Erba, D. | bioRxiv Science

bioRxiv2026

Interplay Between Protein-RNA Binding and Phase Separation Drives Emergent Behavior in RNP Condensates

Protein-RNA binding and biomolecular condensation are two key processes underlying the assembly and function of ribonucleoprotein (RNP) condensates. However, the understanding of the physical consequences of their interplay is still incomplete. To investigate this coupling, here we develop a minimal coarse-grained molecular model that combines specific, saturable protein-RNA binding with multivalent protein-protein interactions. Our results show that RNA acts as a molecular scaffold whose ability to promote condensation depends on the distribution of bound proteins across RNA molecules. This provides a simple microscopic explanation for both RNA-length-dependent condensation and re-entrant phase behavior, showing that condensate dissolution at high RNA concentration can emerge from entropic effects without requiring explicit electrostatic interactions. Conversely, condensate assembly markedly enhances effective protein-RNA binding, demonstrating that substantial changes in binding behavior can emerge without changes in intrinsic affinity. This provides a general physical mechanism through which condensates can reshape molecular competition between RNA-binding proteins. Together, these findings establish a framework linking RNA binding and biomolecular condensation, illustrating how their interplay governs condensate assembly.

biophysics↗

bioRxiv2025

The Heterogeneous Solution Ensemble of the DEAD-box Protein Dhh1 Reveals a Modular Architecture

DEAD-box proteins such as Dhh1 play essential roles in RNA metabolism and the formation of biomolecular condensates, with a modular architecture comprising folded domains and disordered regions. To elucidate how this architecture shapes conformational dynamics in solution, we combined solution scattering experiments and multi-scale simulations on core and full-length constructs. Enhanced-sampling simulations captured a dynamic ensemble of core conformations stabilized by transient interdomain contacts that underpin functional regulation. Coarse-grained modelling revealed that disordered tails behave as independent modules exerting minimal influence on core dynamics. This integrated approach reveals a modular organization balancing structural heterogeneity and functional specificity, providing a framework for studying DEAD-box proteins in phase separation.

biophysics↗

bioRxiv2022

Multi-eGO: an in-silico lens to look into protein aggregation kinetics at atomic resolution

Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 diseases associated that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the characterization of the structures of the transient oligomers formed in the process. Oligomers have been proven elusive to high-resolution structural techniques, while the large sizes and long-time scales typical of aggregation processes have limited, so far, the use of computational methods. To surmount these limitations, we introduce here multi-eGO, an atomistic, hybrid structure-based model, which leveraging on the knowledge of monomers conformational dynamics and of fibril structures, can efficiently capture the essential structural and kinetics aspects of protein aggregation. Multi-eGO molecular dynamics simulations can describe the aggregation kinetics of thousands of monomers. The concentration dependence of the simulated kinetics, as well as the structural features of the resulting fibrils, are in qualitative agreement with in vitro experiments on an amyloidogenic peptide of Transthyretin, a protein responsible for one of the most common cardiac amyloidosis. Multi-eGO simulations allow to observe in time and at atomic resolution the formation of primary nuclei in a sea of transient lower order oligomers, to follow their growth and the subsequent secondary nucleation events, till the maturation of multiple fibrils. Multi-eGO, combined with the many experimental techniques deployed to study protein aggregation, can provide the structural basis needed to advance the design of molecules targeting amyloidogenic diseases. Significance StatementAlzheimers and Parkinsons diseases are uncurable pathologies associated to the aberrant aggregation of specific proteins into amyloid fibrils. Understanding the mechanism leading to protein aggregation, by characterizing the structures of the oligomeric species populated in the process, would have a tremendous impact on the design of therapeutic molecules. We propose that a structure-based approach to molecular dynamics simulations can allow following at high resolution the aggregation kinetics of thousands of monomers. Having shown that simulations can describe the aggregation of a Transthyretin amyloidogenic peptide, we demonstrate how their efficiency allows acquiring a wealth of structural information. We foresee that integrating the latter with the many techniques developed to study protein aggregation will support the design of molecules to modulate amyloidogenesis.

biochemistry↗