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Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation

In the landscape of epigenetic regulation, histone deacetylase 3 (HDAC3) has emerged as a prominent therapeutic target for the design and development of candidate drugs against various types of cancers and other human disorders. Herein, we have performed ligand-based pharmacophore modeling, virtual...

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Autores principales: Kumbhar, Navanath, Nimal, Snehal, Barale, Sagar, Kamble, Subodh, Bavi, Rohit, Sonawane, Kailas, Gacche, Rajesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810932/
https://www.ncbi.nlm.nih.gov/pubmed/35110603
http://dx.doi.org/10.1038/s41598-022-05698-7
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author Kumbhar, Navanath
Nimal, Snehal
Barale, Sagar
Kamble, Subodh
Bavi, Rohit
Sonawane, Kailas
Gacche, Rajesh
author_facet Kumbhar, Navanath
Nimal, Snehal
Barale, Sagar
Kamble, Subodh
Bavi, Rohit
Sonawane, Kailas
Gacche, Rajesh
author_sort Kumbhar, Navanath
collection PubMed
description In the landscape of epigenetic regulation, histone deacetylase 3 (HDAC3) has emerged as a prominent therapeutic target for the design and development of candidate drugs against various types of cancers and other human disorders. Herein, we have performed ligand-based pharmacophore modeling, virtual screening, molecular docking, and MD simulations to design potent and selective inhibitors against HDAC3. The predicted best pharmacophore model ‘Hypo 1’ showed excellent correlation (R(2) = 0.994), lowest RMSD (0.373), lowest total cost value (102.519), and highest cost difference (124.08). Hypo 1 consists of four salient pharmacophore features viz. one hydrogen bond acceptor (HBA), one ring aromatic (RA), and two hydrophobic (HYP). Hypo 1 was validated by Fischer's randomization with a 95% of confidence level and the external test set of 60 compounds with a good correlation coefficient (R(2) = 0.970). The virtual screening of chemical databases, drug-like properties calculations followed by molecular docking resulted in identifying 22 representative hit compounds. Performed 50 ns of MD simulations on top three hits were retained the salient π-stacking, Zn(2+) coordination, hydrogen bonding, and hydrophobic interactions with catalytic residues from the active site pocket of HDAC3. Total binding energy calculated by MM-PBSA showed that the Hit 1 and Hit 2 formed stable complexes with HDAC3 as compared to reference TSA. Further, the PLIP analysis showed a close resemblance between the salient pharmacophore features of Hypo 1 and the presence of molecular interactions in co-crystallized FDA-approved drugs. We conclude that the screened hit compounds may act as potent inhibitors of HDAC3 and further preclinical and clinical studies may pave the way for developing them as effective therapeutic agents for the treatment of different cancers and neurodegenerative disorders.
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spelling pubmed-88109322022-02-07 Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation Kumbhar, Navanath Nimal, Snehal Barale, Sagar Kamble, Subodh Bavi, Rohit Sonawane, Kailas Gacche, Rajesh Sci Rep Article In the landscape of epigenetic regulation, histone deacetylase 3 (HDAC3) has emerged as a prominent therapeutic target for the design and development of candidate drugs against various types of cancers and other human disorders. Herein, we have performed ligand-based pharmacophore modeling, virtual screening, molecular docking, and MD simulations to design potent and selective inhibitors against HDAC3. The predicted best pharmacophore model ‘Hypo 1’ showed excellent correlation (R(2) = 0.994), lowest RMSD (0.373), lowest total cost value (102.519), and highest cost difference (124.08). Hypo 1 consists of four salient pharmacophore features viz. one hydrogen bond acceptor (HBA), one ring aromatic (RA), and two hydrophobic (HYP). Hypo 1 was validated by Fischer's randomization with a 95% of confidence level and the external test set of 60 compounds with a good correlation coefficient (R(2) = 0.970). The virtual screening of chemical databases, drug-like properties calculations followed by molecular docking resulted in identifying 22 representative hit compounds. Performed 50 ns of MD simulations on top three hits were retained the salient π-stacking, Zn(2+) coordination, hydrogen bonding, and hydrophobic interactions with catalytic residues from the active site pocket of HDAC3. Total binding energy calculated by MM-PBSA showed that the Hit 1 and Hit 2 formed stable complexes with HDAC3 as compared to reference TSA. Further, the PLIP analysis showed a close resemblance between the salient pharmacophore features of Hypo 1 and the presence of molecular interactions in co-crystallized FDA-approved drugs. We conclude that the screened hit compounds may act as potent inhibitors of HDAC3 and further preclinical and clinical studies may pave the way for developing them as effective therapeutic agents for the treatment of different cancers and neurodegenerative disorders. Nature Publishing Group UK 2022-02-02 /pmc/articles/PMC8810932/ /pubmed/35110603 http://dx.doi.org/10.1038/s41598-022-05698-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kumbhar, Navanath
Nimal, Snehal
Barale, Sagar
Kamble, Subodh
Bavi, Rohit
Sonawane, Kailas
Gacche, Rajesh
Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation
title Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation
title_full Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation
title_fullStr Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation
title_full_unstemmed Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation
title_short Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation
title_sort identification of novel leads as potent inhibitors of hdac3 using ligand-based pharmacophore modeling and md simulation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810932/
https://www.ncbi.nlm.nih.gov/pubmed/35110603
http://dx.doi.org/10.1038/s41598-022-05698-7
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