METHOD: The SARS-CoV receptor structure files (viral structural components) were retrieved from the Protein Data Bank (PDB) database: membrane protein (PDB ID: 3I6G), main protease (PDB ID: 5RE4), and spike glycoproteins (PDB ID: 6VXX and 6VYB). The receptor binding pocket regions were identified by Discovery Studio (BIOVIA) for targeted docking with TBF polyphenols (genistin, kaempferol, mellein, rhoifolin and scutellarein). The ligand and SARS-CoV family receptor structure files were pre-processed using the AutoDock tools. Molecular docking was performed with the Lamarckian genetic algorithm using AutoDock Vina 4.2 software. The best pose (ligand-receptor complex) from the molecular docking analysis was selected based on the minimum binding energy (MBE) and extent of structural interactions, as indicated by BIOVIA visualization tool. The selected complex was validated by a 100 ns MD simulation run using the GROMACS software. The dynamic behaviour and stability of the receptor-ligand complex were evaluated by the root mean square displacement (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), solvent accessible surface volume (SASV) and number of hydrogen bonds.
RESULTS: At RMSD = 0, the TBF polyphenols showed fairly strong physical interactions with SARS-CoV receptors under all possible combinations. The MBE of TBF polyphenol-bound SARS CoV complexes ranged from -4.6 to -8.3 kcal/mol. Analysis of the structural interactions showed the presence of hydrogen bonds, electrostatic and hydrophobic interactions between the receptor residues (RR) and ligands atoms. Based on the MBE values, the 3I6G-rhoifolin (MBE = -8.3 kcal/mol) and 5RE4-genistin (MBE = -7.6 kcal/mol) complexes were ranked with the least value. However, the latter showed a greater extent of interactions between the RRs and the ligand atoms and thus was further validated by MD simulation. The MD simulation parameters of the 5RE4-genistin complex over a 100 ns run indicated good structural stability with minimal flexibility within genistin binding pocket region. The findings suggest that S. torvum polyphenols hold good therapeutics potential in COVID-19 management.
METHODS: Clinical specimens from three Kathmandu hospitals were processed and S. aureus was identified using conventional microbiological procedures. MRSA was phenotypically identified with cefoxitin (30µg) disc diffusion, while vancomycin susceptibility was assessed using the Ezy MICTM stripes. The mecA and vanA genes were detected by polymerase chain reaction (PCR).
RESULTS: Out of 266 S. aureus samples from various clinical specimen subjected for analysis, 77 (28.9%) were found methicillin-resistant (MRSA) and 10 (3.8%) were observed vancomycin-resistant (VRSA). Vancomycin resistant isolates showed a significant correlation between resistance to ampicillin, chloramphenicol, and cefoxitin. The mecA gene was found in 39 of the MRSA isolates, having 50.64% of MRSA cases, while the vanA gene was detected in 4 of the VRSA cases, constituting 40% of VRSA occurrences.
CONCLUSIONS: The strains with higher vancomycin minimum inhibitory concentration values (≥ 1.5 μg/ml) displayed increased resistance rates to various antibiotics compared to strains with lower minimum inhibitory concentration values (< 1.5 μg/ml). The presence of vanA genes was strongly associated (100%) with vancomycin resistance, while the 10.3% mecA gene was identified from MRSA having resistance towards vancomycin also.