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Molecular Docking, Interaction and Mechanism of Action of Bioactive Peptides

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: closed (30 May 2024) | Viewed by 958

Special Issue Editor


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Guest Editor
School of Food Science and Engineering, Hainan University, Haikou 570228, China
Interests: bioactive peptides; virtual screening; proteomics; metabolomics; bioavailability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, more and more attention has been paid to the exploration of the health-promoting actions of bioactive peptides derived from foods including plant and animal resources. Bioactive peptides could be absorbed and enter the bloodstream then target to different tissues to exert biological effects. Bioactive peptides have a great potential for the development of functional foods and/or medicine in controlling or preventing many diseases. An in-depth understanding of bioactive peptide functionality and the mechanism underlying their bioactivity at a molecular level is an essential precursor to its applications and is vital to warrant efficacy and safe dietary intervention for disease prevention.

This Special Issue of the International Journal of Molecular Sciences is focused on the recent progress achieved in molecular docking/interaction and mechanism of action of bioactive peptides. This includes but is not limited to, functional and mechanistic understanding of peptides, structure–activity relationship between peptide and molecular targets, transmembrane transport and bioavailability of particular bioactive peptides through the application of computational methods (bioinformatics, molecular docking, protein modeling, molecular dynamics simulations, etc.) and molecular biology techniques. The recent advances and challenges in the use of omics technology for the analysis of bioactive peptides are also welcomed.

Prof. Dr. Zhipeng Yu
Guest Editor

Manuscript Submission Information

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Keywords

  • bioactive peptides
  • molecular docking
  • molecular dynamics simulations
  • computer-aided screening
  • structure–activity relationship
  • bioavailability
  • bioinformatics

Published Papers (1 paper)

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Research

15 pages, 3005 KiB  
Article
Computational Screening for the Dipeptidyl Peptidase-IV Inhibitory Peptides from Putative Hemp Seed Hydrolyzed Peptidome as a Potential Antidiabetic Agent
by Arisa Thongtak, Kulpariya Yutisayanuwat, Nathaphat Harnkit, Tipanart Noikaew and Pramote Chumnanpuen
Int. J. Mol. Sci. 2024, 25(11), 5730; https://doi.org/10.3390/ijms25115730 - 24 May 2024
Viewed by 543
Abstract
Dipeptidyl peptidase-IV (DPPIV) inhibitory peptides are a class of antihyperglycemic drugs used in the treatment of type 2 diabetes mellitus, a metabolic disorder resulting from reduced levels of the incretin hormone GLP-1. Given that DPPIV degrades incretin, a key regulator of blood sugar [...] Read more.
Dipeptidyl peptidase-IV (DPPIV) inhibitory peptides are a class of antihyperglycemic drugs used in the treatment of type 2 diabetes mellitus, a metabolic disorder resulting from reduced levels of the incretin hormone GLP-1. Given that DPPIV degrades incretin, a key regulator of blood sugar levels, various antidiabetic medications that inhibit DPPIV, such as vildagliptin, sitagliptin, and linagliptin, are employed. However, the potential side effects of these drugs remain a matter of debate. Therefore, we aimed to investigate food-derived peptides from Cannabis sativa (hemp) seeds. Our developed bioinformatics pipeline was used to identify the putative hydrolyzed peptidome of three highly abundant proteins: albumin, edestin, and vicilin. These proteins were subjected to in silico digestion by different proteases (trypsin, chymotrypsin, and pepsin) and then screened for DPPIV inhibitory peptides using IDPPIV-SCM. To assess potential adverse effects, several prediction tools, namely, TOXINpred, AllerCatPro, and HemoPred, were employed to evaluate toxicity, allergenicity, and hemolytic effects, respectively. COPID was used to determine the amino acid composition. Molecular docking was performed using GalaxyPepDock and HPEPDOCK, 3D visualizations were conducted using the UCSF Chimera program, and MD simulations were carried out with AMBER20 MD software. Based on the predictive outcomes, FNVDTE from edestin and EAQPST from vicilin emerged as promising candidates for DPPIV inhibitors. We anticipate that our findings may pave the way for the development of alternative DPPIV inhibitors. Full article
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