Computational Insights into Papain-Like Protease Inhibition: Antimicrobial Peptides as Potential Therapeutics Against SARS-CoV-2

Context The SARS-CoV-2 papain-like protease (PLpro) is a therapeutic target of interest due to its dual role in cleaving viral polyproteins and suppressing the host immune response. Virtual screening, molecular docking, and molecular dynamics simulations (500 ns) were performed to identify antimicrobial peptides capable of inhibiting PLpro. The results revealed that peptides 10892 and 26956 (docking scores: − 249.1 and − 244.3) exhibited the highest affinity for PLpro, forming stable interactions with the catalytic triad (Cys111–His272–Asp286) and key active-site residues. RMSD (< 0.3 nm), RMSF, and radius of gyration analyses confirmed the stability of the complexes, while MM-PBSA calculations indicated favorable energetic contributions (ΔG = − 11.42 kcal/mol and − 29.21 kcal/mol). This work highlights two peptides, pep10892 and pep26956, as promising candidates for the development of antivirals against COVID-19, combining direct action on viral replication with immune modulation. Methods Peptides were modeled by homology using the BioPep pipeline (https://github.com/lbqc-uesb/biopep), and protein–peptide docking was performed with the HPEPDOCK server. Two-dimensional complex interaction maps were generated using LigPlot + v2.2.8. Molecular dynamics simulations for stability were performed in GROMACS 2024 with the OPLS force field. The system underwent energy minimization (50,000 steps), followed by NVT (100 ps, 300 K, V-rescale) and NPT (100 ps, 1 bar, Parrinello–Rahman) equilibration. Binding energies were calculated with gmx_MMPBSA using the MM-PBSA method and the Generalized Born (GB) solvation model.