Artificial Intelligence-Driven Research into Functional Proteins and Peptides

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Engineering and Technology".

Deadline for manuscript submissions: 30 November 2026 | Viewed by 1449

Special Issue Editors


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Guest Editor
SKL of Marine Food Processing & Safety Control, National Engineering Research Center of Seafood, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China
Interests: in silico prediction of protein/peptide physiological functions; machine learning-driven structure–activity relationship analysis; AI-aided optimization of bioactive peptide delivery systems; nutrigenomics data mining for functional proteins
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
College of Food Science and Engineering, Dalian Ocean University, Dalian 116023, China
Interests: AI-driven functional peptide screening; structure–activity relationships; physiological mechanisms; marine protein high-value utilization
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Information Engineering, Dalian Ocean University, Dalian 116023, China
Interests: deep learning; big data analysis for functional protein/peptide sequence mining and bioactivity prediction; AI-driven marine bioactive molecule research

Special Issue Information

Dear Colleagues,

Functional proteins and bioactive peptides derived from food have attracted attention in nutraceutical and functional food research due to their diverse physiological functions. These bioactive molecules have great potential for preventing chronic diseases and promoting human health. Traditional functional protein/peptide research involves time-consuming novel sequence discovery, extensive function validation of complex SAR and inefficient bioavailability screening.

In recent years, AI technologies (machine learning, deep learning, NLP, and in silico modeling) have emerged as transformative tools. They address key research bottlenecks by enabling prediction of high-throughput physiological functions. They accelerate SAR analysis and simulate in vivo digestion and absorption. They mine large-scale omics data to reveal molecular mechanisms. Integrating AI with traditional research reduces costs, shortens cycles and unlocks new opportunities for functional proteins/peptides.

This Special Issue of Foods highlights cutting-edge AI-functional protein/bioactive peptide research, focusing strictly on physiological functions (excluding processing properties like emulsification). We invite authors to submit original research, reviews and short communications covering the following topics:

  • AI-driven discovery of food-derived functional proteins/peptides;
  • In silico structure–activity relationship analysis of functional peptides/proteins;
  • AI-aided evaluation of physiological functions;
  • AI-simulated digestion, absorption and metabolism of functional proteins/peptides;
  • Omics/clinical data mining for health benefits of functional proteins/peptides;
  • Development of AI-based high-throughput screening platforms;
  • AI-optimized production of functional proteins/peptides for enhanced physiological activity.

Welcoming researchers in food science, nutrition, bioinformatics and computer science to share innovations, this issue fosters interdisciplinary collaboration, advances AI applications and facilitates high-value findings on nutraceutical development.

Dr. Shuzhen Cheng
Prof. Dr. Ming Du
Prof. Dr. Hong Yu
Guest Editors

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Keywords

  • artificial intelligence
  • functional proteins
  • bioactive peptides
  • physiological functions
  • structure–activity relationship
  • machine learning
  • in silico prediction
  • high-throughput screening

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Published Papers (2 papers)

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Research

18 pages, 3221 KB  
Article
Complexation of Walnut Protein with Adenosine Nucleotides: Effects on Protein Functionality and Novel Insight into the Absorption Mechanism of cAMP
by Lei Zhang, Shanxing Gao, Ye Wang, Jingming Li and Jiachen Zang
Foods 2026, 15(8), 1429; https://doi.org/10.3390/foods15081429 - 20 Apr 2026
Viewed by 442
Abstract
Adenosine nucleotides are vital bioactive molecules with potential applications in functional foods and clinical nutrition; however, their poor membrane permeability limits their bioavailability. The utilization of plant proteins is often hindered by their poor solubility and digestibility. To address these challenges, we developed [...] Read more.
Adenosine nucleotides are vital bioactive molecules with potential applications in functional foods and clinical nutrition; however, their poor membrane permeability limits their bioavailability. The utilization of plant proteins is often hindered by their poor solubility and digestibility. To address these challenges, we developed a strategy involving the formation of complexes between the walnut protein (WP) and four adenosine nucleotides. Spectroscopy, mass spectrometry, cell model, molecular docking, and other experimental techniques were conducted in this study; these methods demonstrated that such a complexation significantly enhanced the solubility of the WP to 3~4 mg/mL, while also enhancing its digestive stability in the gastrointestinal tract by 2~3-fold. Most notably, while all adenosines interacted with the protein matrix, cAMP exhibited a superior absorption efficiency, around 100-fold compared with its linear counterparts. Mass spectrometry and molecular docking were combined to reveal a new absorption mechanism for cAMP with the WP hydrolysate. These findings suggest that the complexation of WP and adenosine nucleotides offers a platform to overcome plant protein limitations and achieve efficient intracellular adenosine delivery, thereby establishing a foundation for its use in the development of functional foods. Full article
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17 pages, 2180 KB  
Article
Preparation and Identification of Corn-Derived Bioactive Peptides with Triple Efficacy of ADH-Activating, XOD-Inhibiting and Antioxidant Activity
by Zifan Yuan, Wenfei Zhang, Jiajie Chang, Yunlong Chen, Yinglian Zhu, Qi Wang and Qingli Yang
Foods 2026, 15(6), 1093; https://doi.org/10.3390/foods15061093 - 20 Mar 2026
Viewed by 506
Abstract
The health risks associated with excessive alcohol consumption have emerged as a public health challenge, with alcohol-associated liver disease (ALD) and hyperuricemia (HUA) being particularly prominent health issues. Current treatments often have side effects, driving the need for safe, multi-target natural alternatives. Based [...] Read more.
The health risks associated with excessive alcohol consumption have emerged as a public health challenge, with alcohol-associated liver disease (ALD) and hyperuricemia (HUA) being particularly prominent health issues. Current treatments often have side effects, driving the need for safe, multi-target natural alternatives. Based on the dual barrier strategy of “metabolic regulation–antioxidant defense”, this study developed bioactive peptides from corn germ meal via enzymatic hydrolysis, which simultaneously activated alcohol dehydrogenase (ADH), inhibited xanthine oxidase (XOD), and exhibited antioxidative properties. The fraction <3 kDa emerged with stronger triple bioactivity while also demonstrating sensitivity to strong acids and enhanced activity under trypsin treatment in in vitro stability tests. A total of 841 unique peptides were obtained from purified peptide fractions. After computer-aided screening and molecular docking, three corn-derived peptides (LMFP, FEGLFR, and QLPSYR) were identified, which acted synergistically. Docking simulations revealed that they bind to ADH and XOD via hydrogen bonds and hydrophobic interactions, suggesting potential interactions with these enzymes that may influence their activity. The corn-derived bioactive peptides developed in this study may serve as potential resources for alleviating alcohol metabolism and hyperuricemia symptoms. Full article
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