What question did this study set out to answer?

The research aims to identify peptides from Androctonus mauretanicus venom that inhibit the entry of SARS-CoV-2 through the spike protein.

March 8, 2026Open Access

Computational discovery of SARS-CoV-2 viral entry inhibitory peptides from Androctonus mauretanicus scorpion venom: molecular docking and molecular dynamics simulations targeting the spike protein

RCReda ChahirUniversité Hassan 1er SRSalaheddine RedouaneInstitut Pasteur du Maroc JGJacob A. GalánThe University of Texas Rio Grande Valley

Key Points

The research aims to identify peptides from Androctonus mauretanicus venom that inhibit the entry of SARS-CoV-2 through the spike protein.
Selected six peptides based on bioinformatic and experimental criteria.
Used molecular docking to model interactions with the spike protein's receptor-binding domain.
Conducted molecular dynamics simulations to assess stability and interactions of peptide-protein complexes.
Four peptides exhibited strong antiviral activity, with AM5 showing the highest affinity (ΔG = −14.0 kcal/mol).
Molecular dynamics simulations indicated AM1, AM3, and AM5 formed stable complexes, while AM4 showed significant instability.
Thermodynamic analyses confirmed AM3 and AM5 as the most stable complexes.

Abstract

Background and Objective While vaccination remains central to controlling the COVID-19 pandemic, the emergence of SARS-CoV-2 variants with partial resistance to immune responses has highlighted the need for complementary therapeutic strategies. Among these, antiviral agents that inhibit viral entry mechanisms are of particular interest. Animal venoms, especially scorpion venoms, are a rich source of bioactive peptides with potential antiviral properties. This study aimed to evaluate peptides derived from the Moroccan scorpion Androctonus mauretanicus as inhibitors of SARS-CoV-2 spike glycoprotein, which mediates virus entry into host cells via ACE2 receptor binding. Material and Methodology Six peptides from the venom of the scorpion A. mauretanicus were first selected according to rigorous bioinformatic and experimental criteria, and their 3D structures were obtained or modeled. Their antiviral potential was then screened using the Stack-AVP stacked learning framework. The interactions of promising peptides with the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein were modeled by molecular docking using HADDOCK 2.4 and ClusPro 2.0. The most stable complexes were subjected to molecular dynamics simulations (200 ns) with GROMACS to assess their conformational stability (RMSD, Rg, RMSF) and interactions. Trajectories were analyzed by principal component analysis (PCA) and free energy landscape (FEL) construction, while binding affinity was predicted with PRODIGY. Results Four peptides (AM1, AM3, AM4 and AM5) showed strong predicted antiviral activity (85%). Docking identified AM5 as the most affinity ligand (ΔG = −14.0 kcal/mol), targeting the S2 fusion domain, followed by AM3 (allosteric mechanism), AM4 (targeting the furin cleavage site), and AM1 (specific RBD inhibitor). MD simulations revealed that AM1, AM3, and AM5 form structurally stable complexes (low and constant RMSD). In contrast, AM4 induces significant conformational instability (high and non-convergent RMSD) and overall decompaction. Thermodynamic analyses (FEL) confirm the superior stability of the AM3 and AM5 complexes. These results position AM5 as the most promising blocking candidate.

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