Atomistic simulations reveal sub- µ s contact dynamics in MUT-16 condensates
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eLife Assessment
This study presents valuable findings on phase-separated condensate formation by the MUT-16 protein, which plays a key role in small RNA biogenesis. A detailed analysis of the interactions governing condensate formation was carried out using coarse-grained and all-atom molecular dynamics simulations, complemented by in vitro phase separation experiments. While many of the results appear solid, a number of technical details are lacking, the computational part appears incomplete and would benefit from additional analyses and clarifications, and the novelty of the study should also be clarified, particularly in comparison with the authors' previous work on MUT-16. Overall, the work will be of interest to biophysicists and molecular biologists studying phase separation and biomolecular condensates.
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Abstract
Phase separation of proteins gives rise to biomolecular condensates, which function as membraneless organelles that spatially and temporally organize cellular functions. Such condensates are often formed by intrinsically disordered regions of proteins (IDRs), whose multivalent and transient interactions govern condensate structure and dynamics. However, elucidating the molecular determinants of these interactions at atomistic resolution remains challenging. Here, we present a total of 10 µ s of atomistic molecular dynamics simulations of a phase-separated condensate formed by the foci-forming region (FFR) of MUT-16. MUT-16 serves as a scaffold of the Mutator foci germ granules in Caenorhabditis elegans and is essential for transposon silencing. MUT-16 FFR is enriched in polar uncharged (Gln, Asn), charged, aromatic, and Pro residues, raising the question of how these amino acids interact within condensates. We find that most contacts are short lived, typically breaking within a few nanoseconds (ns), with a median life time of 9.8 ns. A smaller fraction persist for much longer timescales ( > 100 ns). We characterized the relative contributions of different amino acids and specific interaction types, including hydrogen bonding, cation– π interactions, π – π stacking, and salt bridges and theirs dynamics. We further examined the roles of water and ions in modulating condensate interactions, including ion-mediated bridging between similarly charged residues. Our results reveal that salt bridges, cation- π interactions, Na + ions, and water in the condensate are key determinants of contact dynamics in MUT-16 FFR condensates. In parallel, we show that these condensates exhibit upper-critical solution temperature (UCST) phase behavior in vitro , providing a coherent framework to explain both the loss of Mutator foci at elevated temperatures in vivo and the scaffolding role of MUT-16 at lower temperatures.
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eLife Assessment
This study presents valuable findings on phase-separated condensate formation by the MUT-16 protein, which plays a key role in small RNA biogenesis. A detailed analysis of the interactions governing condensate formation was carried out using coarse-grained and all-atom molecular dynamics simulations, complemented by in vitro phase separation experiments. While many of the results appear solid, a number of technical details are lacking, the computational part appears incomplete and would benefit from additional analyses and clarifications, and the novelty of the study should also be clarified, particularly in comparison with the authors' previous work on MUT-16. Overall, the work will be of interest to biophysicists and molecular biologists studying phase separation and biomolecular condensates.
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Reviewer #1 (Public review):
In this work, Gaurav et al. present an extensive study of phase-separated condensates formed by the foci-forming region (FFR) of the MUT-16 protein. The authors first report in vitro experiments showing that these condensates exhibit upper critical solution temperature (UCST) behavior. They then provide a detailed analysis based on atomistic simulations of MUT-16 FFR condensates, identifying key interactions responsible for LLPS, including salt bridges, cation-π interactions, and the role of Na⁺ ions.
Overall, the manuscript is well written. However, there are several concerns that should be addressed.
Major Concerns:
(1) I have several questions regarding the system preparation that require clarification. The authors state that "65 copies of the coarse-grained MUT-16 FFR were embedded in a slab-shaped …
Reviewer #1 (Public review):
In this work, Gaurav et al. present an extensive study of phase-separated condensates formed by the foci-forming region (FFR) of the MUT-16 protein. The authors first report in vitro experiments showing that these condensates exhibit upper critical solution temperature (UCST) behavior. They then provide a detailed analysis based on atomistic simulations of MUT-16 FFR condensates, identifying key interactions responsible for LLPS, including salt bridges, cation-π interactions, and the role of Na⁺ ions.
Overall, the manuscript is well written. However, there are several concerns that should be addressed.
Major Concerns:
(1) I have several questions regarding the system preparation that require clarification. The authors state that "65 copies of the coarse-grained MUT-16 FFR were embedded in a slab-shaped simulation," but it is not clear how this initial configuration was generated. Were the molecules randomly distributed in the simulation box, or were they initially arranged in a preformed condensate? Alternatively, were they randomly inserted and allowed to self-assemble into a condensate during NpT simulations?
In Figure 1, the atomistic snapshot appears to show a well-defined condensate at the center of the simulation box. It would be important to clarify how this configuration was obtained: Was it generated from coarse-grained simulations starting from random initial conditions? Or was a preassembled condensate used as input?
Related to this, how do the authors ensure that the simulations are equilibrated? While 20 μs appears to be a reasonably long simulation time for coarse-grained simulations, it would be useful to demonstrate equilibration explicitly. For example, the authors could plot the center-of-mass positions (in the long axis of the simulation box) of individual proteins over time to show that all molecules reach a steady state and remain within the condensate without systematic drift.
(2) The authors experimentally observe UCST behavior for these condensates. Do the coarse-grained or atomistic simulations reproduce this behavior?
While atomistic simulations may be too computationally demanding to systematically explore temperature dependence, coarse-grained simulations could be used to test whether condensates are stable at lower temperatures and dissolve at higher temperatures. Such an analysis would provide valuable support for the experimental observations.
(3) Regarding the analysis of ions, several points could be clarified and extended:
a) It would be helpful to report the total number of ions and quantify how many are located inside vs. outside the condensate. While qualitative trends can be inferred from density profiles, quantitative analysis would strengthen the conclusions.
b) It would also be interesting to analyze the number of contact ion pairs (e.g., Na⁺-Cl⁻ pairs), as described in J. Chem. Phys. 156, 044505 (2022). It is known that some ion models tend to overestimate ion pairing and underestimate solubility (e.g., J. Chem. Phys. 153, 010903 (2020)).
c) In this context, the use of scaled-charge models has been shown to improve the description of ionic solutions and biomolecular systems (e.g., J. Phys. Chem. Lett. 2019, 10, 23, 7531-7536). I would suggest that, at least for one trajectory, the authors perform a test simulation using scaled charges (e.g., scaling by ~0.8) to evaluate whether ion distributions and protein-ion interactions are significantly affected.
d) Finally, while the selected water model is known to be accurate, it would be useful to assess its performance for concentrated salt solutions. For example, the authors could estimate the density of a 6 m salt solution and compare it with experimental data or validated models (e.g., J. Chem. Phys. 151, 134504 (2019)). This would help clarify to what extent the conclusions depend on the chosen force field.
Minor Concerns
(1) In the Introduction, it would be helpful to elaborate further on the possible driving forces of LLPS in this region. Are there prior hypotheses or evidence pointing to specific interactions (e.g., cation-π, π-π, electrostatic interactions)? While this work addresses these questions, a brief discussion of previous experimental or theoretical insights would provide useful context.
(2) On page 18, the authors state:
"MUT-16 FFR satisfies the length (172 residues), aromatic content (20.35%), and Arg enrichment (85.71%) criteria. Its charge content (10.47%) and charge balance (38.89% positive charge fraction) are slightly below the nominal thresholds."
It would be very helpful to include a schematic representation of the protein sequence highlighting these features (aromatic residues, charge distribution, etc.) in the corresponding figure, to provide a more intuitive understanding.(3) A question regarding ion hydration: What is the coordination environment of the ions that bridge proteins? Are they still hydrated by water molecules, or does the reduced water content inside the condensate significantly affect their solvation?
Typically, Na⁺ and Cl⁻ ions have coordination numbers around 5-6 in aqueous solution. Do protein interactions and reduced solvent conditions within the condensate alter this coordination? A brief analysis or discussion would be valuable. -
Reviewer #2 (Public review):
Summary:
Gaurav et al. investigate residue-level interactions within the MUT-16 FFR condensate using all-atom molecular dynamics simulations. The authors first argue, based on sequence analysis, that MUT-16 FFR is more representative than the widely studied FUS LCD. They then characterize the UCST phase behavior of MUT-16 FFR experimentally, followed by a detailed analysis of residue-level contact frequencies and lifetimes. In addition, the manuscript examines ion-residue interactions and water-mediated interactions. Overall, this work provides a comprehensive view of the dynamic interactions within the MUT-16 FFR condensate.
Strengths:
Large-scale all-atom molecular dynamics simulations have been performed to investigate dynamical interactions within condensates. The analysis is comprehensive and rigorous, …
Reviewer #2 (Public review):
Summary:
Gaurav et al. investigate residue-level interactions within the MUT-16 FFR condensate using all-atom molecular dynamics simulations. The authors first argue, based on sequence analysis, that MUT-16 FFR is more representative than the widely studied FUS LCD. They then characterize the UCST phase behavior of MUT-16 FFR experimentally, followed by a detailed analysis of residue-level contact frequencies and lifetimes. In addition, the manuscript examines ion-residue interactions and water-mediated interactions. Overall, this work provides a comprehensive view of the dynamic interactions within the MUT-16 FFR condensate.
Strengths:
Large-scale all-atom molecular dynamics simulations have been performed to investigate dynamical interactions within condensates. The analysis is comprehensive and rigorous, and the claims are strongly justified by the data.
Weaknesses:
The large amount of detail in the results section sometimes makes it difficult to identify the central take-home messages. I encourage the authors to more clearly highlight the principal findings and the physical insights that may generalize to other condensate-forming systems. The authors may also consider streamlining parts of the Results section to improve focus and readability.
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Reviewer #3 (Public review):
Summary:
The authors aim to characterize the molecular interaction network inside phase-separated condensates formed by the MUT-16 foci-forming region (FFR), using atomistic simulations combined with residue-resolved analyses of contact frequencies, contact lifetimes, specific non-covalent interactions, ions, and water.
Strengths:
The work addresses an interesting and biologically relevant system, and the combination of large-scale atomistic simulations with an extensive contact analysis has clear potential value for the broader condensate field.
Weaknesses:
In its current form, several technical issues need to be addressed before the main conclusions can be considered robust. Most importantly, the simulated sequence is 172 residues long, while the atomistic slab has box dimensions of only 12 nm in two …
Reviewer #3 (Public review):
Summary:
The authors aim to characterize the molecular interaction network inside phase-separated condensates formed by the MUT-16 foci-forming region (FFR), using atomistic simulations combined with residue-resolved analyses of contact frequencies, contact lifetimes, specific non-covalent interactions, ions, and water.
Strengths:
The work addresses an interesting and biologically relevant system, and the combination of large-scale atomistic simulations with an extensive contact analysis has clear potential value for the broader condensate field.
Weaknesses:
In its current form, several technical issues need to be addressed before the main conclusions can be considered robust. Most importantly, the simulated sequence is 172 residues long, while the atomistic slab has box dimensions of only 12 nm in two directions. This length scale is comparable to the expected end-to-end distances of a disordered 172-residue chain. It is therefore not clear whether individual protein chains interact with their own periodic images, which could substantially affect overall chain dynamics and subsequently bias contact lifetimes, residue-residue interaction statistics, and the inferred condensate dynamics. The authors should check, for each chain, histograms of end-to-end distances. For chains for which more than ~2-3% of the end-to-end distances exceed ~11 nm, the authors should explicitly check for self-image interactions (for example, using "gmx mindist -pi") and report whether such interactions occur and for what fraction of the trajectory. Without this control, at least in the Supporting Information, I do not think the simulation-derived contact dynamics are sufficiently trustworthy.
A second major concern is the treatment of ions. The manuscript makes important conclusions about Na⁺ association and Na⁺-mediated bridging, but the atomistic ion model is not explicitly stated. This is a reproducibility problem and also affects interpretation - for example, standard Amber ions are known to bind too strongly to the oppositely charged residues. In their results, one acidic residue appears to interact on average with roughly two Na⁺ ions, which is not obviously expected from charge balance alone. The authors should state the exact Na⁺/Cl⁻ parameters used, justify their compatibility with TIP4P-D and the protein force field, and explicitly interpret why such a strong Na⁺ association with acidic residues is observed.
More generally, because the manuscript is centered on contact lifetimes, the choice of the atomistic force field needs stronger justification. Salt bridges, cation-pi contacts, pi-pi stacking, ion coordination, and water-mediated interactions are all force-field-sensitive. Since there is no direct experimental observable used here to validate the simulations, the authors should discuss the expected limitations of the chosen force field (while I do acknowledge that testing different force fields would be computationally too demanding).
I also find the sequence-comparison section somewhat confusing. The authors compare one specific IDR, MUT-16 FFR, with the average properties of human IDRs and then frame it as more representative than FUS LCD. It is not clear how informative this is because IDR behavior depends strongly on sequence-specific patterning, molecular connectivity, and the particular interaction network of each protein. Averages over human IDRs may provide a broad context, but they do not necessarily define what is physically or biologically representative for phase separation. In addition, FUS LCD is not intended to be a representative human IDR; it is an unusually low-complexity, phase-separating domain. Therefore, the "more representative than FUS" framing should be toned down. At most, this analysis shows that MUT-16 FFR is compositionally less extreme than FUS LCD.
The ion- and water-bridging analyses are also potentially overinterpreted. A distance-based simultaneous contact with two residues does not by itself establish functional mediation or regulation of condensate dynamics. The authors should either add appropriate controls, such as local-density-normalized baselines or randomized-contact expectations, or soften the language to describe these as geometrically defined co-contact events rather than mechanistic bridging interactions.
Finally, the independence of the atomistic replicas is unclear. The manuscript should state whether all ten all-atom simulations were initiated from the same coarse-grained condensate configuration or from distinct CG frames. If the starting structures came from one CG trajectory, the authors should report how far apart those frames were in simulation time and provide evidence that the initial atomistic configurations are structurally independent. If only velocities differ, the simulations should not be described as fully independent structural replicas.
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