Abstract
Food-derived peptides have been studied extensively using classical, bioinformatics, and hybrid combinatorial methods adding important information about their biological activity above and beyond their known nutritional value. Bioinformatics based in silico analyses and research of the food-derived peptides led to a better understanding of peptides’ structural conformations and molecular interactions. In silico-based studies mitigated shortcomings of classical lab-based intensive studies. However, certain aspects like limited understanding of peptides production in simulated enzymatic hydrolysis, the effect of multiple peptides on specific biomarkers, and structural information of molecular docking receptors need further research. More quantitative structure-activity relation models derived additional bioactive compounds, and bioactive peptide bioavailability information needs to be studied. Further development of in silico tools considering proteomic functional predictions and experimental validations of simulated studies and reducing the divergence is essential.
Original language | English (US) |
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Title of host publication | Biologically Active Peptides |
Subtitle of host publication | From Basic Science to Applications for Human Health |
Publisher | Elsevier |
Pages | 239-254 |
Number of pages | 16 |
ISBN (Electronic) | 9780128213896 |
DOIs | |
State | Published - Jan 1 2021 |
Keywords
- Artificial neural networking
- Bioactive peptides
- Hidden markov model
- In silico analysis
- Machine learning
- QSAR
ASJC Scopus subject areas
- General Biochemistry, Genetics and Molecular Biology