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In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1
Hypertension is considered as one of the most common diseases that affect human beings (both male and female) due to its high prevalence and also extending widely to both industrialize and developing countries. Angiotensin-converting enzyme (ACE) has a significant role in the regulation of blood pre...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6996805/ https://www.ncbi.nlm.nih.gov/pubmed/32012183 http://dx.doi.org/10.1371/journal.pone.0228265 |
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author | Tahir, Rana Adnan Bashir, Afsheen Yousaf, Muhammad Noaman Ahmed, Azka Dali, Yasmine Khan, Sanaullah Sehgal, Sheikh Arslan |
author_facet | Tahir, Rana Adnan Bashir, Afsheen Yousaf, Muhammad Noaman Ahmed, Azka Dali, Yasmine Khan, Sanaullah Sehgal, Sheikh Arslan |
author_sort | Tahir, Rana Adnan |
collection | PubMed |
description | Hypertension is considered as one of the most common diseases that affect human beings (both male and female) due to its high prevalence and also extending widely to both industrialize and developing countries. Angiotensin-converting enzyme (ACE) has a significant role in the regulation of blood pressure and ACE inhibition with inhibitory peptides is considered as a major target to prevent hypertension. In the current study, a blood pressure regulating honey protein (MRJP1) was examined to identify the ACE inhibitory peptides. The 3D structure of MRJP1 was predicted by utilizing the threading approach and further optimized by performing molecular dynamics simulation for 30 nanoseconds (ns) to improve the quality factor up to 92.43%. Root mean square deviation and root mean square fluctuations were calculated to evaluate the structural features and observed the fluctuations in the timescale of 30 ns. AHTpin server based on scoring vector machine of regression models, proteolysis and structural characterization approaches were implemented to identify the potential inhibitory peptides. The anti-hypertensive peptides were scrutinized based on the QSAR models of anti-hypertensive activity and the molecular docking analyses were performed to explore the binding affinities and potential interacting residues. The peptide “EALPHVPIFDR” showed the strong binding affinity and higher anti-hypertensive activity along with the global energy of -58.29 and docking score of 9590. The aromatic amino acids especially Tyr was observed as the key residue to design the dietary peptides and drugs like ACE inhibitors. |
format | Online Article Text |
id | pubmed-6996805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-69968052020-02-20 In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1 Tahir, Rana Adnan Bashir, Afsheen Yousaf, Muhammad Noaman Ahmed, Azka Dali, Yasmine Khan, Sanaullah Sehgal, Sheikh Arslan PLoS One Research Article Hypertension is considered as one of the most common diseases that affect human beings (both male and female) due to its high prevalence and also extending widely to both industrialize and developing countries. Angiotensin-converting enzyme (ACE) has a significant role in the regulation of blood pressure and ACE inhibition with inhibitory peptides is considered as a major target to prevent hypertension. In the current study, a blood pressure regulating honey protein (MRJP1) was examined to identify the ACE inhibitory peptides. The 3D structure of MRJP1 was predicted by utilizing the threading approach and further optimized by performing molecular dynamics simulation for 30 nanoseconds (ns) to improve the quality factor up to 92.43%. Root mean square deviation and root mean square fluctuations were calculated to evaluate the structural features and observed the fluctuations in the timescale of 30 ns. AHTpin server based on scoring vector machine of regression models, proteolysis and structural characterization approaches were implemented to identify the potential inhibitory peptides. The anti-hypertensive peptides were scrutinized based on the QSAR models of anti-hypertensive activity and the molecular docking analyses were performed to explore the binding affinities and potential interacting residues. The peptide “EALPHVPIFDR” showed the strong binding affinity and higher anti-hypertensive activity along with the global energy of -58.29 and docking score of 9590. The aromatic amino acids especially Tyr was observed as the key residue to design the dietary peptides and drugs like ACE inhibitors. Public Library of Science 2020-02-03 /pmc/articles/PMC6996805/ /pubmed/32012183 http://dx.doi.org/10.1371/journal.pone.0228265 Text en © 2020 Tahir et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Tahir, Rana Adnan Bashir, Afsheen Yousaf, Muhammad Noaman Ahmed, Azka Dali, Yasmine Khan, Sanaullah Sehgal, Sheikh Arslan In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1 |
title | In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1 |
title_full | In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1 |
title_fullStr | In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1 |
title_full_unstemmed | In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1 |
title_short | In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1 |
title_sort | in silico identification of angiotensin-converting enzyme inhibitory peptides from mrjp1 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6996805/ https://www.ncbi.nlm.nih.gov/pubmed/32012183 http://dx.doi.org/10.1371/journal.pone.0228265 |
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