Structure‐Guided Identification of Peptide Therapeutics Targeting BACE1 for Alzheimer's Disease Through Energy Profiling and Multivariate Analysis

Alzheimer's disease (AD) is a relentless neurodegenerative disorder lacking effective therapeutic interventions, thus necessitating an identification of novel drug candidates. This work deployed an integrated multi‐modal computational approach to identify and characterize the therapeutic peptides targeting β‐Secretase 1(BACE1), a key enzyme involved in amyloid‐β peptide biogenesis. The tertiary structure of peptides was modeled using the GRSA algorithm, followed by molecular docking to evaluate binding affinities. Among the shortlisted peptides, pep12 (WGHE), pep20 (YMGWMDF), pep41 (YGGFL), and pep50 (DRVY) have the highest docking scores (−9.5, −9.2, −9.2, −8.9 Kcal/mol), complemented by favorable ADME profiles indicative of oral bioavailability. Molecular dynamics simulations substantiated the stable interactions of candidate peptides and BACE1complexes, which is evidenced by sustained potential energy landscapes and conformational retention. Detailed Protein‐ligand interaction mapping elucidated critical binding residues involved in drug binding, which provided insight into their molecular drug effectiveness. Free energy landscape analysis, Principal Component Analysis (PCA), and MMPBSA calculations collectively corroborated the structural robustness and therapeutic promise of these peptide‐BACE1 complexes. This computational pipeline exemplifies a rational accelerating peptide‐based drug discovery for treating Alzheimer's disease.