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Prediction of Bioactive Peptides from Chlorella sorokiniana Proteins Using Proteomic Techniques in Combination with Bioinformatics Analyses
Chlorella is one of the most nutritionally important microalgae with high protein content and can be a good source of potential bioactive peptides. In the current study, isolated proteins from Chlorella sorokiniana were subjected to in silico analysis to predict potential peptides with biological ac...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6480496/ https://www.ncbi.nlm.nih.gov/pubmed/30978907 http://dx.doi.org/10.3390/ijms20071786 |
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author | Tejano, Lhumen A. Peralta, Jose P. Yap, Encarnacion Emilia S. Panjaitan, Fenny Crista A. Chang, Yu-Wei |
author_facet | Tejano, Lhumen A. Peralta, Jose P. Yap, Encarnacion Emilia S. Panjaitan, Fenny Crista A. Chang, Yu-Wei |
author_sort | Tejano, Lhumen A. |
collection | PubMed |
description | Chlorella is one of the most nutritionally important microalgae with high protein content and can be a good source of potential bioactive peptides. In the current study, isolated proteins from Chlorella sorokiniana were subjected to in silico analysis to predict potential peptides with biological activities. Molecular characteristics of proteins were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and proteomics techniques. A total of eight proteins were identified by proteomics techniques from 10 protein bands of the SDS-PAGE. The predictive result by BIOPEP’s profile of bioactive peptides tools suggested that proteins of C. sorokiniana have the highest number of dipeptidyl peptidase-IV (DPP IV) inhibitors, with high occurrence of other bioactive peptides such as angiotensin-I converting enzyme (ACE) inhibitor, glucose uptake stimulant, antioxidant, regulating, anti-amnestic and antithrombotic peptides. In silico analysis of enzymatic hydrolysis revealed that pepsin (pH > 2), bromelain and papain were proteases that can release relatively larger quantity of bioactive peptides. In addition, combinations of different enzymes in hydrolysis were observed to dispense higher numbers of bioactive peptides from proteins compared to using individual proteases. Results suggest the potential of protein isolated from C. sorokiniana could be a source of high value products with pharmaceutical and nutraceutical application potential. |
format | Online Article Text |
id | pubmed-6480496 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64804962019-04-29 Prediction of Bioactive Peptides from Chlorella sorokiniana Proteins Using Proteomic Techniques in Combination with Bioinformatics Analyses Tejano, Lhumen A. Peralta, Jose P. Yap, Encarnacion Emilia S. Panjaitan, Fenny Crista A. Chang, Yu-Wei Int J Mol Sci Article Chlorella is one of the most nutritionally important microalgae with high protein content and can be a good source of potential bioactive peptides. In the current study, isolated proteins from Chlorella sorokiniana were subjected to in silico analysis to predict potential peptides with biological activities. Molecular characteristics of proteins were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and proteomics techniques. A total of eight proteins were identified by proteomics techniques from 10 protein bands of the SDS-PAGE. The predictive result by BIOPEP’s profile of bioactive peptides tools suggested that proteins of C. sorokiniana have the highest number of dipeptidyl peptidase-IV (DPP IV) inhibitors, with high occurrence of other bioactive peptides such as angiotensin-I converting enzyme (ACE) inhibitor, glucose uptake stimulant, antioxidant, regulating, anti-amnestic and antithrombotic peptides. In silico analysis of enzymatic hydrolysis revealed that pepsin (pH > 2), bromelain and papain were proteases that can release relatively larger quantity of bioactive peptides. In addition, combinations of different enzymes in hydrolysis were observed to dispense higher numbers of bioactive peptides from proteins compared to using individual proteases. Results suggest the potential of protein isolated from C. sorokiniana could be a source of high value products with pharmaceutical and nutraceutical application potential. MDPI 2019-04-11 /pmc/articles/PMC6480496/ /pubmed/30978907 http://dx.doi.org/10.3390/ijms20071786 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tejano, Lhumen A. Peralta, Jose P. Yap, Encarnacion Emilia S. Panjaitan, Fenny Crista A. Chang, Yu-Wei Prediction of Bioactive Peptides from Chlorella sorokiniana Proteins Using Proteomic Techniques in Combination with Bioinformatics Analyses |
title | Prediction of Bioactive Peptides from Chlorella sorokiniana Proteins Using Proteomic Techniques in Combination with Bioinformatics Analyses |
title_full | Prediction of Bioactive Peptides from Chlorella sorokiniana Proteins Using Proteomic Techniques in Combination with Bioinformatics Analyses |
title_fullStr | Prediction of Bioactive Peptides from Chlorella sorokiniana Proteins Using Proteomic Techniques in Combination with Bioinformatics Analyses |
title_full_unstemmed | Prediction of Bioactive Peptides from Chlorella sorokiniana Proteins Using Proteomic Techniques in Combination with Bioinformatics Analyses |
title_short | Prediction of Bioactive Peptides from Chlorella sorokiniana Proteins Using Proteomic Techniques in Combination with Bioinformatics Analyses |
title_sort | prediction of bioactive peptides from chlorella sorokiniana proteins using proteomic techniques in combination with bioinformatics analyses |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6480496/ https://www.ncbi.nlm.nih.gov/pubmed/30978907 http://dx.doi.org/10.3390/ijms20071786 |
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