Related Experiment Video
Updated: Feb 16, 2026

Measuring RAN Peptide Toxicity in C. elegans
Published on: April 30, 2020
Bioactive hydrolysates from casein: generation, identification, and in silico toxicity and allergenicity prediction
Maolin Tu1, Hanxiong Liu2, Ruyi Zhang2
1Department of Food Science and Engineering, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, China.
Background:
Bioactive casein peptides have attracted considerable attention for their applications in industry. However, there is little clarity regarding mass spectrometric profiles for peptides in enzymatic hydrolysates of casein produced under varying conditions. In this study, the compositions of the peptides from casein hydrolysates were compared for different enzyme/substrate ratio (E/S) and hydrolysis times. The toxicity, allergenicity and bioactivity of the identified peptides were assessed in silico.
Results:
A total of 70 unique peptides were identified, and there were 28, 21, 13 and 8 peptides from αs1 -casein, αs2 -casein, β-casein and κ-casein respectively. The peptide number decreased with the increase in E/S and hydrolysis time. Moreover, peptides with relative molecular mass Mr ranging from 1000 to 1500 Da occupied the highest proportion of 31.43%, and almost all of the peptides showed Mr less than 5000 Da. In silico analysis showed that all of the peptides were non-toxic and non-allergenic, and several of them were assessed by PeptideRanker as having a relatively high likelihood of being bioactive peptides.
Conclusions:
Composition of the peptides in the casein hydrolysates varied with the enzymolysis conditions. This study's results may facilitate the production of target bioactive peptides by controlling E/S and hydrolysis time, which is beneficial for the application of casein peptides in the functional food industry. © 2017 Society of Chemical Industry.
Related Concept Videos
Bioactivation and Tissue Toxicity
Peptide Identification Using Tandem Mass Spectrometry
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
Peptide Bonds
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Toxicity Testing in Animals

