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.

Biphenylsulfonamides as effective MMP-2 inhibitors with promising antileukemic efficacy: Synthesis, in vitro biological evaluation, molecular docking, and MD simulation analysis.

Overexpression of matrix metalloproteinase-2 (MMP-2) possesses a correlation with leukemia especially chronic myeloid leukemia (CML). However, no such MMP-2 inhibitor has come out in the market to date for treating leukemia. In this study, synthesis, biological evaluation, and molecular modeling studies of a set of biphenylsulfonamide derivatives as promising MMP-2 inhibitors were performed, focusing on their potential applications as antileukemic therapeutics. Compounds DH-18 and DH-19 exerted the most effective MMP-2 inhibition (IC50 of 139.45 nM and 115.16 nM, respectively) with potent antileukemic efficacy against the CML cell line K562 (IC50 of 0.338 µM and 0.398 µM, respectively). The lead molecules DH-18 and DH-19 reduced the MMP-2 expression by 21.3% and 17.8%, respectively with effective apoptotic induction (45.4% and 39.8%, respectively) in the K562 cell line. Moreover, both these compounds significantly arrested different phases of the cell cycle. Again, both these molecules depicted promising antiangiogenic efficacy in the ACHN cell line. Nevertheless, the molecular docking and molecular dynamics (MD) simulation studies revealed that DH-18 formed strong bidentate chelation with the catalytic Zn2+ ion through the hydroxamate zinc binding group (ZBG). Apart from that, the MD simulation study also disclosed stable binding interactions of DH-18 and MMP-2 along with crucial interactions with active site amino acid residues namely His120, Glu121, His124, His130, Pro140, and Tyr142. In a nutshell, this study highlighted the importance of biphenylsulfonamide-based novel and promising MMP-2 inhibitors to open up a new avenue for potential therapy against CML.

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.

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.

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.

HDAC6 as privileged target in drug discovery: A perspective.

HDAC6, a class IIB HDAC isoenzyme, stands unique in its structural and physiological functions. Besides histone modification, largely due to its cytoplasmic localization, HDAC6 also targets several non-histone proteins including Hsp90, α-tubulin, cortactin, HSF1, etc. Thus, it is one of the key regulators of different physiological and pathological disease conditions. HDAC6 is involved in different signaling pathways associated with several neurological disorders, various cancers at early and advanced stage, rare diseases and immunological conditions. Therefore, targeting HDAC6 has been found to be effective for various therapeutic purposes in recent years. Though several HDAC6 inhibitors (HDAC6is) have been developed till date, only two ACY-1215 (ricolinostat) and ACY-241 (citarinostat) are in the clinical trials. A lot of work is still needed to pinpoint strictly selective as well as potent HDAC6i. Considering the recent crystal structure of HDAC6, novel HDAC6is of significant therapeutic value can be designed. Notably, the canonical pharmacophore features of HDAC6is consist of a zinc binding group (ZBG), a linker function and a cap group. Significant modifications of cap function may lead to achieve better selectivity of the inhibitors. This review details the study about the structural biology of HDAC6, the physiological and pathological role of HDAC6 in several disease states and the detailed structure-activity relationships (SARs) of the known HDAC6is. This detailed review will provide key insights to design novel and highly effective HDAC6i in the future.

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.

Synthesis, biological evaluation, and molecular docking analysis of novel linker-less benzamide based potent and selective HDAC3 inhibitors.

A series of novel linker-less benzamides with different aryl and heteroaryl cap groups have been designed, synthesized, and screened as potent histone deacetylase (HDAC) inhibitors with promising anticancer activity. Two lead compounds 5e and 5f were found as potent and highly selective HDAC3 inhibitors over other Class-I HDACs and HDAC6. Compound 5e bearing a 6-quinolinyl moiety as the cap group was found to be a highly potent HDAC3 inhibitor (IC50 = 560 nM) and displayed 46-fold selectivity for HDAC3 over HDAC2, and 33-fold selectivity for HDAC3 over HDAC1. The synthesized compounds possess antiproliferative activities against different cancer cell lines and significantly less cytotoxic to normal cells. Molecular Docking studies of compounds 5e and 5f reveal a similar binding mode of interactions as CI994 at the HDAC3 active site. These observations agreed with the in vitro HDAC3 inhibitory activities. Significant enhancement of the endogenous acetylation level on H3K9 and H4K12 was found when B16F10 cells were treated with compounds 5e and 5f in a dose-dependent manner. The compounds induced apoptotic cell death in Annexin-V/FITC-PI assay and caused cell cycle arrest at G2/M phase of cell cycle in B16F10 cells. These compounds may serve as potential HDAC3 inhibitory anticancer therapeutics.

Structure-activity relationships of HDAC8 inhibitors: Non-hydroxamates as anticancer agents.

Histone deacetylase inhibitors (HDACIs) have a paramount importance in the acetylation process of histone and non-histone proteins that are crucial players in the cellular epigenetic modifications. HDACIs exert effective antiproliferation through DNA repairing, cell cycle arrest, apoptosis induction and alteration of genetic expression. HDAC8 is one of the crucial HDACs, affects the epigenetic gene silencing process and cancer progression. Hence, HDAC8 is one of the key cancer targets among class I HDACs that may be effectively blocked as a benchmark therapy to combat malignancy. In the current review, a special emphasis has been given for the non-hydroxamate type of HDAC8 inhibitors. It may provide some fruitful structural information to design newer better active candidates to fight against target specific malignancies in future.

An integrated QSAR modeling approach to explore the structure-property and selectivity relationships of N-benzoyl-L-biphenylalanines as integrin antagonists.

Integrins [Formula: see text] and [Formula: see text] are important targets to treat different inflammatory diseases, such as multiple sclerosis, inflammatory bowel diseases, rheumatoid arthritis, atherosclerosis, and asthma. Despite being valuable targets, only a few work has been reported to date regarding molecular modeling studies on these integrins. Not only that, none of these reports addressed the selectivity issue between integrins [Formula: see text] and [Formula: see text]. Therefore, a major challenge regarding the design and discovery of selective integrin antagonists remains. In this study, a series of 142 N-benzoyl-L-biphenylalanines having both integrin [Formula: see text] and [Formula: see text] inhibitory activities were considered for a variety of QSAR approaches including regression and classification-based 2D-QSARs, Hologram QSARs, 3D-QSAR CoMFA and CoMSIA studies to identify the structural requirements of these integrin antagonists. All these QSAR models were statistically validated and subsequently correlated with each other to get a detailed understanding of the activity and selectivity profiles of these molecules.

Is dual inhibition of metalloenzymes HDAC-8 and MMP-2 a potential pharmacological target to combat hematological malignancies?

For the last three decades, metalloenzymes such as histone deacetylases (HDACs) and matrix metalloproteinases (MMPs) have been identified in promoting solid as well as hematological carcinogenesis. Histone deacetylase 8 (HDAC-8), a class I HDAC enzyme, may serve as 'epigenetic player' that affects in the regulation of transcription factors and alters the structure of chromosome associated with tumorigenesis. It is established that the influence of MMP-2 in invasion, metastasis and angiogenenic events of hematological malignancies may be suppressed by HDAC inhibitors through reversion-inducing-cysteine-rich protein with kazal motifs (RECK) protein. Therefore, the isoform-specific HDAC-8 and MMP-2 inhibitors may provide synergistic medicinal benefit in leukemia. However, a paucity of articles is available on dual acting HDAC-8/MMP-2 inhibitors. In this circumstance, a lot of works are still necessary to identify novel dual HDAC-8/MMP-2 inhibitors and this review will surely provide an initial idea regarding the utility of designing such type of dual inhibitors. Here, the importance of MMP-2 and HDAC-8 inhibition in hematological malignancies are focussed for the first time as per our knowledge along with the structure-activity relationships (SARs) of a handful of molecules, some of which were synthesised in-house, have been highlighted that will inspire more interactions between the medicinal chemistry and biology community to harness their expertise in design and discovery of the better acting dual inhibitors in future.

First molecular modeling report on novel arylpyrimidine kynurenine monooxygenase inhibitors through multi-QSAR analysis against Huntington's disease: A proposal to chemists!

Huntington's disease (HD) is caused by mutation of huntingtin protein (mHtt) leading to neuronal cell death. The mHtt induced toxicity can be rescued by inhibiting the kynurenine monooxygenase (KMO) enzyme. Therefore, KMO is a promising drug target to address the neurodegenerative disorders such as Huntington's diseases. Fiftysix arylpyrimidine KMO inhibitors are structurally explored through regression and classification based multi-QSAR modeling, pharmacophore mapping and molecular docking approaches. Moreover, ten new compounds are proposed and validated through the modeling that may be effective in accelerating Huntington's disease drug discovery efforts.

Robust design of some selective matrix metalloproteinase-2 inhibitors over matrix metalloproteinase-9 through in silico/fragment-based lead identification and de novo lead modification: Syntheses and biological assays.

Broad range of selectivity possesses serious limitation for the development of matrix metalloproteinase-2 (MMP-2) inhibitors for clinical purposes. To develop potent and selective MMP-2 inhibitors, initially multiple molecular modeling techniques were adopted for robust design. Predictive and validated regression models (2D and 3D QSAR and ligand-based pharmacophore mapping studies) were utilized for estimating the potency whereas classification models (Bayesian and recursive partitioning analyses) were used for determining the selectivity of MMP-2 inhibitors over MMP-9. Bayesian model fingerprints were used to design selective lead molecule which was modified using structure-based de novo technique. A series of designed molecules were prepared and screened initially for inhibitions of MMP-2 and MMP-9, respectively, as these are designed followed by other MMPs to observe the broader selectivity. The best active MMP-2 inhibitor had IC50 value of 24nM whereas the best selective inhibitor (IC50=51nM) showed at least 4 times selectivity to MMP-2 against all tested MMPs. Active derivatives were non-cytotoxic against human lung carcinoma cell line-A549. At non-cytotoxic concentrations, these inhibitors reduced intracellular MMP-2 expression up to 78% and also exhibited satisfactory anti-migration and anti-invasive properties against A549 cells. Some of these active compounds may be used as adjuvant therapeutic agents in lung cancer after detailed study.

Structural findings of cinnolines as anti-schizophrenic PDE10A inhibitors through comparative chemometric modeling.

Schizophrenia is a complex psychiatric disorder associated with the distortion of striatopallidal neurotransmission of central nervous system. Phosphodiesterase10A (PDE10A) enzyme plays crucial role in cellular signaling pathways in schizophrenia. Inhibition of this enzyme may facilitate better treatment of this disease. 2D-QSAR, HQSAR, pharmacophore mapping, molecular docking, and 3D-QSAR analyses were performed on 81 cinnoline derivatives having PDE10A inhibitory activity. 2D-QSAR models were developed by multiple linear regression and partial least square analyses using both atom based and whole molecular descriptors. The best model, having considerable internal (q(2) = 0.812) and external (R(2)(pred) = 0.691) predictabilities, demonstrated importance of atom-based topological and whole molecular E-state as well as 3D topological indices. The best HQSAR model was also found to be statistically significant (q(2) = 0.664, R(2)(pred) = 0.513) and it highlighted some important structural features. PHASE-based pharmacophore hypothesis showed the importance of three hydrogen bond acceptor and one each of ring aromatic and hydrophobic features for higher activity. 3D-QSAR CoMFA and CoMSIA models were generated on two different types of alignment procedures-(1) pharmacophore (PHASE) based and (2) docking (GLIDE) based. GLIDE-based alignment produced better results for both CoMFA (Q(2) = 0.578; R(2)(pred) = 0.841) and CoMSIA (Q(2) = 0.610; R(2)(pred) = 0.824) methods. Molecular dynamics (MDs) simulations were performed for two ligand-receptor complexes and these simulations explored some crucial factors for higher activity. These findings of MD simulations were consistent with the interpretations obtained from other methods of analyses. The current study may help in designing new PDE10A inhibitors of this class.

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.

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 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.

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.