Current drug discovery technologies最新文献

Background: Alzheimer's Disease (AD) is related to the total loss of presynaptic neurotransmitters of the cholinergic system in regions of the brain related to memory. Approximately 15% of the population beyond the age of 65 years are suffering from dementia due to AD and the rate is rising exponentially with age.

Objective: The objective of this research was the synthesis of a series of 1-(4-substituted-2- thioxoquinolin-1(2H)-yl)-2-substituted ethanoneV (a-c(1-4)) by undergoing acetylation at the nitrogen of 4-hydroxyquinolin-2-(1H)-one and replacing its oxygen atom with sulphur moiety via the process of thionation. To carry out-docking studies of the title compounds were carried out using Molegro Virtual Docker (MVD-2013, 6.0) software and in-vitro screening of anti-alzheimer's activity by Ellman assay method.

Methods: The synthesis of the title compounds was carried out via the sequential reaction from the initial dianilide to ring closure to the substituted quinoline-2-ones using polyphosphoric acid as a cyclising agent. These substituted quinoline-2-ones on thionation by phosphorous pentasulphide in aluminium trioxide gave quinoline-2-thiones and on further condensation with chloroacetyl chloride, they resulted in compounds with a leaving group. Nucleophilic substitution reaction of chloroacetylquinoline- 2-thiones with secondary amines resulted in the title compounds 1-(4-substituted-2- thioxoquinolin-1(2H)-yl)-2-substituted ethanone V(a-c(1-4)). The pharmacophore mapping of synthesized compounds was performed by using Molegro Virtual Docker (MVD-2013,6.0). The title compounds were tested for their in vitro anti-Alzheimer's activity using the Ellman assay method.

Results: All the synthesized compounds were characterized by IR, ¹H NMR, ¹³C NMR, and Mass spectral data. Docking studies of all the synthesized compounds were carried out using a structural mechanism for the inhibition of CDK5-p25 by roscovitine, aloisine, and indirubin (PDB ID: 1UNG), showed favourable results, with compound (Vb3) showing a MolDock score of -85.9788 that was comparable to that of the active ligand (ALH_1288 [B]) with MolDock score of - 87.7609.

Conclusion: The synthesized derivatives possessed the potential to bind with some of the amino acid residues of the active site. Compound 2-(6-chloro-4-hydroxy-2-thioxoquinolin-1(2H)-yl-1-piperazin- 1-ethanone (Vb3) was found to be the most active among the synthesized derivatives, with IC₅₀ values of 32 ± 0.1681. All the synthesized compounds showed potent to moderate activity in comparison to the reference standard donepezil.

Background: Lung cancer is the leading cause of mortality in India. Adenosine Receptor (AR) has emerged as a novel cancer-specific target. A3AR levels are upregulated in various tumor cells, which may mean that the specific AR may act as a biological marker and target specific ligands leading to cell growth inhibition.

Aim: Our aim was to study the efficacy of the adenosine receptor agonist, AB MECA, by in silico (molecular docking) and in vitro (human cancer cells in xenografted mice) studies.

Methods: Molecular docking on the AB-meca and TNF-α was performed using AutoDock. A549 Human lung cancer 2 ×10⁶ cells per microliter per mouse injected via intrabronchial route. Rat TNF-α level was assessed by ELISA method.

Results: AB Meca's predicted binding energy (beng) with TNF-α was 97.13 kcal/mol, and the compatible docking result of a small molecular inhibitor with TNF-α native ligand beng was 85.76 kcal/mol. In vivo, a single dose of lung cancer cell A549 is being researched to potentiate tumor development. Doxorubicin and A3AR agonist therapies have lowered TNF-alpha levels that were associated with in silico function. The A3AR Agonist showed myeloprotective effects in the groups treated along with doxorubicin.

Conclusion: AB MECA's higher binding energy (beng) with TNF-α mediated reduction of tumor growth in our lung cancer in vivo model suggested that it may be an effective therapy for lung cancer.

Background: Garcinia mangostana, commonly also called mangosteen, is an evergreen tropical tree, and its pericarps have been used in traditional herbal medicine for different diseases. The anticancer efficacy of the ethanolic extract from the pericarps of Garcinia mangostana was investigated in human prostate cancer cells (PC3), melanoma cells (B16F10), breast cancer cells (MCF7), and glioblastoma (U87) cell lines.

Methods: 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assay was used to measure cell viability. Propidium iodide (PI) staining and analysis on a flow cytometer were used to identify apoptosis. Action on cell migration was evaluated by scratch assay and gelatin zymography. Furthermore, the level of intracellular reactive oxygen species (ROS), malondialdehyde (MDA), glutathione (GSH), and superoxide dismutase (SOD) activity was measured. Moreover, we investigated the synergistic efficacy with several combinations of Garcinia mangostana extract (GME) with doxorubicin.

Results: GME reduced cell viability in malignant cell dose time-dependently. GME-induced sub- G1 peak in flow cytometry histogram of treated cells control representing apoptotic cell death is involved in GME toxicity. Furthermore, GME exhibited inhibitory effects on the migration ability of U87 cells, which was accompanied by inhibition in the activity and expression of MMP2 (matrix metalloproteinase-2). Besides, GSH level and SOD activity were significantly reduced while there was an increase in ROS and MDA concentration following 24 hr of GME treatment. Moreover, a combination of GME (1.5-25 μg/mL) with Dox (6 μg/mL) displayed synergistic efficacy and cell growth inhibition.

Conclusion: In conclusion, GME could cause cell death in PC3, MCF7, U87, and B16F10 cell lines, in which apoptosis plays an imperative role. Plant extract decreased the migration ability of the cells by inhibiting the activity and expression of Matrix metalloproteinases (MMPs). G. mangostana could be a promising therapeutic strategy to treat cancer in the future.

Background: The process of drug discovery and development is expensive, complex, timeconsuming, and risky. There are different techniques involved in the process of drug development, including random screening, computational approaches, molecular manipulation, and serendipitous research. Among these methods, the computational approach is considered an efficient strategy to accelerate and economize the drug discovery process.

Objective: This approach is mainly applied in various phases of the drug discovery process, including target identification, target validation, lead identification, and lead optimization. Due to the increase in the availability of information regarding various biological targets of different disease states, computational approaches such as molecular docking, de novo design, molecular similarity calculation, virtual screening, pharmacophore-based modeling, and pharmacophore mapping have been applied extensively.

Methods: Various drug molecules can be designed by applying computational tools to explore the drug candidates for the treatment of Coronavirus infection. The World Health Organization announced the coronavirus disease as COVID-19 and declared it a global pandemic on 11 February 2020. Therefore, it is thought of interest to the scientific community to apply computational methods to design and optimize the pharmacological properties of various clinically available and FDA-approved drugs such as remdesivir, ribavirin, favipiravir, oseltamivir, ritonavir, arbidol, chloroquine, hydroxychloroquine, carfilzomib, baraticinib, prulifloxacin, etc., for effective treatment of COVID-19 infection.

Results: Further, various survey reports suggest that extensive studies are carried out by various research communities to find out the safety and efficacy profile of these drug candidates.

Conclusion: This review is focused on the study of various aspects of these drugs related to their target sites on the virus, binding interactions, physicochemical properties, etc.