Issue 22, 2024

Evaluating the capability of soybean peptides as calcium ion carriers: a study through sequence analysis and molecular dynamics simulations

Abstract

Calcium homeostasis imbalance in the body can lead to a variety of chronic diseases. Supplement efficiency is essential. Peptide calcium chelate, a fourth-generation calcium supplement, offers easy absorption and minimal side effects. Its effectiveness relies on peptide's calcium binding capacity. However, research on amino acid sequences in peptides with high calcium binding capacity (HCBC) is limited, affecting the efficient identification of such peptides. This study used soybean peptides (SP), separated and purified by gel chromatography, to obtain HCBC peptide (137.45 μg mg−1) and normal peptide (≤95.78 μg mg−1). Mass spectrometry identified the sequences of these peptides, and an analysis of the positional distribution of characteristic amino acids followed. Two HCBC peptides with sequences GGDLVS (271.55 μg mg−1) and YEGVIL (272.54 μg mg−1) were discovered. Molecular dynamics showed that when either aspartic acid is located near the N-terminal's middle, or glutamic acid is near the end, or in cases of continuous Asp or Glu, the binding speed, probability, and strength between the peptide and calcium ions are superior compared to those at other locations. The study's goal was to clarify how the positions of characteristic amino acids in peptides affect calcium binding, aiding in developing peptide calcium chelates as a novel calcium supplement.

Graphical abstract: Evaluating the capability of soybean peptides as calcium ion carriers: a study through sequence analysis and molecular dynamics simulations

Supplementary files

Article information

Article type
Paper
Submitted
19 Apr 2024
Accepted
06 May 2024
First published
13 May 2024
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2024,14, 15542-15553

Evaluating the capability of soybean peptides as calcium ion carriers: a study through sequence analysis and molecular dynamics simulations

J. An, Y. Wang, W. Li, W. Liu, X. Zeng, G. Liu, X. Liu and H. Li, RSC Adv., 2024, 14, 15542 DOI: 10.1039/D4RA02916J

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