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Prediction of MMP-9 inhibitory activity of N-hydroxy-α-phenylsulfonylacetamide derivatives by pharmacophore based modeling and 3-D QSAR studies
Matrix metalloproteinase-9 (MMP-9), also known as gelatinase B, is a MMP that is strongly associated with multiple cellular processes including proliferation, angiogenesis, and metastasis. Various studies have shown that N-hydroxy-α-phenylsulfonylacetamide (HPSAs) derivatives are promising and selec...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726302/ https://www.ncbi.nlm.nih.gov/pubmed/31595232 http://dx.doi.org/10.1016/j.pbj.0000000000000006 |
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author | Rathee, Dharmender Lather, Viney Dureja, Harish |
author_facet | Rathee, Dharmender Lather, Viney Dureja, Harish |
author_sort | Rathee, Dharmender |
collection | PubMed |
description | Matrix metalloproteinase-9 (MMP-9), also known as gelatinase B, is a MMP that is strongly associated with multiple cellular processes including proliferation, angiogenesis, and metastasis. Various studies have shown that N-hydroxy-α-phenylsulfonylacetamide (HPSAs) derivatives are promising and selective for the MMP-9 inhibition. In the present study, we have selected and reported 80 HPSAs derivatives as inhibitors of MMP-9 and performed structure-based 3-dimensional quantitative structure–activity relationship (3D-QSAR) studies to elucidate the important structural elements responsible for binding affinity. Developed pharmacophore models; QSAR model I contains 2 hydrogen-bond acceptors (A), 2 hydrogen-bond donors (D), and 1 aromatic ring (R) and QSAR model II contains 3 hydrogen-bond acceptors (A), 1 positive ionic (P), and 1 aromatic ring (R). The statistical results of QSAR models (I and II) such as good correlation coefficient (0.61 for I and 0.63 for II), good predictive power (0.84 and 0.77 for I and II, respectively) with low standard deviation (SD\0.3 for both) strongly suggest that the developed models are virtuous for the future prediction of MMP-9 inhibitory activity of HPSAs derivatives. The geometry and features of pharmacophore were expected to be useful for further design and development of selective MMP-9 inhibitors. |
format | Online Article Text |
id | pubmed-6726302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
record_format | MEDLINE/PubMed |
spelling | pubmed-67263022019-10-08 Prediction of MMP-9 inhibitory activity of N-hydroxy-α-phenylsulfonylacetamide derivatives by pharmacophore based modeling and 3-D QSAR studies Rathee, Dharmender Lather, Viney Dureja, Harish Porto Biomed J Original Article Matrix metalloproteinase-9 (MMP-9), also known as gelatinase B, is a MMP that is strongly associated with multiple cellular processes including proliferation, angiogenesis, and metastasis. Various studies have shown that N-hydroxy-α-phenylsulfonylacetamide (HPSAs) derivatives are promising and selective for the MMP-9 inhibition. In the present study, we have selected and reported 80 HPSAs derivatives as inhibitors of MMP-9 and performed structure-based 3-dimensional quantitative structure–activity relationship (3D-QSAR) studies to elucidate the important structural elements responsible for binding affinity. Developed pharmacophore models; QSAR model I contains 2 hydrogen-bond acceptors (A), 2 hydrogen-bond donors (D), and 1 aromatic ring (R) and QSAR model II contains 3 hydrogen-bond acceptors (A), 1 positive ionic (P), and 1 aromatic ring (R). The statistical results of QSAR models (I and II) such as good correlation coefficient (0.61 for I and 0.63 for II), good predictive power (0.84 and 0.77 for I and II, respectively) with low standard deviation (SD\0.3 for both) strongly suggest that the developed models are virtuous for the future prediction of MMP-9 inhibitory activity of HPSAs derivatives. The geometry and features of pharmacophore were expected to be useful for further design and development of selective MMP-9 inhibitors. 2018-07-03 /pmc/articles/PMC6726302/ /pubmed/31595232 http://dx.doi.org/10.1016/j.pbj.0000000000000006 Text en Copyright © 2018 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of PBJ-Associação Porto Biomedical/Porto Biomedical Society. All rights reserved. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 |
spellingShingle | Original Article Rathee, Dharmender Lather, Viney Dureja, Harish Prediction of MMP-9 inhibitory activity of N-hydroxy-α-phenylsulfonylacetamide derivatives by pharmacophore based modeling and 3-D QSAR studies |
title | Prediction of MMP-9 inhibitory activity of N-hydroxy-α-phenylsulfonylacetamide derivatives by pharmacophore based modeling and 3-D QSAR studies |
title_full | Prediction of MMP-9 inhibitory activity of N-hydroxy-α-phenylsulfonylacetamide derivatives by pharmacophore based modeling and 3-D QSAR studies |
title_fullStr | Prediction of MMP-9 inhibitory activity of N-hydroxy-α-phenylsulfonylacetamide derivatives by pharmacophore based modeling and 3-D QSAR studies |
title_full_unstemmed | Prediction of MMP-9 inhibitory activity of N-hydroxy-α-phenylsulfonylacetamide derivatives by pharmacophore based modeling and 3-D QSAR studies |
title_short | Prediction of MMP-9 inhibitory activity of N-hydroxy-α-phenylsulfonylacetamide derivatives by pharmacophore based modeling and 3-D QSAR studies |
title_sort | prediction of mmp-9 inhibitory activity of n-hydroxy-α-phenylsulfonylacetamide derivatives by pharmacophore based modeling and 3-d qsar studies |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726302/ https://www.ncbi.nlm.nih.gov/pubmed/31595232 http://dx.doi.org/10.1016/j.pbj.0000000000000006 |
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