Diverse classes of HDAC8 inhibitors: in search of molecular fingerprints that regulate activity

Unveiling critical structural features for effective HDAC8 inhibition: a comprehensive study using quantitative read-across structure-activity relationship (q-RASAR) and pharmacophore modeling

Histone deacetylases constitute a group of enzymes that participate in several biological processes. Notably, inhibiting HDAC8 has become a therapeutic strategy for various diseases. The current inhibitors for HDAC8 lack selectivity and target multiple HDACs. Consequently, there is a growing recognition of the need for selective HDAC8 inhibitors to enhance the effectiveness of therapeutic interventions. In our current study, we have utilized a multi-faceted approach, including Quantitative Structure-Activity Relationship (QSAR) combined with Quantitative Read-Across Structure-Activity Relationship (q-RASAR) modeling, pharmacophore mapping, molecular docking, and molecular dynamics (MD) simulations. The developed q-RASAR model has a high statistical significance and predictive ability (Q2F1:0.778, Q2F2:0.775). The contributions of important descriptors are discussed in detail to gain insight into the crucial structural features in HDAC8 inhibition. The best pharmacophore hypothesis exhibits a high regression coefficient (0.969) and a low root mean square deviation (0.944), highlighting the importance of correctly orienting hydrogen bond acceptor (HBA), ring aromatic (RA), and zinc-binding group (ZBG) features in designing potent HDAC8 inhibitors. To confirm the results of q-RASAR and pharmacophore mapping, molecular docking analysis of the five potent compounds (44, 54, 82, 102, and 118) was performed to gain further insights into these structural features crucial for interaction with the HDAC8 enzyme. Lastly, MD simulation studies of the most active compound (54, mapped correctly with the pharmacophore hypothesis) and the least active compound (34, mapped poorly with the pharmacophore hypothesis) were carried out to validate the observations of the studies above. This study not only refines our understanding of essential structural features for HDAC8 inhibition but also provides a robust framework for the rational design of novel selective HDAC8 inhibitors which may offer insights to medicinal chemists and researchers engaged in the development of HDAC8-targeted therapeutics.

A combined ligand-based and structure-based in silico molecular modeling approach to pinpoint the key structural attributes of hydroxamate derivatives as promising meprin β inhibitors

Human meprin β is a Zn2+-containing multidomain metalloprotease enzyme that belongs to the astacin family of the metzincin endopeptidase superfamily. Meprin β, with its diverse tissue expression pattern and wide substrate specificity, plays a significant role in various biological processes, including regulation of IL-6R pathways, lung fibrosis, collagen deposition, cellular migration, neurotoxic amyloid β levels, and inflammation. Again, meprin β is involved in Alzheimer's disease, hyperkeratosis, glomerulonephritis, diabetic kidney injury, inflammatory bowel disease, and cancer. Despite a crucial role in diverse disease processes, no such promising inhibitors of meprin β are marketed to date. Thus, it is an unmet requirement to find novel promising meprin β inhibitors that hold promise as potential therapeutics. In this study, a series of arylsulfonamide and tertiary amine-based hydroxamate derivatives as meprin β inhibitors has been analyzed through ligand-based and structure-based in silico approaches to pinpoint their structural and physiochemical requirements crucial for exerting higher inhibitory potential. This study identified different crucial structural features such as arylcarboxylic acid, sulfonamide, and arylsulfonamide moieties, as well as hydrogen bond donor and hydrophobicity, inevitable for exerting higher meprin β inhibition, providing valuable insight for their further future development.Communicated by Ramaswamy H. Sarma.

Structure-Based Discovery of Selective Histone Deacetylase 8 Degraders with Potent Anticancer Activity

Inducing protein degradation by proteolysis targeting chimeras has gained tremendous momentum as a promising novel therapeutic strategy. Here, we report the design, synthesis, and biological characterization of highly potent proteolysis targeting chimeric small molecules targeting the epigenetic regulator histone deacetylase 8 (HDAC8). We developed potent and effective HDAC8 degraders, as exemplified by SZUH280 (16e), which effectively induced HDAC8 protein degradation and inhibited cancer cell growth even at low micromolar concentrations. Our preliminary mechanistic studies revealed that SZUH280 hampers DNA damage repair in cancer cells, promoting cellular radiosensitization. In mice, a single SZUH280 dose induced rapid and prolonged HDAC8 protein degradation in xenograft tumor tissues. Moreover, SZUH280 alone or in combination with irradiation resulted in long-lasting tumor regression in an A549 tumor mouse model. Our findings qualify a new chemical tool for HDAC8 knockdown and may lead to the development of a new class of cancer therapeutics.

A comparative quantitative structural assessment of benzothiazine-derived HDAC8 inhibitors by predictive ligand-based drug designing approaches

Histone deacetylase 8 (HDAC8) is a verified biomolecular target associated with diverse diseases including cancer. Though several HDAC inhibitors emerged effective against such diseases, no selective HDAC8 inhibitor is approved to date. Therefore, the development of potent HDAC8-selective inhibitors is inevitable to combat such diseases. Here, some benzothiazine-derived HDAC8 inhibitors were considered for a comparative QSAR analysis which may elucidate the prime structural components responsible for modulating their efficacy. Several outcomes from these diverse modelling techniques justified one another and thus validated each other. The ligand-based pharmacophore modelling study identified ring aromatic, positive ionizable, and hydrophobic features as essential structural attributes for HDAC8 inhibition. Besides, MLR, HQSAR and field-based 3D-QSAR studies signified the utility of the positive ionizable and hydrophobic features for potent HDAC8 inhibition. Again, the field-based 3D-QSAR study provided useful insight regarding the substitution in the fused phenyl ring. Moreover, the current observations also validated the previously reported molecular docking observations. Based on the outcomes, some new molecules were designed and predicted. Therefore, this comparative structural analysis of these HDAC8 inhibitors will surely assist in the development of potent HDAC8 inhibitors as promising anticancer therapeutics in the future.

Machine learning & deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry

Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead optimization in drug discovery research, requires molecular representation. Previous reports have demonstrated that machine learning (ML) and deep learning (DL) have substantial implications in virtual screening, peptide synthesis, drug ADMET screening and biomarker discovery. These strategies can increase the positive outcomes in the drug discovery process without false-positive rates and can be achieved in a cost-effective way with a minimum duration of time by high-quality data acquisition. This review substantially discusses the recent updates in AI tools as cheminformatics application in medicinal chemistry for the data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry while improving small-molecule bioactivities and properties.

Exploring sodium glucose cotransporter (SGLT2) inhibitors with machine learning approach: A novel hope in anti-diabetes drug discovery

Conventional anti-diabetes agents exhibit some undesirable side effects. Recently, lactic acidosis and/or bladder cancer were also reported with the use of these agents. Hence, there is an urgent need for alternative anti-diabetes in order to reduce/avoid the unwanted effects. In this scenario sodium glucose cotransporter 2 (SGLT2) inhibitors has already been established as an important class of anti-diabetic drug. The search for new generation SGLT2 inhibitors with high affinity is still an ongoing process. Here, we aim to develop computational models to predict the SGLT2 inhibitory activity of small molecules based on chemical structures. This work provides in-silico analysis to propose possible fragment/fingerprint identification recommended for SGLT2 inhibitors. Up-to-our knowledge, this study is an initiative to propose fingerprints responsible for SGLT2 inhibition. Furthermore, we used nine different algorithms to build machine learning (ML) models that could be used to prioritize compounds as SGLT2 inhibitors from large libraries. The best performing ML models were applied to virtually screen a large collection of FDA approved drugs. The best predicted compounds have been recommended to be biologically investigated in future in order to identify next generation SGLT2 inhibitors with different chemical structure.

Synthesis, anticancer activity, SAR and binding mode of interaction studies of substituted pentanoic acids: part II

Aim: Our previous results suggest that phenyl/naphthylacetyl pentanoic acid derivatives may exhibit dual MMP-2 and HDAC8 inhibitory activities and show effective cytotoxic properties. Methodology: Here, 13 new compounds (C1-C13) were synthesized and characterized. Along with these new compounds, 16 previously reported phenyl/napthylacetyl pentanoic acid derivatives (C14-C29) were biologically evaluated. Results: Compounds C6 and C27 showed good cytotoxicity against leukemia cell line Jurkat E6.1. The mechanisms of cytotoxicity of these compounds were confirmed by DNA deformation assay and reactive oxygen species assay. MMP-2 and HDAC8 expression assays suggested the dual inhibiting property of these two compounds. These findings were supported by results of molecular docking studies. In silico pharmacokinetic properties showed compounds C6 and C27 have high gastrointestinal absorption. Conclusion: This study highlights the action of phenyl/naphthylacetyl pentanoic acid derivatives as anticancer agents.

Unmasking of crucial structural fragments for coronavirus protease inhibitors and its implications in COVID-19 drug discovery

Fragment based drug discovery (FBDD) by the aid of different modelling techniques have been emerged as a key drug discovery tool in the area of pharmaceutical science and technology. The merits of employing these methods, in place of other conventional molecular modelling techniques, endorsed clear detection of the possible structural fragments present in diverse set of investigated compounds and can create alternate possibilities of lead optimization in drug discovery. In this work, two fragment identification tools namely SARpy and Laplacian-corrected Bayesian analysis were used for previous SARS-CoV PLpro and 3CLpro inhibitors. A robust and predictive SARpy based fragments identification was performed which have been validated further by Laplacian-corrected Bayesian model. These comprehensive approaches have advantages since fragments are straight forward to interpret. Moreover, distinguishing the key molecular features (with respect to ECFP_6 fingerprint) revealed good or bad influences for the SARS-CoV protease inhibitory activities. Furthermore, the identified fragments could be implemented in the medicinal chemistry endeavors of COVID-19 drug discovery.

Computational investigations of three main drugs and their comparison with synthesized compounds as potent inhibitors of SARS-CoV-2 main protease (Mpro): DFT, QSAR, molecular docking, and in silico toxicity analysis

In this study, we examined five previously synthesized compounds and checked their binding affinity towards the SARS-CoV-2 main protease (M^pro) by molecular docking study, and compared the data with three FDA approved drugs, i.e., Remdesivir, Ivermectine and Hydroxychlorochine. In addition, we have investigated the docking study against the main protease of SARS-CoV-2 (M^pro) by using Autodock 4.2 software package. The results suggested that the investigated compounds have property to bind the active position of the protein as reported in approved drugs. Hence, further experimental studies are required. The formation of intermolecular interactions, negative values of scoring functions, free binding energy and the calculated binding constants confirmed that the studied compounds have significant affinity for the specified biotarget. These studied compounds were passed the drug-likeness criteria as suggested by calculating ADME data by SwissADME server. Moreover, the ADMET properties suggested that the investigated compounds to be orally active compounds in human. Furthermore, density functional computations (DFT) were executed by applying GAUSSIAN 09 suit program. In addition, Quantitative Structure-Activity Relationship (QSAR) was studied by applying HyperChem Professional 8.0.3 program.

Quantitative activity–activity relationship (QAAR) driven design to develop hydroxamate derivatives of pentanoic acids as selective HDAC8 inhibitors: synthesis, biological evaluation and binding mode of interaction studies

Histone deacetylase 8 (HDAC8) has been implicated as a potential drug target of many diseases including cancer.

Identification of structural fingerprints for ABCG2 inhibition by using Monte Carlo optimization, Bayesian classification, and structural and physicochemical interpretation (SPCI) analysis

The human breast cancer resistance protein (BCRP), one of the members of the large ATP binding cassette (ABC) transporter superfamily, is crucial for resistance against chemotherapeutic agents. Currently, it has been emerged as one of the best biological targets for the designing of small molecule drugs capable of eliminating multidrug resistance in breast cancer. In order to gain insights into the relationship between the molecular structure of compounds and the ABCG2 inhibition, a multi-QSAR approach using different methods was performed on a dataset of 294 ABCG2 inhibitors with diverse scaffolds. The best models obtained by different chemometric methods have the following statistical characteristics: Monte Carlo Optimization-based QSAR (sensitivity = 0.905, specificity = 0.6255, accuracy = 0.756, and MCC = 0.545), Bayesian classification model (sensitivity = 0.735, specificity = 0.775, and concordance = 0.757); structural and physicochemical interpretation analysis-random forest method (balance accuracy = 0.750, sensitivity = 0.810, and specificity = 0.700). Additionally, structural fingerprints modulating the ABCG2 inhibitory properties were identified from the best models of each method and also validated with each other. The current modelling study is an attempt to get a deep insight into the different important structural fingerprints modulating ABCG2 inhibition.

Discriminations of active from inactive HDAC8 inhibitors Part II: Bayesian classification study to find molecular fingerprints

In continuation of our earlier work (Doi: 10.1080/07391102.2019.1661876), a statistically validated and robust Bayesian model was developed on a large diverse set of HDAC8 inhibitors. The training set comprised of 676 small molecules and 293 compounds were considered as test set molecules. The findings of this analysis will help to explore some major directions regarding the HDAC8 inhibitor designing approach. Acrylamide (G1-G3, G9), N-substituted 2-phenylimidazole (G4-G8, G9, G12-G13, G16-G19), benzimidazole (G10-G11), piperidine substituted pyrrole (G13-G14) groups, alkyl/aryl amide (G15) and aryloxy carboxamide (G20) fingerprints were found to play a crucial role in HDAC8 inhibitory activity whereas -CH-N=CH- (B1, B4-B6, B14) motif, benzamide (B2-B3, B9-B13, B16-B17) groups and heptazepine (B7-B8, B15, B18-B20) group were found to influence negatively the HDAC8 inhibitory activity. The importance of such fingerprints was further validated by the HDAC8 enzyme and related inhibitor interactions at the receptor level. These results are in close agreement with those of our previous work that validate each other. Moreover, this comparative learning may enrich future endeavours regarding the designing strategy of HDAC8 inhibitors.

HDAC8 inhibitor attenuates airway responses to antigen stimulus through synchronously suppressing galectin-3 expression and reducing macrophage-2 polarization

BACKGROUND

This study was to investigate of the mechanism by which histone deacetylase (HDAC) 8 inhibitor ameliorated airway hyperresponsiveness (AHR) and allergic airway inflammation.

METHODS

Mice were sensitized and then treated with budesonide (BUD) or PCI-34051 (PCI) prior to exposing to normal saline (NS) or ovalbumin (OVA). The raw264.7 cells were treated with interleukin (IL)-4 and PCI or shRNA alone. Repetitive measurements of enhanced pause (Penh) were executed by increasing concentrations of acetyl-β-methacholine chloride (0 - 50 mg/ml). Cells in bronchoalveolar lavage fluid (BALF) and pathological changes of lungs were examined, respectively. The expression levels of HDAC8, Galecitn (Gal)-3, CD68, CD86, CD163, Arg1 and NOS2 in lungs were measured. Co-regulation of HDAC8 and Gal-3 proteins was observed by immunofluorescence staining and co-immunoprecipitation assay (Co-IP).

RESULTS

Significant increases in Penh and IL-4 level were detected with a large inflammatory infiltrate, comprised predominantly of macrophages and eosinophils, into the BALF in OVA-exposed lungs. HDAC8, Gal-3, CD68, CD86, CD163, Arg1 and NOS2 proteins were over-expressed with the significant changes in the Arg1 and NOS2 mRNA levels in the lungs and the IL-4-treated cells. PCI intervention obviously reduced the counts of CD163+ cells. Furthermore, Gal-3 knockdown suppressed Arg1 expression in the cells. Immunofluorescence staining displayed simultaneous changes in HDAC8 and Gal-3 expression in the investigated samples. Treatment with PCI resulted in synchronous reduction of HDAC8 and Gal-3 expression in the Co-IP complexes.

CONCLUSIONS

The HDAC8 inhibitor ameliorates AHR and airway inflammation in animal model of allergic asthma through reducing HDAC8-Gal-3 interaction and M2 macrophage polarization.

Exploring indole derivatives as myeloid cell leukaemia-1 (Mcl-1) inhibitors with multi-QSAR approach: a novel hope in anti-cancer drug discovery

In humans, the over-expression of Mcl-1 protein causes different cancers and it is also responsible for cancer resistance to different cytotoxic agents.

In silico modelling, identification of crucial molecular fingerprints, and prediction of new possible substrates of human organic cationic transporters 1 and 2

The cation membrane transporters are crucial to regulate movement of foreign molecules within the body. The present study found out structural fingerprints within molecules to be recognized as substrate/non-substrate against these transporters.

Insight into structural features of phenyltetrazole derivatives as ABCG2 inhibitors for the treatment of multidrug resistance in cancer

ABCG2 is the principal ABC transporter involved in the multidrug resistance of breast cancer. Looking at the current demand in the development of ABCG2 inhibitors for the treatment of multidrug-resistant cancer, we have explored structural requirements of phenyltetrazole derivatives for ABCG2 inhibition by combining classical QSAR, Bayesian classification modelling and molecular docking studies. For classical QSAR, structural descriptors were calculated from the free software tool PaDEL-descriptor. Stepwise multiple linear regression (SMLR) was used for model generation. A statistically significant model was generated and validated with different parameters (For training set: r = 0.825; Q² = 0.570 and for test set: r = 0.894, r²_pred = 0.783). The predicted model was found to satisfy the Golbraikh and Trospha criteria for model acceptability. Bayesian classification modelling was also performed (ROC scores were 0.722 and 0.767 for the training and test sets, respectively). Finally, the binding interactions of phenyltetrazole type inhibitor with the ABCG2 receptor were mapped with the help of molecular docking study. The result of the docking analysis is aligned with the classical QSAR and Bayesian classification studies. The combined modelling study will guide the medicinal chemists to act faster in the drug discovery of ABCG2 inhibitors for the management of resistant breast cancer.

Synthesis, anticancer activity, structure–activity relationship and binding mode of interaction studies of substituted pentanoic acids

Aim: Simultaneous inhibition of MMP-2 and HDAC8 may be an effective strategy to target cancer. Methodology: In continuation of our earlier efforts, a series of substituted pentanoic acids (1–18) were synthesized and checked for their biological activity along with some earlier reported compounds (19 –35). Results: Compounds 18 and 31 were found to induce apoptosis effectively in a dose-dependent fashion in Jurkat-E6.1 cell line. They reduced the expression of both MMP-2 and HDAC8 effectively. 31 also produced prominent intensity of fluorescence to bring nick in Jurkat-E6.1 cells. 31 also showed cellular arrest in sub-G0 phase. Conclusion: Such compounds may be useful to battle against cancer.

Structural exploration of tetrahydroisoquinoline derivatives as HDAC8 inhibitors through multi-QSAR modeling study

Histone deacetylase 8 (HDAC8) is one of the crucial HDACs responsible for influencing the epigenetic functions of the body. Overexpression of HDAC8 is found to be involved in numerous disease conditions such as tumorigenesis, cell proliferation, cancer, viral infections, neuronal disorders and other epigenetic diseases. Therefore, inhibition of HDAC8 is a primary method to combat these diseases. In this article, a multi-QSAR modeling study on tetrahydroisoquinoline derivatives was conducted to identify important contributions of the structural features of these compounds toward HDAC8 inhibition. All these QSAR modeling techniques were individually validated and justified the observations of each other. The results implied that the tetrahydroisoquinoline moiety may be effective as a cap group than as a linker moiety for HDAC8 inhibition. Different substitutions at the tetrahydroisoquinoline scaffold were also found to be crucial in modulating HDAC8 inhibition.Communicated by Ramaswamy H. Sarma.

Exploration of good and bad structural fingerprints for inhibition of indoleamine-2,3-dioxygenase enzyme in cancer immunotherapy using Monte Carlo optimization and Bayesian classification QSAR modeling

Indoleamine-2,3-dioxygenase 1 (IDO1) is an extrahepatic, heme-containing and tryptophan-catalyzing enzyme responsible for causing blockade of T-cell proliferation and differentiation by depleting tryptophan level in cancerous cells. Therefore, inhibition of IDO1 may be a useful strategy for immunotherapy against cancer. In this study, 448 structurally diverse IDO1 inhibitors with a wide range of activity has been taken into consideration for classification QSAR analysis through Monte Carlo Optimization by using different splits as well as different combinations of SMILES-based, graph-based and hybrid descriptors. The best model from Monte Carlo optimization was interpreted to find out the good and bad structural fingerprints for IDO1 and further justified by using Bayesian classification QSAR modeling. Among the three splits in Monte Carlo optimization, the statistics of the best model was obtained from Split 3: sensitivity = 0.87, specificity = 0.91, accuracy = 0.89 and MCC = 0.78. In Bayesian classification modeling, the ROC scores for training and test set were found to be 0.91 and 0.86, respectively. The combined modeling analysis revealed that the presence of aryl hydrazyl sulphonyl moiety, furazan ring, halogen substitution, nitro group and hetero atoms in aromatic system can be very useful in designing IDO1 inhibitors. All the good and bad structural fingerprints for IDO1 were identified and are justified by correlating these fragments to the inhibition of IDO1 enzyme. These structural fingerprints will guide the researchers in this field to design better inhibitors against IDO1 enzyme for cancer immunotherapy.Communicated by Ramaswamy H. Sarma.

Selective and nonselective HDAC8 inhibitors: a therapeutic patent review

Histone deacetylase 8 (HDAC8) is one of the attractive therapeutic anticancer targets. HDAC8 has been overexpressed in a variety of human cancers. Therefore, HDAC8 inhibitors offer beneficial effects in the treatment of solid and hematological tumors. Different HDAC inhibitors entered into different phases of clinical studies. However, selectivity towards specific HDAC8 enzyme is still demanding. In this patent review, a number of patented selective and nonselective HDAC8 inhibitors along with their implication as anticancer agents have been discussed in details. Molecules should possess modified fish-like structural arrangement to impart potency and selectivity towards HDAC8. This comprehensive patent analysis will surely provide newer aspects of designing selective HDAC8 inhibitors targeted to anticancer therapy in future.

Histone deacetylase 8 (HDAC8) and its inhibitors with selectivity to other isoforms: An overview

The histone deacetylases (HDACs) enzymes provided crucial role in transcriptional regulation of cells through deacetylation of nuclear histone proteins. Discoveries related to the HDAC8 enzyme activity signified the importance of HDAC8 isoform in cell proliferation, tumorigenesis, cancer, neuronal disorders, parasitic/viral infections and other epigenetic regulations. The pan-HDAC inhibitors can confront these conditions but have chances to affect epigenetic functions of other HDAC isoforms. Designing of selective HDAC8 inhibitors is a key feature to combat the pathophysiological and diseased conditions involving the HDAC8 activity. This review is concerned about the structural and positional aspects of HDAC8 in the HDAC family. It also covers the contributions of HDAC8 in the pathophysiological conditions, a preliminary discussion about the recent scenario of HDAC8 inhibitors. This review might help to deliver the structural, functional and computational information in order to identify and design potent and selective HDAC8 inhibitors for target specific treatment of diseases involving HDAC8 enzymatic activity.