Biology subjects

Gamez, F.

Publications and source records attributed to Gamez, F..

3 recordsLinked to original sources

bioRxiv2026

Compositional control of FUS condensate ageing through aggregation-prone interaction networks

Stress granules are multicomponent biomolecular condensates whose aberrant ageing has been implicated in numerous neurodegenerative diseases. Although their composition is known to influence condensate properties, the molecular principles linking composition to structural maturation remain poorly understood. Here, we perform equilibrium and non-equilibrium residue-resolution molecular dynamics simulations to determine how RNA and heterotypic protein interactions regulate the pathological hardening of multicomponent FUS-containing condensates inspired by stress-granule composition. We show that diverse compositional changes--including RNA concentration, heterotypic protein partitioning, interfacial enrichment of G3BP1, and charged peptide recruitment--reshape condensate organization through distinct molecular mechanisms. Despite these different modes of action, all converge on a common physical principle: modulation of the local clustering and persistence of contacts between low-complexity aromatic-rich kinked segments (LARKS) governs the nucleation and accumulation of long-lived intermolecular cross-{beta}-sheet structures. Intermediate RNA concentrations enhance condensate density and promote LARKS contacts, whereas high RNA levels, heterotypic interactions, and interfacial coating reduce their availability and delay ageing. Our results establish a unified molecular framework linking condensate composition, internal organization and ageing. This framework provides mechanistic insight into the regulation of multicomponent condensate material properties and suggests general design principles for modulating their pathological aggregation.

biophysics↗

bioRxiv2025

Predicting Saturation Concentrations of Phase-Separating Proteins via Thermodynamic Integration

Phase separation of proteins and nucleic acids into biomolecular condensates contributes to the regulation of cellular compartmentalisation in membrane-less environments. A key parameter controlling the onset of biomolecular condensate formation via liquid--liquid phase separation is the saturation concentration (Csat)-- the threshold concentration above which condensation takes place. While measuring Csat for protein solutions in vitro is experimentally accessible, determining this quantity in simulations remains challenging due to the extremely low equilibrium concentrations at which many proteins phase separate. This occurs because the gold standard in simulations consists on combining a residue-resolution coarse-grained model with the Direct Coexistence simulation method, which yields poor estimates of the equilibrium concentrations of the dilute phase due to lack of statistics. In this work, we present two independent thermodynamic integration (TI) schemes which, when combined with Direct Coexistence simulations, enable accurate calculation of saturation concentrations and phase diagrams--facilitating direct comparison with experimental measurements across a wide range of conditions. Our methods, combined with the Mpipi-Recharged residue-resolution coarse-grained model, accurately estimate Csat for a wide range of intrinsically disordered and multi-domain proteins, including disease-associated RNA- and DNA-binding proteins involved in the formation of stress granules and P granules, as well as engineered mutants of hnRNPA1. Furthermore, we compare our TI methods against a computationally efficient machine-learning predictor trained to estimate saturation concentrations at sub-physiological temperatures. While both approaches yield realistic predictions, explicit molecular dynamics simulations enable the calculation of complete phase diagrams and provide insight into the molecular mechanisms and interactions driving phase-separation. Overall, our approach offers a robust, physically grounded framework for improving and validating coarse-grained models of biomolecular phase behaviour, effectively bridging the gap between simulation and experiment.

biophysics↗

bioRxiv2025

Charged mutations in the FUS low-complexity domain modulate condensate ageing kinetics

The assembly of biomolecular condensates is tightly regulated by the intracellular environment. Disruptions in the balance between condensate formation and dissolution--such as irreversible aggregation of low-complexity aromatic-rich kinked segments (LARKS)--have been implicated in multiple neuropathologies. Here, we employ non-equilibrium, residue-resolution coarse-grained simulations to investigate how specific mutations in FUS, an RNA-binding protein associated with amyotrophic lateral sclerosis and frontotemporal dementia, modulate its phase separation propensity and transition into insoluble aggregates. Our simulations reveal that mutations increasing the content of negatively charged amino acids in the low-complexity domain slow down inter-protein {beta}-sheet accumulation, while preserving the phase diagram and viscoelastic properties of the wild-type sequence. Conversely, mutations increasing the arginine content accelerate disorder-to-order LARKS transitions, driving rapid formation of amorphous kinetically trapped aggregates. Our computational approach thus provides molecular-level insights into how specific amino acid mutations and associated intermolecular interactions control the ageing kinetics of protein condensates, promoting aberrant solid-like phases.

biophysics↗