Biomolecular condensates, some of which are liquid-like during health, can age over time becoming gel-like pathological systems. One potential source of loss of liquid-like properties during ageing of RNA-binding protein condensates is the progressive formation of inter-protein β-sheets. To bridge microscopic understanding between accumulation of inter-protein β-sheets over time and the modulation of FUS and hnRNPA1 condensate viscoelasticity, we develop a multiscale simulation approach. Our method integrates atomistic simulations with sequence-dependent coarse-grained modelling of condensates that exhibit accumulation of inter-protein β-sheets over time. We reveal that inter-protein β-sheets notably increase condensate viscosity but does not transform the phase diagrams. Strikingly, the network of molecular connections within condensates is drastically altered, culminating in gelation when the network of strong β-sheets fully percolates. However, high concentrations of RNA decelerate the emergence of inter-protein β-sheets. Our study uncovers molecular and kinetic factors explaining how the accumulation of inter-protein β-sheets can trigger liquid-to-solid transitions in condensates, and suggests a potential mechanism to slow such transitions down.

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One of the key mechanisms employed by cells to control their spatiotemporal organization is the formation and dissolution of phase-separated condensates. Such balance between condensate assembly and disassembly can be critically regulated by the presence of RNA. In this work, we use a novel chemically accurate coarse-grained model for proteins and RNA to unravel the impact of poly-uridine RNA in modulating the protein mobility and stability within different biomolecular condensates. We explore the behavior of FUS, hnRNPA1 and TDP-43 proteins along their corresponding prion-like domains from absence to moderately high RNA concentration. By characterising the phase diagram, key molecular interactions, surface tension and viscoelastic properties, we report a dual RNA-induced behavior: On the one hand, poly-uridine enhances phase separation at low concentration, whilst at high concentration, it inhibits the ability of proteins to self-assemble. On the other hand, as a consequence of such stability modulation, the transport properties of proteins within the condensates are significantly enhanced at moderately high RNA concentration, as long as the length of poly-uridine strands is comparable or moderately shorter than those of the proteins. On the whole, our work elucidates the different routes by which RNA can regulate phase separation and condensate dynamics, as well as the subsequent aberrant rigidification implicated in the emergence of various neuropathologies and age-related diseases.

Biomolecular condensates, some of which are liquid-like during health, can age over time becoming gel-like pathological systems. Ageing of RNA-binding protein condensates can emerge from the progressive accumulation of inter-protein β-sheets. To bridge microscopic understanding of such time-dependent transformation with the modulation of FUS and hnRNPA1 condensate viscoelasticity, we develop a multiscale simulation approach. Our method integrates atomistic simulations with sequence-dependent coarse-grained modelling of condensates that age over time due to accumulation of inter-protein β-sheets. We reveal that ageing notably increases condensate viscosity but does not transform the phase diagrams. Strikingly, the network of molecular connections within condensates is drastically altered during ageing and culminates in gelation when the network of strong inter-protein β-sheets fully percolates. High concentrations of RNA decelerate the accumulation of inter-protein β-sheets, abrogating the effects of ageing. Our study uncovers molecular and kinetic factors explaining condensate ageing, and suggests a potential mechanism to slow ageing down.

Biomolecular condensates are important contributors to the internal organization of the cell material. While initially described as liquid-like droplets, the term biomolecular condensates is now used to describe a diversity of condensed phase assemblies with material properties extending from low to high viscous liquids, gels, and even glasses. Because the material properties of condensates are determined by the intrinsic behaviour of their molecules, characterising such properties is integral to rationalising the molecular mechanisms that dictate their functions and roles in health and disease. Here, we apply and compare three distinct computational methods to measure the viscoelasticity of biomolecular condensates in molecular simulations. These methods are the shear stress relaxation modulus integration (SSRMI), the oscillatory shear (OS) technique, and the bead tracking (BT) method. We find that, although all of these methods provide consistent results for the viscosity of the condensates, the SSRMI and OS techniques outperform the BT method in terms of computational efficiency and statistical uncertainty. We, thus, apply the SSRMI and OS techniques for a set of 12 different protein/RNA systems using a sequence-dependent high-resolution coarse-grained model. Our results reveal a strong correlation between condensate viscosity and density, as well as with protein/RNA length and the number of stickers vs. spacers in the amino-acid protein sequence. Moreover, we couple the SSRMI and the OS technique to nonequilibrium molecular dynamics simulations that mimic the progressive liquid-to-gel transition of protein condensates due to the accumulation of inter-protein β-sheets. We compare the behaviour of three different protein condensates -i.e., those formed by either hnRNPA1, FUS, or TDP-43 proteins- whose liquid-to-gel transitions are associated with the onset of amyotrophic lateral sclerosis and frontotemporal dementia. We find that both SSRMI and OS techniques successfully predict the transition from functional liquid-like behaviour to kinetically arrested states once the network of inter-protein β-sheets has percolated through the condensates. Overall, our work provides a comparison of different modelling rheological techniques to assess the viscosity of biomolecular condensates, a critical magnitude that provides information on the behaviour of biomolecules inside condensates.

Reptating linear polymers with drift give rise to enhanced transport properties.

Freezing of water is the most common liquid-to-crystal phase transition on Earth; however, despite its critical implications on climate change and cryopreservation among other disciplines, its characterization through experimental and computational techniques remains elusive. In this work, we make use of computer simulations to measure the nucleation rate ( J) of water at normal pressure under different supercooling conditions, ranging from 215 to 240 K. We employ two different water models: mW, a coarse-grained potential for water, and TIP4P/ICE, an atomistic nonpolarizable water model that provides one of the most accurate representations of the different ice phases. To evaluate J, we apply the Lattice Mold technique, a computational method based on the use of molds to induce the nucleus formation from the metastable liquid under conditions at which observing spontaneous nucleation would be unfeasible. With this method, we obtain estimates of the nucleation rate for ice Ih and Ic and a stacking mixture of ice Ih/Ic, reaching consensus with most of the previously reported rates, although differing with some others. Furthermore, we confirm that the predicted nucleation rates obtained by the TIP4P/ICE model are in better agreement with experimental data than those obtained through the mW potential. Taken together, our study provides a reliable methodology to measure nucleation rates in a simple and computationally efficient manner that contributes to benchmarking the freezing behavior of two popular water models.

Maturation of functional liquid-like biomolecular condensates into solid-like aggregates has been linked to the onset of several neurodegenerative disorders. Low-complexity aromatic-rich kinked segments (LARKS) contained in numerous RNA-binding proteins can promote the aggregation process by forming inter-protein beta-sheet fibrils that accumulate over time - ultimately driving the liquid-to-solid transition of the condensate. Here, we combine atomistic molecular dynamics simulations with sequence-dependent coarse-grained models of various resolutions to investigate the role of LARKS abundance and position within the amino acid sequence in the maturation of biomolecular condensates. We find that the location of the LARKS motifs along the protein sequence crucially modulates the rate of cross-beta sheet transitions and the associated loss of liquid-like behaviour over time. Our simulations show that shifting the location of the LARKS in fused in sarcoma (FUS) protein towards its center slows down condensate aggregation. More strikingly, our simulations further predict that adding RNA to FUS with re-located LARKS fully inhibits the accumulation of beta-sheet fibrils, maintaining functional liquid-like behaviour without ageing.