Introduction: Alzheimer’s disease is the most common type of neurodegenerative disorder, and amyloid-β (Aβ) plaques are associated with this disorder. According to the amyloid cascade hypothesis, the accumulation of neurotoxic Aβ42 generally plays a crucial role in the disease's progression. Emerging evidence shows that soluble oligomeric forms, especially tetramers and larger assemblies, are more neurotoxic than mature fibrils. Although several anti-Aβ antibodies target different states of aggregation (from monomers to plaques), nanobody-based therapies do not exist yet. Here, we aim to identify nanobodies targeting the Aβ42 octamer computationally.

Materials and Methods: A total of 40 nanobodies were modeled based on three enzymes known to interact with Aβ42. Using three Aβ42-interacting enzymes as templates, we designed 40 nanobody sequences through Essential Site Scanning Analysis, Peptide Atlas, and AbNatiV, with structural modeling performed via SWISS-MODEL and AlphaFold3. Then, a site-specific docking approach using ClusPro was performed to evaluate nanobody–Aβ42 binding, producing 120 nanobody–Aβ42 octamer complexes. They were ranked based on docking scores, salt bridge formation, stable interface interactions, and solvent-accessible surface area, narrowing the candidates down to seven promising complexes. This pipeline prioritized seven high-affinity candidates, which were further evaluated by conventional molecular dynamics (MD) simulations to assess complex stability.

Results: Among all screened complexes, a single nanobody exhibited persistent binding to the Aβ42 octamer, marked by prolonged interfacial contacts and minimal structural deviation. This candidate emerges as a potential diagnostic or therapeutic lead.

Conclusion: This study establishes an integrative computational framework for the systematic identification and evaluation of nanobodies targeting pathogenic amyloid aggregates, additionally offering a scalable strategy to prioritize high-affinity binders against disease targets.