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A series of 3-[2-chloroquinolin-3-yl)methylene]-5-aryl-furan-2(3H)-ones {3(a-p)} were synthesized. The required 3-(substitutedbenzoyl) propionic acids {2(a-d)} were prepared under Friedal Craft acylation reaction conditions. The substituted 2-chloroquinoline-3-carbaldehydes {1(a-d)} were synthesized by reaction of substitutedphenylethanone-oxime with phosphorus oxychloride in presence of dimethyl formamide using the Vilsmeir Haack reaction method. These compounds were screened for their anti-inflammatory and antibacterial activities along with their ulcerogenic and lipid peroxidation potentials. The compounds that showed significant anti-inflammatory activity were further screened for their analgesic activity. The compounds were less toxic in terms of ulcerogenicity as compared to a standard, which was also supported by lipid peroxidation studies. The antibacterial activities were performed against Staphylococcus aureus and Escherichia coli. Compounds 3f, 3n and 3o showed significant activity against both S. aureus and E. coli having an MIC value of 6.25μg mL-1.

Drug discovery is the process by which new drug candidates are discovered and drug development takes place. To enhance the efficiency, accuracy, and speed of the drug discovery process, machine learning (ML) could play a transformative role. For this research study, antidiabetic natural compounds from C. intybus, which is commonly known as chicory, were selected, as they have promising antidiabetic properties that can complement conventional diabetes treatments. A bioactive natural compound dataset was retrieved on the chicory plant using Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMPPAT) public source information. This collected dataset was analyzed for its absorption, distribution, metabolism, and excretion (ADME) properties using the SwissADME online tool. Principal component analysis (PCA) and correlation analysis were performed using trial-version XLSTAT software 2014.5.03 and Python. The obtained dataset from SwissADME was subjected to cleaning, after that, it was used to develop machine learning models, such as support vacuum (SVM) ML, random forest (RF), Naive Bayes (NB), and decision tree (DT). The Lipinski rule of violation was chosen as the target variable. To improve the vitality of the created ADME dataset, PCA, a biplot graph, and correlation analysis were carried out. A large dataset of naturally occurring antidiabetic compounds was used to predict the drug-likeness of ML models that were effectively deployed on heterogeneous ADME datasets. Among all these ML models, DT performed better than the rest of the models. [ABSTRACT FROM AUTHOR]

A series of N-substituted-3-(napthalen-2-yl)-5-substituted phenyl-4,5-dihydropyrazole-1-carbothioamide derivatives (4a-n) were synthesized with the view of structural requirements of pharmacophore for potential anticonvulsant agents. The synthesized compounds were assayed intraperitoneally (i.p.) and subcutaneously (s.c.) in mice against seizures induced by MES and scPTZ methods, respectively.Neurologic deficit was evaluated by rotarod method. Among the tested compounds, 4g, 4i, 4j and 4n emerged as the most active molecule in the MES model at a dose of 30 mg/kg at 0.5h comparable to standardscarbamazepine and phenytoin. In the scPTZ test,4e and 4l were found to be most active compounds at the lowest dose of 30 mg/kg at 0.5h, in the management of the convulsive disorder. Molecular docking studies of the titled compounds were also donewith 3D crystal structure of human cytosolic branched chain amino transferase (hBCATc) enzyme and compound 4e was found to have five hydrogen bond interactions with the most important active site residues.In neurotoxicity studies, except compounds 4b, 4c, 4h and 4k, rest of the compounds showed no sign of toxicity.

Despite the existence of modern antidiabetic medications, diabetes still affects millions of individuals worldwide, with a high death and disability rate. There has been a concerted search for alternative natural medicinal agents; luteolin (LUT), a polyphenolic molecule, might be a good choice, both because of its efficacy and because of it having fewer side effects, compared to conventional medicines. This study aims to explore the antidiabetic potential of LUT in diabetic rats, induced by streptozotocin (STZ; 50 mg/kg b.w.), intraperitoneally. The level of blood glucose, oral glucose tolerance test (OGTT), body weight, glycated hemoglobin A1c (HbA1c), lipidemic status, antioxidant enzymes, and cytokines were assessed. Also, its action mechanism was explored through molecular docking and molecular dynamics simulations. Oral supplementation of LUT for 21 days resulted in a significant decrease in the blood glucose, oxidative stress, and proinflammatory cytokine levels, and modulated the hyperlipidemia profile. LUT also ameliorated the tested biomarkers of liver and kidney function. In addition, LUT markedly reversed the damage to the pancreas, liver, and kidney cells. Moreover, molecular docking and molecular dynamics simulations revealed excellent antidiabetic behavior of LUT. In conclusion, the current investigation revealed that LUT possesses antidiabetic activity, through the reversing of hyperlipidemia, oxidative stress, and proinflammatory status in diabetic groups. Therefore, LUT might be a good remedy for the management or treatment of diabetes. [ABSTRACT FROM AUTHOR]

Neratinib, a tyrosine kinase inhibitor, was very recently approved by USFDA in 2017 as an anticancer drug to treat of HER2 positive breast cancers. The present work provides an account on the development of a validated bioanalytical UPLC–MS/MS method for quantification of neratinib and internal standard (imatinib) in rat plasma and tissue homogenates. A UPLC having a 100 mm C18 column (1.7 μm sized particles) was used with acetonitrile (0.1% formic acid): 2 mMol of ammonium acetate in water (pH 3.5) as the mobile phase. An efficient chromatographic separation was performed and detection was achieved by monitoring precursor-to-product ion transitions with m/z 557.29 → 112.06 for neratinib and m/z 494.43 → 294.17 for IS. The method demonstrated excellent linearity in the spiked plasma drug concentrating ranging between 1 and 800 ng.mL−1 (r2 = 0999), with lower limit of quantification (LLOQ) was observed at 1 ng.mL−1. Intra-assay and inter-assay precision relative standard deviations were found to be within 6.58. Mean extraction recovery for neratinib and IS were 99.44 and 99.33%, while matrix effect for neratinib and IS was ranging between −4.35 and − 3.66%, respectively. Overall, the method showed successful applicability in pharmacokinetic analysis of pure various formulations in Wistar rat plasma. [ABSTRACT FROM AUTHOR]