The relationship between hepatitis B virus (HBV) infection and C-reactive protein (CRP), which is an inflammatory biomarker, is limited in studies on the general population. Thus, this study aimed at determining the relationship between CRP levels and Hepatitis B surface antigen in patients with hepatitis B. A total of 70 samples were screened for the presence of hepatitis surface antigen by one step hepatitis B Surface antigen test strip (serum/plasma) package insert. The samples were further subjected to ELISA test and quantitative real time PCR to determine the viral load. The performance of the assay on the 70 samples showed 17 (24.29%) patients were positive and 53 (75.71%) patients were negative for serological test. Out of the 17 samples which were positive for HBV, CRP was positive in 5 patients while 12 patients were negative for CRP. While out of 53 patients who were negative for HBV, 9 were positive for CRP and 44 were negative for CRP. For the significance of viral load for clinical monitoring, three titer groups were presented. Among the 70 samples tested for viral load of HBV, 50% (35/70) of samples showed low titer by the Ct˂30, while only 15.71% (11/70) of samples were detected with high viral load by Ct˃30. Statistical analysis showed insignificant relationship between CRP and HBV. Positive predictive value of CRP was lower;it is revealed that the presence of HBV infection cannot be predicted on the basis of CRP analysis only. The reason behind lower CRP concentration in HBV positive cases remains unclear but there is a perception that high CRP levels in the blood can be a marker of inflammation.
Diabetes mellitus (DM) is a long term disorder of metabolism characterized by high level of blood sugar (hyperglycemia) due to insufficient secretion of insulin, insulin resistance, or both, as well as poor lipid, protein and carbohydrate metabolism. These complications occur as a result of derangement in glucose storage for the regulatory system and metabolic fuel mobilization, including carbohydrate, protein and lipid anabolism and catabolism emanating from impaired action of insulin, secretion of insulin, or both. The in silico study was conducted with the help of molecular docking to treat diabetes to inhibit the activities of α-amylase and α-glucosidase by drug molecule. All the studies were based on docking with molecules. The docking was done using a docking software between all the ligands and the target protein receptors. Natural compounds, such as Conduritol A, Catechin and Quercetin were picked, and protein targets as α-amylase and α-glucosidase. Ligands were imported for visual screening into PyRx software while Biovia Discovery Studio Visualizer was used for protein preparation. Analysis of the properties of drug likeliness of the ligands was done via SwissADME online server according to Lipinski’s Rule of Five. Final docking analysis was done through AutoDockVina and Biovia Discovery Studio client 2020. Molecular docking analysis of the ligands Conduritol A, Catechin and Quercetin showed strong binding interaction with both α-amylase and α-glucosidase. The test revealed different binding affinities, hydrogen bond interactions, hydrophobicity, solvent accessibility surface (SAS), root mean square deviation lower bound (RMSD LB) and root mean square deviation upper bound (RMSD UB). Conduritol A was the strongest compound against the protein targets, with its low binding strength, according to the PyRx test and Lipinski 's Rule of Five. The same molecules were further docked, and the interactions were visualized under PyMol Via Biovia Discovery Studio. According to the in silico study, we have found that these natural compounds can inhibit the activities of α-amylase and α-glucosidase which can be promising drugs for the treatment of diabetes after subjecting them to in vitro and in vivo studies.
Gymnema sylvestre (GS) is a powerful antidiabetic plant that has been utilized in ayurvedic, folk and homeopathic medicine for centuries. In this research, we evaluated the antidiabetic potential of methanolic leaf extract of Gymnema sylvestre. Fractionation was carried out using column chromatography and a total of twenty-eight (28) sub-fractions were obtained which were further screened and pooled into three (3) fractions (A, B and C) by thin layer chromatography based on their retention factor (Rf) values. The fractions were subjected to in vitro α-amylase and α-glucosidase inhibition activity. Some of the compounds identified from LC-MS were subjected to in silico analysis between all the ligands and the receptors with the aid of a docking software. Ligands were imported for visual screening into PyRx software while Biovia Discovery Studio Visualizer was used for protein preparation. Analysis of the properties of drug likeliness of the ligands was done via SwissADME online server according to Lipinski’s Rule of Five. Final docking analysis was done through AutoDockVina and Biovia Discovery Studio client 2020. Fraction C showed the best IC50 of 0.84µg/ml α-glucosidase inhibitory activity when compared with fraction A and B, 2.00µg/ml and 1.58µg/ml (α-glucosidase), fraction A produced the best α-amylase activity among the fractions with IC50 of 16.78µg/ml, fraction B with 23.17µg/ml and fraction C with 28.22µg/ml. Molecular docking analysis of the ligands Orcinol (-5.5 kcal/mol) showed strong binding interaction with α-amylase, followed by 3-hydroxy-3'-methoxyflavone and Curcumin (-7.1 kcal/mol and -7.6 kcal/mol respectively) compared to acarbose (-8.0 kcal/mol) and Glyinflanin A (-8.4 kcal/mol) interactions. The binding affinity of Orcinol, 3-hydroxy-3'-methoxyflavone, Curcumin and Glyinflanin A (-5.7 kcal/mol, -8.0 kcal/mol, -7.6 kcal/mol and -9.1 kcal/mol respectively) were lower compared to acarbose (-9.7 kcal/mol) interaction with α-glucosidase. Thus, compounds identified from Gymnema sylvestre were found to have antidiabetic potentials with Orcinol displaying the most effective binding affinity in potential for drug development.
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