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Background: Angiotensin-converting enzyme 2 (ACE2) is a pivotal molecular nexus linking novel coronavirus disease to breast cancer. In-silico investigations have repurposed carnosine for both these conditions based on its potential ACE2 inhibitory properties. Methods: Utilizing an ACE2 inhibitor screening kit, we determined the inhibitory range of carnosine doses. Subsequently, we examined the effect of carnosine on ACE2 expression in supernatants from various breast cancer cell lines (MCF-7, MDA-MB-231, and EMT-6). Additionally, we compared ACE2 activity in cell line pellets with and without carnosine and a putative ACE2 activator using a fluorometric activity assay kit. Finally, we performed a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay across overlapping concentrations. Results: Carnosine exhibited dose-dependent ACE2 inhibition within the 100-300 mM range. ACE2 expression significantly diminished after exposure to carnosine for 2 and 24 h in MDA-MB-231 and MCF-7 cell lines, respectively. MTT assay unveiled notable antiproliferative effects in MDA-MB-231 (50 % survival at approximately 265 mM) and EMT-6 cell lines (unquantifiable 50 % survival dose). Conversely, the MCF-7 cell line displayed a modest increase in proliferation (Effective concentration 50-186 mM, â¼40 % increased survival). Conclusion: This pioneering study delineates evident dose-dependent ACE2 inhibition by carnosine. Moreover, it unveils the modulatory impact of this ACE2 inhibitor in breast cancer cell lines. Carnosine demonstrated a significant antiproliferative effect on aggressive cell lines while sparing luminal cell lines from substantial toxic or proliferative effects.
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BACKGROUND: Phosphoinositide-Dependent Kinase-1 (PDK1) is a serine/threonine kinase, which belongs to AGC kinase family required by cancer cells. METHODS: Pharmacophoric space of 86 PDK1 inhibitors using six diverse sets of inhibitors was explored to identify high-quality pharmacophores. The best combination of pharmacophoric models and physicochemical descriptors was selected by genetic algorithm-based QSAR analysis that can elucidate the variation of bioactivity within the training inhibitors. Two successful orthogonal pharmacophores emerged in the optimum QSAR equation (r2 69 = 0.90, r2 LOO= 0.86, F= 51.92, r2 PRESS against 17 test inhibitors = 0.79). Receiver Operating Characteristic (ROC) curve analyses were used to estimate the QSAR-selected pharmacophores. RESULTS: 5 out of 11 compounds tested had shown potential intracellular PDK1 inhibition with the highest inhibition percent for compounds 92 and 93 as follows; 90 and 92% PDK1 inhibition, respectively. CONCLUSION: PDK1 inhibitors are potential anticancer agents that can be discovered by combination method of ligand based design with QSAR and ROC analysis.
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Proteínas Quinasas Dependientes de 3-Fosfoinosítido/antagonistas & inhibidores , Antineoplásicos/química , Antineoplásicos/farmacología , Inhibidores de Proteínas Quinasas/química , Inhibidores de Proteínas Quinasas/farmacología , Proteínas Quinasas Dependientes de 3-Fosfoinosítido/metabolismo , Línea Celular Tumoral , Descubrimiento de Drogas , Humanos , Ligandos , Modelos Moleculares , Neoplasias/tratamiento farmacológico , Neoplasias/metabolismo , Relación Estructura-Actividad CuantitativaRESUMEN
BACKGROUND: 3-Phosphoinositide Dependent Protein Kinase-1 (PDK1) is being lately considered as an attractive and forthcoming anticancer target. A Protein Data Bank (PDB) cocrystallized crystal provides not only rigid theoretical data but also a realistic molecular recognition data that can be explored and used to discover new hits. OBJECTIVE: This incited us to investigate the co-crystallized ligands' contacts inside the PDK1 binding pocket via a structure-based receptor-ligand pharmacophore generation technique in Discovery Studio 4.5 (DS 4.5). METHODS: Accordingly, 35 crystals for PDK1 were collected and studied. Every single receptorligand interaction was validated and the significant ones were converted into their corresponding pharmacophoric features. The generated pharmacophores were scored by the Receiver Operating Characteristic (ROC) curve analysis. RESULTS: Consequently, 169 pharmacophores were generated and sorted, 11 pharmacophores acquired good ROC-AUC results of 0.8 and a selectivity value above 8. Pharmacophore 1UU3_2_01 was used in particular as a searching filter to screen NCI database because of its acceptable validity criteria and its distinctive positive ionizable feature. Several low micromolar PDK1 inhibitors were revealed. The most potent hit illustrated anti-PDK1 IC50 values of 200 nM with 70% inhibition against SW480 cell lines. CONCLUSION: Eventually, the active hits were docked inside the PDK1 binding pocket and the recognition points between the active hits and the receptor were analyzed that led to the discovery of new scaffolds as potential PDK1 inhibitors.
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Fosfatidilinositoles/farmacología , Inhibidores de Proteínas Quinasas/farmacología , Piruvato Deshidrogenasa Quinasa Acetil-Transferidora/antagonistas & inhibidores , Sitios de Unión/efectos de los fármacos , Evaluación Preclínica de Medicamentos , Humanos , Ligandos , Modelos Moleculares , Estructura Molecular , Fosfatidilinositoles/síntesis química , Fosfatidilinositoles/química , Inhibidores de Proteínas Quinasas/síntesis química , Inhibidores de Proteínas Quinasas/química , Piruvato Deshidrogenasa Quinasa Acetil-Transferidora/metabolismoRESUMEN
Targeting tropomycin kinase A (TrkA) by small molecule inhibitors is considered as a promising strategy for treating several human cancers. To achieve this goal, a ligand based QSAR model was applied using the Discovery studio 4.5 (DS 4.5). Hence, a total list of 161 TrkA inhibitors was investigated. The TrkA inhibitors were extensively explored to detect their optimal physicochemical properties and pharmacophoric binding modes, which were converted into numeric descriptors and allowed to compete within the context of the Genetic Function Algorithm (GFA) approximations to find the subset of terms that correlates best with the activity. The resulted successful QSAR equation had statistical criteria of (r2129=0.67, r2LOO=0.61 r2PRESS against 32 external test inhibitors=0.50). Afterwards, the most successful pharmacophore: HypoB-T5-3, was used to screen compounds within the National Cancer institute (NCI) database. Only 41 compounds were retrieved and 21 of them exhibited anti-TrkA activity. The most potent hit had an IC50 value of 2.4µM. Later, upon docking the active hits into the TrkA binding pocket, important interactions were revealed including hydrogen bonding with the amino acids Asp668 and Lys544 in addition to the cation-π interactions with the sidechain of Arg559.
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Diseño de Fármacos , Modelos Moleculares , Inhibidores de Proteínas Quinasas/química , Relación Estructura-Actividad Cuantitativa , Receptor trkA/química , Humanos , Ligandos , Estructura Molecular , Inhibidores de Proteínas Quinasas/farmacología , Receptor trkA/antagonistas & inhibidores , Reproducibilidad de los Resultados , Programas InformáticosRESUMEN
Rosemary (Rosmarinus officinalis L.) is a popular herb in cooking, traditional healing, and aromatherapy. The essential oils of R. officinalis were obtained from plants growing in Victoria (Australia), Alabama (USA), Western Cape (South Africa), Kenya, Nepal, and Yemen. Chemical compositions of the rosemary oils were analyzed by gas chromatography-mass spectrometry as well as chiral gas chromatography. The oils were dominated by (+)-α-pinene (13.5%-37.7%), 1,8-cineole (16.1%-29.3%), (+)-verbenone (0.8%-16.9%), (-)-borneol (2.1%-6.9%), (-)-camphor (0.7%-7.0%), and racemic limonene (1.6%-4.4%). Hierarchical cluster analysis, based on the compositions of these essential oils in addition to 72 compositions reported in the literature, revealed at least five different chemotypes of rosemary oil. Antifungal, cytotoxicity, xanthine oxidase inhibitory, and tyrosinase inhibitory activity screenings were carried out, but showed only marginal activities.
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The pharmacophoric features of the virtual cocrystallized protein of 178 Hsp90 proteins were obtained from the protein data bank and explored to generate 1260 pharmacophores evaluated using the decoy list composed of 1022 compounds. Accordingly, 51 pharmacophores were selected with high receiver operating characteristic (ROC) value for further processing. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of accessing a self-consistent quantitative structure-activity relationship (QSAR) of optimal predictive potential (R672 = 0.819, F = 43.0, R2LOO = 0.782, R2PRESS against 16 external test inhibitors equal 0.735). Two orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least two binding modes accessible to ligands within the Hsp90 binding pocket. The fifth generated pharmacophoric model from Hsp90 protein 2XJX (2XJX_2_05), and the forth generated cocrystallized pharmacophoric model from Hsp90 protein 4LWF (4LWF_2_04) with area under the curve AUC-ROC values 0.812 and 0.876, respectively were selected to be used as a searching tool sequentially of the National Cancer Institute (NCI) database. The captured hits were mapped based on successful hypotheses and the best predicted hits were selected. Twenty-four hits showed Hsp90 inhibition, 15 hits were measured with low micromolar IC50 ranged from 5.0 µM to 77.1 µM.
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Descubrimiento de Drogas , Proteínas HSP90 de Choque Térmico/antagonistas & inhibidores , Algoritmos , Cristalización , Proteínas HSP90 de Choque Térmico/metabolismo , Humanos , Ligandos , Modelos LinealesRESUMEN
The pharmacophoric features of the virtual co-crystallized protein of 17 Akt1 proteins were downloaded from the protein data bank, and explored to end up with 132 generated pharmacophores that had been evaluated using the decoy list composed of 1724 compounds. The areas under the curve of the Receiver-Operating Characteristic (ROC-AUC) were sorted, and the highest ranked pharmacophore 3MV5_2_01 was selected to be used as a searching tool in the National Cancer Institute (NCI) database. The captured hits were mapped based on successful hypotheses and the best fitted compounds were selected. The inhibition of Akt1 was measured and expressed as a percentage of inhibition. 24 out of the 40 compounds showed inhibition of Akt1, out of which 13 compounds showed more than 50% inhibition. Compound 1 showed 93.3% inhibition at 100 µM concentration. To confirm the inhibition of Akt1 phosphorylation, MCF10A cell line was co-treated with 12-O-tetradecanoylphorbol-13-acetate (TPA) and 100 µM of each of the most potent 13 Akt inhibitors (1-13). It was found that compounds 1 exert 91.6% inhibition of Akt1 phosphorylation in MCF10A cell line.
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Antineoplásicos/química , Inhibidores de Proteínas Quinasas/química , Proteínas Proto-Oncogénicas c-akt/química , Antineoplásicos/farmacología , Dominio Catalítico , Línea Celular Tumoral , Cristalografía por Rayos X , Ensayos de Selección de Medicamentos Antitumorales , Humanos , Enlace de Hidrógeno , Simulación del Acoplamiento Molecular , Unión Proteica , Inhibidores de Proteínas Quinasas/farmacología , Proteínas Proto-Oncogénicas c-akt/antagonistas & inhibidores , Curva ROCRESUMEN
Three derivatives of substituted 1,2,3-thia- or 1,2,3-selenadiazole (4a-c) were prepared and characterized by different chemical techniques. These compounds were evaluated for their antimicrobial and antitumor activities. Compounds 4a (propenoxide derivative), 4b (carbaldehyde derivative), and 4c (benzene derivative) were active against the yeast-like fungi Candida albicans. Compound 4a was active against gram-negative Escherichia coli, and compound 4c was active against the gram-positive Staphylococcus aureus. For the antitumor activity, both compounds 4b and 4c were active against all tested tumor cell lines, namely, SW480, HCT116, C32, MV3, HMT3522, and MCF-7. The activity of compound 4c was greater than that of compound 4b and more than that of the reference antitumor 5-flourouracil against the SW480, HCT116, and MCF-7 tumor cell lines. In conclusion, a number of the prepared 1,2,3-thia- or 1,2,3-selenadiazole compounds showed promising antifungal, antibacterial, and in vitro antitumor activities. Further investigations are required to explore the mechanism by which active compound are inducing their cytotoxicity.