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...

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Main Authors: Rana Adnan Tahir, Afsheen Bashir, Muhammad Noaman Yousaf, Azka Ahmed, Yasmine Dali, Sanaullah Khan, Sheikh Arslan Sehgal
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0228265
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spelling doaj-5144d9eaf04e4d929bd51118308f13ed2021-03-03T21:28:10ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01152e022826510.1371/journal.pone.0228265In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1.Rana Adnan TahirAfsheen BashirMuhammad Noaman YousafAzka AhmedYasmine DaliSanaullah KhanSheikh Arslan SehgalHypertension 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.https://doi.org/10.1371/journal.pone.0228265
collection DOAJ
language English
format Article
sources DOAJ
author Rana Adnan Tahir
Afsheen Bashir
Muhammad Noaman Yousaf
Azka Ahmed
Yasmine Dali
Sanaullah Khan
Sheikh Arslan Sehgal
spellingShingle Rana Adnan Tahir
Afsheen Bashir
Muhammad Noaman Yousaf
Azka Ahmed
Yasmine Dali
Sanaullah Khan
Sheikh Arslan Sehgal
In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1.
PLoS ONE
author_facet Rana Adnan Tahir
Afsheen Bashir
Muhammad Noaman Yousaf
Azka Ahmed
Yasmine Dali
Sanaullah Khan
Sheikh Arslan Sehgal
author_sort Rana Adnan Tahir
title 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_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_sort in silico identification of angiotensin-converting enzyme inhibitory peptides from mrjp1.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2020-01-01
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.
url https://doi.org/10.1371/journal.pone.0228265
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