Natural compounds for oxidative stress and neuroprotection in schizophrenia: composition, mechanisms, and therapeutic potential.

OBJECTIVE: An imbalance between the generation of reactive oxygen species (ROS) and the body's antioxidant defense mechanisms is believed to be a critical factor in the development of schizophrenia (SCZ) like neurological illnesses. Understanding the roles of ROS in the development of SCZ and the potential activity of natural antioxidants against SCZ could lead to more effective therapeutic options for the prevention and treatment of the illness. METHODS: SCZ is a mental disorder characterised by progressive impairments in working memory, attention, and executive functioning. In present investigation, we summarized the experimental findings for understanding the role of oxidative stress (OS) in the development of SCZ and the potential neuroprotective effects of natural antioxidants in the treatment of SCZ. RESULTS: Current study supports the use of the mentioned antioxidant natural compounds as a potential therapeutic candidates for the treatment of OS mediated neurodegeneration in SCZ. DISCUSSION: Elevated levels of harmful ROS and reduced antioxidant defense mechanisms are indicative of increased oxidative stress (OS), which is associated with SCZ. Previous research has shown that individuals with SCZ, including non-medicated, medicated, first-episode, and chronic patients, exhibit decreased levels of total antioxidants and GSH. Additionally, they have reduced antioxidant enzyme levels such as catalase (CAT), glutathione (GPx), and, superoxide dismutase (SOD) and lower serum levels of brain-derived neurotrophic factor (BDNF) in their brain tissue. The mentioned natural antioxidants may assist in reducing oxidative damage in individuals with SCZ and increasing BDNF expression in the brain, potentially improving cognitive function and learning ability.

Mechanistic QSAR modeling derived virtual screening, drug repurposing, ADMET and in-vitro evaluation to identify anticancer lead as lysine-specific demethylase 5a inhibitor.

A lysine-specific demethylase is an enzyme that selectively eliminates methyl groups from lysine residues. KDM5A, also known as JARID1A or RBP2, belongs to the KDM5 Jumonji histone demethylase subfamily. To identify novel molecules that interact with the LSD5A receptor, we created a quantitative structure-activity relationship (QSAR) model. A group of 435 compounds was used in a study of the quantitative relationship between structure and activity to guess the IC50 values for blocking LASD5A. We used a genetic algorithm-multilinear regression-based quantitative structure-activity connection model to forecast the bioactivity (PIC50) of 1615 food and drug administration pharmaceuticals from the zinc database with the goal of repurposing clinically used medications. We used molecular docking, molecular dynamic simulation modelling, and molecular mechanics generalised surface area analysis to investigate the molecule's binding mechanism. A genetic algorithm and multi-linear regression method were used to make six variable-based quantitative structure-activity relationship models that worked well (R2 = 0.8521, Q2LOO = 0.8438, and Q2LMO = 0.8414). ZINC000000538621 was found to be a new hit against LSD5A after a quantitative structure-activity relationship-based virtual screening of 1615 zinc food and drug administration compounds. The docking analysis revealed that the hit molecule 11 in the KDM5A binding pocket adopted a conformation similar to the pdb-6bh1 ligand (docking score: -8.61 kcal/mol). The results from molecular docking and the quantitative structure-activity relationship were complementary and consistent. The most active lead molecule 11, which has shown encouraging results, has good absorption, distribution, metabolism, and excretion (ADME) properties, and its toxicity has been shown to be minimal. In addition, the MTT assay of ZINC000000538621 with MCF-7 cell lines backs up the in silico studies. We used molecular mechanics generalise borne surface area analysis and a 200-ns molecular dynamics simulation to find structural motifs for KDM5A enzyme interactions. Thus, our strategy will likely expand food and drug administration molecule repurposing research to find better anticancer drugs and therapies.Communicated by Ramaswamy H. Sarma.

Maximizing the extraction yield of plant gum exudate using response surface methodology and artificial neural networking and pharmacological characterization.

Prunus armeniaca gum is used as food additive and ethno medicinal purpose. Two empirical models response surface methodology and artificial neural network were used to search for optimized extraction parameters for gum extraction. A four-factor design was implemented for optimization of extraction process for maximum yield which was obtained under the optimized extraction parameter (temperature, pH, extraction time, and gum/water ratio). Micro and macro-elemental composition of gum was determined by using laser induced breakdown spectroscopy. Gum was evaluated for toxicological effect and pharmacological properties. The maximum predicted yield obtained by response surface methodology and artificial neural network was 30.44 and 30.70% which was very close to maximum experimental yield 30.23%. Laser induced breakdown spectroscopic spectra confirmed the presence Calcium, Potassium, Magnesium, Sodium, Lithium, Carbon, Hydrogen, Nitrogen and Oxygen. Acute oral toxicity study showed that gum is non-toxic up to 2000 mg/Kg body weight in rabbits, accompanied by high cytotoxic effects of gum against HepG2 and MCF-7cells by MTT assay. Overall, Aqueous solution of gum showed various pharmacological activities with significant value of antioxidant, antibacterial, anti-nociceptive, anti-cancer, anti-inflammatory and thrombolytic activities. Thus, optimization of parameters using mathematical models cans offer better prediction and estimations with enhanced pharmacological properties of extracted components.

Green Synthesis: The Antibacterial and Photocatalytic Potential of Silver Nanoparticles Using Extract of Teucrium stocksianum.

Green synthesis is one of the promising pathways for biologically active nanoscale materials. Herein, an eco-friendly synthesis of silver nanoparticles (SNPs) was carried out using an extract of Teucrium stocksianum. The biological reduction and size of NPS were optimized by controlling the physicochemical parameters such as concentration, temperature, and pH. A comparison of fresh and air-dried plant extracts was also undertaken to establish a reproducible methodology. The biosynthesized SNPs were characterized by UV-Vis spectroscopy, FT-IR, SEM, DLS, and XRD analyses. The prepared SNPs exhibited significant biological potential against multi-drug-resistant pathogenic strains. The results revealed that the biosynthesized SNPs exhibit high antimicrobial activity at low concentrations compared to the parent plant extract. Minimum inhibition concentration (MIC) values were found between 5.3 µg/mL to 9.7 µg/mL for the biosynthesized SNPs, whereas the aqueous extract of the plant showed many high values of MIC, i.e., between 69 and 98 µg/ML. Furthermore, the synthesized SNPs were found efficient in the photolytic degradation of methylene blue under sunlight.

QSAR, Molecular Docking, MD Simulation and MMGBSA Calculations Approaches to Recognize Concealed Pharmacophoric Features Requisite for the Optimization of ALK Tyrosine Kinase Inhibitors as Anticancer Leads.

ALK tyrosine kinase ALK TK is an important target in the development of anticancer drugs. In the present work, we have performed a QSAR analysis on a dataset of 224 molecules in order to quickly predict anticancer activity on query compounds. Double cross validation assigns an upward plunge to the genetic algorithm−multi linear regression (GA-MLR) based on robust univariate and multivariate QSAR models with high statistical performance reflected in various parameters like, fitting parameters; R2 = 0.69−0.87, F = 403.46−292.11, etc., internal validation parameters; Q2LOO = 0.69−0.86, Q2LMO = 0.69−0.86, CCCcv = 0.82−0.93, etc., or external validation parameters Q2F1 = 0.64−0.82, Q2F2 = 0.63−0.82, Q2F3 = 0.65−0.81, R2ext = 0.65−0.83 including RMSEtr < RMSEcv. The present QSAR evaluation successfully identified certain distinct structural features responsible for ALK TK inhibitory potency, such as planar Nitrogen within four bonds from the Nitrogen atom, Fluorine atom within five bonds beside the non-ring Oxygen atom, lipophilic atoms within two bonds from the ring Carbon atoms. Molecular docking, MD simulation, and MMGBSA computation results are in consensus with and complementary to the QSAR evaluations. As a result, the current study assists medicinal chemists in prioritizing compounds for experimental detection of anticancer activity, as well as their optimization towards more potent ALK tyrosine kinase inhibitor.

Synthesis and α-Glucosidase Inhibition Activity of 2-[3-(Benzoyl/4-bromobenzoyl)-4-hydroxy-1,1-dioxido-2H-benzo[e][1,2]thiazin-2-yl]-N-arylacetamides: An In Silico and Biochemical Approach.

Diabetes mellitus (DM) is a chronic disorder and has affected a large number of people worldwide. Insufficient insulin production causes an increase in blood glucose level that results in DM. To lower the blood glucose level, various drugs are employed that block the activity of the α-glucosidase enzyme, which is considered responsible for the breakdown of polysaccharides into monosaccharides leading to an increase in the intestinal blood glucose level. We have synthesized novel 2-(3-(benzoyl/4-bromobenzoyl)-4-hydroxy-1,1-dioxido-2H-benzo[e][1,2]thiazin-2-yl)-N-arylacetamides and have screened them for their in silico and in vitro α-glucosidase inhibition activity. The derivatives 11c, 12a, 12d, 12e, and 12g emerged as potent inhibitors of the α-glucosidase enzyme. These compounds exhibited good docking scores and excellent binding interactions with the selected residues (Asp203, Asp542, Asp327, His600, Arg526) during in silico screening. Similarly, these compounds also showed good in vitro α-glucosidase inhibitions with IC50 values of 30.65, 18.25, 20.76, 35.14, and 24.24 µM, respectively, which were better than the standard drug, acarbose (IC50 = 58.8 µM). Furthermore, a good agreement was observed between in silico and in vitro modes of study.

Design, Synthesis and Anticancer Activity of New Polycyclic: Imidazole, Thiazine, Oxathiine, Pyrrolo-Quinoxaline and Thienotriazolopyrimidine Derivatives.

In this article, we showed the synthesis of new polycyclic aromatic compounds, such as thienotriazolopyrimidinones, N-(thienotriazolopyrimidine) acetamide, 2-mercapto-thienotriazolo-pyrimidinones, 2-(((thieno-triazolopyrimidine) methyl) thio) thieno-triazolopyrimidines, thieno-pyrimidotriazolo-thiazines, pyrrolo-triazolo-thienopyrimidines, thienopyrimido-triazolopyrrolo-quinoxalines, thienopyrimido-triazolo-pyrrolo-oxathiino-quinoxalinones, 1,4-oxathiino-pyrrolo- triazolothienopyrimidinones, imidazopyrrolotriazolothienopyrimidines and 1,2,4-triazoloimidazo- pyrrolotriazolothienopyrimidindiones, based on the starting material 2,3-diamino-6-benzoyl-5- methylthieno[2,3-d]pyrimidin-4(3H)-one (3). The chemical structures were confirmed using many spectroscopic ways (IR, 1H, 13C, -NMR and MS) and elemental analyses. A series of thiazine, imidazole, pyrrole, thienotriazolopyrimidine derivatives were synthesized and evaluated for their antiproliferative activity against four human cancer cell lines, i.e., CNE2 (nasopharyngeal), KB (oral), MCF-7 (breast) and MGC-803 (gastric) carcinoma cells. The compounds 20, 19, 17, 16 and 11 showed significant cytotoxicity against types of human cancer cell lines.