Multiscale modelling of liquid-liquid and liquid-solid transitions in biomolecular condensates

The spontaneous self-assembly of proteins and nucleic acids through phase separation into membraneless organelles—known as biomolecular condensates—plays a central role in the functional compartmentalization of the cytoplasm and nucleoplasm [1,2]. However, some condensates undergo an additional phase transition from functional liquid-like states to pathological solid-like assemblies, a process known as condensate ageing [3,4]. Such liquid-to-solid transition is typically driven by the accumulation of cross-β-sheet structures and represents a hallmark of several neurodegenerative disorders [5]. In this talk, I will present the Mpipi-Recharged model [6], a residue-resolution coarse-grained force field that improves the treatment of charge effects in biomolecular condensates containing disordered proteins, multi-domain proteins, and disordered single-stranded RNAs. I will show how the asymmetric coarse-graining of electrostatic interactions enables a more accurate description of the phase behaviour of highly charged condensates, including charge blockiness, stoichiometry variations in complex coacervates, and salt-dependent modulation—without requiring explicit solvation. By combining this model with atomistic simulations, I will discuss how sequence mutations [7], small peptide insertions [8], and RNAs [9] affect the ageing kinetics of protein condensates. Our simulations revealed that introducing negatively charged mutations in the low-complexity domain of FUS—an RNA-binding protein linked to amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD)—delays the accumulation of inter-protein β-sheets while preserving the phase diagram and viscoelastic properties of the wild-type protein. Conversely, arginine mutations strongly accelerate disorder-to-order β-sheet transitions [7]. I will also show how specific peptide sequences, varying in composition, patterning, and net charge, can notably modulate the phase behaviour and ageing kinetics of phase-separating proteins such as TDP-43 and FUS [8], both related to ALS and FTD. By fine-tuning the balance of aromatic and charged residues within these peptides, we can either enhance or frustrate condensate hardening. Overall, our computational framework aims to provide a powerful approach to analyse how sequence mutations, small molecules, RNAs, or multi-component condensate composition [10] shape the intermolecular interactions governing the stability and time-dependent material properties of biomolecular condensates.

References
[1] Brangwynne et al., Science, vol. 324, no. 5935, pp. 1729–1732, 2009. [2] Boeynaems et al., Trends in Cell Biology, vol. 28, no. 6, pp. 420–435, 2018. [3] Patel et al., Cell, vol. 162, no. 5, pp. 1066–1077, 2015. [4] Molliex et al., Cell, vol. 163, no. 1, pp. 123–133, 2015. [5] Alberti and Hyman, Nature Reviews Molecular Cell Biology, vol. 22, no. 3, pp. 196–213, 2021. [6] Tejedor et al., ACS Central Science, vol. 11, pp. 302−321, 2025. [7] Pedraza et al., Cell Reports Physical Science, 6, 102803, 2025. [8] Sanchez-Burgos et al., Nat. Communs, 16, 8050 2025. [9] Tejedor et al., Nat. Communs., 13, 5717, 2022. [10] Espejo et al., bioRxiv, 10.1101/2025.02.21.639421, 2025

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