TY - JOUR
T1 - Application of in silico approaches for the generation of milk protein-derived bioactive peptides
AU - FitzGerald, Richard J.
AU - Cermeño, Maria
AU - Khalesi, Mohammadreza
AU - Kleekayai, Thanyaporn
AU - Amigo-Benavent, Miryam
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2020/1
Y1 - 2020/1
N2 - Milk protein derived peptides have numerous well-documented bioactive properties. The conventional approach for the generation, identification and validation of bioactive peptides (BAPs) has involved (i) protein hydrolysis, (ii) bioactivity screening and (iii) validation in vivo. The low potency (in comparison to conventional drugs), susceptibility to breakdown during gastrointestinal transit and low intestinal permeability are key challenges in the development of highly bioactive food protein hydrolysates/peptides. However, the generation of potent and effective health enhancing hydrolysates/peptides can benefit from a range of in silico techniques including the application of structure bioactivity relationship modelling (e.g., quantitative structure activity relationship (QSAR) modelling), molecular docking and design of experiments (DOE) approaches to optimise BAP production and identification. Some examples of how these approaches have been employed in BAP discovery and generation will be outlined.
AB - Milk protein derived peptides have numerous well-documented bioactive properties. The conventional approach for the generation, identification and validation of bioactive peptides (BAPs) has involved (i) protein hydrolysis, (ii) bioactivity screening and (iii) validation in vivo. The low potency (in comparison to conventional drugs), susceptibility to breakdown during gastrointestinal transit and low intestinal permeability are key challenges in the development of highly bioactive food protein hydrolysates/peptides. However, the generation of potent and effective health enhancing hydrolysates/peptides can benefit from a range of in silico techniques including the application of structure bioactivity relationship modelling (e.g., quantitative structure activity relationship (QSAR) modelling), molecular docking and design of experiments (DOE) approaches to optimise BAP production and identification. Some examples of how these approaches have been employed in BAP discovery and generation will be outlined.
KW - Bioactive peptides
KW - DOE
KW - Docking
KW - In silico
KW - Milk protein
KW - QSAR
KW - RSM
UR - http://www.scopus.com/inward/record.url?scp=85074463682&partnerID=8YFLogxK
U2 - 10.1016/j.jff.2019.103636
DO - 10.1016/j.jff.2019.103636
M3 - Article
AN - SCOPUS:85074463682
SN - 1756-4646
VL - 64
JO - Journal of Functional Foods
JF - Journal of Functional Foods
M1 - 103636
ER -