REDD1 promotes obesity-induced metabolic dysfunction via atypical NF-κB activation.

Regulated in development and DNA damage response 1 (REDD1) expression is upregulated in response to metabolic imbalance and obesity. However, its role in obesity-associated complications is unclear. Here, we demonstrate that the REDD1-NF-κB axis is crucial for metabolic inflammation and dysregulation. Mice lacking Redd1 in the whole body or adipocytes exhibited restrained diet-induced obesity, inflammation, insulin resistance, and hepatic steatosis. Myeloid Redd1-deficient mice showed similar results, without restrained obesity and hepatic steatosis. Redd1-deficient adipose-derived stem cells lost their potential to differentiate into adipocytes; however, REDD1 overexpression stimulated preadipocyte differentiation and proinflammatory cytokine expression through atypical IKK-independent NF-κB activation by sequestering IκBα from the NF-κB/IκBα complex. REDD1 with mutated Lys219/220Ala, key amino acid residues for IκBα binding, could not stimulate NF-κB activation, adipogenesis, and inflammation in vitro and prevented obesity-related phenotypes in knock-in mice. The REDD1-atypical NF-κB activation axis is a therapeutic target for obesity, meta-inflammation, and metabolic complications.

A Computational Approach with Biological Evaluation: Combinatorial Treatment of Curcumin and Exemestane Synergistically Regulates DDX3 Expression in Cancer Cell Lines.

DDX3 belongs to RNA helicase family that demonstrates oncogenic properties and has gained wider attention due to its role in cancer progression, proliferation and transformation. Mounting reports have evidenced the role of DDX3 in cancers making it a promising target to abrogate DDX3 triggered cancers. Dual pharmacophore models were generated and were subsequently validated. They were used as 3D queries to screen the InterBioScreen database, resulting in the selection of curcumin that was escalated to molecular dynamics simulation studies. In vitro anti-cancer analysis was conducted on three cell lines such as MCF-7, MDA-MB-231 and HeLa, which were evaluated along with exemestane. Curcumin was docked into the active site of the protein target (PDB code 2I4I) to estimate the binding affinity. The compound has interacted with two key residues and has displayed stable molecular dynamics simulation results. In vitro analysis has demonstrated that both the candidate compounds have reduced the expression of DDX3 in three cell lines. However, upon combinatorial treatment of curcumin (10 and 20 µM) and exemestane (50 µM) a synergism was exhibited, strikingly downregulating the DDX3 expression and has enhanced apoptosis in three cell lines. The obtained results illuminate the use of curcumin as an alternative DDX3 inhibitor and can serve as a chemical scaffold to design new small molecules.

Discovery of Lonafarnib-Like Compounds: Pharmacophore Modeling and Molecular Dynamics Studies.

Progeria is a globally noticed rare genetic disorder manifested by premature aging with no effective treatment. Under these circumstances, farnesyltransferase inhibitors (FTIs) are marked as promising drug candidates. Correspondingly, a pharmacophore model was generated exploiting the features of lonafarnib. The selected pharmacophore model was allowed to screen the InterBioScreen natural compound database to retrieve the potential lead candidates. A series of filtering steps were applied to assess the drug-likeness of the compounds. The obtained compounds were advanced to molecular docking employing the CDOCKER module available with Discovery Studio (DS). Subsequently, three compounds (Hits) have displayed a higher dock score and demonstrated key residue interactions with stable molecular dynamics simulation results compared to the reference compound. Taken together, we therefore put forth three identified Hits as FTIs that may further serve as chemical spaces in designing new compounds.

Competitive α-glucosidase inhibitors, dihydrobenzoxanthones, from the barks of Artocarpus elasticus.

This study aimed to search the α-glucosidase inhibitors from the barks part of Artocarpus elasticus. The responsible compounds for α-glucosidase inhibition were found out as dihydrobenzoxanthones (1-4) and alkylated flavones (5-6). All compounds showed a significant enzyme inhibition toward α-glucosidase with IC50s of 7.6-25.4 µM. Dihydrobenzoxanthones (1-4) exhibited a competitive inhibition to α-glucosidase. This competitive behaviour was fully characterised by double reciprocal plots, Yang's method, and time-dependent experiments. The compound 1 manifested as the competitive and reversible simple slow-binding, with kinetic parameters k3 = 0.0437 µM-1 min-1, k4 = 0.0166 min-1, and Kiapp = 0.3795 µM. Alkylated flavones (5-6) were mixed type I (KI < KIS) inhibitors. The binding affinities (KSV) represented by all inhibitors were correlated to their concentrations and inhibitory potencies (IC50). Moreover, compounds 1 and 5 were identified as new ones named as artoindonesianin W and artoflavone B, respectively. Molecular modelling study proposed the putative binding conformation of competitive inhibitors (1-4) to α-glucosidase at the atomic level.

Natural compounds as potential Hsp90 inhibitors for breast cancer-Pharmacophore guided molecular modelling studies.

Breast cancer is one of the major impediments affecting women globally. The ATP-dependant heat shock protein 90 (Hsp90) forms the central component of molecular chaperone machinery that predominantly governs the folding of newly synthesized peptides and their conformational maturation. It regulates the stability and function of numerous client proteins that are frequently upregulated and/or mutated in cancer cells, therefore, making Hsp90 inhibition a promising therapeutic strategy for the development of new efficacious drugs to treat breast cancer. In the present in silico investigation, a structure-based pharmacophore model was generated with hydrogen bond donor, hydrogen bond acceptor and hydrophobic features complementary to crucial residues Ala55, Lys58, Asp93, Ile96, Met98 and Thr184 directed at inhibiting the ATP-binding activity of Hsp90. Subsequently, the phytochemical dataset of 3210 natural compounds was screened to retrieve the prospective inhibitors after rigorous validation of the model pharmacophore. The retrieved 135 phytocompounds were further filtered by drug-likeness parameters including Lipinski's rule of five and ADMET properties, then investigated via molecular docking-based scoring. Molecular interactions were assessed using Genetic Optimisation for Ligand Docking program for 95 drug-like natural compounds against Hsp90 along with two clinical drugs as reference compounds - Geldanamycin and Radicicol. Docking studies revealed three phytochemicals are better than the investigated clinical drugs. The reference and hit compounds with dock scores of 48.27 (Geldanamycin), 40.90 (Radicicol), 73.04 (Hit1), 72.92 (Hit2) and 68.12 (Hit3) were further validated for their binding stability through molecular dynamics simulations. We propose that the non-macrocyclic scaffolds of three identified phytochemicals might aid in the development of novel therapeutic candidates against Hsp90-driven cancers.

Pharmacotherapeutics and Molecular Mechanism of Phytochemicals in Alleviating Hormone-Responsive Breast Cancer.

Breast cancer (BC) is the leading cause of death among women worldwide devoid of effective treatment. It is therefore important to develop agents that can reverse, reduce, or slow the growth of BC. The use of natural products as chemopreventive agents provides enormous advantages. The aim of the current investigation is to determine the efficacy of the phytochemicals against BC along with the approved drugs to screen the most desirable and effective phytocompound. In the current study, 36 phytochemicals have been evaluated against aromatase to identify the potential candidate drug along with the approved drugs employing the Cdocker module accessible on the Discovery Studio (DS) v4.5 and thereafter analysing the stability of the protein ligand complex using GROningen MAchine for Chemical Simulations v5.0.6 (GROMACS). Additionally, these compounds were assessed for the inhibitory features employing the structure-based pharmacophore (SBP). The Cdocker protocol available with the DS has computed higher dock scores for the phytochemicals complemented by lower binding energies. The top-ranked compounds that have anchored with key residues located at the binding pocket of the protein were subjected to molecular dynamics (MD) simulations employing GROMACS. The resultant findings reveal the stability of the protein backbone and further guide to comprehend on the involvement of key residues Phe134, Val370, and Met374 that mechanistically inhibit BC. Among 36 compounds, curcumin, capsaicin, rosmarinic acid, and 6-shogaol have emerged as promising phytochemicals conferred with the highest Cdocker interaction energy, key residue interactions, stable MD results than reference drugs, and imbibing the key inhibitory features. Taken together, the current study illuminates the use of natural compounds as potential drugs against BC. Additionally, these compounds could also serve as scaffolds in designing and development of new drugs.

Discovery of Small Molecules that Target Vascular Endothelial Growth Factor Receptor-2 Signalling Pathway Employing Molecular Modelling Studies.

Angiogenesis is defined as the formation of new blood vessels and is a key phenomenon manifested in a host of cancers during which tyrosine kinases play a crucial role. Vascular endothelial growth factor receptor-2 (VEGFR-2) is pivotal in cancer angiogenesis, which warrants the urgency of discovering new anti-angiogenic inhibitors that target the signalling pathways. To obtain this objective, a structure-based pharmacophore model was built from the drug target VEGFR-2 (PDB code: 4AG8), complexed with axitinib and was subsequently validated and employed as a 3D query to retrieve the candidate compounds with the key inhibitory features. The model was escalated to molecular docking studies resulting in seven candidate compounds. The molecular docking studies revealed that the seven compounds displayed a higher dock score than the reference-cocrystallised compound. The GROningen MAchine for Chemical Simulations (GROMACS) package guided molecular dynamics (MD) results determined their binding mode and affirmed stable root mean square deviation. Furthermore, these compounds have preserved their key interactions with the residues Glu885, Glu917, Cys919 and Asp1046. The obtained findings deem that the seven compounds could act as novel anti-angiogenic inhibitors and may further assist as the prototype in designing and developing new inhibitors.

Discovery of Novel Acetylcholinesterase Inhibitors as Potential Candidates for the Treatment of Alzheimer's Disease.

Acetylcholinesterase (AChE) catalyzes the hydrolysis of neurotransmitter acetylcholine to acetate and choline in a synaptic cleft. Deficits in cholinergic neurotransmitters are linked closely with the progression of Alzheimer's disease (AD), which is a neurodegenerative disorder characterized by memory impairment, and a disordered cognitive function. Since the previously approved AChE inhibitors, donepezil (Aricept), galantamine (Reminyl), and rivastigmine (Exelon), have side effects and several studies are being carried out out to develop novel AD drugs, we have applied a three-dimensional quantitative structure-activity relationship (3D QSAR) and structure-based pharmacophore modeling methodologies to identify potential candidate inhibitors against AChE. Herein, 3D QSAR and structure-based pharmacophore models were built from known inhibitors and crystal structures of human AChE in complex with donepezil, galantamine, huperzine A, and huprine W, respectively. The generated models were used as 3D queries to screen new scaffolds from various chemical databases. The hit compounds obtained from the virtual screening were subjected to an assessment of drug-like properties, followed by molecular docking. The final hit compounds were selected based on binding modes and molecular interactions in the active site of the enzyme. Furthermore, molecular dynamics simulations for AChE in complex with the final hits were performed to evaluate that they maintained stable interactions with the active site residues. The binding free energies of the final hits were also calculated using molecular mechanics/Poisson-Boltzmann surface area method. Taken together, we proposed that these hits can be promising candidates for anti-AD drugs.

In Silico Study Probes Potential Inhibitors of Human Dihydrofolate Reductase for Cancer Therapeutics.

Dihydrofolate reductase (DHFR) is an essential cellular enzyme and thereby catalyzes thereduction of dihydrofolate to tetrahydrofolate (THF). In cancer medication, inhibition of humanDHFR (hDHFR) remains a promising strategy, as it depletes THF and slows DNA synthesis and cellproliferation. In the current study, ligand-based pharmacophore modeling identified and evaluatedthe critical chemical features of hDHFR inhibitors. A pharmacophore model (Hypo1) was generatedfrom known inhibitors of DHFR with a correlation coefficient (0.94), root mean square (RMS)deviation (0.99), and total cost value (125.28). Hypo1 was comprised of four chemical features,including two hydrogen bond donors (HDB), one hydrogen bond acceptor (HBA), and onehydrophobic (HYP). Hypo1 was validated using Fischer's randomization, test set, and decoy setvalidations, employed as a 3D query in a virtual screening at Maybridge, Chembridge, Asinex,National Cancer Institute (NCI), and Zinc databases. Hypo1-retrieved compounds were filtered byan absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment test andLipinski's rule of five, where the drug-like hit compounds were identified. The hit compounds weredocked in the active site of hDHFR and compounds with Goldfitness score was greater than 44.67(docking score for the reference compound), clustering analysis, and hydrogen bond interactionswere identified. Furthermore, molecular dynamics (MD) simulation identified three compounds asthe best inhibitors of hDHFR with the lowest root mean square deviation (1.2 Å to 1.8 Å), hydrogenbond interactions with hDHFR, and low binding free energy (-127 kJ/mol to -178 kJ/mol). Finally,the toxicity prediction by computer (TOPKAT) affirmed the safety of the novel inhibitors of hDHFRin human body. Overall, we recommend novel hit compounds of hDHFR for cancer and rheumatoidarthritis chemotherapeutics.

Investigation of novel chemical scaffolds targeting prolyl oligopeptidase for neurological therapeutics.

Prolyl oligopeptidase (POP) is a potential therapeutic target for treatment of several neurological disorders and α-synucleinopathies including Parkinson's disease. Most of the known POP inhibitors failed in the clinical trials due to poor pharmacokinetic properties and blood-brain impermeability. Therefore, a training set of 30 structurally diverse compounds with a wide range of inhibitory activity against POP was used to generate a quantitative pharmacophore model, Hypo 3, to identify potential POP inhibitors with desirable drug-like properties. Validations through test set, cost analysis, and Fisher's randomization methods proved that Hypo 3 accurately predicted the known inhibitors among inactive compounds. Hypo 3 was employed as 3D query for virtual screening on an in-house drug-like chemical database containing compounds with good brain permeability and ADMET parameters. Database screening with Hypo 3 resulted in 99 compounds that were narrowed down to 21 compounds through molecular docking. Among them, five compounds were identified in our earlier studies, while two compounds showed in vitro POP inhibition. The current study proposed new 16 virtually screened compounds as potential inhibitors against POP that possess Gold docking score in the range of 64.61-75.74 and Chemscore of -32.25 to -38.35. Furthermore, the top scoring four hit compounds were subjected to molecular dynamics simulations to reveal their appropriate binding modes and assessing binding free energies. The hit compounds interacted with POP effectively via hydrogen bonds with important active site residues along with hydrophobic interactions. Moreover, the hit compounds had key inter-molecular interactions and better binding free energies as compared to the reference inhibitor. A potential new hydrogen bond interaction was discovered between Hit 2 with the Arg252 residue of POP. To conclude, we propose four hit compounds with new structural scaffolds against POP for the lead development of POP-based therapeutics for neurological disorders.

Investigation of Grignard Reagent as an Advanced Base for Aza-Claisen Rearrangement.

Employing iPrMgCl as an advanced base instead of lithium hexamethyldisilazane (LHMDS) resulted in dramatic improvements in aza-Claisen rearrangement. This advance is considered responsible for the increased bulkiness of the alkoxide moiety (including magnesium cation and ligands), followed by a resultant conformational change of the transition state. To support this hypothesis, various substrates of aza-Claisen rearrangement were prepared and screened. In addition, a molecular dynamic simulation study was performed to investigate and compare the structural stability of reaction intermediates.

Structure-Based Drug Designing Recommends HDAC6 Inhibitors To Attenuate Microtubule-Associated Tau-Pathogenesis.

Protein acetylation and deacetylation play vital roles in the structural and physiological behavior of target proteins. Histone deacetylase 6 (HDAC6) remains a key therapeutic target in several chronic diseases such as cancer, neurodegenerative, and hematological diseases. In tau-pathogenesis, HDAC6 tightly regulates microtubule-associated tau physiology, and its inhibition suppresses Alzheimer's phenotype. To this end, the current study has identified novel HDAC6 inhibitors by structure-based drug designing method. A pharmacophore was generated from HDAC6 in complex with trichostatin A. The selected pharmacophore had five features including two hydrogen bond donors, one hydrogen bond acceptor, and two hydrophobic features. Pharmacophore validation obtained the highest GH score of 0.80. By applying Lipinski's rule of five and ADMET Descriptors, a drug-like database of 29 183 molecules was generated from the Zinc Natural Product Database. The validated pharmacophore screened 841 drug-like molecules and was subsequently subjected to molecular docking in the active site of HDAC6. Molecular docking identified 11 hits, where they showed the highest ChemPLP score (>90.00), stable conformation, and hydrogen-bond interactions with catalytic residues of HDAC6. Finally, molecular dynamics simulation identified three molecules as potent HDAC6 inhibitors with stable root-mean-square deviation and the highest number of hydrogen bonds with the catalytic residues of HDAC6. Overall, we recommend three novel inhibitors of HDAC6, capable of suppressing the microtubule-associated tau-pathogenesis.

Identification of Novel Scaffolds with Dual Role as Antiepileptic and Anti-Breast Cancer.

Aromatase inhibitors with an $\mathrm{IC}_{50}$ IC 50 value ranging from 1.4 to 49.7 µM are known to act as antiepileptic drugs besides being potential breast cancer inhibitors. The aim of the present study is to identify novel antiepileptic aromatase inhibitors with higher activity exploiting the ligand-based pharmacophore approach utilizing the experimentally known inhibitors. The resultant Hypo1 consists of four features and was further validated by using three different strategies. Hypo1 was allowed to screen different databases to identify lead molecules and were further subjected to Lipinski's Rule of Five and ADMET to establish their drug-like properties. Consequently, the obtained 68-screened molecules were subjected to molecular docking by GOLD v5.2.2. Furthermore, the compounds with the highest dock scores were assessed for molecular interactions. Later, the MD simulation was applied to evaluate the protein backbone stabilities and binding energies adapting GROMACS v5.0.6 and MM/PBSA which was followed by the density functional theory (DFT), to analyze their orbital energies, and further the energy gap between them. Eventually, the number of Hit molecules was culled to three projecting Hit1, Hit2, and Hit3 as the potential lead compounds based on their highest dock scores, hydrogen bond interaction, lowest energy gap, and the least binding energies and stable MD results.

Discovery of Potential Plant-Derived Peptide Deformylase (PDF) Inhibitors for Multidrug-Resistant Bacteria Using Computational Studies.

Bacterial peptide deformylase (PDF) is an attractive target for developing novel inhibitors against several types of multidrug-resistant bacteria. The objective of the current study is to retrieve potential phytochemicals as prospective drugs against Staphylococcus aureus peptide deformylase (SaPDF). The current study focuses on applying ligand-based pharmacophore model (PharmL) and receptor-based pharmacophore (PharmR) approaches. Utilizing 20 known active compounds, pharmL was built and validated using Fischer's randomization, test set method and the decoy set method. PharmR was generated from the knowledge imparted by the Interaction Generation protocol implemented on the Discovery Studio (DS) v4.5 and was validated using the decoy set that was employed for pharmL. The selection of pharmR was performed based upon the selectivity score and further utilizing the Pharmacophore Comparison module available on the DS. Subsequently, the validated pharmacophore models were escalated for Taiwan Indigenous Plants (TIP) database screening and furthermore, a drug-like evaluation was performed. Molecular docking was initiated for the resultant compounds, employing CDOCKER (available on the DS) and GOLD. Eventually, the stability of the final PDF⁻hit complexes was affirmed using molecular dynamics (MD) simulation conducted by GROMACS v5.0.6. The redeemed hits demonstrated a similar binding mode and stable intermolecular interactions with the key residues, as determined by no aberrant behaviour for 50 ns. Taken together, it can be stated that the hits can act as putative scaffolds against SaPDF, with a higher therapeutic value. Furthermore, they can act as fundamental structures for designing new drug candidates.

Discovery of Non-Peptidic Compounds against Chagas Disease Applying Pharmacophore Guided Molecular Modelling Approaches.

Chagas disease is one of the primary causes of heart diseases accounting to 50,000 lives annually and is listed as the neglected tropical disease. Because the currently available therapies have greater toxic effects with higher resistance, there is a dire need to develop new drugs to combat the disease. In this pursuit, the 3D QSAR ligand-pharmacophore (pharm 1) and receptor-based pharmacophore (pharm 2) search was initiated to retrieve the candidate compounds from universal natural compounds database. The validated models were allowed to map the universal natural compounds database. The obtained lead candidates were subjected to molecular docking against cysteine protease (PDB code: 1ME3) employing -Cdocker available on the discovery studio. Subsequently, two Hits have satisfied the selection criteria and were escalated to molecular dynamics simulation and binding free energy calculations. These Hits have demonstrated higher dock scores, displayed interactions with the key residues portraying an ideal binding mode complemented by mapping to all the features of pharm 1 and pharm 2. Additionally, they have rendered stable root mean square deviation (RMSD) and potential energy profiles illuminating their potentiality as the prospective antichagastic agents. The study further demonstrates the mechanism of inhibition by tetrad residues compromising of Gly23 and Asn70 holding the ligand at each ends and the residues Gly65 and Gly160 clamping the Hits at the center. The notable feature is that the Hits lie in close proximity with the residues Glu66 and Leu67, accommodating within the S1, S2 and S3 subsites. Considering these findings, the study suggests that the Hits may be regarded as effective therapeutics against Chagas disease.

Investigation of non-hydroxamate scaffolds against HDAC6 inhibition: A pharmacophore modeling, molecular docking, and molecular dynamics simulation approach.

Proteins deacetylation by Histone deacetylase 6 (HDAC6) has been shown in various human chronic diseases like neurodegenerative diseases and cancer, and hence is an important therapeutic target. Since, the existing inhibitors have hydroxamate group, and are not HDAC6-selective, therefore, this study has designed to investigate non-hydroxamate HDAC6 inhibitors. Ligand-based pharmacophore was generated from 26 training set compounds of HDAC6 inhibitors. The statistical parameters of pharmacophore (Hypo1) included lowest total cost of 115.63, highest cost difference of 135.00, lowest RMSD of 0.70 and the highest correlation of 0.98. The pharmacophore was validated by Fischer's Randomization and Test Set validation, and used as screening tool for chemical databases. The screened compounds were filtered by fit value ([Formula: see text]), estimated Inhibitory Concentration (IC[Formula: see text]) ([Formula: see text]), Lipinski's Rule of Five and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Descriptors to identify drug-like compounds. Furthermore, the drug-like compounds were docked into the active site of HDAC6. The best docked compounds were selected having goldfitness score [Formula: see text] and [Formula: see text], and hydrogen bond interaction with catalytic active residues. Finally, three inhibitors having sulfamoyl group were selected by Molecular Dynamic (MD) simulation, which showed stable root mean square deviation (RMSD) (1.6-1.9[Formula: see text]Å), lowest potential energy ([Formula: see text][Formula: see text]kJ/mol), and hydrogen bonding with catalytic active residues of HDAC6.

Targeting natural compounds against HER2 kinase domain as potential anticancer drugs applying pharmacophore based molecular modelling approaches.

Human epidermal growth factor receptors are implicated in several types of cancers characterized by aberrant signal transduction. This family comprises of EGFR (ErbB1), HER2 (ErbB2, HER2/neu), HER3 (ErbB3), and HER4 (ErbB4). Amongst them, HER2 is associated with breast cancer and is one of the most valuable targets in addressing the breast cancer incidences. For the current investigation, we have performed 3D-QSAR based pharmacophore search for the identification of potential inhibitors against the kinase domain of HER2 protein. Correspondingly, a pharmacophore model, Hypo1, with four features was generated and was validated employing Fischer's randomization, test set method and the decoy test method. The validated pharmacophore was allowed to screen the colossal natural compounds database (UNPD). Subsequently, the identified 33 compounds were docked into the proteins active site along with the reference after subjecting them to ADMET and Lipinski's Rule of Five (RoF) employing the CDOCKER implemented on the Discovery Studio. The compounds that have displayed higher dock scores than the reference compound were scrutinized for interactions with the key residues and were escalated to MD simulations. Additionally, molecular dynamics simulations performed by GROMACS have rendered stable root mean square deviation values, radius of gyration and potential energy values. Eventually, based upon the molecular dock score, interactions between the ligands and the active site residues and the stable MD results, the number of Hits was culled to two identifying Hit1 and Hit2 has potential leads against HER2 breast cancers.

Computational Exploration for Lead Compounds That Can Reverse the Nuclear Morphology in Progeria.

Progeria is a rare genetic disorder characterized by premature aging that eventually leads to death and is noticed globally. Despite alarming conditions, this disease lacks effective medications; however, the farnesyltransferase inhibitors (FTIs) are a hope in the dark. Therefore, the objective of the present article is to identify new compounds from the databases employing pharmacophore based virtual screening. Utilizing nine training set compounds along with lonafarnib, a common feature pharmacophore was constructed consisting of four features. The validated Hypo1 was subsequently allowed to screen Maybridge, Chembridge, and Asinex databases to retrieve the novel lead candidates, which were then subjected to Lipinski's rule of 5 and ADMET for drug-like assessment. The obtained 3,372 compounds were forwarded to docking simulations and were manually examined for the key interactions with the crucial residues. Two compounds that have demonstrated a higher dock score than the reference compounds and showed interactions with the crucial residues were subjected to MD simulations and binding free energy calculations to assess the stability of docked conformation and to investigate the binding interactions in detail. Furthermore, this study suggests that the Hits may be more effective against progeria and further the DFT studies were executed to understand their orbital energies.

Competitive protein tyrosine phosphatase 1B (PTP1B) inhibitors, prenylated caged xanthones from Garcinia hanburyi and their inhibitory mechanism.

Protein tyrosine phosphatase 1B (PTP1B) plays important role in diabetes, obesity and cancer. The methanol extract of the gum resin of Garcinia hanburyi (G. hanburyi) showed potent PTP1B inhibition at 10µg/ml. The active compounds were identified as prenylated caged xanthones (1-9) which inhibited PTP1B in dose-dependent manner. Carboxybutenyl group within caged motif (A ring) was found to play a critical role in enzyme inhibition such as 1-6 (IC50s=0.47-4.69µM), whereas compounds having hydroxymethylbutenyl 7 (IC50=70.25µM) and methylbutenyl 8 (IC50>200µM) showed less activity. The most potent inhibitor, gambogic acid 1 (IC50=0.47µM) showed 30-fold more potency than ursolic acid (IC50=15.5µM), a positive control. In kinetic study, all isolated xanthones behaved as competitive inhibitors which were fully demonstrated with Km, Vmax and Kik/Kiv ratio. It was also proved that inhibitor 1 operated under the enzyme isomerization model having k5=0.0751µM-1S-1, k6=0.0249µM-1S-1 and Kiapp=0.499µM. To develop a pharmacophore model, we explored the binding sites of compound 1 and 7 in PTP1B. These modeling results were in agreement with our findings, which revealed that the inhibitory activities are tightly related to caged motif and prenyl group in A ring.