In silico Evaluation of Potential Bioactive Peptides of Phycoerythrins from Selected Rhodophytes
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Bentham Science Publishers Ltd.
Abstract
Background: Rhodophytes typically possess a higher protein content than Chlorophytes and members of Class Phaeophyceae. The predominant proteins in rhodophytes are phycobiliproteins, constituting up to 50% of the overall protein composition. Phycoerythrin, phycocyanin, allophycocyanin, and phycoerythrocyanin are the principal phycobiliproteins. The objective of the study is to identify and test the activity of putative bioactive peptides derived from selected identical sequences of Rhodophytes. This study employs an in silico methodology to examine identical sequences of phycoerythrin from several rhodophytes as potential bioactive peptide precursors Methods: in silico modeling of proteolysis was conducted utilizing papain, bromelain, thermolysin, pepsin, trypsin, and chymotrypsin A. Various bioinformatics tools, including PeptideRanker, PepCalc, ToxinPred, and AllerTop, were employed to assess the properties of the peptides Results: The simulation revealed that the inhibitory effects of dipeptidyl peptidase IV (DPP IV) and angiotensin-converting enzyme (ACE) had the greatest potential. Peptides that inhibit alpha-glucosidase also exhibited certain efficacy. Stem bromelain had superior efficacy in hydrolysis percentages. This work illustrates those particular identical sequences, including phycoerythrin protein from rhodophytes may serve as a feasible natural alternative to synthetic ACE inhibitor medications. The research also indicates that the peptides may be advantageous in treating type 2 diabetes mellitus due to the existence of dipeptidyl peptidase IV peptides. Additionally, the analysis identified several novel peptides that may exhibit advantageous bioactivities Conclusion: This study explored a prospective alternative supply of bioactive peptides in the food and pharmaceutical industry. These results establish a foundation for subsequent in vitro and in vivo investigationsDescription
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Open Bioinformatics Journal, ISSN: 1875-0362 (Print); 1875-0362 (Online), Bentham Science Publishers Ltd., 18(1). doi: 10.2174/0118750362370187250307055547
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© 2025 The Author(s). Published by Bentham Open open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.