Computational Discovery of SARS-CoV-2 viral entry Inhibitors Peptides from Androctonus mauretanicus Scorpion Venom: Molecular Docking and Dynamics Simulations Targeting the Protein Spike S

REDA CHAHIR^1,2*Salaheddine Redouane^1*Jacob Galan^3,4Hicham Hboub⁵Lahoussaine Aserrar⁶Salma Chakir^1,2Ahmed Salim Lahlou¹Hinde Aassila²Rachid El Fatimy⁵Naoual Oukkache^1*

• ¹Institut Pasteur du Maroc, Casablanca, Morocco
• ²Universite Hassan 1er, Settat, Morocco
• ³The University of Texas Rio Grande Valley, Brownsville, United States
• ⁴Department of Human Genetics, The University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78539, USA., Texas, United States
• ⁵Universite Mohammed VI Polytechnique Faculty of Medical Sciences, Ben Guerir, Morocco
• ⁶Universite Mohammed VI des Sciences et de la Sante, Casablanca, Morocco

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 ven-oms, 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 Androctonus maure-tanicus 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 con-formational 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.