Salvador Ventura

LRRK2 G2019S iPSC-derived microglia exposed to neuromelanin, but not α-synuclein fibrils, reduce healthy dopaminergic neuron numbers in co-culture; ivermectin prevents this, and post-mortem midbrain supports it.

This paper investigates the kinetic mechanism of p53 condensation and amyloid aggregation, revealing a pathway from coacervates to fibrils and suggesting therapeutic targets for p53-related cancers.

The paper presents a database of structure-based protein aggregation predictions for the human proteome using AlphaFold structures and the A3D tool.

The paper introduces two web servers, SolupHred and DispHred, to predict pH-dependent aggregation and disorder in intrinsically disordered proteins.

This paper updates A3D to predict and optimize protein solubility using a computational pipeline and RESTful service for handling large protein collections.

The paper introduces Aggrescan3D, a tool for designing protein variants with improved solubility and reduced aggregation using 3D structures, and demonstrates its application on therapeutic proteins.

The paper evaluates 43 methods for predicting intrinsically disordered regions and binding regions in proteins, finding that deep learning methods outperform older physicochemical approaches but binding prediction remains challenging.

The paper quantifies the fitness costs and benefits of protein deposit formation via phase separation in yeast, showing environmental and functional demands influence fitness outcomes and generate phenotypic variability.