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Keywords = histone dynamics and drug discovery

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22 pages, 11258 KiB  
Article
High-Risk Neuroblastoma Stage 4 (NBS4): Developing a Medicinal Chemistry Multi-Target Drug Approach
by Amgad Gerges and Una Canning
Molecules 2025, 30(10), 2211; https://doi.org/10.3390/molecules30102211 - 19 May 2025
Viewed by 715
Abstract
Childhood neuroblastoma (NB) is a malignant tumour that is a member of a class of embryonic tumours that have their origins in sympathoadrenal progenitor cells. There are five stages in the clinical NB staging system: 1, 2A, 2B, 3, 4S, and 4. For [...] Read more.
Childhood neuroblastoma (NB) is a malignant tumour that is a member of a class of embryonic tumours that have their origins in sympathoadrenal progenitor cells. There are five stages in the clinical NB staging system: 1, 2A, 2B, 3, 4S, and 4. For those diagnosed with stage 4 neuroblastoma (NBS4), the treatment options are limited with a survival rate of between 40 and 50%. Since 1975, more than 15 targets have been identified in the search for a treatment for high-risk NBS4. This article is concerned with the search for a multi-target drug treatment for high-risk NBS4 and focuses on four possible treatment targets that research has identified as having a role in the development of NBS4 and includes the inhibitors Histone Deacetylase (HDAC), Bromodomain (BRD), Hedgehog (HH), and Tropomyosin Kinase (TRK). Computer-aided drug design and molecular modelling have greatly assisted drug discovery in medicinal chemistry. Computational methods such as molecular docking, homology modelling, molecular dynamics, and quantitative structure–activity relationships (QSAR) are frequently used as part of the process for finding new therapeutic drug targets. Relying on these techniques, the authors describe a medicinal chemistry strategy that successfully identified eight compounds (inhibitors) that were thought to be potential inhibitors for each of the four targets listed above. Results revealed that all four targets BRD, HDAC, HH and TRK receptors binding sites share similar amino acid sequencing that ranges from 80 to 100%, offering the possibility of further testing for multi-target drug use. Two additional targets were also tested as part of this work, Retinoic Acid (RA) and c-Src (Csk), which showed similarity (of the binding pocket) across their receptors of 80–100% but lower than 80% for the other four targets. The work for these two targets is the subject of a paper currently in progress. Full article
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13 pages, 2719 KiB  
Article
Structure-Based Identification of Novel Histone Deacetylase 4 (HDAC4) Inhibitors
by Rupesh Agarwal, Pawat Pattarawat, Michael R. Duff, Hwa-Chain Robert Wang, Jerome Baudry and Jeremy C. Smith
Pharmaceuticals 2024, 17(7), 867; https://doi.org/10.3390/ph17070867 - 2 Jul 2024
Cited by 1 | Viewed by 2208
Abstract
Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential [...] Read more.
Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the transcriptional corepressor component protein NCoR. These pockets were screened using an ensemble docking approach combined with consensus scoring to identify compounds with a different binding mechanism than the currently known HDAC modulators. Binding was compared in experimental assays between HDAC4 and HDAC3, which belong to a different family of HDACs. HDAC4 was significantly inhibited by compound 88402 but not HDAC3. Two other compounds (67436 and 134199) had IC50 values in the low micromolar range for both HDACs, which is comparable to the known inhibitor of HDAC4, SAHA (Vorinostat). However, both of these compounds were significantly weaker inhibitors of HDAC3 than SAHA and thus more selective, albeit to a limited extent. Five compounds exhibited activity on human breast carcinoma and/or urothelial carcinoma cell lines. The present result suggests potential mechanistic and chemical approaches for developing selective HDAC4 modulators. Full article
(This article belongs to the Special Issue Small Molecule Drug Discovery: Driven by In-Silico Techniques)
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30 pages, 8716 KiB  
Article
Comparative Structure-Based Virtual Screening Utilizing Optimized AlphaFold Model Identifies Selective HDAC11 Inhibitor
by Fady Baselious, Sebastian Hilscher, Dina Robaa, Cyril Barinka, Mike Schutkowski and Wolfgang Sippl
Int. J. Mol. Sci. 2024, 25(2), 1358; https://doi.org/10.3390/ijms25021358 - 22 Jan 2024
Cited by 13 | Viewed by 4369
Abstract
HDAC11 is a class IV histone deacylase with no crystal structure reported so far. The catalytic domain of HDAC11 shares low sequence identity with other HDAC isoforms, which makes conventional homology modeling less reliable. AlphaFold is a machine learning approach that can predict [...] Read more.
HDAC11 is a class IV histone deacylase with no crystal structure reported so far. The catalytic domain of HDAC11 shares low sequence identity with other HDAC isoforms, which makes conventional homology modeling less reliable. AlphaFold is a machine learning approach that can predict the 3D structure of proteins with high accuracy even in absence of similar structures. However, the fact that AlphaFold models are predicted in the absence of small molecules and ions/cofactors complicates their utilization for drug design. Previously, we optimized an HDAC11 AlphaFold model by adding the catalytic zinc ion and minimization in the presence of reported HDAC11 inhibitors. In the current study, we implement a comparative structure-based virtual screening approach utilizing the previously optimized HDAC11 AlphaFold model to identify novel and selective HDAC11 inhibitors. The stepwise virtual screening approach was successful in identifying a hit that was subsequently tested using an in vitro enzymatic assay. The hit compound showed an IC50 value of 3.5 µM for HDAC11 and could selectively inhibit HDAC11 over other HDAC subtypes at 10 µM concentration. In addition, we carried out molecular dynamics simulations to further confirm the binding hypothesis obtained by the docking study. These results reinforce the previously presented AlphaFold optimization approach and confirm the applicability of AlphaFold models in the search for novel inhibitors for drug discovery. Full article
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17 pages, 1071 KiB  
Review
Chemical Inhibitors Targeting the Histone Lysine Demethylase Families with Potential for Drug Discovery
by Nando Dulal Das, Hideaki Niwa and Takashi Umehara
Epigenomes 2023, 7(1), 7; https://doi.org/10.3390/epigenomes7010007 - 11 Mar 2023
Cited by 14 | Viewed by 4770
Abstract
The dynamic regulation of histone methylation and demethylation plays an important role in the regulation of gene expression. Aberrant expression of histone lysine demethylases has been implicated in various diseases including intractable cancers, and thus lysine demethylases serve as promising therapeutic targets. Recent [...] Read more.
The dynamic regulation of histone methylation and demethylation plays an important role in the regulation of gene expression. Aberrant expression of histone lysine demethylases has been implicated in various diseases including intractable cancers, and thus lysine demethylases serve as promising therapeutic targets. Recent studies in epigenomics and chemical biology have led to the development of a series of small-molecule demethylase inhibitors that are potent, specific, and have in vivo efficacy. In this review, we highlight emerging small-molecule inhibitors targeting the histone lysine demethylases and their progress toward drug discovery. Full article
(This article belongs to the Special Issue Epidrugs: Toward Understanding and Treating Diverse Diseases)
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13 pages, 3587 KiB  
Article
Exploring the Potential of Phytocompounds for Targeting Epigenetic Mechanisms in Rheumatoid Arthritis: An In Silico Study Using Similarity Indexing
by Sanjay H. Deshpande, Zabin K. Bagewadi, T. M. Yunus Khan, Mater H. Mahnashi, Ibrahim Ahmed Shaikh, Sultan Alshehery, Aejaz A. Khan, Vishal S. Patil and Subarna Roy
Molecules 2023, 28(6), 2430; https://doi.org/10.3390/molecules28062430 - 7 Mar 2023
Cited by 5 | Viewed by 2675
Abstract
Finding structurally similar compounds in compound databases is highly efficient and is widely used in present-day drug discovery methodology. The most-trusted and -followed similarity indexing method is Tanimoto similarity indexing. Epigenetic proteins like histone deacetylases (HDACs) inhibitors are traditionally used to target cancer, [...] Read more.
Finding structurally similar compounds in compound databases is highly efficient and is widely used in present-day drug discovery methodology. The most-trusted and -followed similarity indexing method is Tanimoto similarity indexing. Epigenetic proteins like histone deacetylases (HDACs) inhibitors are traditionally used to target cancer, but have only been investigated very recently for their possible effectiveness against rheumatoid arthritis (RA). The synthetic drugs that have been identified and used for the inhibition of HDACs include SAHA, which is being used to inhibit the activity of HDACs of different classes. SAHA was chosen as a compound of high importance as it is reported to inhibit the activity of many HDAC types. Similarity searching using the UNPD database as a reference identified aglaithioduline from the Aglaia leptantha compound as having a ~70% similarity of molecular fingerprints with SAHA, based on the Tanimoto indexing method using ChemmineR. Aglaithioduline is abundantly present in the shell and fruits of A. leptantha. In silico studies with aglaithioduline were carried out against the HDAC8 protein target and showed a binding affinity of −8.5 kcal mol. The complex was further subjected to molecular dynamics simulation using Gromacs. The RMSD, RMSF, compactness and SASA plots of the target with aglaithioduline, in comparison with the co-crystallized ligand (SAHA) system, showed a very stable configuration. The results of the study are supportive of the usage of A. leptantha and A. edulis in Indian traditional medicine for the treatment of pain-related ailments similar to RA. Our study therefore calls for further investigation of A. leptantha and A. edulis for their potential use against RA by targeting epigenetic changes, using in vivo and in vitro studies. Full article
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27 pages, 3565 KiB  
Review
Insights into the Conserved Regulatory Mechanisms of Human and Yeast Aging
by Rashmi Dahiya, Taj Mohammad, Mohamed F. Alajmi, Md. Tabish Rehman, Gulam Mustafa Hasan, Afzal Hussain and Md. Imtaiyaz Hassan
Biomolecules 2020, 10(6), 882; https://doi.org/10.3390/biom10060882 - 9 Jun 2020
Cited by 23 | Viewed by 6329
Abstract
Aging represents a significant biological process having strong associations with cancer, diabetes, and neurodegenerative and cardiovascular disorders, which leads to progressive loss of cellular functions and viability. Astonishingly, age-related disorders share several genetic and molecular mechanisms with the normal aging process. Over the [...] Read more.
Aging represents a significant biological process having strong associations with cancer, diabetes, and neurodegenerative and cardiovascular disorders, which leads to progressive loss of cellular functions and viability. Astonishingly, age-related disorders share several genetic and molecular mechanisms with the normal aging process. Over the last three decades, budding yeast Saccharomyces cerevisiae has emerged as a powerful yet simple model organism for aging research. Genetic approaches using yeast RLS have led to the identification of hundreds of genes impacting lifespan in higher eukaryotes. Numerous interventions to extend yeast lifespan showed an analogous outcome in multi-cellular eukaryotes like fruit flies, nematodes, rodents, and humans. We collected and analyzed a multitude of observations from published literature and provide the contribution of yeast in the understanding of aging hallmarks most applicable to humans. Here, we discuss key pathways and molecular mechanisms that underpin the evolutionarily conserved aging process and summarize the current understanding and clinical applicability of its trajectories. Gathering critical information on aging biology would pave the way for future investigation targeted at the discovery of aging interventions. Full article
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23 pages, 1041 KiB  
Article
Dynamic Structure-Based Pharmacophore Model Development: A New and Effective Addition in the Histone Deacetylase 8 (HDAC8) Inhibitor Discovery
by Sundarapandian Thangapandian, Shalini John, Yuno Lee, Songmi Kim and Keun Woo Lee
Int. J. Mol. Sci. 2011, 12(12), 9440-9462; https://doi.org/10.3390/ijms12129440 - 19 Dec 2011
Cited by 44 | Viewed by 10061
Abstract
Histone deacetylase 8 (HDAC8) is an enzyme involved in deacetylating the amino groups of terminal lysine residues, thereby repressing the transcription of various genes including tumor suppressor gene. The over expression of HDAC8 was observed in many cancers and thus inhibition of this [...] Read more.
Histone deacetylase 8 (HDAC8) is an enzyme involved in deacetylating the amino groups of terminal lysine residues, thereby repressing the transcription of various genes including tumor suppressor gene. The over expression of HDAC8 was observed in many cancers and thus inhibition of this enzyme has emerged as an efficient cancer therapeutic strategy. In an effort to facilitate the future discovery of HDAC8 inhibitors, we developed two pharmacophore models containing six and five pharmacophoric features, respectively, using the representative structures from two molecular dynamic (MD) simulations performed in Gromacs 4.0.5 package. Various analyses of trajectories obtained from MD simulations have displayed the changes upon inhibitor binding. Thus utilization of the dynamically-responded protein structures in pharmacophore development has the added advantage of considering the conformational flexibility of protein. The MD trajectories were clustered based on single-linkage method and representative structures were taken to be used in the pharmacophore model development. Active site complimenting structure-based pharmacophore models were developed using Discovery Studio 2.5 program and validated using a dataset of known HDAC8 inhibitors. Virtual screening of chemical database coupled with drug-like filter has identified drug-like hit compounds that match the pharmacophore models. Molecular docking of these hits reduced the false positives and identified two potential compounds to be used in future HDAC8 inhibitor design. Full article
(This article belongs to the Section Physical Chemistry, Theoretical and Computational Chemistry)
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