Potent angiotensin-converting enzyme inhibitory tripeptides identified by a computer-based approach

Tran Hai-Bang, Kuniyoshi Shimizu

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Currently, peptides and peptidomimetics are the main focus in attempts to identify inhibitors of angiotensin-converting enzyme (ACE), the dipeptidyl carboxypeptidase that causes blood vessels to constrict and blood pressure to increase. This study was conducted to identify the most potent ACE-inhibitory tripeptides with a proline C-terminus, using a novel three-step (tautomerization-docking-ADME simulation) virtual screening process and in vitro assays. Sixteen candidates were identified, and their IC50 values ranged from 5.6 to 274.4 μM. ACE inhibition activity for 14 of the 16 tripeptides was reported for the first time. We also found that changing from the L-form to the D-form of the amino acid at the amino and carboxyl termini resulted in a decrease of inhibition, but a greater decrease was observed for C-terminal changes. With low IC50 values and high-predicted bioavailability, the peptides identified by our protocol are comparable in terms of ACE-inhibition to those derived from costly and time-consuming wet screening. Our in vitro and docking results showed that the configuration of the C-terminus is a critical parameter contributing to the inhibitory activity of tripeptides with proline at this position. These findings will contribute to the use of simulation tools for rational drug design, especially for ACE inhibitors.

Original languageEnglish
Pages (from-to)206-211
Number of pages6
JournalJournal of Molecular Graphics and Modelling
Volume53
DOIs
Publication statusPublished - Sep 2014

Fingerprint

angiotensins
Peptidyl-Dipeptidase A
Enzyme inhibition
enzymes
Enzymes
Angiotensin-Converting Enzyme Inhibitors
Proline
Peptides
Screening
Peptidomimetics
Blood pressure
Blood vessels
peptides
screening
enzyme inhibitors
Amino acids
Assays
bioavailability
blood pressure
blood vessels

All Science Journal Classification (ASJC) codes

  • Spectroscopy
  • Physical and Theoretical Chemistry
  • Computer Graphics and Computer-Aided Design
  • Materials Chemistry

Cite this

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