: Alzheimer's disease is a neurodegenerative disorder characterized by progressive cognitive decline and memory loss. It is associated with the self-assembly of the amyloid-β peptide, a soluble intrinsically disordered protein naturally present in the brain parenchyma in various alloforms. This study presents a computational approach to identify possible modulators of the monomeric aggregation-prone conformations of amyloid-β, a critical intermediate in the fibrillation process. A structure-based virtual screening campaign was designed using a structural ensemble to identify potential binders. The workflow included binding site identification, small molecule-peptide docking, protein-protein docking, and molecular dynamics simulations to evaluate interaction stability and aggregation propensity. From this pipeline, a set of novel molecules was identified as capable of interacting with aggregation-prone forms of amyloid-β, potentially reducing their tendency to form toxic aggregates.

Bosio, S., Falchi, F., Rauzi, C., Bellucci, L. (2025). Morphological inhibitors of aggregation-prone amyloid-β conformers: A computational exploration. COMPUTERS IN BIOLOGY AND MEDICINE, 196(Pt A), 1-9 [10.1016/j.compbiomed.2025.110545].

Morphological inhibitors of aggregation-prone amyloid-β conformers: A computational exploration

Bosio S.
Co-primo
;
Falchi F.
Co-primo
;
2025

Abstract

: Alzheimer's disease is a neurodegenerative disorder characterized by progressive cognitive decline and memory loss. It is associated with the self-assembly of the amyloid-β peptide, a soluble intrinsically disordered protein naturally present in the brain parenchyma in various alloforms. This study presents a computational approach to identify possible modulators of the monomeric aggregation-prone conformations of amyloid-β, a critical intermediate in the fibrillation process. A structure-based virtual screening campaign was designed using a structural ensemble to identify potential binders. The workflow included binding site identification, small molecule-peptide docking, protein-protein docking, and molecular dynamics simulations to evaluate interaction stability and aggregation propensity. From this pipeline, a set of novel molecules was identified as capable of interacting with aggregation-prone forms of amyloid-β, potentially reducing their tendency to form toxic aggregates.
2025
Bosio, S., Falchi, F., Rauzi, C., Bellucci, L. (2025). Morphological inhibitors of aggregation-prone amyloid-β conformers: A computational exploration. COMPUTERS IN BIOLOGY AND MEDICINE, 196(Pt A), 1-9 [10.1016/j.compbiomed.2025.110545].
Bosio, S.; Falchi, F.; Rauzi, C.; Bellucci, L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1030179
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