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Quantitative Structure-Activity Relationship Modeling of Pea Protein-Derived Acetylcholinesterase and Butyrylcholinesterase Inhibitory Peptides.

Nancy D AsenChibuike C UdenigweRotimi Emmanuel Aluko
Published in: Journal of agricultural and food chemistry (2023)
The aim of this work was to determine the structural requirements for peptides that inhibit acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) activities. The data set used consisted of 19 oligopeptides that had been identified through mass spectrometry analysis of enzymatic digests of yellow field pea protein. The structure-function relationship was analyzed by partial least squares regression using the 5 z scores. A nine-component model was created from 16 peptides for AChE inhibitory peptides ( Q 2 = 67.2% and R 2 = 0.9974), while three data sets were prepared for BuChE inhibitory peptides to improve the quality of the models ( Q 2 = 26.7-46.4% and R 2 = 0.9577-0.9958). The most active peptides from the PLS models have threonine, leucine, alanine, and valine at the N terminal, asparagine, histidine, proline, and arginine at the second position, with aspartic acid and serine at the third, and arginine at the C terminal.
Keyphrases
  • amino acid
  • mass spectrometry
  • nitric oxide
  • high resolution
  • big data
  • structure activity relationship
  • liquid chromatography
  • hydrogen peroxide
  • ms ms
  • artificial intelligence