Peptide-Based Therapeutics for Alzheimer’s Disease: Medicinal Chemistry, AI-Guided Computational Design, and Blood–Brain Barrier Delivery

Abdulaziz H Al Khzem, Mohamed S Gomaa Department of Pharmaceutical Chemistry, College of Pharmacy, Imam Abdulrahman Bin Faisal University, Dammam, Eastern Province, 31441, Kingdom of Saudi ArabiaCorrespondence: Abdulaziz H Al Khzem, Mohamed S Gomaa, Email [email protected]; [email protected]: Alzheimer’s disease (AD) represents a pressing challenge in modern medicine, with current therapeutics offering only symptomatic relief. Peptide-based therapeutics have emerged as promising candidates owing to their target specificity, favorable safety profiles, and ability to modulate protein–protein interactions inaccessible to small molecules. This narrative review evaluates medicinal chemistry and artificial intelligence (AI)-driven approaches that are reshaping peptide drug discovery for AD, spanning target selection, sequence design, synthesis optimization, and central nervous system (CNS) delivery. Peptides targeting key AD pathological mechanisms-including amyloid-β (Aβ) aggregation inhibition, tau hyperphosphorylation disruption, and neurotrophic signaling enhancement-are discussed alongside strategies such as cyclization, D-amino acid incorporation, PEGylation, and peptidomimetic design to improve metabolic stability and blood–brain barrier (BBB) penetration. We review automated fast-flow peptide synthesis with inline UV-vis monitoring as a platform for rapid, high-fidelity preparation of complex sequences suitable for translational development. Delivery platforms-including cell-penetrating peptides, intranasal formulations, and nanocarrier systems-which primarily increase systemic exposure or fundamentally alter CNS distribution mechanisms are presented. AI and machine-learning (ML) technologies, molecular simulations, and structure-prediction systems are examined as an integrated pipeline that supports end-to-end design, validation, and optimization, with emphasis on rigorous QSAR and docking/MD validation practices. Clinical translation is analyzed through peptide repurposing (e.g. GLP‑1 receptor agonists, intranasal insulin, oxytocin), dedicated peptide candidates, and evolving regulatory expectations. Finally, we outline concrete design checklists for CNS ready peptides, discuss key translational bottlenecks, and propose priorities for the next 5– 10 years of peptide-based AD therapy development.Keywords: Alzheimer’s disease, blood–brain barrier, peptide drugs, artificial intelligence, drug discovery, pharmaceutical medicinal chemistry, clinical translation