Innovative Peptide Therapeutics for SARS-CoV-2: Design, Docking, and Functional Analysis

Area of Science:

• Computational drug discovery
• Structural biology
• Bioinformatics

Background:

• Emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants necessitate rapid development of novel therapeutics.
• Peptide-based drugs present high specificity and low toxicity, ideal for targeting conserved viral proteins.

Purpose of the Study:

• To design and evaluate novel peptide analogs targeting key SARS-CoV-2 proteins: Spike (S), RNA-dependent RNA polymerase (RdRp), and nucleocapsid (N).
• To utilize an integrated computational approach combining structural biology, molecular docking, and molecular dynamics (MD) simulations.

Main Methods:

• Dataset preparation of anti-SARS-CoV-2 peptides from DRAVP database and literature.
• Screening and design of analogous peptides using AVPPred and lead peptide information.
• Molecular docking via nCoVDock2 server and 100 ns explicit solvent MD simulations for top-ranked complexes.

Main Results:

• Designed peptide W showed superior inhibition of S protein (-303.41 a.u.) compared to EK1 lead peptide.
• Peptide A5 demonstrated effective inhibition of RdRp protein (-187.36 a.u.) compared to lead peptide 5.
• Peptide A7 exhibited strong inhibition of N protein (-317.69 a.u.), outperforming Plectasin. MD simulations confirmed stability for W and A5 complexes.

Conclusions:

• Bioinformatics-driven design of engineered peptides offers a promising strategy for SARS-CoV-2 peptide-based therapies.
• This approach holds potential for developing therapeutic methods against other viral diseases.
• Computational findings provide a foundation for future in vitro and in vivo validation studies.