Gene set enrichment analysis of α-amylase and α-glucosidase inhibitors of Cassia glauca.
Ontology highlight
ABSTRACT: Background
The present study aimed to evaluate in vitro α-amylase and α-glucosidase inhibitory activity of various extracts of Cassia glauca, predict the binding affinity of multiple phytoconstituents with both enzymes via in silico molecular docking and identify the probably modulated pathways by the lead hit.Methods
Different extracts of Cassia glauca i.e. acetone, ethanol, and aqueous extracts were evaluated for α-amylase and α-glucosidase inhibitory activity using in vitro method in which starch and 4-Nitrophenyl β-D-glucopyranoside were used as substrate respectively. Similarly, the docking study was performed using autodock4 to predict the binding affinity of phytoconstituents with α-amylase and α-glucosidase. After docking, ten different poses were obtained for the ligand molecule. Among them, the pose of ligand molecule with the lowest binding energy was visualized in Discovery Studio 2019.Results and conclusion
Among the multiple extracts, the aqueous extract showed the highest α-amylase (IC50:652.10 ± 20.09) and α-glucosidase (IC50:482.46 ± 8.70) inhibitory activity. Similarly, cassiaoccidentalin B was predicted to have the highest binding affinity with both enzymes. The potency of aqueous extract to inhibit α-amylase and α-glucosidase could be due to multiple water-soluble compounds like saponins, flavonoids, and glycosides.
SUBMITTER: Ternikar SG
PROVIDER: S-EPMC7843725 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Diabetes is a metabolic disorder affecting about 220 million people worldwide. One of the most critical complications of diabetes is post-prandial hyper-glycemia (PPHG). Glucosidase inhibitor and ?-amylase inhibitors are class of compounds that help in managing PPHG. Low-cost herbal treatment is recommended due to their lesser side effect for treatment of diabetes. Two plants with significant traditional therapeutic potential, namely, Gnidia glauca and Dioscorea bulbifera, were tested for their efficiency to inhibit ?-amylase and ?-glucosidase. Stem, leaf, and flower of G. glauca and bulb of D. bulbifera were sequentially extracted with petroleum ether, ethyl acetate, and methanol as well as separately with 70% ethanol. Petroleum ether extract of flower of G. glauca was found to inhibit ?-amylase significantly (78.56%). Extracts were further tested against crude murine pancreatic, small intestinal, and liver glucosidase enzyme which revealed excellent inhibitory properties. ?-glucosidase inhibition provided a strong in vitro evidence for confirmation of both G. glauca and D. bulbifera as excellent antidiabetic remedy. This is the first report of its kind that provides a strong biochemical basis for management of type II diabetes using G. glauca and D. bulbifera. These results provide intense rationale for further in vivo and clinical study.
| S-EPMC3140190 | biostudies-literature
Project description:BackgroundPPAR-γ has an integrative role in the management of insulin resistance; ligands of this receptor have emerged as potent insulin sensitizers and may modulate proteins involved in the pathogenesis of diabetes mellitus. Hence the present study is aimed to identify PPAR-γ modulators from the plant Cassia glauca and predict the ontology enrichment analysis utilizing various in-silico tools.MethodsChEBI database was used to mine the phytoconstituents present in the plant C. glauca, SwissTargetPrediction database was used to identify the targets, and scrutinizing of phytoconstituents modulating PPAR-γ was performed. Autodock4.0 was used to dock phytoconstituent ligands with the target PPAR-γ. Multiple open-source databases and in-silico tools were utilized to predict the drug-likeness characters and predict side effects of the phytoconstituents modulating PPAR-γ and STRING database was used to construct a network between the modulated genes.ResultsTwenty-four phytoconstituents were identified from the plant Cassia glauca from which four were found to modulate PPAR-γ, sennoside was predicted to have the greatest drug-likeness score and a significantly less side effect whereas diphenyl sulfone was predicted to show hepatotoxicity with the greatest pharmacological activity of 0.815. [epicatechin-(4beta- > 8)]5-epicatechin showed the lowest binding affinity with target PPAR-γ i.e. -8.6 kcal/mol and possessing a positive drug-likeness score with no side effect data.ConclusionBioctives were found free from probable side effects leaving out diphenyl sulfone having a prediction of hepatotoxicity, the anti-diabetic property of the plant may be due to the presence of [epicatechin-(4beta- > 8)]5-epicatechin which needs further validation by in-vitro and in-vivo protocols.
| S-EPMC8630302 | biostudies-literature
Project description:BackgroundAlthough α-amylase is the choice of target to manage postprandial hyperglycemia, inhibitors of this enzyme may get absorbed into the systemic circulation and modulate proteins involved in the pathogenesis of diabetes mellitus. Hence, the present study aimed to identify α-amylase inhibitors from Duranta repens via in silico and in vitro and predict their role in the modulation of multiple pathways involved in diabetes mellitus.Methodsα-amylase inhibitory activity of hydroalcoholic extract/fractions (s) and pure compounds from D. repens was performed using in vitro enzyme inhibitory assay. Multiple open-source databases and published literature were used to retrieve reported phytoconstituents present in D. repens and their targets. The network was constructed between α-amylase inhibitors, modulated proteins, and expressed pathways. Further, hit molecules were also confirmed for their potency to inhibit α-amylase using in silico molecular docking and in vitro enzyme inhibitory assay. The glucose uptake assay was performed to assess the effect of hydrolcoholic extract/fraction(s) using rat hemidiaphragm.ResultsFraction rich in flavonoids showed the highest α-amylase inhibitory activity with a IC50 of 644.29 ± 4.36 µg/ml compared to other fractions. PI3K-Akt signaling pathway and p53 signaling pathway were predicted to be primarily modulated in the compound-protein-pathway network. Similarly, scutellarein was predicted as lead hit based on α-amylase inhibitory action, binding affinity, and regulated pathways. Further, α-amylase inhibitors were also predicted to modulate the pathways involved in diabetes complications like AGE-RAGE and FoxO signaling pathway. Fraction rich in flavonoids showed the highest glucose uptake in rat hemidiaphragm with an effective concentration of 534.73 ± 0.79 µg/ml.ConclusionsThe α-amylase inhibitors from D. repens may not be limited within the gastrointestinal tract to inhibit α-amylase but may get absorbed into the systemic circulation and modulate multiple pathways involved in the pathogenesis of diabetes mellitus to produce synergistic/additive effect.
| S-EPMC7843765 | biostudies-literature
Project description:Type-II diabetes mellitus (T2DM) results from a combination of genetic and lifestyle factors, and the prevalence of T2DM is increasing worldwide. Clinically, both α-glucosidase and α-amylase enzymes inhibitors can suppress peaks of postprandial glucose with surplus adverse effects, leading to efforts devoted to urgently seeking new anti-diabetes drugs from natural sources for delayed starch digestion. This review attempts to explore 10 families e.g., Bignoniaceae, Ericaceae, Dryopteridaceae, Campanulaceae, Geraniaceae, Euphorbiaceae, Rubiaceae, Acanthaceae, Rutaceae, and Moraceae as medicinal plants, and folk and herb medicines for lowering blood glucose level, or alternative anti-diabetic natural products. Many natural products have been studied in silico, in vitro, and in vivo assays to restrain hyperglycemia. In addition, natural products, and particularly polyphenols, possess diverse structures for exploring them as inhibitors of α-glucosidase and α-amylase. Interestingly, an in silico discovery approach using natural compounds via virtual screening could directly target α-glucosidase and α-amylase enzymes through Monte Carto molecular modeling. Autodock, MOE-Dock, Biovia Discovery Studio, PyMOL, and Accelrys have been used to discover new candidates as inhibitors or activators. While docking score, binding energy (Kcal/mol), the number of hydrogen bonds, or interactions with critical amino acid residues have been taken into concerning the reliability of software for validation of enzymatic analysis, in vitro cell assay and in vivo animal tests are required to obtain leads, hits, and candidates in drug discovery and development.
| S-EPMC8699780 | biostudies-literature
Project description:Diabetes mellitus remains a major global health issue, and great attention is directed at natural therapeutics. This systematic review aimed to assess the potential of flavonoids as antidiabetic agents by investigating their inhibitory effects on α-glucosidase and α-amylase, two key enzymes involved in starch digestion. Six scientific databases (PubMed, Virtual Health Library, EMBASE, SCOPUS, Web of Science, and WHO Global Index Medicus) were searched until August 21, 2022, for in vitro studies reporting IC50 values of purified flavonoids on α-amylase and α-glucosidase, along with corresponding data for acarbose as a positive control. A total of 339 eligible articles were analyzed, resulting in the retrieval of 1643 flavonoid structures. These structures were rigorously standardized and curated, yielding 974 unique compounds, among which 177 flavonoids exhibited inhibition of both α-glucosidase and α-amylase are presented. Quality assessment utilizing a modified CONSORT checklist and structure-activity relationship (SAR) analysis were performed, revealing crucial features for the simultaneous inhibition of flavonoids against both enzymes. Moreover, the review also addressed several limitations in the current research landscape and proposed potential solutions. The curated datasets are available online at https://github.com/MedChemUMP/FDIGA .
| S-EPMC10772047 | biostudies-literature
Project description:Diabetes mellitus is a major predisposing factor for cardiovascular disease and mortality. α-Amylase and α-glucosidase enzymes are the rate-limiting steps for carbohydrate digestion. The inhibition of these two enzymes is clinically used for the treatment of diabetes mellitus. Here, in vitro study and machine learning models were employed for the chemical screening of inhibiting the activity of 31 plant samples on α-amylase and α-glucosidase enzymes. The results showed that the ethanolic twig extract of Pinus kesiya had the highest inhibitory activity against the α-amylase enzyme. The respective ethanolic extract of Croton oblongifolius stem, Parinari anamense twig, and Polyalthia evecta leaf showed high inhibitory activity against the α-glucosidase enzyme. The classification analysis revealed that the α-glucosidase inhibitory activity of Thai indigenous plants was more predictive based on phytochemical constituents, compared with the α-amylase inhibitory activity (1.00 versus 0.97 accuracy score). The correlation loading plot revealed that flavonoids and alkaloids contributed to the α-amylase inhibitory activity, while flavonoids, tannins, and reducing sugars contributed to the α-glucosidase inhibitory activity. In conclusion, the ethanolic extracts of P. kesiya, C. oblongifolius, P. anamense, and P. evecta have the potential for further chemical characterization and the development of anti-diabetic recipes.
| S-EPMC8781461 | biostudies-literature
Project description:A series of benzylidene analogs of oleanolic acid 4a∼4s were synthesized and assessed for their α-glucosidase and α-amylase inhibitory activities. The results presented that all synthesized analogs exhibited excellent-to-moderate inhibitory effects on α-glucosidase and α-amylase. Analog 4i showed the highest α-glucosidase inhibition (IC50: 0.40 μM), and analog 4o presented the strongest α-amylase inhibition (IC50: 9.59 μM). Inhibition kinetics results showed that analogs 4i and 4o were reversible and mixed-type inhibitors against α-glucosidase and α-amylase, respectively. Simulation docking results demonstrated the interaction between analogs and two enzymes. Moreover, analogs 4i and 4o showed a high level of safety against 3T3-L1 and HepG2 cells.
| S-EPMC9213889 | biostudies-literature
Project description:Compounds from Zanthoxylum chalybeum Engl. were previously reported for inhibitory activities of amylase and glucosidase enzymatic action on starch as a preliminary study toward the establishment of a management strategy against postprandial hyperglycemia, however, the inhibitory kinetics and molecular interaction of these compounds were never established. A study was thus designed to establish the inhibitory kinetics and in silico molecular interaction of α-glucosidase and α-amylase with Z. chalybeum metabolites based on Lineweaver-Burk/Dixon plot analyses and using Molecular Operating Environment (MOE) software, respectively. Skimmianine (5), Norchelerythrine (6), 6-Acetonyldihydrochelerythrine (7), and 6-Hydroxy-N-methyldecarine (8) alkaloids showed mixed inhibition against both α-glucosidase and α-amylase with comparable Ki to the reference acarbose (p > 0.05) on amylase but significantly higher activity than acarbose on α-glucosidase. One phenolic 2,3-Epoxy-6,7-methylenedioxyconiferol (10) showed a competitive mode of inhibition both on amylase and glucosidase which were comparable (p > 0.05) to the activity of acarbose. The other compounds analyzed and displayed varied modes of inhibition between noncompetitive and uncompetitive with moderate inhibition constants included chaylbemide A (1), chalybeate B (2) and chalybemide C (3), fagaramide (4), ailanthoidol (9), and sesame (11). The important residues of the proteins α-glucosidase and α-amylase were found to have exceptional binding affinities and significant interactions through molecular docking studies. The binding affinities were observed in the range of -9.4 to -13.8 and -8.0 to -12.6 relative to the acarbose affinities at -17.6 and -20.5 kcal/mol on α-amylase and α-glucosidase residue, respectively. H-bonding, π-H, and ionic interactions were noted on variable amino acid residues on both enzymes. The study thus provides the basic information validating the application of extracts of Z. chalybeum in the management of postprandial hyperglycemia. Additionally, the molecular binding mechanism discovered in this study could be useful for optimizing and designing new molecular analogs as pharmacological agents against diabetes.
| S-EPMC10059848 | biostudies-literature
Project description:BackgroundGene-set enrichment analyses (GEA or GSEA) are commonly used for biological characterization of an experimental gene-set. This is done by finding known functional categories, such as pathways or Gene Ontology terms, that are over-represented in the experimental set; the assessment is based on an overlap statistic. Rich biological information in terms of gene interaction network is now widely available, but this topological information is not used by GEA, so there is a need for methods that exploit this type of information in high-throughput data analysis.ResultsWe developed a method of network enrichment analysis (NEA) that extends the overlap statistic in GEA to network links between genes in the experimental set and those in the functional categories. For the crucial step in statistical inference, we developed a fast network randomization algorithm in order to obtain the distribution of any network statistic under the null hypothesis of no association between an experimental gene-set and a functional category. We illustrate the NEA method using gene and protein expression data from a lung cancer study.ConclusionsThe results indicate that the NEA method is more powerful than the traditional GEA, primarily because the relationships between gene sets were more strongly captured by network connectivity rather than by simple overlaps.
| S-EPMC3505158 | biostudies-literature
Project description:Assessing functional associations between an experimentally derived gene or protein set of interest and a database of known gene/protein sets is a common task in the analysis of large-scale functional genomics data. For this purpose, a frequently used approach is to apply an over-representation-based enrichment analysis. However, this approach has four drawbacks: (i) it can only score functional associations of overlapping gene/proteins sets; (ii) it disregards genes with missing annotations; (iii) it does not take into account the network structure of physical interactions between the gene/protein sets of interest and (iv) tissue-specific gene/protein set associations cannot be recognized.To address these limitations, we introduce an integrative analysis approach and web-application called EnrichNet. It combines a novel graph-based statistic with an interactive sub-network visualization to accomplish two complementary goals: improving the prioritization of putative functional gene/protein set associations by exploiting information from molecular interaction networks and tissue-specific gene expression data and enabling a direct biological interpretation of the results. By using the approach to analyse sets of genes with known involvement in human diseases, new pathway associations are identified, reflecting a dense sub-network of interactions between their corresponding proteins.EnrichNet is freely available at http://www.enrichnet.org.Natalio.Krasnogor@nottingham.ac.uk, reinhard.schneider@uni.lu or avalencia@cnio.esSupplementary data are available at Bioinformatics Online.
| S-EPMC3436816 | biostudies-other