Cytotoxic activity of Thymus capitatus collected from Hail region in Saudi Arabia with mechanistic study via induction of caspase-dependent apoptosis and S-phase arrest

Thymus capitatus is a plant grows in Mediterranean area and some Arab countries such as Saudi Arabia. It possesses numerous medicinal values. Its common name is Zaatar and it belongs to family Lamiaceae Thymus capitatus leaves and stem were collected from Hail region, Saudi Arabia. Then both leaves and stem were extracted with ethanol. This study was performed to evaluate cytotoxic activity of Thymus capitatus leaves and stem ethanolic extract in details. Doxorubicin was used as a standard and the relevant half maximal inhibitory concentration (IC50) values were computed for each cell line by 3-(4,5- diemthylthiazole-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. In addition, further mechanistic study was carried out by using Apoptosis assay to explore cytotoxic activity of plant extract. Both leaves and stems extracts were screened against HepG2, A-549, HCT-116 and   MCF-7 cancer cell lines. It was found that leaves’ extract shows high and moderate cytotoxic activity against both A-549 and HepG2 cancer cell lines, respectively (with IC50 = 13.6 and 21.5 μg/ml, respectively), while stem’s extract exerted moderate cytotoxic activity against A-549 cancer cell lines (with IC50 = 21.38 μg/ml).  Further mechanistic study was carried out on A-549 cells by using apoptosis assay. It showed that leaves’ extract resulted in arrest of S-phase and caused apoptosis through activation of caspase-3, p53 and Bax, in addition to down regulation of Bcl-2

Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization

Nowadays, supercritical fluid technology (SFT) has been an interesting scientific subject in disparate industrial-based activities such as drug delivery, chromatography, and purification. In this technology, solubility plays an incontrovertible role. Therefore, achieving more knowledge about the development of promising numerical/computational methods of solubility prediction to validate the experimental data may be advantageous for increasing the quality of research and therefore, the efficacy of novel drugs. Decitabine with the chemical formula C₈H₁₂N₄O₄ is a chemotherapeutic agent applied for the treatment of disparate bone-marrow-related malignancies such as acute myeloid leukemia (AML) by preventing DNA methyltransferase and activation of silent genes. This study aims to predict the optimum value of decitabine solubility in CO₂SCF by employing different machine learning-based mathematical models. In this investigation, we used AdaBoost (Adaptive Boosting) to boost three base models including Linear Regression (LR), Decision Tree (DT), and GRNN. We used a dataset that has 32 sample points to make solubility models. One of the two input features is P (bar) and the other is T (k). ADA-DT (Adaboost Algorithm Decision Tree), ADA-LR (Adaboost Algorithm-Linear Regresion), and ADA-GRNN (Generative Regression Neural Network) models showed MAE of 6.54 ˣ 10ˉ⁵, 4.66 10 ˉ⁵, and 8.35 10 ˉ⁵, respectively. Also, in terms of R-squared score, these models have 0.986, 0.983, and 0.911 scores, respectively. ADA-LR was selected as the primary model according to numerical and visual analysis. Finally, the optimal values are (P = 400 bar, T = 3.38 K 102, Y = 1.064 10ˉ³ mol fraction) using this model

Design, Synthesis and Antineoplastic Evaluation of a Variety of Small Molecule Scaffolds

Several appealing strategies emerged for selective anticancer therapy. Mitochondrial respiratory complex II (CII) is a potential target for many human diseases, including cancer. We have designed, synthesized, and characterized a library of potent CII inhibitors atpenin A5 and diazoxide analogs with enhanced ‘drug-likeness’ and evaluated their antineoplastic activity. Several of these derivatives showed greater activity and selectivity to inhibit the CII. Design aspects of lead derivatives (16c) include optimum ligand lipophilicity efficiency of \u3e5, and half-life of \u3e3 hours. This derivative displayed potent and selective inhibition of cell proliferation in both multiple human prostate cancer cell lines and reactive stromal cells in a dose-dependent manner which maybe a novel therapeutic strategy which can confer significant benefit to patients. Also, several diazoxide derivatives displayed potent and selective inhibition of cell proliferation in triple-negative breast cancer MDA-MB-468 cells. Antiangiogenesis drugs play a beneficial role in cancer treatment. Inhibition of vascular endothelial growth factor (VEGF) is one of the significant targets in tumor angiogenesis. Suppressing vascular permeability in tumor cells leads to inhibition of tumor growth by locking the survival factor that delivers the oxygen and nutrients to the tumors. We have designed and synthesized a library of potent VEGF inhibitors that had potency to inhibit the HUVEC-VEGF treated cells. Inhibition of specific carbonic anhydrases (CA) enzymes emerged as a new strategy for anticancer therapy. The CA isoforms IX and XII were known to be overexpressed in various human solid tumors and play a critical role in regulating tumor acidification, proliferation, and progression. Series of novel sulfonamides containing coumarin moieties were synthesized as potent CA inhibitors. These compounds would be able to selectively target the tumor-associated CA IX and CA XII with high inhibition activity. Several of these compounds have anticancer activity against the MDA-MB-468 cells. The current dissertation emphasizes on the synthesis and evaluation of novel compounds that inhibit CII, VEGF, and CA as anticancer agents. I envision that further studies will lead to the optimization of the structure-activity relationship of these new derivatives and recognize molecular and signaling pathways that could further result in the outcome of anticancer therapy

Anti-Cancer Drug Solubility Development within a Green Solvent: Design of Novel and Robust Mathematical Models Based on Artificial Intelligence

Nowadays, supercritical CO2(SC-CO2) is known as a promising alternative for challengeable organic solvents in the pharmaceutical industry. The mathematical prediction and validation of drug solubility through SC-CO2 system using novel artificial intelligence (AI) approach has been considered as an interesting method. This work aims to evaluate the solubility of tamoxifen as a chemotherapeutic drug inside the SC-CO2 via the machine learning (ML) technique. This research employs and boosts three distinct models utilizing Adaboost methods. These models include K-nearest Neighbor (KNN), Theil-Sen Regression (TSR), and Gaussian Process (GPR). Two inputs, pressure and temperature, are considered to analyze the available data. Furthermore, the output is Y, which is solubility. As a result, ADA-KNN, ADA-GPR, and ADA-TSR show an R2 of 0.996, 0.967, 0.883, respectively, based on the analysis results. Additionally, with MAE metric, they had error rates of 1.98 × 10−6, 1.33 × 10−6, and 2.33 × 10−6, respectively. A model called ADA-KNN was selected as the best model and employed to obtain the optimum values, which can be represented as a vector: (X1 = 329, X2 = 318.0, Y = 6.004 × 10−5) according to the mentioned metrics and other visual analysis

Development of computational intelligence models for assessment of drug nanonization using green chemistry technique: Improvement of drug solubility

Determination of solubility via theoretical approaches was carried out in this study. Because of its importance to the expansion of the pharmaceutical industry, this study models Lenalidomide solubility in supercritical carbon dioxide using multiple tree-based techniques which are of machine learning nature. These parameters are molded based on temperature and pressure input features due to the significant variability of drug solubility with the temperature and pressure. The experimental data have been collected and inputted the models to train them and used the data for testing the machine learning models. The results are useful for production of nanomedicine with enhanced solubility in solvents. Decision Tree (DT), Extra Trees (ET), and Gradient Boosting (GB) models are used and optimized using SCA algorithm to obtain more robust models for prediction of the drug solubility in the solvent. So, the developed models are called SCA-DT, SCA-ET, and SCA-GB in this study and have R2-scores of 0.932, 0.951, and 0.997, respectively. The SCA-DT model has an RMSE error rate of 0.0948, this rate is 0.0822 for SCA-ET, and 0.0203 for SCA-GB. So, the SCA-GB is introduced as the best model of this research for prediction of Lenalidomide solubility in the solvent

Synthesis, Molecular Docking Study, and Cytotoxic Activity against MCF Cells of New Thiazole–Thiophene Scaffolds

Investigating novel compounds that may be useful in designing new, less toxic, selective, and potent breast anticancer agents is still the main challenge for medicinal chemists. Thus, in the present work, acetylthiophene was used as a building block to synthesize a novel series of thiazole-bearing thiophene derivatives. The structures of the synthesized compounds were elucidated based on elemental analysis and spectral measurements. The cytotoxic activities of the synthesized compounds were evaluated against MCF-7 tumor cells and compared to a cisplatin reference drug, and against the LLC-Mk2 normal cell line using the MTT assay, and the results revealed promising activities for compounds 4b and 13a. The active compounds were subjected to molecular modeling using MOE 2019, the pharmacokinetics were studied using SwissADME, and a toxicity radar was obtained from the biological screening data. The results obtained from the computational studies supported the results obtained from the anticancer biological studies

Expedient Single Step Access to Strained Tricyclic Ketals

The synthesis of cyclopropyl methyl ketones and highly strained fused substituted dihydrobenzopyran cyclopropyl lactones derived from coumarin carboxylates and chloroacetone in the presence of potassium carbonate is reported. One step synthetic access to the previously unknown dihydrobenzopyran cyclopropyl tricyclic ketals is achieved with wide substrate scope. Substituted coumarin carboxylates, phenylamides or a quinolin-2(1H)-one possessing alkyl electron donating (methyl, t-butyl) and electron withdrawing groups (F, Cl, Br, NO2) in the 4 or 6 positions formed the highly strained dihydrobenzopyran cyclopropyl tricyclic ketals in moderate yield alongside the expected coumarin carboxylate. Saturation or substitution at the 5-position or 6-OMe afforded no tricyclic ketal compound but solely coumarin carboxylates. The formation of both structures in selected derivatives was confirmed by X-ray crystallography. A plausible mechanism is proposed for the formation of the fused lactone; via intramolecular rearrangement of cis cyclopropyl methyl ketones with phenolic acetate via the formation of a hemiacetal

Selective Carbonic Anhydrase IX and XII Inhibitors Based Around a Functionalized Coumarin Scaffold

Inhibition of specific carbonic anhydrase (CA) enzymes is a validated strategy for the development of agents to target cancer. The CA isoforms IX and XII are overexpressed in various human solid tumors wherein they play a critical role in regulating extracellular tumor acidification, proliferation, and progression. A series of novel sulfonamides based on the coumarin scaffold were designed, synthesized and characterized as potent and selective CA inhibitors. Selected compounds show significant activity and selectivity over CA I and CA II to target the tumor-associated CA IX and CA XII with high inhibition activity at the single digit nanomolar level. Twelve compounds were identified to be more potent compared with acetazolamide (AAZ) control to inhibit CA IX while one was also more potent than AAZ to inhibit CA XII. Compound 18f (Ki’s = 955 nM, 515 nM, 21 nM and 5 nM for CA’s I, II, IX and XII respectively) is highlighted as a novel CA IX and XII inhibitor for further development

Discovery of Halogenated Benzothiadiazine Derivatives with Anticancer Activity

Mitochondrial respiratory complex II (CII), also known as succinate dehydrogenase, plays a critical role in mitochondrial metabolism. Known but low potency CII inhibitors are selectively cytotoxic to cancer cells including the benzothiadiazine-based anti-hypoglycemic diazoxide. Herein, we study the structure-activity relationship of benzothiadiazine derivatives for CII inhibition for the first time. A number of more potent derivatives were identified. Cytotoxicity evaluation of the novel derivatives resulted in the identification of compounds with greater anticancer effect than the parent; two benzothiadiazine derivative classes (24a-d and 30a, 30c, 30d) that possess activity to reduce the cell viability of 22Rv1 prostate cancer cells and five novel 7-fluorobenzothiadiazine derivatives which possessed significant cytotoxicity in a cellular model of triple negative breast cancer. No correlation between cytotoxicity and CII inhibition was found, indicating an as yet undefined mechanism of action of this scaffold. </div

Digalloyl Glycoside: A Potential Inhibitor of Trypanosomal PFK from <i>Euphorbia abyssinica</i> J.F. Gmel

Human African trypanosomiasis is an endemic infectious disease caused by Trypanosoma brucei via the bite of tsetse-fly. Most of the drugs used for the treatment, e.g., Suramin, have shown several problems, including the high level of toxicity. Accordingly, the discovery of anti-trypanosomal drugs from natural sources has become an urgent requirement. In our previous study on the anti-trypanosomal potential of Euphorbia species, Euphorbia abyssinica displayed significant anti-trypanosomal activity. Therefore, a phytochemical investigation of the methanolic extract of E. abyssinica was carried out. Twelve compounds, including two triterpenes (1, 2); one sterol-glucoside (4); three ellagic acid derivatives (3, 9, 11); three gallic acid derivatives (5, 6, 10); and three flavonoids (7, 8, 12), were isolated. The structures of isolated compounds were determined through different spectroscopic techniques. Compound (10) was obtained for the first time from genus Euphorbia while all other compounds except compound (4), were firstly reported in E. abyssinica. Consequently, an in silico study was used to estimate the anti-trypanosomal activity of the isolated compounds. Several compounds displayed interesting activity where 1,6-di-O-galloyl-d-glucose (10) appeared as the most potent inhibitor of trypanosomal phosphofructokinase (PFK). Moreover, molecular dynamics (MD) simulations and ADMET calculations were performed for 1,6-di-O-galloyl-d-glucose. In conclusion, 1,6-di-O-galloyl-d-glucose revealed high binding free energy as well as desirable molecular dynamics and pharmacokinetic properties; therefore, it could be suggested for further in vitro and in vivo studies for trypanosomiasis