RESUMEN
Bacterial vaginosis (BV) is a prevalent vaginal illness resulting from a disruption in the vaginal microbial equilibrium. The vaginal microbiota has been shown to have a substantial impact on the development and continuation of BV. This work utilized 16S rRNA sequence analysis of vaginal microbiome samples (Control vs BV samples) utilizing Parallel-Meta 3 to investigate the variations in microbial composition. The unique genes identified were used to determine prospective therapeutic targets and their corresponding inhibitory ligands. Further, molecular docking was conducted and then MD simulations were carried out to confirm the docking outcomes. In the BV samples, we detected several anaerobic bacteria recognized for their ability to generate biofilms, namely Acetohalobium, Anaerolineaceae, Desulfobacteraceae, and others. Furthermore, we identified Dalfopristin, Clorgyline, and Hydrazine as potential therapeutic options for the management of BV. This research provides new insights into the causes of BV and shows the potential effectiveness of novel pharmacological treatments.
Asunto(s)
Hidrazinas , Microbiota , ARN Ribosómico 16S , Vagina , Vaginosis Bacteriana , Femenino , Vaginosis Bacteriana/tratamiento farmacológico , Vaginosis Bacteriana/microbiología , ARN Ribosómico 16S/genética , Humanos , Microbiota/efectos de los fármacos , Microbiota/genética , Vagina/microbiología , Hidrazinas/farmacología , Hidrazinas/uso terapéutico , Antibacterianos/farmacología , Antibacterianos/uso terapéutico , Simulación del Acoplamiento Molecular , Bacterias/efectos de los fármacos , Bacterias/genética , Bacterias/clasificaciónRESUMEN
The fourth most frequent type of cancer in women and the leading cause of mortality for females worldwide is cervical cancer. Traditionally, medicinal plants have been utilized to treat various illnesses and ailments. The molecular docking method is used in the current study to look into the phytoconstituents of Juglans regia's possible anticancer effects on cervical cancer target proteins. This work uses the microarray dataset analysis of GSE63678 from the NCBI Gene Expression Omnibus database to find differentially expressed genes. Furthermore, protein-protein interactions of differentially expressed genes were constructed using network biology techniques. The top five hub genes (IGF1, FGF2, ESR1, MYL9, and MYH11) are then determined by computing topological parameters with Cytohubba. In addition, molecular docking research was performed on Juglans regia phytocompounds that were extracted from the IMPPAT database versus hub genes that had been identified. Utilizing molecular dynamics, simulation confirmed that prioritized docked complexes with low binding energies were stable.