Binding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors.
Stilbene urea derivatives as a novel and competitive class of non-glycosidic α-glucosidase inhibitors are effective for the treatment of type II diabetes and obesity. The main purposes of our molecular modeling study are to explore the most suitable binding poses of stilbene derivatives with analyzi...
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oai:doaj.org-article:d3ce32c651c1477a9d8cc4227adf0de62021-11-18T08:36:57ZBinding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors.1932-620310.1371/journal.pone.0085827https://doaj.org/article/d3ce32c651c1477a9d8cc4227adf0de62014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24465730/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Stilbene urea derivatives as a novel and competitive class of non-glycosidic α-glucosidase inhibitors are effective for the treatment of type II diabetes and obesity. The main purposes of our molecular modeling study are to explore the most suitable binding poses of stilbene derivatives with analyzing the binding affinity differences and finally to develop a pharmacophore model which would represents critical features responsible for α-glucosidase inhibitory activity. Three-dimensional structure of S. cerevisiae α-glucosidase was built by homology modeling method and the structure was used for the molecular docking study to find out the initial binding mode of compound 12, which is the most highly active one. The initial structure was subjected to molecular dynamics (MD) simulations for protein structure adjustment at compound 12-bound state. Based on the adjusted conformation, the more reasonable binding modes of the stilbene urea derivatives were obtained from molecular docking and MD simulations. The binding mode of the derivatives was validated by correlation analysis between experimental Ki value and interaction energy. Our results revealed that the binding modes of the potent inhibitors were engaged with important hydrogen bond, hydrophobic, and π-interactions. With the validated compound 12-bound structure obtained from combining approach of docking and MD simulation, a proper four featured pharmacophore model was generated. It was also validated by comparison of fit values with the Ki values. Thus, these results will be helpful for understanding the relationship between binding mode and bioactivity and for designing better inhibitors from stilbene derivatives.Yuno LeeSongmi KimJun Young KimMahreen AroojSiu KimSwan HwangByeong-Woo KimKi Hun ParkKeun Woo LeePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 1, p e85827 (2014) |
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Medicine R Science Q Yuno Lee Songmi Kim Jun Young Kim Mahreen Arooj Siu Kim Swan Hwang Byeong-Woo Kim Ki Hun Park Keun Woo Lee Binding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors. |
description |
Stilbene urea derivatives as a novel and competitive class of non-glycosidic α-glucosidase inhibitors are effective for the treatment of type II diabetes and obesity. The main purposes of our molecular modeling study are to explore the most suitable binding poses of stilbene derivatives with analyzing the binding affinity differences and finally to develop a pharmacophore model which would represents critical features responsible for α-glucosidase inhibitory activity. Three-dimensional structure of S. cerevisiae α-glucosidase was built by homology modeling method and the structure was used for the molecular docking study to find out the initial binding mode of compound 12, which is the most highly active one. The initial structure was subjected to molecular dynamics (MD) simulations for protein structure adjustment at compound 12-bound state. Based on the adjusted conformation, the more reasonable binding modes of the stilbene urea derivatives were obtained from molecular docking and MD simulations. The binding mode of the derivatives was validated by correlation analysis between experimental Ki value and interaction energy. Our results revealed that the binding modes of the potent inhibitors were engaged with important hydrogen bond, hydrophobic, and π-interactions. With the validated compound 12-bound structure obtained from combining approach of docking and MD simulation, a proper four featured pharmacophore model was generated. It was also validated by comparison of fit values with the Ki values. Thus, these results will be helpful for understanding the relationship between binding mode and bioactivity and for designing better inhibitors from stilbene derivatives. |
format |
article |
author |
Yuno Lee Songmi Kim Jun Young Kim Mahreen Arooj Siu Kim Swan Hwang Byeong-Woo Kim Ki Hun Park Keun Woo Lee |
author_facet |
Yuno Lee Songmi Kim Jun Young Kim Mahreen Arooj Siu Kim Swan Hwang Byeong-Woo Kim Ki Hun Park Keun Woo Lee |
author_sort |
Yuno Lee |
title |
Binding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors. |
title_short |
Binding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors. |
title_full |
Binding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors. |
title_fullStr |
Binding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors. |
title_full_unstemmed |
Binding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors. |
title_sort |
binding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2014 |
url |
https://doaj.org/article/d3ce32c651c1477a9d8cc4227adf0de6 |
work_keys_str_mv |
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