Author
Salvador Ventura
Universitat Autònoma de BarcelonaORCID 0000-0002-9652-6351Unclaimed ORCID profile · follow to get notified of new preprints
Biology Disciplines
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2019-2026 · peak 4/yrCo-Author Collaboration Network
10 top collaborators · 24 mutual co-author links9 papers
Recent·Most cited
LRRK2-mutant microglia and neuromelanin synergize to drive dopaminergic neurodegeneration in an iPSC-based Parkinson's disease model
Lucas Blasco-Agell, Meritxell Pons‐Espinal, Veronica Testa, Gerard Roch, Jara Montero-Muñoz, Irene Fernández‐Carasa, Valentina Baruffi, Marta González-Sepúlveda, Yvonne Richaud‐Patín, Senda Jiménez‐Delgado, Thais Cuadros, Joana M. Cladera-Sastre, Joan Compte, Zoe Manglano-Artuñedo, Salvador Ventura, , Antonella Consiglio
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.
Communications Biology · Aug 12, 2025Peer-reviewedCell Biology✦ In-depth digest
EXPERIMENTAL KINETIC MECHANISM OF P53 CONDENSATION-AMYLOID AGGREGATION
Silvia Susana Borkosky, Ramon Peralta-Martinez, Alicia Armella-Sierra, Sebastián Esperante, Leonardo Lizárraga, Javier García‐Pardo, Salvador Ventura, Ignacio Enrique Sanchez, Gonzalo de Prat Gay
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.
Biophysical Journal · Apr 11, 2025Peer-reviewedBiophysics
A3D Database: Structure-based Protein Aggregation Predictions for the Human Proteome
Aleksandra Elzbieta Badaczewska-Dawid, Javier García‐Pardo, Aleksander Kuriata, Jordi Pujols, Salvador Ventura, Sebastian Kmiecik
The paper presents a database of structure-based protein aggregation predictions for the human proteome using AlphaFold structures and the A3D tool.
Bioinformatics · Apr 19, 2022Peer-reviewedBioinformatics
Prediction of the effect of pH on the aggregation and conditional folding of intrinsically disordered proteins with SolupHred and DispHred.
Valentín Iglesias, Carlos Pintado‐Grima, Jaime Santos, Marc Fornt‐Suñé, Salvador Ventura
The paper introduces two web servers, SolupHred and DispHred, to predict pH-dependent aggregation and disorder in intrinsically disordered proteins.
Methods in molecular biology · Jan 1, 2022Peer-reviewedBioinformatics
A3D 2.0 update for the prediction and optimization of protein solubility
Jordi Pujols, Valentín Iglesias, Jaime Santos, Aleksander Kuriata, Sebastian Kmiecik, Salvador Ventura
This paper updates A3D to predict and optimize protein solubility using a computational pipeline and RESTful service for handling large protein collections.
Methods in molecular biology · Jan 1, 2022Peer-reviewedBioinformatics
Protocols for rational design of protein solubility and aggregation properties using Aggrescan3D standalone
Aleksander Kuriata, Aleksandra Elzbieta Badaczewska-Dawid, Jordi Pujols, Salvador Ventura, Sebastian Kmiecik
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.
Methods in molecular biology · Jan 1, 2022Peer-reviewedBioinformatics
Critical Assessment of Protein Intrinsic Disorder Prediction
Marco Necci, Damiano Piovesan, CAID Predictors, Md Tamjidul Hoque, Ian Walsh, Sumaiya Iqbal, Michele Vendruscolo, Pietro Sormanni, Chen Wang, Daniele Raimondi, Ronesh Sharma, Yaoqi Zhou, Thomas Litfin, Oxana V. Galzitskaya, Michail Yu. Lobanov, , Silvio C. E. Tosatto
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.
Nature Methods · Apr 19, 2021Peer-reviewedBioinformatics
The fitness cost and benefit of phase separated protein deposits
Natalia Sánchez de Groot, Marc Torrent, Charles N. J. Ravarani, Ala Trusina, Salvador Ventura, M. Madan Babu
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.
Molecular Systems Biology · Apr 1, 2019Peer-reviewedSystems Biology