Fragment-based discovery of new potential DNMT1 inhibitors integrating multiple pharmacophore modeling, 3D-QSAR, virtual screening, molecular docking, ADME, and molecular dynamics simulation approaches.

DNA methyl transferases (DNMTs) are one of the crucial epigenetic modulators associated with a wide variety of cancer conditions. Among the DNMT isoforms, DNMT1 is correlated with bladder, pancreatic, and breast cancer, as well as acute myeloid leukemia and esophagus squamous cell carcinoma. Therefore, the inhibition of DNMT1 could be an attractive target for combating cancers and other metabolic disorders. The disadvantages of the existing nucleoside and non-nucleoside DNMT1 inhibitors are the main motive for the discovery of novel promising inhibitors. Here, pharmacophore modeling, 3D-QSAR, and e-pharmacophore modeling of DNMT1 inhibitors were performed for the large fragment database screening. The resulting fragments with high dock scores were combined into molecules. The current study revealed several constitutional pharmacophoric features that can be essential for selective DNMT1 inhibition. The fragment docking and virtual screening identified 10 final hit molecules that exhibited good binding affinities in terms of docking score, binding free energies, and acceptable ADME properties. Also, the modified lead molecules (GL1b and GL2b) designed in this study showed effective binding with DNMT1 confirmed by their docking scores, binding free energies, 3D-QSAR predicted activities and acceptable drug-like properties. The MD simulation studies also suggested that leads (GL1b and GL2b) formed stable complexes with DNMT1. Therefore, the findings of this study can provide effective information for the development/identification of novel DNMT1 inhibitors as effective anticancer agents.

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.

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.

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.

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.

Pharmacophore-based virtual screening, 3D QSAR, Docking, ADMET, and MD simulation studies: An in silico perspective for the identification of new potential HDAC3 inhibitors.

Histone deacetylase 3 (HDAC3) is an epigenetic regulator that involves gene expression, apoptosis, and cell cycle progression, and the overexpression of HDAC3 is accountable for several cancers, neurodegeneracy, and many other diseases. Therefore, HDAC3 emerged as a promising drug target for the novel drug design. Here, we carried out the pharmacophore modeling using 50 benzamide-based HDAC3 selective inhibitors and utilized it for PHASE ligand screening to retrieve the hits with similar pharmacophore features. The dataset inhibitors of best hypotheses used to build the 3D QSAR model and the generated 3D QSAR model resulted in good PLS statistics with a regression coefficient (R2) of 0.89, predictive coefficient (Q2) of 0.88, and Pearson-R factor of 0.94 indicating its excellent predictive ability. The hits retrieved from pharmacophore-based virtual screening were subjected to docking against HDAC3 for the identification of potential inhibitors. A total of 10 hitsM1 to M10 were ranked using their scoring functions and further subject to lead optimization. The Prime MM/GBSA, AutoDock binding free energies, and ADMET studies were implemented for the selection of lead candidates. The four ligand molecules M1, M2, M3, and M4 were identified as potential leads against HDAC3 after lead optimization. The top two leads M1 and M2 were subjected to MD simulations for their stability evaluation with HDAC3. The newly designed leads M11 and M12 were identified as HDAC3 potential inhibitors from MD simulations studies. Therefore, the outcomes of the present study could provide insights into the discovery of new potential HDAC3 inhibitors with improved selectivity and activity against a variety of cancers and neurodegenerative diseases.

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.

Development and validation of machine learning models for the prediction of SH-2 containing protein tyrosine phosphatase 2 inhibitors.

Discovery and development of a new drug to the market is a highly challenging and resource consuming process. Although, modern drug discovery technologies have enabled the rapid identification of lead compounds, translation of the lead compounds into successful clinical candidates remains a big challenge. In recent years, the availability of massive structural and biological data of diverse small molecules and macromolecules has helped the researchers to deep mine the multidimensional data with the help of artificial intelligence-based predictive tools to draw useful insights on the structural features of biological or therapeutic significance. The aim of this study was to utilize the available data on small molecule (SH2)-containing protein tyrosine phosphatase 2 (SHP2) inhibitors to build and develop machine learning (ML) models that can predict the SHP2 inhibitory potential of new compounds. The dataset contained 2739 unique small molecule SHP2 inhibitors obtained from the BindingDB, ChEMBL and recent literature. After curation of the data, the predictive models such as XGBoost, K nearest neighbours, neural networks were developed and validated through a tenfold cross-validation testing procedure. Out of the seven models developed, the XGBoost model showed an excellent performance with ROC AUC score of 0.96 and accuracy of 0.97 on the test data. Moreover, the Shapley Additive Explanations method was applied to assess a more in-depth understanding of the influence of variables on the model's predictions. In summary, the XGBoost model developed in this study can be useful in the identification of novel SHP2 inhibitors and therefore, can accelerate the discovery of novel therapeutics for cancer therapy.

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.

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.

Glycyrrhizin as a promising kryptonite against SARS-CoV-2: Clinical, experimental, and theoretical evidences.

COVID-19 is the most devastating disease in recent times affecting most people globally. The higher rate of transmissibility and mutations of SARS-CoV-2 along with the lack of potential therapeutics has made it a global crisis. Potential molecules from natural sources could be a fruitful remedy to combat COVID-19. This systematic review highlights the detailed therapeutic implication of naturally occurring glycyrrhizin and its related derivatives against COVID-19. Glycyrrhizin has already been established for blocking different biomolecular targets related to the SARS-CoV-2 replication cycle. In this article, several experimental and theoretical evidences of glycyrrhizin and related derivatives have been discussed in detail to evaluate their potential as a promising therapeutic strategy against COVID-19. Moreover, the implication of glycyrrhizin in traditional Chinese medicines for alleviating the symptoms of COVID-19 has been reviewed. The potential role of glycyrrhizin and related compounds in affecting various stages of the SARS-CoV-2 life cycle has also been discussed in detail. Derivatization of glycyrrhizin for designing potential lead compounds along with combination therapy with other anti-SARS-CoV-2 agents followed by extensive evaluation may assist in the formulation of novel anti-coronaviral therapy for better treatment to combat COVID-19.

Selective Inhibitors of Medium-Size S1' Pocket Matrix Metalloproteinases: A Stepping Stone of Future Drug Discovery.

Among various matrix metalloproteinases (MMPs), MMPs having medium-size S1' pockets are established as promising biomolecular targets for executing crucial roles in cancer, cardiovascular diseases, and neurodegenerative diseases. However, no such MMP inhibitors (MMPIs) are available to date as drug candidates despite a lot of continuous research work for more than three decades. Due to a high degree of structural resemblance among these MMPs, designing selective MMPIs is quite challenging. However, the variability and uniqueness of the S1' pockets of these MMPs make them promising targets for designing selective MMPIs. In this perspective, the overall structural aspects of medium-size S1' pocket MMPs including the unique binding patterns of enzyme-inhibitor interactions have been discussed in detail to acquire knowledge regarding selective inhibitor designing. This overall knowledge will surely be a curtain raiser for the designing of selective MMPIs as drug candidates in the future.

Selective inhibition of histone deacetylase 3 by novel hydrazide based small molecules as therapeutic intervention for the treatment of cancer.

A promising hydrazide based small molecule lead as a potent and selective histone deacetylase 3 (HDAC3) inhibitor has been developed from a small series of synthesized novel chemical entities. The lead compound (4e) displayed high HDAC3 inhibitory potency (IC50 = 15.41 nM) and a minimum of 18-fold selectivity over other HDAC isoforms. It also exhibited potent cytotoxicity against several cancer cell lines with minimal toxicity against normal cell lines tested. Compound 4e also enhanced acetylation levels on H3K9, H4K12 and H3K27 both in vitro and in vivo. It also induced cell cycle arrest at the G2/M phase in B16F10 and 4T1 cells. It caused significant apoptosis and upregulated the expression of caspase-3, caspase-7, cytochrome c and downregulated the expression of BCL2 in tumour tissue. In addition, the downregulation of CD44, EGFR and Ki-67 suggested the potential of compound 4e in reducing cell proliferation and metastasis in mice. Further, a marked decrease in the tumour volume was observed with no general toxicity in the major organs when treated with 4e in the 4T1-Luc xenograft mouse model. Therefore, compound 4e is a promising candidate selectively targeting HDAC3 with a significant antitumour activity that can be evaluated further in preclinical and clinical evaluation.

Ligand-based quantitative structural assessments of SARS-CoV-2 3CLpro inhibitors: An analysis in light of structure-based multi-molecular modeling evidences.

Due to COVID-19, the whole world is undergoing a devastating situation, but treatment with no such drug candidates still has been established exclusively. In that context, 69 diverse chemicals with potential SARS-CoV-2 3CLpro inhibitory property were taken into consideration for building different internally and externally validated linear (SW-MLR and GA-MLR), non-linear (ANN and SVM) QSAR, and HQSAR models to identify important structural and physicochemical characters required for SARS-CoV-2 3CLpro inhibition. Importantly, 2-oxopyrrolidinyl methyl and benzylester functions, and methylene (hydroxy) sulphonic acid warhead group, were crucial for retaining higher SARS-CoV-2 3CLpro inhibition. These GA-MLR and HQSAR models were also applied to predict some already repurposed drugs. As per the GA-MLR model, curcumin, ribavirin, saquinavir, sepimostat, and remdesivir were found to be the potent ones, whereas according to the HQSAR model, lurasidone, saquinavir, lopinavir, elbasvir, and paritaprevir were the highly effective SARS-CoV-2 3CLpro inhibitors. The binding modes of those repurposed drugs were also justified by the molecular docking, molecular dynamics (MD) simulation, and binding energy calculations conducted by several groups of researchers. This current work, therefore, may be able to find out important structural parameters to accelerate the COVID-19 drug discovery processes in the future.

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.

Design, synthesis and binding mode of interaction of novel small molecule o-hydroxy benzamides as HDAC3-selective inhibitors with promising antitumor effects in 4T1-Luc breast cancer xenograft model.

Histone deacetylase 3 (HDAC3) is one of the most promising targets to develop anticancer therapeutics. In continuation of our quest for selective HDAC3 inhibitors, a series of small molecules having o-hydroxy benzamide as the novel zinc binding group (ZBG) has been introduced for the first time that can be able to produce good HDAC3-selectivity over other HDACs. The most promising HDAC3 inhibitors, 11a and 12b, displayed promising in vitro anticancer activities with less toxicity to normal kidney cells. These compounds significantly upregulate histone acetylation and induce apoptosis with a G2/M phase arrest in B16F10 cells. Compound 11a exhibited potent antitumor efficacy in 4T1-Luc breast cancer xenograft mouse model in female Balb/c mice. It also showed significant tumor growth suppression with no general toxicity and extended survival rates post-tumor resection. It significantly induced higher ROS generation, leading to apoptosis. No considerable toxicity was noticed in major organs isolated from the compound 11a-treated mice. Compound 11a also induced the upregulation of acH3K9, acH4K12, caspase-3 and caspase-7 as analyzed by immunoblotting with treated tumor tissue. Overall, HDAC3 selective inhibitor 11a might be a potential lead for the clinical translation as an emerging drug candidate.

Ligand-based design of anticancer MMP2 inhibitors: a review.

MMP2, a Zn2+-dependent metalloproteinase, is related to cancer and angiogenesis. Inhibition of this enzyme might result in a potential antimetastatic drug to leverage the anticancer drug armory. In silico or computer-aided ligand-based drug design is a method of rational drug design that takes multiple chemometrics (i.e., multi-quantitative structure-activity relationship methods) into account for virtually selecting or developing a series of probable selective MMP2 inhibitors. Though existing matrix metalloproteinase inhibitors have shown plausible pan-matrix metalloproteinase (MMP) activity, they have resulted in various adverse effects leading to their being rescinded in later phases of clinical trials. Therefore a review of the ligand-based designing methods of MMP2 inhibitors would result in an explicit route map toward successfully designing and synthesizing novel and selective MMP2 inhibitors.

Dissecting Histone Deacetylase 3 in Multiple Disease Conditions: Selective Inhibition as a Promising Therapeutic Strategy.

The acetylation of histone and non-histone proteins has been implicated in several disease states. Modulation of such epigenetic modifications has therefore made histone deacetylases (HDACs) important drug targets. HDAC3, among various class I HDACs, has been signified as a potentially validated target in multiple diseases, namely, cancer, neurodegenerative diseases, diabetes, obesity, cardiovascular disorders, autoimmune diseases, inflammatory diseases, parasitic infections, and HIV. However, only a handful of HDAC3-selective inhibitors have been reported in spite of continuous efforts in design and development of HDAC3-selective inhibitors. In this Perspective, the roles of HDAC3 in various diseases as well as numerous potent and HDAC3-selective inhibitors have been discussed in detail. It will surely open up a new vista in the discovery of newer, more effective, and more selective HDAC3 inhibitors.