Computational and immunoinformatics approaches for designing phytocompound-based drugs and a multi-epitope vaccine...

Staphylococcus aureus, a bacterial pathogen, is increasingly linked to severe healthcare-associated diseases, from mild skin infections to toxic shock syndrome. Due to limitations in conventional methods, we use computational techniques to screen potential phytocompounds for new drug development and to construct a multiepitope vaccine. Aminoacyltransferase FemA, essential for peptidoglycan formation, was chosen as the target protein for drug and vaccine development. Meanwhile, 1100 phytocompounds were retrieved from 54 plants using the NPASS database and analyzed for drug-likeness and ADMET properties. Paulownin was selected for its higher binding affinity (-7.78 Kcal/mol) than the control drug, Doxycycline (-7.5 Kcal/mol) in molecular docking. It also showed lower RMSD, RMSF, and stronger hydrogen bonding (1.11/0.8 Å, 1.594/1.613 Å, and 3/2, respectively) in molecular dynamics simulations. It demonstrated potential higher affinity, scoring -39.74 ± 6.05 Kcal/mol, outperforming Doxycycline's -28.15 ± 5.90 Kcal/mol in MM-GBSA. For the vaccine, 12 selected epitopes were compiled utilizing GPGPG, two KK peptides, and AAY linkers. The N-flanking immunogenicity of the vaccine was enhanced by adding a lipoprotein adjuvant, LprG. The vaccine alone and the vaccine with the receptor molecule TLR2 showed RMSF (4.247 Å/2.42 Å), RMSD (12.9 Å/7.52 Å), SASA (228.48 nm²/220.29 nm²), Rg (33.76 Å/28.48 Å), and hydrogen bonds (171/165), indicating the vaccine's predicted immune response patterns. These findings computationally prioritize Paulownin and the multi-epitope construct as candidates for further experimental evaluation. As the study is entirely in silico, experimental validation is required to confirm biological activity and immunogenicity.