Computational screening of dipeptidyl peptidase IV inhibitors from micoroalgal metabolites by pharmacophore modeling and molecular docking

SUMMARY Dipeptidyl peptidase IV (DPP‐IV) catalyzes conversion of GLP‐1 (glucagon like peptide 1) to inert structure, which results in insufficient secretion of insulin and increase in postprandial blood glucose level. The present study attempts to identify novel inhibitors from bioactive metabolites...

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Published in:Phycological research Vol. 64; no. 4; pp. 291 - 299
Main Authors: Selvaraj, Gurudeeban, Kaliamurthi, Satyavani, Cakmak, Zeynep E., Cakmak, Turgay
Format: Journal Article
Language:English
Published: Kyoto, Japan John Wiley & Sons Australia, Ltd 01-10-2016
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Summary:SUMMARY Dipeptidyl peptidase IV (DPP‐IV) catalyzes conversion of GLP‐1 (glucagon like peptide 1) to inert structure, which results in insufficient secretion of insulin and increase in postprandial blood glucose level. The present study attempts to identify novel inhibitors from bioactive metabolites present in microalgae against DPP‐IV through virtual screening, molecular docking, and pharmacophore modeling for the active target. Possible binding modes of all 60 ligands against DPP‐IV receptor were constructed using MTiOpenScreen virtual screening server. Pharmacophore model was built based on identified 38 DPP‐IV test ligands by using the web‐based PharmaGist program which encompasses hydrogen‐bond acceptors, hydrophobic groups, spatial features, and aromatic rings. The pharmacophore model having highest scores was selected to screen active DPP‐IV ligands. Highest scoring model was used as a query in ZincPharmer screening. All identified ligands were filtered, based on the Lipinski's rule‐of‐five and were subjected to docking studies. In the process of docking analyses, we considered different bonding modes of one ligand with multiple active cavities of DPP‐IV with the help of AutoDock 4.0. The docking analyses indicate that the bioactive constituents, namely, β‐stigmasterol, barbamide, docosahexaenoic acid, arachidonic acid, and harman showed the best binding energies on DPP‐IV receptor and hydrogen bonding with ASP545, GLY741, TYR754, TYR666, ARG125, TYR547, SER630, and LYS554 residues. This study concludes that docosahexaenoic acid, arachidonic acid, β‐stigmasterol, barbamide, harman, ZINC58564986, ZINC56907325, ZINC69432950, ZINC69431828, ZINC73533041, ZINC84287073, ZINC69849395, and ZINC10508406 act as possible DPP‐IV inhibitors.
Bibliography:ark:/67375/WNG-MHCR0238-5
The Scientific and Technological Research Council of Turkey - No. TUBITAK -2216; No. Project#112Y029
Table S1. Parameters of molecular docking studies using Autodock 4.0.Table S2. Virtual screening of bioactive substances from microalgae and cyanobacteria on DPP IV receptor (2RIP).Table S3. Molecular property of selected ligands using Molinspiration tool.Table S4. QSAR and toxicity studies of selected ligands using Vega QSAR tool.Table S5. Various molecular features of 38 input molecules to find out best pharmacophore.Table S6. The summary of the possible pharmacophore.Table S7. ZincPharmer screened out potential DPP-IV inhibitors.
ArticleID:PRE12141
istex:10631620C768BDE51F3512005D0FC1579E6AABA0
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1322-0829
1440-1835
DOI:10.1111/pre.12141