Biology subjects

R. Espinosa, J.

Publications and source records attributed to R. Espinosa, J..

5 recordsLinked to original sources

bioRxiv2026

Charge-Driven Fibril Recognition and Covalent Disruption of Aβ42 byPaddlewheel Diruthenium Complexes

The inhibition of A{beta}42 ({beta}-amyloid) fibril formation is a key therapeutic strategy in Alzheimers disease research. Paddlewheel diruthenium complexes have shown promising activity against A{beta}42 aggregation and preformed fibril disaggregation, yet their molecular mode of action remains poorly understood. In this work, we perform atomistic simulations to explore how charge modulation influences the interactions of three analogous paddlewheel diruthenium complexes, the parent neutral complex [Ru2Cl(D-p-FPhF)(O2CCH3)3], and its anionic [Ru2Cl2(D-p-FPhF)(O2CCH3)3]- and cationic [Ru2(D-p-FPhF)(O2CCH3)3]+ counterparts (D-p-FPhF- is the N,N -bis(4-fluorophenyl)formamidinato ligand) with A{beta}42. Our results indicate that electrostatic tuning governs binding affinity and the extent of interaction across the A{beta}42 fibril surface. As the complexes charge changes from -1 to +1, the interaction pattern shifts from localized contacts to widespread, multi-site engagement encompassing key charged, aromatic, and hydrophobic regions of A{beta}42. This enhanced binding correlates with longer-lived, thermodynamically stable interactions at the fibril interface, which effectively lower the free energy penalty for fibril disassembly. Overall, our findings propose a mechanism in which charge-dependent activation through ligand exchange enhances fibril recognition and promotes disruptive binding modes, demonstrating the potential of charge-tunable diruthenium complexes as therapeutic modulators of A{beta}42 fibril stability.

biophysics↗

bioRxiv2026

RNA synthesis and degradation regulate biomolecular condensates through non-equilibrium feedback

Transcriptional condensates operate far from equilibrium, where continuous RNA synthesis and degradation dynamically reshape condensate composition. To investigate how RNA synthesis regulates condensate properties at sub-molecular resolution, we introduce REACT-RNA, a chemically specific coarse-grained molecular dynamics framework that explicitly couples RNA polymerisation, degradation, and nucleotide fluxes to sequence-dependent protein-RNA phase behaviour. Using FUS and MED1 as model systems, we show that RNA growth remodels condensate phase behaviour by altering RNA length distributions and intermolecular connectivity. Sustained RNA polymerisation drives re-entrant condensate dissolution, even of aged gel-like condensates, whereas RNA degradation stabilises long-lived non-equilibrium condensates containing excess RNA and negative charge beyond that tolerated at equilibrium. Our results suggest that RNA synthesis, degradation, and nucleotide fluxes drive transcriptional condensates out of thermodynamic equilibrium while condensates in turn promote reactive molecular configurations that favour RNA production, enabling transient accumulation of excess RNA and negative charge beyond equilibrium electroneutrality constraints during bursts of transcription.

biophysics↗

bioRxiv2025

Benchmarking Free Energy Computational Methods for Revealing the Interactions Driving PARP1 Selective Inhibition

Accurate prediction of inhibitor selectivity across protein paralogues remains a central challenge in computational drug discovery. Here, we systematically benchmark three computational methods--Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA), free energy perturbation (FEP) and potential of mean force (PMF) calculations--in their ability to recapitulate PARP1 versus PARP2 selectivity for eight clinically relevant PARP enzyme inhibitors used in ovarian, breast and prostate tumors among others. We demonstrate how MM/PBSA calculations offer rapid and qualitative insights, but show pronounced sensitivity to the chosen static conformational pose, being particularly challenging for ligands with subtle energetic differences between distinct protein paralogues. In contrast, both FEP and PMF calculations using atomistic models with explicit solvent result in substantially improved agreement with experimental binding affinities. The FEP method exhibits the strongest quantitative correlation with experimental binding free energy differences, remarkably reproducing selectivity trends even among nearly isoenergetic complexes. Notably, our structural contact analysis reveals how contact connectivity controls ligand selectivity, providing valuable mechanistic and molecular insight into the key residues that stabilize each inhibitor in both protein enzymes. Together, our multi-method computational study contributes to elucidate potential chemical modifications across the ligand chemical space to enhance potency and specificity, informing the future design and evaluation of selective inhibitors for precision oncology, including therapies targeting homologous recombination-deficient cancers.

bioinformatics↗

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↗