Benedetta Bolognesi

This study maps the mutational landscape of SOD1 by analyzing monomer folding and dimerization, identifying protein destabilization as a key driver of ALS and uncovering potential therapeutic targets.

This study quantifies how mutations affect IAPP amyloid formation using deep mutational scanning and identifies key residues involved in aggregation.

This study maps mutations in RIPK1 and RIPK3 to reveal how amyloid formation is optimized for necroptosis, showing conserved mechanisms across species and evolutionary constraints.

The paper uses genetic perturbation and machine learning to analyze the energetics of amyloid beta nucleation, revealing its genetic architecture and transition state structure.

The paper experimentally quantifies amyloid nucleation for >100,000 sequences, trains an interpretable deep learning model to predict it, and reveals the model's decision-making process.

The paper investigates the amyloid-forming potential of C-terminal extensions of Bri2, identifying an incomplete amyloid motif that becomes pathogenic upon extension.

The paper creates an atlas of amyloid beta fibril nucleation effects caused by various mutations, showing that non-substitution variants also significantly impact aggregation.

The paper quantifies the effects of mutations on amyloid beta fibril nucleation using deep mutational scanning and identifies key residues that prevent nucleation, validating a cell-based assay for familial Alzheimer's disease mutations.

This study systematically mutates the prion-like domain of TDP-43 to determine how sequence changes affect cellular toxicity and aggregation, finding that increased aggregation reduces toxicity.

The paper identifies scaffolding RNAs and a new player, TRA2A, in Fragile X-associated Tremor/Ataxia Syndrome by studying RNA-RBP interactions and their aggregation.