monte Carlo simulations and prediction algorithms. In solution, gliadins with α-helix structures (dip at 205 nm in CD) were primarily present as monomeric molecules and clusters of gliadins (peaks at 650- and 700-s on SE-HPLC). At drying, large polymers (Rg 90.3 nm by DLS) were formed and β-sheets increased (14% by FTIR). Trained algorithms predicted aggregation areas at amino acids 115–140, 150–179, and 250–268, and induction of liquid-liquid phase separation at P- and Poly-Q-sequences (Score = 1). Simulations showed that gliadins formed polymers by tail-to-tail or a hydrophobic core (Kratky plots and Ree = 35 and 60 for C- and N-terminal). Thus, the N-terminal formed clusters while the C-terminal formed aggregates by disulphide and lanthionine bonds, with favoured hydrophobic clustering of similar/exact peptide sections (synthetic peptide mixtures on SE-HPLC). Mechanisms of clustering and cross-linking of the gliadins presented here, contribute ability to tailor processing results, using these proteins.
KW - Disulphide bonds
KW - Monte Carlo simulations
KW - Polymers
KW - Synthetic peptides
U2 - 10.1016/j.ijbiomac.2022.05.032
DO - 10.1016/j.ijbiomac.2022.05.032
M3 - Article
C2 - 35577195
AN - SCOPUS:85130808839
SN - 0141-8130
VL - 211
SP - 592
EP - 615
JO - International Journal of Biological Macromolecules
JF - International Journal of Biological Macromolecules
ER -