Molecular modeling study of uracil-based hydroxamic acids-containing histone deacetylase inhibitors

Sharma, Mukesh C.; Sharma, Saksham

doi:10.1016/j.arabjc.2014.12.030

Cited by 3 publications

(2 citation statements)

References 30 publications

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“…Histone deacetylases (HDACs) forms one of the promising classes of anti-cancer drug targets as they are capable of reversing abnormal epigenetic states related to cancer. Cell-cycle arrest, apoptosis, and differentiation are some of the cell type-specific effects that they elicit [19]. HDAC6, a member of the HDAC family, is known to be upregulated in OSCC and it increases during the advanced stages of the cancer.…”

Section: Introductionmentioning

confidence: 99%

Virtual screening for novel inhibitors of human Histone Deacetylase 6: Promising new leads for Oral Squamous Cell Carcinoma

Vijayasarathy¹,

Chatterjee²

2021

J App Biol Biotech

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Over 90% of Oral Cancers are Oral Squamous Cell Carcinomas (OSCCs). Despite having advanced treatment modalities, there is no significant improvement in the survival rate of Oral Cancer patients over the years. Thus, there arises a need for the identification of new drug targets besides development of new and effective drugs for this disease. Since Histone Deacetylase 6 (HDAC6), a class IIB member of HDAC family, is known to be upregulated in this disease in addition to being associated with tumor growth, it can be considered as a promising drug target for this disease. In this study, a structure-based virtual screening strategy was used to screen a library of 1,539 natural compounds from Naturally Occurring Plant-based Anti-cancerous Compound-Activity-Target (NPACT) database. Upon filtering and docking, top 30 hits were identified and two of them, namely Camptothecin and Diosgenin, were tested experimentally on OSCCs cell lines for anti-proliferative effects. Both of these compounds exhibited inhibitory activity against Oral Cancer cells, therefore suggesting that they can be potential HDAC6 inhibitors, which can further serve as promising leads for OSCCs.

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Section: Introductionmentioning

confidence: 99%

Virtual screening for novel inhibitors of human Histone Deacetylase 6: Promising new leads for Oral Squamous Cell Carcinoma

Vijayasarathy¹,

Chatterjee²

2021

J App Biol Biotech

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“…1). These compounds were recollected from published To predict HDAC inhibition activity Sharma and Sharma [20] QSAR: Quantitative structure-activity relationship, HDAC: Histone deacetylase…”

Section: Datasetmentioning

confidence: 99%

Integrating Structure and Ligand-Based Approaches for Modelling the Histone Deacetylase Inhibition Activity of Hydroxamic Acid Derivatives

Pham-The

Le-Thi-Thu

2018

Asian J Pharm Clin Res

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Objective: Structure and ligand-based drug design approaches have be been integrated to accurately predict the inhibition activity of hydroxamic acid (HA) derivatives against the histone deacetylase-2 enzyme (HDAC2). Methods:The "active conformations" of the ligands in the binding site of the enzyme were determined by docking assays. More than 1000 0-3 dimensional molecular descriptors included in Dragon package were calculated and utilized for developing quantitative structure-activity relationship (QSAR) models through a multiple linear regression approach coupled with the genetic algorithm (GA-MLR). Results:The final model obtained showed suitable robustness and stability, with low correlation between descriptors and good predictive power. QSAR model was then used for screening bioactivity from a series of 36 novel HAs and found five candidates with very good bioactivity (half maximal inhibitory concentration<0.1 μM). Docking experiment revealed the binding mode of these compounds into the active site of HDAC2. Druglikeness and toxicity profiles of the compounds were checked through chemoinformatics tools. Conclusion:The results from this study can lead to rational design and synthesis of highly selective and potent HDAC2 inhibitors.

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QSAR Regression Models for Predicting HMG-CoA Reductase Inhibition

Ancuceanu,

Popovici,

Drăgănescu

et al. 2024

Pharmaceuticals

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Background/Objectives: HMG-CoA reductase is an enzyme that regulates the initial stage of cholesterol synthesis, and its inhibitors are widely used in the treatment of cardiovascular diseases. Methods: We have created a set of quantitative structure-activity relationship (QSAR) models for human HMG-CoA reductase inhibitors using nested cross-validation as the primary validation method. To develop the QSAR models, we employed various machine learning regression algorithms, feature selection methods, and fingerprints or descriptor datasets. Results: We built and evaluated a total of 300 models, selecting 21 that demonstrated good performance (coefficient of determination, R2 ≥ 0.70 or concordance correlation coefficient, CCC ≥ 0.85). Six of these top-performing models met both performance criteria and were used to construct five ensemble models. We identified the descriptors most important in explaining HMG-CoA inhibition for each of the six best-performing models. We used the top models to search through over 220,000 chemical compounds from a large database (ZINC 15) for potential new inhibitors. Only a small fraction (237 out of approximately 220,000 compounds) had reliable predictions with mean pIC50 values ≥ 8 (IC50 values ≤ 10 nM). Our svm-based ensemble model predicted IC50 values < 10 nM for roughly 0.08% of the screened compounds. We have also illustrated the potential applications of these QSAR models in understanding the cholesterol-lowering activities of herbal extracts, such as those reported for an extract prepared from the Iris × germanica rhizome. Conclusions: Our QSAR models can accurately predict human HMG-CoA reductase inhibitors, having the potential to accelerate the discovery of novel cholesterol-lowering agents and may also be applied to understand the mechanisms underlying the reported cholesterol-lowering activities of herbal extracts.

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Molecular modeling study of uracil-based hydroxamic acids-containing histone deacetylase inhibitors

Cited by 3 publications

References 30 publications

Virtual screening for novel inhibitors of human Histone Deacetylase 6: Promising new leads for Oral Squamous Cell Carcinoma

Virtual screening for novel inhibitors of human Histone Deacetylase 6: Promising new leads for Oral Squamous Cell Carcinoma

Integrating Structure and Ligand-Based Approaches for Modelling the Histone Deacetylase Inhibition Activity of Hydroxamic Acid Derivatives

QSAR Regression Models for Predicting HMG-CoA Reductase Inhibition

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