Derivatives of D(-) glutamine-based MMP-2 inhibitors as an effective remedy for the management of chronic myeloid leukemia-Part-I: Synthesis, biological screening and in silico binding interaction analysis.

Chronic myeloid leukemia (CML) is a global issue and the available drugs such as tyrosine kinase inhibitors (TKIs) comprise various toxic effects as well as resistance and cross-resistance. Therefore, novel molecules targeting specific enzymes may unravel a new direction in antileukemic drug discovery. In this context, targeting gelatinases (MMP-2 and MMP-9) can be an alternative option for the development of novel molecules effective against CML. In this article, some D(-)glutamine derivatives were synthesized and evaluated through cell-based antileukemic assays and tested against gelatinases. The lead compounds, i.e., benzyl analogs exerted the most promising antileukemic potential showing nontoxicity in normal cell line including efficacious gelatinase inhibition. Both these lead molecules yielded effective apoptosis and displayed marked reductions in MMP-2 expression in the K562 cell line. Not only that, but both of them also revealed effective antiangiogenic efficacy. Importantly, the most potent MMP-2 inhibitor, i.e., benzyl derivative of p-tosyl D(-)glutamine disclosed stable binding interaction at the MMP-2 active site correlating with the highly effective MMP-2 inhibitory activity. Therefore, such D(-)glutamine derivatives might be explored further as promising MMP-2 inhibitors with efficacious antileukemic profiles for the treatment of CML in the future.

Identification of structural fingerprints among natural inhibitors of HDAC1 to accelerate nature-inspired drug discovery in cancer epigenetics.

Histone deacetylase 1 (HDAC1), a class I HDAC enzyme, is crucial for histone modification. Currently, it is emerged as one of the important biological targets for designing small molecule drugs through cancer epigenetics. Along with synthetic inhibitors different natural inhibitors are showing potential HDAC1 inhibitions. In order to gain insights into the relationship between the molecular structures of the natural inhibitors and HDAC1, different molecular modelling techniques (Bayesian classification, recursive partitioning, molecular docking and molecular dynamics simulations) have been applied on a dataset of 155 HDAC1 nature-inspired inhibitors with diverse scaffolds. The Bayesian study showed acceptable ROC values for both the training set and test sets. The Recursive partitioning study produced decision tree 1 with 6 leaves. Further, molecular docking study was processed for generating the protein ligand complex which identified some potential amino acid residues such as F205, H28, L271, P29, F150, Y204 for the binding interactions in case of natural inhibitors. Stability of these HDAC1-natutal inhibitors complexes has been also evaluated by molecular dynamics simulation study. The current modelling study is an attempt to get a deep insight into the different important structural fingerprints among different natural compounds modulating HDAC1 inhibition.Communicated by Ramaswamy H. Sarma.

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.

Unraveling HDAC11: Epigenetic orchestra in different diseases and structural insights for inhibitor design.

Histone deacetylase 11 (HDAC11), a member of the HDAC family, has emerged as a critical regulator in numerous physiological as well as pathological processes. Due to its diverse roles, HDAC11 has been a focal point of research in recent times. Different non-selective inhibitors are already approved, and research is going on to find selective HDAC11 inhibitors. The objective of this review is to comprehensively explore the role of HDAC11 as a pivotal regulator in a multitude of physiological and pathological processes. It aims to delve into the intricate details of HDAC11's structural and functional aspects, elucidating its molecular interactions and implications in different disease contexts. With a primary focus on elucidating the structure-activity relationships (SARs) of HDAC11 inhibitors, this review also aims to provide a holistic understanding of how its molecular architecture influences its inhibition. Additionally, by integrating both established knowledge and recent research, the review seeks to contribute novel insights into the potential therapeutic applications of HDAC11 inhibitors. Overall, the scope of this review spans from fundamental research elucidating the complexities of HDAC11 biology to the potential of targeting HDAC11 in therapeutic interventions.

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.

An assessment of crucial structural contributors of HDAC6 inhibitors through fragment-based non-linear pattern recognition and molecular dynamics simulation approaches.

Amidst the Zn2+-dependant isoforms of the HDAC family, HDAC6 has emerged as a potential target associated with an array of diseases, especially cancer and neuronal disorders like Rett's Syndrome, Alzheimer's disease, Huntington's disease, etc. Also, despite the availability of a handful of HDAC inhibitors in the market, their non-selective nature has restricted their use in different disease conditions. In this situation, the development of selective and potent HDAC6 inhibitors will provide efficacious therapeutic agents to treat different diseases. In this context, this study has been carried out to evaluate the potential structural contributors of quinazoline-cap-containing HDAC6 inhibitors via machine learning (ML), conventional classification-dependant QSAR, and MD simulation-based binding mode of interaction analysis toward HDAC6 binding. This combined conventional and modern molecular modeling study has revealed the significance of the quinazoline moiety, substitutions present at the quinazoline cap group, as well as the importance of molecular property, number of hydrogen bond donor-acceptor functions, carbon-chlorine distance that significantly affects the HDAC6 binding of these inhibitors, subsequently affecting their potency . Interestingly, the study also revealed that the substitutions such as the chloroethyl group, and bulky quinazolinyl cap group can affect the binding of the cap function with the amino acid residues present in the loops proximal to the catalytic site of HDAC6. Such contributions of cap groups can lead to both stabilization and destabilization of the cap function after occupying the hydrophobic catalytic site by the aryl hydroxamate linker-ZBG functions.

Exploration of Fingerprints and Data Mining-based Prediction of Some Bioactive Compounds from Allium sativum as Histone Deacetylase 9 (HDAC9) Inhibitors.

BACKGROUND: Histone deacetylase 9 (HDAC9) is an important member of the class IIa family of histone deacetylases. It is well established that over-expression of HDAC9 causes various types of cancers including gastric cancer, breast cancer, ovarian cancer, liver cancer, lung cancer, lymphoblastic leukaemia, etc. The important role of HDAC9 is also recognized in the development of bone, cardiac muscles, and innate immunity. Thus, it will be beneficial to find out the important structural attributes of HDAC9 inhibitors for developing selective HDAC9 inhibitors with higher potency. METHODS: The classification QSAR-based methods namely Bayesian classification and recursive partitioning method were applied to a dataset consisting of HADC9 inhibitors. The structural features strongly suggested that sulphur-containing compounds can be a good choice for HDAC9 inhibition. For this reason, these models were applied further to screen some natural compounds from Allium sativum. The screened compounds were further accessed for the ADME properties and docked in the homology-modelled structure of HDAC9 in order to find important amino acids for the interaction. The best-docked compound was considered for molecular dynamics (MD) simulation study. RESULTS: The classification models have identified good and bad fingerprints for HDAC9 inhibition. The screened compounds like ajoene, 1,2 vinyl dithiine, diallyl disulphide and diallyl trisulphide had been identified as compounds having potent HDAC9 inhibitory activity. The results from ADME and molecular docking study of these compounds show the binding interaction inside the active site of the HDAC9. The best-docked compound ajoene shows satisfactory results in terms of different validation parameters of MD simulation study. CONCLUSION: This in-silico modelling study has identified the natural potential lead (s) from Allium sativum. Specifically, the ajoene with the best in-silico features can be considered for further in-vitro and in-vivo investigation to establish as potential HDAC9 inhibitors.

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

Human meprin ß is a Zn2+-containing multidomain metalloprotease enzyme that belongs to the astacin family of the metzincin endopeptidase superfamily. Meprin ß, 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 ß levels, and inflammation. Again, meprin ß 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 ß are marketed to date. Thus, it is an unmet requirement to find novel promising meprin ß inhibitors that hold promise as potential therapeutics. In this study, a series of arylsulfonamide and tertiary amine-based hydroxamate derivatives as meprin ß 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 ß inhibition, providing valuable insight for their further future development.Communicated by Ramaswamy H. Sarma.

Advances in structure-activity relationships of HDAC inhibitors as HIV latency-reversing agents.

INTRODUCTION: HIV-infected cells may rebound due to the existence of the silent HIV-infected memory CD4+ T cells (HIV latency). This HIV latency makes the disease almost incurable. In latency, the integrated proviral DNA of HIV is transcriptionally silenced partly due to the activity of histone deacetylases (HDACs). Hence, inhibition of HDAC is considered a prime target for HIV latency reversal. AREAS COVERED: A brief biology and function of HDACs have been discussed to identify key points to design HDAC inhibitors (HDACis). This article summarizes recent achievements in the development of HDACis to achieve HIV latency reversal. Structure-activity relationships (SARs) of some series of compounds were also explored. EXPERT OPINION: Depletion of the HIV reservoir is the only way to end this deadly epidemic. HDACis are latency-reversing agents (LRA) that can be used to 'shock' the latently infected CD4+ T cells to induce them to produce viral proteins. It is interesting to note that HDAC3, which is extensively expressed in resting T cells, is specifically preferred by benzamide-containing HDACis for inhibition. Thus, the benzamide class of compounds should be explored. Nevertheless, more data on selective HDAC inhibition is needed for further development of HDACis in HIV latency reversal.

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.

A fragment-based exploration of diverse MMP-9 inhibitors through classification-dependent structural assessment.

Matrix metalloproteinases (MMPs) are belonging to the Zn2+-dependent metalloenzymes. These can degenerate the extracellular matrix (ECM) that is entailed with various biological processes. Among the MMP family members, MMP-9 is associated with several pathophysiological circumstances. Apart from wound healing, remodeling of bone, inflammatory mechanisms, and rheumatoid arthritis, MMP-9 has also significant roles in tumor invasion and metastasis. Therefore, MMP-9 has been in the spotlight of anticancer drug discovery programs for more than a decade. In this present study, classification-based QSAR techniques along with fragment-based data mining have been carried out on divergent MMP-9 inhibitors to point out the important structural attributes. This current study may be able to elucidate the importance of several pivotal molecular fragments such as sulfonamide, hydroxamate, i-butyl, and ethoxy functions for imparting potential MMP-9 inhibition. These observations are in correlation with the ligand-bound co-crystal structures of MMP-9. Therefore, these findings are beneficial for the design and discovery of effective MMP-9 inhibitors in the future.

An updated patent review of matrix metalloproteinase (MMP) inhibitors (2021-present).

INTRODUCTION: Matrix metalloproteinases (MMPs) are strongly interlinked with the progression and mechanisms of several life-threatening diseases including cancer. Thus, novel MMP inhibitors (MMPIs) as promising drug candidates can be effective in combating these diseases. However, no MMPIs are marketed to date due to poor pharmacokinetics and lower selectivity. Therefore, this review was performed to study the newer MMPIs patented after the COVID-19 period for an updated perspective on MMPIs. AREAS COVERED: This review highlights patents related to MMPIs, and their therapeutic implications published between January 2021 and August 2023 available in the Google Patents, Patentscope, and Espacenet databases. EXPERT OPINION: Despite various MMP-related patents disclosed up to 2020, newer patent applications in the post-COVID-19 period decreased a lot. Besides major MMPs, other isoforms (i.e. MMP-3 and MMP-7) have gained attention recently for drug development. This may open up newer dimensions targeting these MMPs for therapeutic advancements. The isoform selectivity and bioavailability are major concerns for effective MMPI development. Thus, adopting theoretical approaches and experimental methodologies can unveil the development of novel MMPIs with improved pharmacokinetic profiles. Nevertheless, the involvement of MMPs in cancer, and the mechanisms of such MMPs in other diseases should be extensively studied for novel MMPI development.

HDAC9 as a Privileged Target: Reviewing its Role in Different Diseases and Structure-activity Relationships (SARs) of its Inhibitors.

HDAC9 is a histone deacetylase enzyme belonging to the class IIa of HDACs which catalyses histone deacetylation. HDAC9 inhibit cell proliferation by repairing DNA, arresting the cell cycle, inducing apoptosis, and altering genetic expression. HDAC9 plays a significant part in human physiological system and are involved in various type of diseases like cancer, diabetes, atherosclerosis and CVD, autoimmune response, inflammatory disease, osteoporosis and liver fibrosis. This review discusses the role of HDAC9 in different diseases and structure-activity relationships (SARs) of various hydroxamate and non-hydroxamate-based inhibitors. SAR of compounds containing several scaffolds have been discussed in detail. Moreover, structural requirements regarding the various components of HDAC9 inhibitor (cap group, linker and zinc-binding group) has been highlighted in this review. Though, HDAC9 is a promising target for the treatment of a number of diseases including cancer, a very few research are available. Thus, this review may provide useful information for designing novel HDAC9 inhibitors to fight against different diseases in the future.

Selective HDAC3 Inhibitors with Potent In Vivo Antitumor Efficacy against Triple-Negative Breast Cancer.

HDAC3 modulation shows promise for breast cancer, including triple-negative cases. Novel pyrazino-hydrazide-based HDAC3 inhibitors were designed and synthesized. Lead compound 4i exhibited potent HDAC3 inhibition (IC50 = 14 nM) with at least 121-fold selectivity. It demonstrated strong cytotoxicity against triple-negative breast cancer cells (IC50: 0.55 µM for 4T1, 0.74 µM for MDA-MB-231) with least normal cell toxicity. Metabolically stable 4i displayed a superior pharmacokinetic profile. A dose-dependent therapeutic efficacy of 4i was observed in a tumor-bearing mouse model. The biomarker analysis with tumor tissues displayed enhanced acetylation on Ac-H3K9, Ac-H3K27, and Ac-H4K12 compared to Ac-tubulin and Ac-SMC3 indicating HDAC3 selectivity of 4i in vivo. The immunoblotting study with tumor tissue showed upregulation of apoptotic proteins caspase-3, caspase-7, and cytochrome c and the downregulation of proliferation markers Bcl-2, CD44, EGFR, and Ki-67. Compound 4i represents a promising candidate for targeted breast cancer therapy, particularly for cases with triple-negative breast cancer.

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.

Are inhibitors of histone deacetylase 8 (HDAC8) effective in hematological cancers especially acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL)?

Histone deacetylase 8 (HDAC8) aberrantly deacetylates histone and non-histone proteins. These include structural maintenance of chromosome 3 (SMC3) cohesin protein, retinoic acid induced 1 (RAI1), p53, etc and thus, regulating diverse processes such as leukemic stem cell (LSC) transformation and maintenance. HDAC8, one of the crucial HDACs, affects the gene silencing process in solid and hematological cancer progressions especially on acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). A specific HDAC8 inhibitor PCI-34051 showed promising results against both T-cell lymphoma and AML. Here, we summarize the role of HDAC8 in hematological malignancies, especially in AML and ALL. This article also introduces the structure/function of HDAC8 and a special attention has been paid to address the HDAC8 enzyme selectivity issue in hematological cancer especially against AML and ALL.

Employing comparative QSAR techniques for the recognition of dibenzofuran and dibenzothiophene derivatives toward MMP-12 inhibition.

Among various matrix metalloproteinases (MMPs), MMP-12 is one of the potential targets for cancer and other diseases. However, none of the MMP-12 inhibitors has passed the clinical trials to date. Therefore, designing potential MMP-12 inhibitors as new drug molecules can provide effective therapeutic strategies for several diseases. In this study, a series of dibenzofuran and dibenzothiophene derivatives were subjected to different 2D and 3D-QSAR techniques to point out the crucial structural contributions highly influential toward the MMP-12 inhibitory activity. These techniques identified some structural attributes of these compounds that are responsible for influencing their MMP-12 inhibition. The carboxylic group may enhance proper binding with catalytic Zn2+ ion at the MMP-12 active site. Again, the i-propyl sulfonamido carboxylic acid function contributed positively toward MMP-12 inhibition. Moreover, the dibenzofuran moiety conferred stable binding at the S1' pocket for higher MMP-12 inhibition. The steric and hydrophobic groups were found favourable near the furan ring substituted at the dibenzofuran moiety. Besides these ligand-based approaches, molecular docking and molecular dynamic (MD) simulation studies not only elucidated the importance of several aspects of these MMP-12 inhibitors while disclosing the significance of the finding of these QSAR studies and their influences toward MMP-12 inhibition. The MD simulation study also revealed stable and compact binding between such compounds at the MMP-12 active site. Therefore, the findings of these validated ligand-based and structure-based molecular modeling studies can aid the development of selective and potent lead molecules that can be used for the treatment of MMP-12-associated diseases.Communicated by Ramaswamy H. Sarma.

Exploring molecular fingerprints of different drugs having bile interaction: a stepping stone towards better drug delivery.

Bile acids are amphiphilic substances produced naturally in humans. In the context of drug delivery and dosage form design, it is critical to understand whether a drug interacts with bile inside the gastrointestinal (GI) tract or not. This study focuses on the identification of structural fingerprints/features important for bile interaction. Molecular modelling methods such as Bayesian classification and recursive partitioning (RP) studies are executed to find important fingerprints/features for the bile interaction. For the Bayesian classification study, the ROC score of 0.837 and 0.950 are found for the training set and the test set compounds, respectively. The fluorine-containing aliphatic/aromatic group, the branched chain of the alkyl group containing hydroxyl moiety and the phenothiazine ring etc. are identified as good fingerprints having a positive contribution towards bile interactions, whereas, the bad fingerprints such as free carboxylate group, purine, and pyrimidine ring etc. have a negative contribution towards bile interactions. The best tree (tree ID: 1) from the RP study classifies the bile interacting or non-interacting compounds with a ROC score of 0.941 for the training and 0.875 for the test set. Additionally, SARpy and QSAR-Co analyses are also been performed to classify compounds as bile interacting/non-interacting. Moreover, forty-six recently FDA-approved drugs have been screened by the developed SARpy and QSAR-Co models to assess their bile interaction properties. Overall, this attempt may facilitate the researchers to identify bile interacting/non-interacting molecules in a faster way and help in the design of formulations and target-specific drug development.

Exploring structural requirements of HDAC10 inhibitors through comparative machine learning approaches.

Histone deacetylase (HDAC) inhibitors are in the limelight of anticancer drug development and research. HDAC10 is one of the class-IIb HDACs, responsible for cancer progression. The search for potent and effective HDAC10 selective inhibitors is going on. However, the absence of human HDAC10 crystal/NMR structure hampers the structure-based drug design of HDAC10 inhibitors. Different ligand-based modeling techniques are the only hope to speed up the inhibitor design. In this study, we applied different ligand-based modeling techniques on a diverse set of HDAC10 inhibitors (n = 484). Machine learning (ML) models were developed that could be used to screen unknown compounds as HDAC10 inhibitors from a large chemical database. Moreover, Bayesian classification and Recursive partitioning models were used to identify the structural fingerprints regulating the HDAC10 inhibitory activity. Additionally, a molecular docking study was performed to understand the binding pattern of the identified structural fingerprints towards the active site of HDAC10. Overall, the modeling insight might offer helpful information for medicinal chemists to design and develop efficient HDAC10 inhibitors.

Hydrazides as Potential HDAC Inhibitors: Structure-activity Relationships and Biological Implications.

Epigenetic modulations by HDACs are associated with multiple disease conditions. In this context, HDACs play vital roles in the progression of diseases including several cancers, neurodegenerative diseases, inflammatory diseases, and metabolic disorders. Though several HDAC inhibitors have been established as drug candidates, their usage has been restricted because of broad-spectrum inhibition, highly toxic character, and off-target adverse effects. Therefore, specific HDAC selectivity is essential to get rid of such adverse effects. Hydrazide-based compounds have already been proven to exert higher inhibitory efficacy and specific HDAC selectivity. In this article, the detailed structure-activity relationship (SAR) of the existing hydrazide-based HDAC inhibitors has been elucidated to gather crucial information that can be utilized further for the development of promising drug candidates for combating diverse diseases in the future.