ArticleThe journal of physical chemistry. B2023
Time-Dependent Material Properties of Aging Biomolecular Condensates from Different Viscoelasticity Measurements in Molecular Dynamics Simulations.
Article in The journal of physical chemistry. B, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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41 citing papers in PubMed, 70 citations in OpenAlex.
- Article
- Progress toward linking single-molecule behavior and condensate material properties.Current opinion in structural biology · 2026Review
- CondenSimAdapter: A Versatile Builder for Multiscale Simulations of Protein Condensates with Broad Force-Field Compatibility and Robust Dense-Phase Relaxation.Journal of chemical information and modeling · 2026Article
- In Search of Shape in the Unshaped: Constructing Ensembles of Intrinsically Disordered Proteins.Biophysics reviews · 2026Article
- Biomolecular condensates provide a unique environment for redox-mediated protein crosslinking.bioRxiv : the preprint server for biology · 2026Article
- Backbone rigidity encodes universal viscoelastic signatures in biomolecular condensates.Biophysical journal · 2026Article
- The Electromechanical Connectome: Integrating Voltage, Mechanical Nano-Forces, and Subcellular Fluid Phase Dynamics in Human Neural Computation.International journal of molecular sciences · 2026Review
- From biomolecular condensates to functional nanomaterials: LLPS-inspired frameworks for nanoscale hydrogels and adaptive materials.Journal of nanobiotechnology · 2026Review
- Molecular origins of viscoelasticity in biomolecular condensates.The Journal of chemical physics · 2026Article
- Sticky interactions govern sequence-dependent dynamics in biomolecular condensates.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Multiscale structure of chromatin condensates explains phase separation and material properties.Science (New York, N.Y.) · 2025Article
- In-Depth Study of Low-Complexity Domains: From Structural Diversity to Disease Mechanisms.Cells · 2025Review
- Molecular insights on the mechanism of α1-antitrypsin condensate formation and maturation.PLoS computational biology · 2025Article
- How the Extent of Protein Folding and Oligomerization Modulate Condensate Formation and Properties.The journal of physical chemistry letters · 2025Article
- Biomolecular condensate viscoelasticity is dictated by the interplay between single-molecule shape memory and mesh reconfigurability.bioRxiv : the preprint server for biology · 2025Article
- Charged peptides enriched in aromatic residues decelerate condensate ageing driven by cross-β-sheet formation.Nature communications · 2025Article
- Current practices in the study of biomolecular condensates: a community comment.Nature communications · 2025Article
- Article
- Material properties of biomolecular condensates emerge from nanoscale dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Emergent mechanics of a networked multivalent protein condensate.Nature communications · 2025Article
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4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 behavior of their molecules, characterizing such properties is integral to rationalizing 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 Green-Kubo (GK) relation, 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 GK and OS techniques outperform the BT method in terms of computational efficiency and statistical uncertainty. We thus apply the GK and OS techniques for a set of 12 different protein/RNA systems using a sequence-dependent 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 GK 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 interprotein β-sheets. We compare the behavior 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 the GK and OS techniques successfully predict the transition from functional liquid-like behavior to kinetically arrested states once the network of interprotein β-sheets has percolated through the condensates. Overall, our work provides a comparison of different modeling rheological techniques to assess the viscosity of biomolecular condensates, a critical magnitude that provides information on the behavior of biomolecules inside condensates.
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