Evidence map›Paper›PMID 39659946›Full record

ArticleCurrent research in food science2024

Identification of novel antioxidant and anti-inflammatory peptides from bovine hemoglobin by computer simulation of enzymolysis, molecular docking and molecular dynamics.

Xuan-Ying Xin, Chao-Hui Ruan, Yi-Hui Liu, Huai-Na Jin, Sung-Kwon Park, Sun-Jin Hur, Xiang-Zi Li, Seong-Ho Choi

Abstract read
In one paragraph

Article in Current research in food science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xuan-Ying XinEngineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji, 133002, China.
Chao-Hui RuanEngineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji, 133002, China.
Yi-Hui LiuEngineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji, 133002, China.
Huai-Na JinEngineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji, 133002, China.
Sung-Kwon ParkDepartment of Food Science and Biotechnology, Sejong University, Seoul, 05006, Republic of Korea.
Sun-Jin HurDepartment of Animal Science and Technology, Chung-Ang University, Anseong, 17546, Republic of Korea.
Xiang-Zi LiEngineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji, 133002, China.
Seong-Ho ChoiDepartment of Animal Science, Chungbuk National University, Cheongju, 28644, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the structural diversity and complex mechanisms of action of bioactive peptides, screening for specific functional peptides is often challenging. To efficiently screen bioactive peptides with antioxidant and anti-inflammatory effects from bovine hemoglobin, we employed bioinformatics methods to perform virtual enzymatic hydrolysis using online tools and predicted the bioactivity, toxicity, and sensitization scores of the resulting peptides. Molecular docking and molecular dynamics simulations with Keap1 and TLR4 were subsequently conducted to screen for antioxidant and anti-inflammatory peptides. Finally, peptides ARRF and ARNF were synthesized using the Fmoc solid-phase method. The oxidative stress and inflammation model in RAW264.7 cells was induced using lipopolysaccharide (LPS), followed by treatment with peptides ARRF and ARNF to verify their antioxidant and anti-inflammatory activities. The results demonstrated that 529 bovine hemoglobin oligopeptides were produced following virtual enzymatic hydrolysis, of which nine were identified as eligible based on predictions of biological activity, toxicity, solubility, and sensitization. Molecular docking results indicated that the oligopeptides ARNF, QADF, and ARRF exhibited favorable interactions with Keap1, while ARNF, RRF, and ARRF showed strong interactions with TLR4. The primary active sites binding to the Keap1 receptor included Val465, Thr560, and Gly464. The main active sites binding to the TLR4 receptor were Asn309, Asn305, and Glu286. Hydrogen bonding, electrostatic interactions, and hydrophobic interactions were identified as the primary modes of interaction between the oligopeptides and the Keap1 and TLR4 receptors. Molecular dynamics simulations further confirmed that the selected bovine hemoglobin peptides could stably bind to Keap1 and TLR4 receptors. Cell experiments demonstrated that ARRF and ARNF effectively ameliorated LPS-induced oxidative stress and inflammation in RAW264.7 cells. Conclusion: Compared to traditional methods, this study promptly screens bovine hemoglobin antioxidant and anti-inflammatory peptides, offering a novel approach for rapidly identifying food-derived bioactive peptides.

Indexed as

Anti-inflammatory peptideAntioxidant peptideBovine hemoglobinKeap1Molecular dockingMolecular dynamicsTLR4Virtual enzymatic hydrolysis

Identifiers

PMID39659946
PMCPMC11629252

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.