Comparative in silico analysis identifies potent natural and synthetic peptide candidates for targeting SARS-CoV-2 viral proteins.

Publication date: Feb 01, 2026

The recent SARS-CoV-2 pandemic has highlighted the urgent need for novel therapeutic approaches, particularly the discovery of new antimicrobial peptides (AMPs). While; previous studies have primarily focused on small molecules, limited efforts have been made to explore virtual screening for peptides targeting key SARS-CoV-2 proteins. Antimicrobial peptides, due to their short length, positive charge, safety, specificity, and efficacy, represent a promising class of therapeutics against emerging viral pathogens. In this study, 108 synthetic AMPs and 104 natural antiviral peptides (ranging from 5 to 50 amino acids) were selected from the DBAASP and APD databases. Their tertiary structures were modeled using PEP-FOLD3, refined with MODELLER, and prepared for docking using AutoDock Tools. Peptides were docked against three critical SARS-CoV-2 proteins-Spike, Mpro, and PLpro-using AutoDock Vina. Six peptide-protein complexes showing the best binding energies were selected for molecular dynamics (MD) simulations under physiological conditions using the GROMOS54a7 force field, followed by structural stability analysis and binding free energy estimation using g-MMPBSA. The results indicated that natural peptides generally exhibited stronger interactions with the receptors than synthetic peptides. Among all peptides, AP00241 (Spike), AP00225 (Mpro), and 15648 (PLpro) demonstrated the most favorable binding energies of -134. 533, -629. 465, and -151. 283 kJ/mol, respectively, and maintained stable interactions throughout the simulations. These findings highlight the potential of AP00241, AP00225, and 15648 as promising candidates for further development of peptide-based therapeutics against SARS-CoV-2.

Semantics