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DOI 10.3389/fbinf.2026.1677524

Медицинская библиотека · Frontiers in bioinformatics · 2026

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.

Chahir Reda, Redouane Salaheddine, Galan Jacob, Hboub Hicham, Aserrar Lahoussaine, Chakir Salma, Lahlou Ahmed Salim, Aassila Hinde, El Fatimy Rachid, Oukkache Naoual

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Аннотация

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.

Для цитирования: Chahir Reda, Redouane Salaheddine, Galan Jacob, Hboub Hicham, Aserrar Lahoussaine, Chakir Salma, Lahlou Ahmed Salim, Aassila Hinde, El Fatimy Rachid, Oukkache Naoual. 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.. Frontiers in bioinformatics. 2026. DOI: 10.3389/fbinf.2026.1677524.
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