Design, synthesis, in silico studies, and antidiabetic activity of several sulfanilamide incorporated 2,3-disubstitut-ed thiazolidin-4-ones

A panel of 2,3-disubstituted thiazolidin-4-ones 4a-n was synthesised from Schiff bases 3a-n derived from sulfanilamide, by reaction with thioglycolic acid. The compounds were characterised by means of IR, NMR, and Mass spectral data. Compounds 4a-n were screened for DPPH scavenging assay and compounds 4e, 4h, 4i, and 4n exhibited moderate activity. Compounds 4e, 4h, and 4i were tested at 200 mg/kg and 4e at 50 mg/kg b.w. orally for antidiabetic activity in fructose induced diabetic rats. They exhibited significant antidiabetic activity compared to the control group. Pioglitazone was used as a standard drug. The tested compounds exhibited better and ignificant serum cholesterol lowering activity when compared with the control and standard groups. They also reduced the triglyceride level after the 21st day; however, it was insignificant when compared to the control group. Compound 4n displayed the highest binding energy when docked with PPAR-γ followed by compounds 4e, 4h, and 4i when compared to pioglitazone. The physicochemical, drug likeness and ADME properties of the title compounds were found to be satisfactory.

Se sintetizó un panel de tiazolidinas-4-onas 2,3-disustituidas 4a-n a partir de las bases de Schiff 3a-n derivadas de la sulfanilamida por reacción con ácido tioglicólico. Los compuestos se caracterizaron por IR, RMN y datos espectrales de masa. Los compuestos 4a-n se analizaron para DPPH y los compuestos 4e, 4h, 4i y 4n mostraron una actividad moderada. Los compuestos 4e, 4h y 4i se probaron a 200 mg/kg y 4e a 50 mg/kg b.w. oralmente para la actividad antidiabética en ratas diabéticas, inducida por fructosa. Los compuestos mostraron una actividad antidiabética muy significativa en comparación con el grupo control. La pioglitazona se utilizó como fármaco estándar. Los compuestos ensayados mostraron una mejor y significativa actividad reductora del colesterol sérico en comparación con los grupos control y estándar. Estos compuestos también redujeron el nivel de triglicéridos después del 21° día, aunque fue insignificante en comparación con el grupo control. El compuesto 4n mostró la mayor afinidad de unión cuando se acopló a PPAR-γ, seguido de 4e, 4h y 4i en comparación con la pioglitazona. Las propiedades fisicoquímicas, la similitud con el fármaco y las propiedades ADME de los compuestos fueron satisfactorias, lo que los convierte en útiles agentes antidiabéticos.

Um painel de 2,3-disubstituído thiazolidina-4-ones 4a-n foram sintetizados a partir de bases Schiff 3a-n derivado da sulfanilamida por reacção com ácido tioglicólico. Os compostos eram caracterizado por IR, NMR e dados espectrais de massa. Os compostos 4a-n foram rastreados para O ensaio DPPH de limpeza radical e os compostos 4e, 4h, 4i e 4n exibiram actividade moderada. Os compostos 4e, 4h e 4i foram testados a 200 mg/kg e 4e a 50 mg/kg de peso corporal por via oral para antidiabéticos. actividade em ratos diabéticos induzidos por frutose. Exibiram uma actividade antidiabética altamente significativa actividade em comparação com o controlo. A pioglitazona foi utilizada como droga padrão. Os compostos testados exibiu uma melhor e significativa actividade de redução do colesterol sérico quando comparado comde triglicéridos após o 21° dia; no entanto, foi insignificante quando comparado com o controlo. O composto 4n mostrou a maior afinidade de ligação quando acoplado com PPAR-γ seguido de 4e, 4h, 4i quando comparado com pioglitazona. O propriedades físico-químicas, de semelhança com drogas e ADME dos compostos do título de propriedade também foram encontrados paraser satisfatórios, tornando-os agentes antidiabéticos úteis.

Computational studies on the structural variations of MAO-A and MAO-B inhibitors - An in silico docking approach-Supplementary data

The neurological disorder is a concerning problem in the present social scenario. The malfunction of the monoamine oxidase (MAO) enzyme is the responsible factor behind this disorder because this enzyme regulates the metabolism of monoamine neurotransmitters. This work aimed to design and propose the best MAO inhibitors through extensive computational analysis so that the favourable drug-like molecules could be identified for future synthesis. The drugs selected in this study were three MAO-A inhibitors namely Moclobemide, Tolxatone and Brofaromine and two MAO-B inhibitors namely Selegiline and Rasagiline. By substituting hydrophilic and hydrophobic groups at the specified positions, structural variations were designed for each drug. The designed variations and their parent drugs were optimized (basis set is B3LYP/6-311G(d, p)) and the optimized structures were docked to the target using PyRx software. The binding energy of each variation was compared to that of parent drug. The drug-likeness, physicochemical properties (solubility, polarity, flexibility, gastrointestinal absorption, saturation etc.) and toxicity of the lower binding energy variations were analysed using the swissADME, Osiris property explorer and ProTox-II servers. The interacting residues of the enzymes were obtained from the LigPlot+ program. The safe and low binding energy variations with favourable drug properties are suggested for further drug research

Computational studies on the structural variations of MAO-A and MAO-B inhibitors - An in silico docking approach-Supplementary data

The neurological disorder is a concerning problem in the present social scenario. The malfunction of the monoamine oxidase (MAO) enzyme is the responsible factor behind this disorder because this enzyme regulates the metabolism of monoamine neurotransmitters. This work aimed to design and propose the best MAO inhibitors through extensive computational analysis so that the favourable drug-like molecules could be identified for future synthesis. The drugs selected in this study were three MAO-A inhibitors namely Moclobemide, Tolxatone and Brofaromine and two MAO-B inhibitors namely Selegiline and Rasagiline. By substituting hydrophilic and hydrophobic groups at the specified positions, structural variations were designed for each drug. The designed variations and their parent drugs were optimized (basis set is B3LYP/6-311G(d, p)) and the optimized structures were docked to the target using PyRx software. The binding energy of each variation was compared to that of parent drug. The drug-likeness, physicochemical properties (solubility, polarity, flexibility, gastrointestinal absorption, saturation etc.) and toxicity of the lower binding energy variations were analysed using the swissADME, Osiris property explorer and ProTox-II servers. The interacting residues of the enzymes were obtained from the LigPlot+ program. The safe and low binding energy variations with favourable drug properties are suggested for further drug research

Computational studies on the structural variations of MAO-A and MAO-B inhibitors - An in silico docking approach

The neurological disorder is a concerning problem in the present social scenario. The malfunction of the monoamine oxidase (MAO) enzyme is the responsible factor behind this disorder because this enzyme regulates the metabolism of monoamine neurotransmitters. This work aimed to design and propose the best MAO inhibitors through extensive computational analysis so that the favourable drug-like molecules could be identified for future synthesis. The drugs selected in this study were three MAO-A inhibitors namely Moclobemide, Tolxatone and Brofaromine and two MAO-B inhibitors namely Selegiline and Rasagiline. By substituting hydrophilic and hydrophobic groups at the specified positions, structural variations were designed for each drug. The designed variations and their parent drugs were optimized (basis set is B3LYP/6-311G(d, p)) and the optimized structures were docked to the target using PyRx software. The binding energy of each variation was compared to that of parent drug. The drug-likeness, physicochemical properties (solubility, polarity, flexibility, gastrointestinal absorption, saturation etc.) and toxicity of the lower binding energy variations were analysed using the swissADME, Osiris property explorer and ProTox-II servers. The interacting residues of the enzymes were obtained from the LigPlot+ program. The safe and low binding energy variations with favourable drug properties are suggested for further drug research

Computational evaluation of 2-arylbenzofurans for their potential use against SARS-CoV-2: A DFT, molecular docking, molecular dynamics simulation study

Natural compounds obtained from various sources have been used in the treatment of many diseases for many years and are very important compounds for drug development studies. They can also be an option to treat COVID-19, which is affecting the whole world and not curable with medication, yet. In this study, two 2-arylbenzofuran derivatives from Sesbania cannabina which are newly entered the literature were investigated computationally with the assistance of computational techniques including DFT calculations, molecular docking calculation and molecular dynamics simulations. The study consists of four parts, in the first part of the study DFT calculations were performed on the 2-arylbenzofurans, and geometry optimizations, vibrational analyses, molecular electrostatic potential (MEP) map calculations, frontier molecular orbital (FMO) calculations and Mulliken charge analyses were carried out.In the second part, molecular docking calculations were performed to investigate the interactions between the molecules and two potential target, SARS-CoV-2 main protease (SARS-CoV-2 Mpro) and SARS-CoV-2 spike receptor binding domain – human angiotensin converting enzyme 2 complex (SARS-CoV-2 SRBD – hACE2). In the third part, MD simulations were performed on the top-scoring ligand – receptor complexes to investigate the stability of the complex and the interactions between ligands and receptors in more detail. Finally, drug-likeness analyses and ADME (adsorption, desorption, metabolism, excretion) predictions were performed on the investigated compounds. Results showed that investigated natural compounds effectively interacted with the target receptors and gave comparable results to the reference drug molecules.

Antimicrobial evaluation and molecular properties prediction of pyrazolines incorporating benzofuran and pyrazole moieties

A series of chalcones 3–5, 1H-pyrazolines 6–8, N-phenylpyrazolines 9–11, and N-acetylpyrazolines 12–14incorporating benzofuran and pyrazole moieties were synthesized and screened for their in vitro antimicrobial activityagainst some of pathogenic microorganisms. Among the screened compounds, 7 and 13 showed the most promisingantibacterial activity against Escherichia coli (G-). Compound 11 displayed broad spectrum antibacterial activityagainst Bacillus subtilis (G+). Moreover, compounds 10 and 4 were found to be the most potent antifungal agentagainst Candida albicans and Aspergillus niger, respectively. Also, the molecular properties prediction and druglikeness model score (DLS) of all the synthesized compounds were calculated by SwissADME and MolSoft websites,respectively. The two compounds 7 and 13 were found to be maximum DLS of 0.75 and 0.83, respectively.

Integrating drug-likeness and network target to analyze the potential molecular mechanism of Danggui Buxue Jiawei decoction in the prevention and treatment of diabetic retinopathy / 国际药学研究杂志

Objective: Integrating drug-likeness and network targets to preliminarily predict and explore the targets and pathways of Danggui Buxue Jiawei decoction(DBJD)in the prevention and treatment of diabetic retinopathy(DR). Methods: The chemical constituents of DBJD were identified by UPLC-Q-TOF/HRMS E analytical techniques. The related websites were used to esti mate the drug-likeness for all identified constituents. Then, for the selected drug-like constituents, targets-predicting was carried out on PharmMapper, and the targets for DR were searched by CTD, TTD and GeneCards. The component-target and disease-target net works were integrated to establish a large network, and core targets were searched on the basis of the DC, CC and BC values of the large network. Moreover, indirect targets were further searched on the basis of the core targets. Then, an all potential targets-related network was constructed and related key targets were searched by the constructed network. The key targets were verified by docking with the related components. Gene ontology(GO)biological analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis and Reactome pathway analysis were carried out on all potential targets. Eventually, a large Prescription-Medicinal material-Component-Direct target-Indirect target-Pathway integrated network was established for the DBJD studies. Results: A total of 55 chemical constituents were identified by UPLC-Q-TOF/HRMS E. Among them, 33 components were selected by the drug-likeness esti mation. The core targets consisted of 36 targets, and 20 indirect targets were obtained by relating with the core targets. By comparing de gree values, 6 key targets were established: AKT1, MAPK3, VEGFA, INS, MAPK1 and CASP3. In molecular docking tests, these key targets showed good binding activities with tanshinone, salvianolic acid B, ginsenoside Rg 1, notoginsenoside R 1, tanshinone Ⅱ A and other quality control components. Pathway analysis suggested that DBJD could likely interfere with the diabetic retinopathy by regulating oxidative stress, inflammatory factors and sugar metabolism. Conclusion: Accurate prediction of the action mechanism of complex Chinese medicinal ingredients based on the drug-likeness and network targets may be helpful to improve the blindness in relat ed research and accelerate the research process in modernization of traditional Chinese medicine. In this study, the molecular mecha nism of DBJD for the prevention and treatment of DR is preliminarily investigated and discussed, which could provide a valuable refer ence for future in-depth study.

Mechanism of Huangqi Jianzhong Decoction in treating chronic atrophic gastritis based on network pharmacology / 中草药

Objective: To predict the active ingredients and their potential targets of Huangqi Jianzhong Decoction (HQJZ) against chronic atrophic gastritis (CAG) based on the “single drug-active ingredient-action targets” network. Methods: Using pharmacokinetic parameters [oral bioavailability (OB) and drug likeness (DL)] of traditional Chinese medicine system pharmacology platform (TCMSP) to screen the active ingredient of HQJZ, and then integrating target prediction database (STPD), human gene database (Genecard), and Online Mendelian Inheritance in Man (OMIM) to predict and screen its target genes for the treatment of CAG, and using Cytoscape software to construct the network of “single drug-active ingredient-action targets”. The molecular docking of those main active ingredient and action targets were confirmed through Systems Dock Web Site. String database and Cytoscape software were used to draw the protein interaction network, and DisGeNET database was used to assign their target type. Finally the biological function and metabolic pathway of these targets were analyzed by DAVID database. Results: A total of 118 potential active ingredients were screened based on their OB and DL parameters, and 16 CAG-related genes were involved, 52 active ingredients were related to disease target, which mainly involved in the regulations of cancer pathway, focal adhesion, arginine and proline metabolism, vascular endothelial growth factor signal transduction and neurotrophic factor signaling pathway in the treatment of chronic atrophic gastritis. Conclusion: The therapeutic mechanism of HQJZ reflects the characteristics of multi-component, multi-target, and multi-pathway of traditional Chinese medicines, which provides a scientific basis for further explaining the action mechanism and the material basis of HQJZ against CAG.

Network pharmacology study of effective constituents of traditional Chinese medicine for Alzheimer's disease treatment / 药学学报

This study aims to investigate the network pharmacology of Chinese medicinal formulae for treatment of Alzheimer's disease. Machine learning algorithms were applied to construct classifiers in predicting the active molecules against 25 key targets toward Alzheimer's disease (AD). By extensive data profiling, we compiled 13 classical traditional Chinese medicine (TCM) formulas with clinical efficacy for AD. There were 7 Chinese herbs with a frequency of 5 or higher in our study. Based on the predicted results, we built constituent-target, and further construct target-target interaction network by STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) and target-disease network by DAVID (Database for Annotation, Visualization and Integrated Discovery) and gene disease database to study the synergistic mechanism of the herbal constituents in the Chinese traditional patent medicine. By prediction of blood-brain penetration and validation by TCMsp (traditional Chinese medicine systems pharmacology) and Drugbank, we found 7 typical multi-target constituents which have diverse structure. The mechanism uncovered by this study may offer a deep insight into the action mechanism of TCMs for AD. The predicted inhibitors for the AD-related targets may provide a good source of new lead constituents against AD.

Drug-like properties of potential anti-cancer compounds from Cameroonian flora: A virtual studies.

Assessment of the ‘drug-like’ using a set of calculated molecular descriptors, of a collection of 195compounds from plants in Cameroon exhibiting in vitro or/and in vivo activities against various cancer cell lines was made. Lipinski’s ‘Rule of Five’ (Ro5) was used to evaluate drug-likeness/oral availability of the compounds by making use of popular parameters like Molecular Weight (MW), predicted lipophilicity (log P), number of Hydrogen Bond Donors/Acceptors (HBD and HBA) and Number of Rotatable Bonds (NRB). The drug-like properties of the studied compounds were compared to that of the Dictionary of Natural Products (DNP). Our results revealed that79.50%, 43.60% and 12.30% of our dataset fall within the recommended range for ‘drug-like’, ‘lead-like’ and ‘fragment-like’ respectively with significant enhancement of some oral availability parameters over DNP and this paints the significant of our dataset in search for lead-like anti-cancer molecules with desirable ‘drug-like’ properties.