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

Pinpointing prime structural attributes of potential MMP-2 inhibitors comprising alkyl/arylsulfonyl pyrrolidine scaffold: a ligand-based molecular modelling approach validated by molecular dynamics simulation analysis

MMP-2 overexpression is strongly related to several diseases including cancer. However, none of the MMP-2 inhibitors have been marketed as drug candidates due to various adverse effects. Here, a set of sulphonyl pyrrolidines was subjected to validation of molecular modelling followed by binding mode analysis to explore the crucial structural features required for the discovery of promising MMP-2 inhibitors. This study revealed the importance of hydroxamate as a potential zinc-binding group compared to the esters. Importantly, hydrophobic and sterical substituents were found favourable at the terminal aryl moiety attached to the sulphonyl group. The binding interaction study revealed that the S1' pocket of MMP-2 similar to 'a basketball passing through a hoop' allows the aryl moiety for proper fitting and interaction at the active site to execute potential MMP-2 inhibition. Again, the sulphonyl pyrrolidine moiety can be a good fragment necessary for MMP-2 inhibition. Moreover, some novel MMP-2 inhibitors were also reported. They showed the significance of the 3rd position substitution of the pyrrolidine ring to produce interaction inside S2' pocket. The current study can assist in the design and development of potential MMP-2 inhibitors as effective drug candidates for the management of several diseases including cancers in the future.

A patent review of histone deacetylase 8 (HDAC8) inhibitors (2013-present)

INTRODUCTION

The processes and course of several fatal illnesses, such as cancer, inflammatory diseases, and neurological disorders are closely correlated with HDAC8. Therefore, novel HDAC8 inhibitors represent effective therapeutic possibilities that may help treat these conditions. To yet, there are not any such particular HDAC8 inhibitors available for sale. This review was conducted to examine recent HDAC8 inhibitors that have been patented over the last 10 years.

AREAS COVERED

This review focuses on HDAC8 inhibitor-related patents and their therapeutic applications that have been published within the last 10 years and are accessible through the Patentscope and Google Patents databases.

EXPERT OPINION

A handful of HDAC8 inhibitor-related patents have been submitted over the previous 10 years, more selective, and specific HDAC8 inhibitors that are intended to treat a variety of medical diseases. This could lead to the development of novel treatment approaches that target HDAC8. Employing theoretical frameworks and experimental procedures can reveal the creation of new HDAC8 inhibitors with enhanced pharmacokinetic characteristics. A thorough understanding of the role that HDAC8 inhibitors play in cancer, including the mechanisms behind HDAC8 in other disorders is necessary.

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.

Density functional theory (DFT) studies in HDAC-based chemotherapeutics: Current findings, case studies and future perspectives

Density Functional Theory (DFT) is a quantum chemical computational method used to predict and analyze the electronic properties of atoms, molecules, and solids based on the density of electrons rather than wavefunctions. It provides insights into the structure, bonding, and behavior of different molecules, including those involved in the development of chemotherapeutic agents, such as histone deacetylase inhibitors (HDACis). HDACs are a wide group of metalloenzymes that facilitate the removal of acetyl groups from acetyl-lysine residues situated in the N-terminal tail of histones. Abnormal HDAC recruitment has been linked to several human diseases, especially cancer. Therefore, it has been recognized as a prospective target for accelerating the development of anticancer therapies. Researchers have studied HDACs and its inhibitors extensively using a combination of experimental methods and diverse in-silico approaches such as machine learning and quantitative structure-activity relationship (QSAR) methods, molecular docking, molecular dynamics, pharmacophore mapping, and more. In this context, DFT studies can make significant contribution by shedding light on the molecular properties, interactions, reaction pathways, transition states, reactivity and mechanisms involved in the development of HDACis. This review attempted to elucidate the scope in which DFT methodologies may be used to enhance our comprehension of the molecular aspects of HDAC inhibitors, aiding in the rational design and optimization of these compounds for therapeutic applications in cancer and other ailments. The insights gained can guide experimental efforts toward developing more potent and selective HDAC inhibitors.

Advances in targeting histone deacetylase for treatment of solid tumors

Histone deacetylase (HDAC) serves as a critical molecular regulator in the pathobiology of various malignancies and have garnered attention as a viable target for therapeutic intervention. A variety of HDAC inhibitors (HDACis) have been developed to target HDACs. Many preclinical studies have conclusively demonstrated the antitumor effects of HDACis, whether used as monotherapy or in combination treatments. On this basis, researchers have conducted various clinical studies to evaluate the potential of selective and pan-HDACis in clinical settings. In our work, we extensively summarized and organized current clinical trials, providing a comprehensive overview of the current clinical advancements in targeting HDAC therapy. Furthermore, we engaged in discussions about several clinical trials that did not yield positive outcomes, analyzing the factors that led to their lack of anticipated therapeutic effectiveness. Apart from the experimental design factors, issues such as toxicological side effects, tumor heterogeneity, and unexpected off-target effects also contributed to these less-than-expected results. These challenges have naturally become significant barriers to the application of HDACis. Despite these challenges, we believe that advancements in HDACi research and improvements in combination therapies will pave the way or lead to a broad and hopeful future in the treatment of solid tumors.

The Histone Deacetylase Family: Structural Features and Application of Combined Computational Methods

Histone deacetylases (HDACs) are crucial in gene transcription, removing acetyl groups from histones. They also influence the deacetylation of non-histone proteins, contributing to the regulation of various biological processes. Thus, HDACs play pivotal roles in various diseases, including cancer, neurodegenerative disorders, and inflammatory conditions, highlighting their potential as therapeutic targets. This paper reviews the structure and function of the four classes of human HDACs. While four HDAC inhibitors are currently available for treating hematological malignancies, numerous others are undergoing clinical trials. However, their non-selective toxicity necessitates ongoing research into safer and more efficient class-selective or isoform-selective inhibitors. Computational methods have aided the discovery of HDAC inhibitors with the desired potency and/or selectivity. These methods include ligand-based approaches, such as scaffold hopping, pharmacophore modeling, three-dimensional quantitative structure-activity relationships, and structure-based virtual screening (molecular docking). Moreover, recent developments in the field of molecular dynamics simulations, combined with Poisson-Boltzmann/molecular mechanics generalized Born surface area techniques, have improved the prediction of ligand binding affinity. In this review, we delve into the ways in which these methods have contributed to designing and identifying HDAC inhibitors.

Fragment-based investigation of thiourea derivatives as VEGFR-2 inhibitors: a cross-validated approach of ligand-based and structure-based molecular modeling studies

Angiogenesis is mediated by the vascular endothelial growth factor (VEGF) that plays a key role in the modulation of progression, invasion and metastasis, related to solid tumors and hematological malignancies. Several small-molecule VEGFR-2 inhibitors are marketed, but their usage is restricted to specific cancers due to severe toxicities. Therefore, cost-effective novel small molecule VEGFR-2 inhibitors may be an alternative to overcome these adverse effects. Here, a set of thiourea-based VEGFR-2 inhibitors were considered for a combined fragment-based QSAR technique, structure-based molecular docking followed by molecular dynamics simulation studies to acquire insights into the key structural attributes and the binding pattern of enzyme-ligand interactions. Noticeably, amine-substituted quinazoline phenyl ring and a higher number of nitrogen atoms, and the hydrazide function in the molecular structure are crucial for VEGFR-2 inhibition whereas methoxy groups are detrimental to VEGFR-2 inhibition. The MD simulation study of sorafenib and thiourea derivatives explored the significance of urea and thiourea moiety binding at VEGFR-2 active site that can be utilized further in the future to design molecules for greater binding stability and better VEGFR-2 selectivity. Therefore, such findings can be beneficial for the development of newer VEGFR-2 inhibitors for further refinement to acquire better therapeutic efficacy.Communicated by Ramaswamy H. Sarma.

In the quest for histone deacetylase inhibitors: current trends in the application of multilayered computational methods

Histone deacetylase (HDAC) inhibitors have gained attention over the past three decades because of their potential in the treatment of different diseases including various forms of cancers, neurodegenerative disorders, autoimmune, inflammatory diseases, and other metabolic disorders. To date, 5 HDAC inhibitor drugs are marketed for the treatment of hematological malignancies and several drug-candidate HDAC inhibitors are at different stages of clinical trials. However, due to the toxic side effects of these drugs resulting from the lack of target selectivity, active studies are ongoing to design and develop either class-selective or isoform-selective inhibitors. Computational methods have aided the discovery of HDAC inhibitors with the desired potency and/or selectivity. These methods include ligand-based approaches such as scaffold hopping, pharmacophore modeling, three-dimensional quantitative structure-activity relationships (3D-QSAR); and structure-based virtual screening (molecular docking). The current trends involve the application of the combination of these methods and incorporating molecular dynamics simulations coupled with Poisson-Boltzmann/molecular mechanics generalized Born surface area (MM-PBSA/MM-GBSA) to improve the prediction of ligand binding affinity. This review aimed at understanding the current trends in applying these multilayered strategies and their contribution to the design/identification of HDAC inhibitors.

Fragment-based structural exploration and chemico-biological interaction study of HDAC3 inhibitors through non-linear pattern recognition, chemical space, and binding mode of interaction analysis

HDAC3 is an emerging target for the identification and discovery of novel drug candidates against several disease conditions including cancer. Here, a fragment-based non-linear machine learning (ML) method along with chemical space exploration followed by a structure-based binding mode of interaction analysis study was carried out on some HDAC3 inhibitors to obtain the key structural features modulating HDAC3 inhibition. Both the ML and chemical space analysis identified several physicochemical and structural properties namely lipophilicity, polar and relative polar surface area, arylcarboxamide moiety, bulky fused aromatic group, n-alkyl, and cinnamoyl moieties, the higher number of oxygen atoms, π-electrons for the substituted tetrahydrofuronaphthodioxolone moiety favorable for higher HDAC3 inhibition. Moreover, hydrogen bond forming capabilities, the length and substitution position of the linker moiety, the importance of phenyl ring in the linker motif, the contribution of heterocyclic cap moieties for effective inhibitor binding at the HDAC3 catalytic site that correspondingly affects the HDAC3 inhibitory potency. Again, macrocyclic ring structure and cyclohexyl cap moiety are responsible for lower HDAC3 inhibition. The MD simulation study of selected compounds explained strong binding patterns at the HDAC3 active site as evidenced by the lower RMSD and RMSF values. Nevertheless, it also explained the importance of the crucial structural fragments derived from the fragment-based analysis during ligand-enzyme interactions. Therefore, the outcomes of this current structural analysis will be a useful tool for fragment-based drug discovery of effective HDAC3 inhibitors for clinical therapeutics in the future.Communicated by Ramaswamy H. Sarma.

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.

The first report on predictive comparative ligand-based multi-QSAR modeling analysis of 4-pyrimidinone and 2-pyridinone based APJ inhibitors

The APJ system participates in several major disorders including cancer. A multi-QSAR modeling study on some APJ inhibitors was performed for the first time. Some potential molecules were also designed based on the QSAR study conducted.

Molecular modeling studies of novel naphthyridine and isoquinoline derivatives as CDK8 inhibitors

Cell cycle is an important part of cellular activities. The selective inhibition of cyclin-dependent kinases (CDK) activity in tumor cells can lead to continuous cell proliferation. Thirty-nine CDK8 inhibitors were systematically investigated on the basis of a three-dimensional quantitative structure-activity relationship (3D-QSAR). Models for comparative molecular field analysis (q²=0.64, r²=0.98) and comparative molecular similarity index analysis (q²=0.609, r²=0.952) were obtained. Contour maps illustrated that bioactivity of inhibitors is most affected by steric, electrostatic, hydrogen bond donor, and receptor interactions of molecular groups. Twenty new CDK8 inhibitors (DS01-DS20) were designed based on the contour maps. The results of ADME prediction illustrated that the designed compounds had potential druggability. The binding mode between a ligand and receptor was explored through molecular docking and molecular dynamics. Results revealed that the hydrogen bond interaction with residue LYS52 remarkably affected the activity of these compounds. Further analysis indicated that the introduction of fluorine to an amino naphthyridine ring of compound 28 contributes to the improvement of molecular activities. Pharmacophore-based virtual screening and Surflex-Sim in the ZINC database of 1,30,000 molecules demonstrated that 14 compounds with an indazole ring might be antitumor inhibitors. 3D-QSAR, molecular docking, molecular dynamics and pharmacophore results are consistent. These findings can be used as a reference for the design and discovery of new CDK8 inhibitors that can reduce design errors.Communicated by Ramaswamy H. Sarma.

Exploring the structural aspects of ureido-amino acid-based APN inhibitors: a validated comparative multi-QSAR modelling study

The zinc-dependent enzyme aminopeptidase N (APN) is a member of the M1 metalloenzyme family. The multi-functionality of APN as a peptidase, a receptor and a signalling molecule has provided it the access to influence a number of disease conditions namely viral diseases, angiogenesis, cellular metastasis and invasion including different cancer conditions. Hence, the development of potent APN inhibitors is a possible route for the treatment of diseases related to the activity of APN. In this study, different QSAR approaches have been adopted to identify the structural features of a group of hydroxamate-based ureido-amino acid derivative APN inhibitors. This study was able to identify different constitutional aspects of these APN inhibitors which are important for their inhibitory potency. Additionally, some of these observations were also aligned with the observations of previously performed QSAR studies conducted on different APN inhibitors. Therefore, the results of this study may help to design potent and effective APN inhibitors in the future.

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.

Identification of HDAC6 selective inhibitors: pharmacophore based virtual screening, molecular docking and molecular dynamics simulation

HDAC6 regulates the expression and activity of various tumor-related proteins, but currently there is no selective inhibitor targeting HDAC6 for clinical application. In order to discover novel HDAC6 inhibitors, virtual screening methods comprised of pharmacophore based virtual screening, molecular docking and molecular dynamics (MD) simulations were employed. 15 molecules were obtained after virtual screening. After in vitro bioassays, two of the hits showed inhibition activity against HDAC6, among which the inhibition activity of G1 to HDAC6 reached 81% at concentration of 20 μM. In addition, the inhibitory activity against HDAC1 and HDAC10 demonstrated that G1 and G10 were highly selective to HDAC6. The analysis of the binding modes of G1 and G10 provides a reference for further development of highly active HDAC6 inhibitors. Communicated by Ramaswamy H. Sarma.