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Bioinformatic Prediction and Characterization of Proteins in Porphyra dentata by Shotgun Proteomics
Porphyra dentata is an edible red seaweed with high nutritional value. It is widely cultivated and consumed in East Asia and has vast economic benefits. Studies have found that P. dentata is rich in bioactive substances and is a potential natural resource. In this study, label-free shotgun proteomic...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301277/ https://www.ncbi.nlm.nih.gov/pubmed/35873412 http://dx.doi.org/10.3389/fnut.2022.924524 |
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author | Yang, Mingchang Ma, Lizhen Yang, Xianqing Li, Laihao Chen, Shengjun Qi, Bo Wang, Yueqi Li, Chunsheng Yang, Shaoling Zhao, Yongqiang |
author_facet | Yang, Mingchang Ma, Lizhen Yang, Xianqing Li, Laihao Chen, Shengjun Qi, Bo Wang, Yueqi Li, Chunsheng Yang, Shaoling Zhao, Yongqiang |
author_sort | Yang, Mingchang |
collection | PubMed |
description | Porphyra dentata is an edible red seaweed with high nutritional value. It is widely cultivated and consumed in East Asia and has vast economic benefits. Studies have found that P. dentata is rich in bioactive substances and is a potential natural resource. In this study, label-free shotgun proteomics was first applied to identify and characterize different harvest proteins in P. dentata. A total of 13,046 different peptides were identified and 419 co-expression target proteins were characterized. Bioinformatics was used to study protein characteristics, functional expression, and interaction of two important functional annotations, amino acid, and carbohydrate metabolism. Potential bioactive peptides, protein structure, and potential ligand conformations were predicted, and the results suggest that bioactive peptides may be utilized as high-quality active fermentation substances and potential targets for drug production. Our research integrated the global protein database, the first time bioinformatic analysis of the P. dentata proteome during different harvest periods, improves the information database construction and provides a framework for future research based on a comprehensive understanding. |
format | Online Article Text |
id | pubmed-9301277 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93012772022-07-22 Bioinformatic Prediction and Characterization of Proteins in Porphyra dentata by Shotgun Proteomics Yang, Mingchang Ma, Lizhen Yang, Xianqing Li, Laihao Chen, Shengjun Qi, Bo Wang, Yueqi Li, Chunsheng Yang, Shaoling Zhao, Yongqiang Front Nutr Nutrition Porphyra dentata is an edible red seaweed with high nutritional value. It is widely cultivated and consumed in East Asia and has vast economic benefits. Studies have found that P. dentata is rich in bioactive substances and is a potential natural resource. In this study, label-free shotgun proteomics was first applied to identify and characterize different harvest proteins in P. dentata. A total of 13,046 different peptides were identified and 419 co-expression target proteins were characterized. Bioinformatics was used to study protein characteristics, functional expression, and interaction of two important functional annotations, amino acid, and carbohydrate metabolism. Potential bioactive peptides, protein structure, and potential ligand conformations were predicted, and the results suggest that bioactive peptides may be utilized as high-quality active fermentation substances and potential targets for drug production. Our research integrated the global protein database, the first time bioinformatic analysis of the P. dentata proteome during different harvest periods, improves the information database construction and provides a framework for future research based on a comprehensive understanding. Frontiers Media S.A. 2022-07-07 /pmc/articles/PMC9301277/ /pubmed/35873412 http://dx.doi.org/10.3389/fnut.2022.924524 Text en Copyright © 2022 Yang, Ma, Yang, Li, Chen, Qi, Wang, Li, Yang and Zhao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Nutrition Yang, Mingchang Ma, Lizhen Yang, Xianqing Li, Laihao Chen, Shengjun Qi, Bo Wang, Yueqi Li, Chunsheng Yang, Shaoling Zhao, Yongqiang Bioinformatic Prediction and Characterization of Proteins in Porphyra dentata by Shotgun Proteomics |
title | Bioinformatic Prediction and Characterization of Proteins in Porphyra dentata by Shotgun Proteomics |
title_full | Bioinformatic Prediction and Characterization of Proteins in Porphyra dentata by Shotgun Proteomics |
title_fullStr | Bioinformatic Prediction and Characterization of Proteins in Porphyra dentata by Shotgun Proteomics |
title_full_unstemmed | Bioinformatic Prediction and Characterization of Proteins in Porphyra dentata by Shotgun Proteomics |
title_short | Bioinformatic Prediction and Characterization of Proteins in Porphyra dentata by Shotgun Proteomics |
title_sort | bioinformatic prediction and characterization of proteins in porphyra dentata by shotgun proteomics |
topic | Nutrition |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301277/ https://www.ncbi.nlm.nih.gov/pubmed/35873412 http://dx.doi.org/10.3389/fnut.2022.924524 |
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