Effect of quercetin on doxorubicin cytotoxicity in sensitive and resistant human MCF7 breast cancer cell lines.

Chemoresistance is the major cause of cancer recurrence, relapse and eventual death. Doxorubicin resistance is one such challenge in breast cancer. The use of quercetin, an antioxidant, in combination with doxorubicin has been investigated for offering protection to normal cells from the toxic side effects of doxorubicin in addition to modulation of its resistance. The present study aimed to investigate the effects of quercetin in prevention of a doxorubicin-chemoresistant phenotype in both doxorubicin-sensitive and -resistant human MCF-7 breast cancer cell lines. A doxorubicin-resistant MCF-7 cell line was established. The development of resistant cells was closely monitored for changes in morphological features. Sensitivity to doxorubicin and the doxorubicin/quercetin combination was assessed using the tetrazolium assay. To determine the mechanism by which quercetin sensitizes the doxorubicin MCF-7-resistant cell line to doxorubicin, gene expression alterations in breast cancer-related genes were examined using the reverse transcription-quantitative PCR (RT-qPCR) array technology. Resistant MCF cells were successfully developed and the inhibitory concentration (IC50) value of doxorubicin increased from 0.133 to 4 µM (wild-type to resistant). The effects of the quercetin/doxorubicin combination exhibited different effects on wild-type vs. resistant cells. The IC50 of doxorubicin was reduced in wild cells, whereas resistant cells showed an increase in cell viability at lower concentrations and a potentiation of the effects of doxorubicin only at higher concentrations. Annexin V/propidium iodide staining demonstrated that quercetin drives cells into late apoptosis and necrosis, but in resistant cells, necrosis predominates. RT-qPCR results revealed that quercetin led to a reversal in doxorubicin effects via up- and downregulation of important genes such as SNAI2, PLAU and CSF1 genes. Downregulation of cell migration genes, SNAI2 (-31.23-fold) and plasminogen activator, urokinase (PLAU; -30.62-fold), and the apoptotic pathway gene, colony stimulating factor 1 (CSF1; -17.25-fold) were the most important querticin-associated events. Other gene alterations were also observed involving cell cycle arrest and DNA repair pathways. The results of the present study indicated that quercetin could lead to a reversal of doxorubicin resistance in breast cancer cells via downregulation of the expression of important genes, such as SNAI2, PLAU and CSF1. Such findings may represent a potential strategy for reversing breast cancer cell-related chemoresistance.

Anti-Proliferative Effect of Potential LSD1/CoREST Inhibitors Based on Molecular Dynamics Model for Treatment of SH-SY5Y Neuroblastoma Cancer Cell Line.

BACKGROUND: Lysine-specific demethylase is a demethylase enzyme that can remove methyl groups from histones H3K4me1/2 and H3K9me1/2. It is expressed in many cancers, where it impedes differentiation and contributes to cancer cell proliferation, cell metastasis and invasiveness, and is associated with inferior prognosis. LSD1 is associated with its corepressor protein CoREST, and utilizes tetrahydrofolate as a cofactor to accept CH2 from the demethylation process. The fact that the cofactor is best bound to the active site inspired us to explore its interactions to LSD1/CoREST enzyme complex utilizing molecular dynamics simulation, which aids designing novel and potent inhibitors. OBJECTIVE: In this study we minted to identify a new potential LSD1/CoREST inhibitors and test the potency and the safety of such inhibitors against human neuroblastoma and fibroblast cells lines. METHODS: We have implemented a previously derived model from the molecular dynamics simulation study and the key contacts to the active site in a subsequent structure based drug design and in-silico screening, which revealed a number of potential inhibitors toward LSD1/CoREST complex. The anti-proliferative activities of the identified compounds will be tested against neuroblastoma SH-SY5Y cancer cell line which known to highly express LSD1/CoREST complex. RESULTS: In-silico mining on National Cancer Institute (NCI) database identified 55 promising and structurally diverse inhibitors. Applying the abovementioned molecular modeling procedure yielded four compounds of LSD1/CoREST inhibiters with IC50 < 2µM. The four lead compounds were tested against SH-SY5Y neuroblastoma cell line that known to express high level of LSD1 and illustrated a potent activity with an IC50 ranging from 0.195 to 1.52µM. To estimate the toxicity of the selective leads, they were tested against normal fibroblast cells and scored a relatively high IC50 ranging from 0.303 to ≥ 100µM. CONCLUSION: Our model revealed promising inhibitors that can be used in treating cancers that overexpress the LSD1 enzyme such as the SH-SY5Y neuroblastoma.

1,4-Naphthoquinone Is a Potent Inhibitor of IRAK1 Kinases and the Production of Inflammatory Cytokines in THP-1 Differentiated Macrophages.

Quinones are a class of cyclic organic compounds that are widely distributed in nature and have been shown to exhibit anti-inflammatory, antioxidant, and anticancerous activities. However, the molecular mechanisms/signaling by which these molecules exert their effect are still not fully understood. In this study, a group of quinone-derived compounds were examined for their potential inhibitory effect against human IRAK1 and IRAK4 kinases in vitro. We have identified five compounds: 1,4-naphthoquinone, emodin, shikonin, plumbagin, and menadione (vitamin K3) as active and selective inhibitors of human IRAK1 enzyme in vitro. The biochemical binding and molecular interactions between the active compounds and IRAK1's catalytic site were demonstrated in silico using structural-based docking and dynamic simulation analysis. Also, 1,4-naphthoquinone was found to effectively inhibit the growth of cancer cell lines overexpressing IRAK1. Furthermore, 1,4-naphthoquinone potently suppressed the production and secretion of key proinflammatory cytokine proteins IL-8, IL-1ß, IL-10, TNF-α, and IL-6 in LPS-stimulated PMA-induced human THP-1 macrophages. In conclusion, 1,4-naphthoquinone is an effective inhibitor of IRAK1 kinases and their mediated inflammatory cytokines production in LPS-stimulated PMA-induced human THP-1 macrophages.

Coffee Bean Polyphenols Can Form Biocompatible Template-free Antioxidant Nanoparticles with Various Sizes and Distinct Colors.

Plant polyphenols have attracted attention in recent years due to their ability to undergo oxidative coupling reactions enabled by the presence of multiple phenolic hydroxyl groups, forming chemically versatile coatings and biocompatible nanoparticles (NPs) for various applications. The aim of this study was to investigate whether coffee bean aqueous extracts, which are known to be rich in polyphenols, could serve as a natural source of NP building blocks. Extracts were prepared by heating ground Arabica beans of varying roasting degrees in water with or without the addition of sodium metaperiodate or copper sulfate as an oxidizing agent, followed by filtration. NP formation was verified by dynamic light scattering and transmission electron microscopy, which revealed the presence of nano-sized particles with varying sizes and polydispersities as a function of the coffee type and oxidizing agent used. NP colors ranged from light to medium to dark brown, and particle sizes were between 44 and 250 nm with relatively low polydispersity indices. In vitro antioxidant assays showed that oxidizing agent-treated coffee NPs had lower antioxidant potency compared to air-oxidized NPs, but the free-radical scavenging activity was still retained. Coffee NPs exhibited no antimicrobial activity against common bacterial and fungal strains. Cell viability assays demonstrated that the NPs were biocompatible in human dermal fibroblasts, while exhibiting antiproliferative activity against MCF7 breast cancer cells, particularly copper sulfate-oxidized NPs. This study presents a facile and economical method to produce template-free antioxidant NPs that may be explored for various applications such as drug delivery and cosmetics.

Comparative anti-proliferative effects of potential HER2 inhibitors on a panel of breast cancer cell lines.

BACKGROUND: Breast cancer is one of the most lethal types of cancer in women worldwide. The human epidermal growth factor receptor 2 (HER2) is considered as a validated target in breast cancer therapy. Previously, we have used quantitative structure activity relationship QSAR equations and their associated pharmacophore models to screen for new promising HER2 structurally diverse inhibitory leads which were tested against HER2-overexpressing SKOV3 ovarian cancer cell line. OBJECTIVE: In this study, we sought to explore the effect of most active ligands against different normal and breast cancer cell lines that represent different breast cancer subtypes with distinguished expression levels in HER2 and HER1. METHODS: We have tested the promising compounds against SKBR3, MDA-MB-231, MCF7, human fibroblast, and MCF10 cell lines. To understand the inhibitory effects of the active ligands against HER2 over expressed breast cancer cell lines, all inhibitors and the control compound, lapatinib, were docked into the active site of HER2 enzyme performed using Ligand Fit docking engine and PMF scoring function. RESULTS: Five ligands exhibited promising results with relatively low IC50 values on cells that amplify HER2 and high IC50 on those that do not express such a receptor. The most potent compound (compound 13) showed an IC50 of 0.046 µM. To test their toxicity against normal cells, the active compounds were tested against both normal fibroblast and normal breast cancer cell MCF-10 and relatively high IC50 values were scored. The IC50 values on HER2 over-expressed breast cancer and normal fibroblast cells provided a promising safety index. Docking results showed the highest similarity in the binding site between the most active ligand and the lapatinib. CONCLUSION: Our pharmacophore model resulted in a high potent ligand that shows high potency against HER2 positive breast cancer and relatively low toxicity towards the normal human cells.

Nature-Inspired Polymerization of Quercetin to Produce Antioxidant Nanoparticles with Controlled Size and Skin Tone-Matching Colors.

Plant polyphenols have received considerable attention in recent years due to their ability to undergo oxidation-triggered self-polymerization, forming biocompatible versatile coatings and templated nanoparticles (NPs) that can be leveraged for a variety of biomedical applications. Here we show for the first time that untemplated NPs can be conveniently synthesized from the abundant plant polyphenol quercetin (QCT) simply by incubation with an oxidizing agent in a universal organic solvent, followed by self-assembly upon gradual addition of water. The process yielded NPs of around 180-200 nm in size with a range of colors that resembled light to medium-brown skin tones. The NPs were characterized by UV-Vis, FT-IR, and 1H-NMR spectroscopy and by dynamic light scattering and transmission electron microscopy to understand their physicochemical properties. Antioxidant and cell viability assays were also conducted to demonstrate the NPs' free-radical scavenging activity and biocompatibility, altogether providing valuable insights into the structure and function of this emerging class of nanomaterials to guide future biomedical applications.

Pancreatic lipase inhibitory activity of selected pharmaceutical agents.

Twenty-five structurally diverse compounds have been tested in vitro for their pancreatic lipase (PL) inhibitory activity. Despite the diversity of tested compounds, the relationship comprising structural attributes of the compounds could be established to correlate with the observed inhibitory activity. Compounds that exerted inhibitory action through surface activity were of different profile from the rest of compounds. When co-incubated with orlistat (OsT), important synergistic effects for some compounds (orphenadrine, gliclazide, cefuroxime and sulfacetamide) were revealed, while antagonistic effects were demonstrated for others (camphor sulfonic acid and dinitro salicylic acid). Docking studies for the most active molecules were performed and molecular interaction forces with the PL active site were identified. The results suggested co-binding of OsT along with the other inhibitor in the binding site in cases of synergistic effect but not in the case of antagonistic effect. These results were additionally supported by affinity capillary electrophoresis. In conclusion, synergistic lipase inhibitory activity between OsT and some other pharmaceutical compounds was demonstrated for the first time, which might help improve the pharmacological effect of OsT.

Exploring the Active Center of the LSD1/CoREST Complex by Molecular Dynamics Simulation Utilizing Its Co-crystallized Co-factor Tetrahydrofolate as a Probe.

Epigenetic targeting of cancer is a recent effort to manipulate the gene without destroying the genetic material. Lysine-specific demethylase 1 (LSD1) is one of the enzymes associated with the chromatin for post-translational modifications, where it demethylates lysine amino acid in the chromatin H3 tail. Many studies showed that inhibiting LSD1 could potentially be used to treat cancer epigenetically. LSD1 is associated with its corepressor protein CoREST, and it uses tetrahydrofolate as a co-factor to accept CH2 from the demethylation process. In this study, the co-crystallized co-factor tetrahydrofolate was utilized to determine possible binding regions in the active center of the LSD1/CoREST complex. Also, the flexibility of the complex has been investigated by molecular dynamics simulation and subsequent analysis by clustering and principal component analysis. This research supported other studies and showed that LSD1/CoREST complex exists in two main conformational structures: open and closed. Furthermore, this study showed that tetrahydrofolate stably binds to the LSD1/CoREST complex, in its open conformation, at its entrance. It then binds to the core of the complex, inducing the closed conformation. Furthermore, the interactions of tetrahydrofolate to these two binding regions and the corresponding binding mode of tetrahydrofolate were investigated to be used in structure-based drug design.

Discovery of new human epidermal growth factor receptor-2 (HER2) inhibitors for potential use as anticancer agents via ligand-based pharmacophore modeling.

To discover potential antitumor agents directed toward human epidermal growth factor receptor-2HER2/ErbB2 overexpression in cancer, we have explored the pharmacophoric space of 115 HER2/ErbB2 inhibitors. This identified 240 pharmacophores which were subsequently clustered into 20 groups and cluster centers were used as 3D-pharmacophoric descriptors in QSAR analysis with 2D-physicochemical descriptors to select the optimal combination. We were obliged to use ligand efficiency as the response variable because the logarithmic transformation of bioactivities failed to access self-consistent QSAR models. Two binding pharmacophore models emerged in the optimal QSAR equation, suggesting the existence of distinct binding modes accessible to ligands within the HER2/ErbB2 binding pocket. The QSAR equation and its associated pharmacophore models were employed to screen the National Cancer Institute (NCI) and Drug Bank databases to search for new, promising, and structurally diverse HER2 inhibitory leads. Inhibitory activities were tested against HER2-overexpressing SKOV3 Ovarian cancer cell line and MCF-7 which express low levels of HER2. In silico mining identified 80 inhibitors out of which four HER2 selective compounds inhibited the growth of SKOV3 cells with IC50 values < 5µM and with virtually no effect in MCF-7 cells. These lead compounds are excellent candidates for further optimization.

Ligand-based designing, in silico screening, and biological evaluation of new potent fructose-1,6-bisphosphatase (FBPase) inhibitors.

Fructose-1,6-bisphosphatase - hereafter abbreviated as FBPase has been recently implicated in diabetes prompting several attempts to discover and optimize new FBPase inhibitors. Toward this end we explored the pharmacophoric space of 136 FBPase inhibitors using three diverse sets of inhibitors. This identified 520 pharmacophores that were subsequently clustered into 104 groups. Cluster centers were evaluated by receiver operating characteristic (ROC) curves analysis and correlation with bioactivities of collected compounds. Pharmacophore model Hypo1/7 illustrated the best combination of classification power (ROC-AUC) and correlation with bioactivity. Two other pharmacophores (Hypo2/1 and Hypo2/6) were found to be mergeable and their combined model (Hypo2-1/2-6) illustrated excellent ROC performance. We employed Hypo1/7 and Hypo2-1/2-6 models to screen the National Cancer Institute (NCI) list of compounds. In silico mining identified 18 FBPase inhibitors out of which six were of sub-micromolar IC(50) values.

Discovery of new antifungal leads via pharmacophore modeling and QSAR analysis of fungal N-myristoyl transferase inhibitors followed by in silico screening.

N-Myristoyl transferase is an essential enzyme for fungal growth and survival. The continuous interest in the development of new antifungal agents prompted recent interest in developing new potent inhibitors of fungal N-myristoyl transferase. In this context, we combined pharmacophore and QSAR modeling to explore the structural requirements for potent N-myristoyl transferase inhibitors employing 55 known N-myristoyl transferase ligands. Four binding pharmacophore models emerged in the optimal QSAR equations (R(2)(44) = 0.81-0.83, F-statistic = 47.89-58.83, r(2)(L00)= 0.77-0.80, against 11 external test inhibitors = 0.61-0.71). The successful pharmacophores were complemented with exclusion spheres to optimize their receiver operating characteristic curve profiles. The QSAR equations and their associated pharmacophore models were validated by the identification and experimental evaluation of new promising antifungal leads retrieved from the NCI database and our in-house-built database of established drugs and agrochemicals.

Pharmacophore and QSAR modeling of estrogen receptor beta ligands and subsequent validation and in silico search for new hits.

The pharmacophoric space of estrogen receptor beta (ERbeta) was explored using a set of 119 known ligands. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select optimal combinations of pharmacophoric models and physicochemical descriptors in self-consistent and predictive quantitative structure-activity relationships (QSARs) (r(96)(2)=0.79-0.83, F-statistic=40.96-36.20, r(LOO)(2)=0.74-0.76 and r(PRESS)(2) against 23 external compounds=0.54-0.56, respectively). Four binding hypotheses emerged in two optimal QSAR equations suggesting the existence of distinct binding modes accessible to ligands within ERbeta binding pocket. The close similarity among the resulting pharmacophores prompted us to merge them in two hybrid models. The hybrid pharmacophores illustrated superior receiver operator characteristic curves (ROCs) and closely resembled binding interactions suggested by docking experiments. The resulting models and associated QSAR equations were employed to screen the national cancer institute (NCI) list of compounds and an in house built database of known drugs and agrochemicals to search for new ERbeta ligands.

Homology modeling of MCH1 receptor and validation by docking/scoring and protein-aligned CoMFA.

Homology modeling is becoming a valid method for obtaining three-dimensional coordinates for proteins. However, it is hard to judge the qualities of the resulting models warranting robust subsequent validations. In an attempt to evaluate the quality of Melanin-concentrating hormone 1 receptor (MCH1R) homology models, a number of homology structures were scanned for potential binding cavities. Subsequently, a group of 35 benzylpiperidines' MCH1R inhibitors were docked into each of the proposed binding sites via four different scoring functions. The docked structures were utilized to construct corresponding protein-aligned comparative molecular field analysis (CoMFA) models by employing probe-based (H(+), OH, CH(3)) energy grids and genetic partial least squares (G/PLS) statistical analysis. The docking-based alignment succeeded in accessing self-consistent CoMFA models upon employing JAIN scoring function in one of the proposed binding pockets in a particular homology model. Furthermore, a ligand-based pharmacophore model was developed for the same set of inhibitors and was found to agree with the successful docking configuration. Therefore, we proved that the overall procedure of docking, scoring, and CoMFA evaluation can be a useful tool to validate homology models, which can be of value for structure-based design, in-silico screening, and in understanding the structural basis of ligand binding to MCH1R.

Development of predictive in silico model for cyclosporine- and aureobasidin-based P-glycoprotein inhibitors employing receptor surface analysis.

P-glycoprotein (Pgp) is implicated in multiple drug resistance (MDR) exhibited by several types of cancer against a multitude of anticancer chemotherapeutic agents. This problem prompted several research groups to search for effective P-gp inhibitors. Cyclosporine A (CsA), aureobasidin A (AbA) and related analogues were reported to possess potent inhibitory actions against Pgp. In this work we employed receptor surface analysis (RSA) to construct two satisfactory receptor surface models (RSMs) for cyclosporine- and aureobasidin-based Pgp inhibitors. These pseudoreceptors were combined to achieve satisfactory three-dimensional quantitative structure activity relationship (3D-QSAR) for 68 different cyclosporine and aureobasidin derivatives. Upon validation against an external set of 16 randomly selected Pgp inhibitors, the optimal 3D-QSAR was found to be self-consistent and predictive (r(LOO)(2)=0.673, r(PRESS)(2)=0.600). The resulting 3D-QSAR was employed to probe the structural factors that control the inhibitory activities of cyclosporine and aureobasidin analogues against Pgp.

Combining ligand-based pharmacophore modeling, quantitative structure-activity relationship analysis and in silico screening for the discovery of new potent hormone sensitive lipase inhibitors.

Hormone sensitive lipase (HSL) has been recently implicated in diabetes and obesity, prompting attempts to discover new HSL inhibitors. Toward this end, we explored the pharmacophoric space of HSL inhibitors using four diverse sets of compounds. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of yielding a self-consistent and predictive quantitative structure-activity relationship (QSAR) (r = 0.822, n = 99, F = 11.1, r LOO (2) = 0.521, r PRESS (2) against 23 external test inhibitors = 0.522). Interestingly, two pharmacophoric models emerged in the QSAR equation suggesting at least two binding modes. These pharmacophores were employed to screen the National Cancer Institute (NCI) list of compounds and our in-house built database of established drugs and agrochemicals. Active hits included the safe herbicidal agent bifenox (IC 50 = 0.43 microM) and the nonsteroidal anti-inflammatory naproxen (IC 50 = 1.20 microM). Our active hits undermined the traditional believe that HSL inhibitors should possess covalent bond-forming groups.

Pharmacophore modeling, quantitative structure-activity relationship analysis, and in silico screening reveal potent glycogen synthase kinase-3beta inhibitory activities for cimetidine, hydroxychloroquine, and gemifloxacin.

The pharmacophoric space of glycogen synthase kinase-3beta (GSK-3beta) was explored using two diverse sets of inhibitors. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select optimal combination of pharmacophores and physicochemical descriptors that access self-consistent and predictive quantitative structure-activity relationship (QSAR) against 132 training compounds ( r (2) 123 = 0.663, F = 24.6, r (2) LOO = 0.592, r (2) PRESS against 29 external test inhibitors = 0.695). Two orthogonal pharmacophores emerged in the QSAR, suggesting the existence of at least two distinct binding modes accessible to ligands within GSK-3beta binding pocket. The validity of the QSAR equation and the associated pharmacophores was established by the identification of three nanomolar GSK-3beta inhibitors retrieved from our in-house-built structural database of established drugs, namely, hydroxychloroquine, cimetidine, and gemifloxacin. Docking studies supported the binding modes suggested by the pharmacophore/QSAR analysis. In addition to being excellent leads for subsequent optimization, the anti-GSK-3beta activities of these drugs should have significant clinical implications.

Discovery of new MurF inhibitors via pharmacophore modeling and QSAR analysis followed by in-silico screening.

The pharmacophoric space of streptococcal MurF was explored using a set of 39 known inhibitors. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and physicochemical descriptors that access self-consistent quantitative structure-activity relationship (QSAR) (r(2)=0.93,F=56.9,r(LOO)(2)=0.91,r(PRESS)(2) against eight external test inhibitors=0.75). Two orthogonal pharmacophores (of cross-correlation r(2)=0.26) emerged in the QSAR equation suggesting the existence of at least two distinct binding modes accessible to ligands within MurF binding pocket. The validity of the QSAR equation and the associated pharmacophore models was experimentally established by the identification of three promising new MurF inhibitors retrieved from the NCI database. Docking studies conducted on active hits supported the binding modes suggested by the pharmacophore/QSAR analysis.