Methodologies for studying the structure-function relationship of food-derived peptides with biological activities

Advaita Ganguly, Kumakshi Sharma, Kaustav Majumder

Research output: Chapter in Book/Report/Conference proceedingChapter


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 languageEnglish (US)
Title of host publicationBiologically Active Peptides
Subtitle of host publicationFrom Basic Science to Applications for Human Health
Number of pages16
ISBN (Electronic)9780128213896
StatePublished - Jan 1 2021


  • Artificial neural networking
  • Bioactive peptides
  • Hidden markov model
  • In silico analysis
  • Machine learning
  • QSAR

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)


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