Figures and data in Role of desolvation on biomolecular liquid–liquid phase separation

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Tables
Additional files

5 figures, 3 tables and 1 additional file

Figures

Figure 1 with 1 supplement

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Desolvation-related PMF features of intermolecular interactions.

(A) Potential of mean force along the intermolecular distances for the amino acid analogues from all-atom MD simulations with different solvent polarities. (B) Schematic diagram of desolvation effects. (C) Pairwise effective potential incorporating desolvation-inspired terms. Different curves correspond to different desolvation parameters.

Figure 1—figure supplement 1

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Desolvation-related PMF features and fitted parameters from all-atom analogue simulations.

(**A–D**) PMFs obtained from all-atom simulations of representative amino-acid analogue pairs, together with fits using the desolvation-aware effective potential in Equation 1. (E) Overlay of fitted PMF profiles for different analogue pairs, illustrating the shared double-minimum/barrier structure and the pair-dependent variation in desolvation features. (F) Desolvation coefficients $α_{b}$ and $α_{s s}$ obtained by expressing the fitted barrier height and solvent-separated minimum depth relative to the global reference energy scale $ϵ$ used in the effective potential.

Figure 2 with 1 supplement

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Thermodynamic regulation and microscopic mechanisms of desolvation-mediated phase separation.

(A) Baseline phase diagram of the poly-50 system using the standard HPS model. (B) Representative simulation snapshots visualizing the transition from a stable condensate ( $T^{*} = 2.58$ ) to a near-critical state ( $T^{*} = 2.98$ ) and a homogeneous solution ( $T^{*} = 3.18$ ). (C) Time-averaged density profiles along the $z$ -axis identifying the coexisting dense and dilute phases. (**D, E**) Macroscopic phase boundaries under varying desolvation barrier heights $ϵ_{b}$ (D) and solvent-separated potential depths $ϵ_{s s}$ (E). Insets show the monotonic dependence of $T_{c}$ on the respective parameters. The lower panels schematically illustrate how changes in $ϵ_{b}$ and $ϵ_{s s}$ alter the distribution of residue-pair configurations. The small circles indicate schematic populations of residue-pair configurations along the potential profile, with denser circles representing a higher population. (**F, G**) Renormalized phase behavior plotted against normalized temperature $T^{*} / T_{c}$ for varying $ϵ_{b}$ (F) and varying $ϵ_{s s}$ (G).

Figure 2—figure supplement 1

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Microscopic residue-pair distributions and integrated effective attraction under varying desolvation parameters.

(**A, B**) Schematic illustration of the effective pair potential corresponding to different values of $ϵ_{b}$ or $ϵ_{s s}$ . (**C, D**) Radial distribution functions of all residue pairs under varying $ϵ_{b}$ (C) or $ϵ_{s s}$ (D) at the same reduced temperature, $T^{*} = 1.49$ . (**E, F**) Radial distribution functions of all residue pairs in the dense phase at the same normalized temperature ( $T^{*} = 0.8 T_{c}^{*}$ ). (**G, H**) Bead-level second virial coefficient ( $B_{2} / σ^{3}$ ) calculated from the effective pair potential under varying $ϵ_{b}$ at fixed $ϵ_{s s} = 0.02 k c a l / m o l$ (G) and varying $ϵ_{s s}$ at fixed $ϵ_{b} = 0.12 k c a l / m o l$ (H).

Figure 3

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Effect of desolvation on protein conformations.

(A) Schematic illustration of the conformational distributions of the protein in the high- and low-density phases under different desolvation parameters. (B, C) Distribution of $R_{g}$ with different $ϵ_{b}$ (B) and $ϵ_{s s}$ (C) at $T_{s i m}^{*} = 1.59$ . The solid and dashed lines represent the results for the condensed and dilute phases, respectively. The inset illustrates the mean value of $R_{g}$ as a function of desolvation parameters. (D) Correlation between temperature difference ( $T_{c}^{*} - T_{s i m}^{*}$ ) and the averaged $R_{g}$ difference between two phases. The purple and yellow dashed lines represent linear fits to the data obtained at low- ( $T_{s i m}^{*} < 1.2$ ) and high-simulation-temperature ( $T_{s i m}^{*} > 2.4$ ) regimes, respectively. The inset displays the improved linearity obtained when the temperature difference is rescaled by the simulation temperature, $(T_{c}^{*} - T_{s i m}^{*}) / T_{s i m}^{*}$ . (E) Correlation between the density difference and $R_{g}$ difference in the two phases with varying temperatures and desolvation parameters. The plot is shown on a log–log scale.

Figure 4

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Desolvation-mediated modulation of diffusion and coarsening dynamics.

(A) Snapshots of phase-separation dynamics after a temperature quench and the subsequent FRAP-like analysis of chain self-diffusion in an equilibrated slab. Upper snapshots show the simulation box along the $z$ -axis at $t_{s i m}$ = 0, 10, and 500 ns. The vertical schematic summarizes the dynamical progression described in the main text, from the post-quench spinodal instability to kinetic arrest, domain coarsening, and dynamic equilibrium. Lower panels show enlarged slab views for tracking chains initially located near the slab center, with the TAMSD plot quantifying their mobility. (B) Density profiles along the $z$ -axis for the entire system (orange) and for the highlighted chains (red) at different time lags, with and without desolvation. Shaded histograms show instantaneous snapshots, and solid curves represent normalized time averages over $1 μ s$ . (C) Diffusion coefficients as a function of the desolvation strength ( $ϵ_{b}$ , $ϵ_{s s}$ ) and dense-phase density ( $ρ_{d e n s e}$ ) at different temperatures. (D) Reduced diffusion coefficient $\tilde{K}$ versus quench depth for varying $ϵ_{b}$ . The schematic insets summarize the reduced chain mobility observed for higher desolvation barriers at comparable quench depths. (E) Schematic illustration of the three-stage phase-separation mechanism, including early density-fluctuation growth, a transiently arrested plateau, and late-stage coarsening. In the zoom-in view, yellow beads denote residues involved in transient inter-chain contacts, and black springs denote schematic network connections formed by these contacts. (**F, G**) Kinetics of density fluctuations and domain growth under varying $ϵ_{b}$ (F) and $ϵ_{s s}$ (G). Top panels show the time evolution of the normalized density variance $⟨ {\hat{σ}}_{ρ}^{2} ⟩$ , with the inset showing the characteristic time $τ_{1 / 2}$ . Bottom panels show the growth of the average slab size $⟨ ξ ⟩$ on a logarithmic scale. The colored timeline highlights the initial fluctuation, plateau, and late-stage coarsening regimes.

Figure 5 with 4 supplements

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Parameterization of desolvation terms for the HPS and CALVADOS2 models based on IDPs.

(A) Schematic workflow of the desolvation parameterization. (B) Correlation between experimental $R_{g}$ and simulation $R_{g}$ for the original HPS model (blue) and the revised HPS model with default desolvation scales ( $α_{b} = 0.33$ and $α_{s s} = 0.06$ ) (purple). The $⟨ χ_{R_{g}}^{2} ⟩$ for different models are also shown. (C) Correlation between experimental $R_{g}$ and simulation $R_{g}$ for the original CALVADOS2 model (orange), the revised CALVADOS2 model with default desolvation (yellow), and the revised CALVADOS2 model with optimized desolvation ( $α_{b} = 0.3$ , $α_{s s} = 0.03$ and $ϵ = 0.262 k c a l / m o l$ , red). (D) Coexistence curves of FUS LC simulated with the original HPS model (blue), the revised HPS model with default desolvation scales (purple), the energy-rescaled HPS model (green), the default CALVADOS2 model (orange), and the revised CALVADOS2 model with optimized desolvation scales (red). The green shaded regions highlight the deviations of the desolvation models relative to the original frameworks.

Figure 5—figure supplement 1

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Optimization of the CALVADOS2+desolvation energy scale using experimental $R_{g}$ data.

(**A, C, E, G**) Correlations between experimental and simulated $R_{g}$ values for the IDP dataset under selected desolvation-parameter combinations. Each panel corresponds to simulations performed at fixed $α_{b}$ and $α_{s s}$ with different values of the overall energy scale $ϵ$ . (**B, D, F, H**) Corresponding $⟨ χ_{R_{g}}^{2} ⟩$ values as a function of $ϵ$ , used to identify the optimal energy scale for each desolvation-parameter set. The optimized $ϵ$ values are indicated in each panel.

Figure 5—figure supplement 2

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Global scan of CALVADOS2+desolvation parameter combinations against experimental $R_{g}$ values.

(**A–D**) Comparison between experimental and simulated $R_{g}$ values for different combinations of $α_{b}$ and $α_{s s}$ , with the overall energy scale ( $ϵ$ ) optimized separately for each parameter set. The corresponding optimized ( $ϵ$ ) values are shown to illustrate how the energy rescaling compensates for different desolvation strengths while preserving agreement with single-chain dimensions.

Figure 5—figure supplement 3

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Single-chain $R_{g}$ comparison of FUS LC under different coarse-grained model variants.

Single-chain radius of gyration of FUS LC simulated using the original HPS model, HPS +desolvation, energy-rescaled HPS, original CALVADOS2, and CALVADOS2+desolvation models. The energy-rescaled HPS model was included to separate the effect of global interaction-strength rescaling from the effect of adding desolvation terms.

Figure 5—figure supplement 4

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Phase behavior of the LAF-1 RGG domain simulated with CALVADOS2 and CALVADOS2+desolvation.

Coexistence curves of the LAF-1 RGG domain simulated using the original CALVADOS2 model and the desolvation-aware CALVADOS2 model. Symbols show the coexisting dilute- and dense-phase densities obtained from slab simulations at different simulation temperatures, and dashed curves represent binodal fits using the same critical-scaling procedure as in the main text.

Tables

Table 1

Global desolvation coefficients $α_{b}$ and $α_{s s}$ used in the HPS and CALVADOS2 frameworks.

The HPS baseline coefficients were obtained by averaging values fitted to the all-atom analogue PMFs, whereas the CALVADOS2 coefficients and global energy scale $ϵ$ were selected through optimization against experimental $R_{g}$ data.

Parameters	HPS model	CALVADOS2 model
$α_{b}$	0.33	0.30
$α_{s s}$	0.06	0.03
$ϵ$ (kcal/mol)	0.20	0.262

Table 2

Summary of the production run parameters for all-atom molecular dynamics simulations.

Parameter	Value/method	Description
Software	GROMACS	Version 2021.3
Force field	OPLS-AA	-
Simulation time	100 ns	5 × 10⁷ steps
Integration step (Δt)	2 fs	-
Integrator	Leap-frog	Standard MD algorithm
Temperature coupling
Temperature (T)	298 K	Reference temperature
Thermostat	Nosé–Hoover	$τ_{T} = 2.0 p s$
Pressure coupling
Pressure (P)	1.0 atm	Reference pressure
Barostat	Parrinello–Rahman	$τ_{P} = 4.0 p s$
Compressibility (κ)	4.46 × 10^-5 bar^-1	-
Non-bonded interactions
Electrostatics	PME	Particle Mesh Ewald
Coulomb cut-off ( $r_{e l e c}$ )	1.0 nm	-
vdW cut-off ( $r_{v d w}$ )	1.0 nm	-
Dispersion correction	EnerPres	For energy and pressure
Constraints
Algorithm	LINCS	Linear Constraint Solver
Constraints	h-bonds	Bonds involving H atoms

Table 3

Summary of the coarse-grained molecular dynamics simulation parameters used in the slab simulations.

Parameter	Value/method	Description
General settings
Software	HOOMD-blue	v2.9.7 with azplugins
Software	OpenMM	v8.2.0
Integrator	Langevin	Stochastic dynamics
Time step (Δt)	0.01 ps	-
Total production time	$1 μ s$	10⁸ steps
Temperature (T)	Variable	See main text
Langevin damping rate ( $γ_{i} / m_{i}$ )	$0.01 p s^{- 1}$	Mass-dependent
System geometry
Box dimensions (x, y)	15.0 nm	Periodic boundaries
Box dimension (z)	280.0 nm	Slab configuration
Interactions
Bond potential	Harmonic	$k = 8368 k J \cdot {m o l}^{- 1} \cdot n m^{- 2}$ , $r_{0} = 0.38 n m$
Non-bonded potential	Ashbaugh–Hatch	HPS model (via azplugins)
Non-bonded cut-off	2.4 nm	-
Electrostatics	Yukawa	Screened Coulomb potential
Screening constant (κ)	$1.0 n m^{- 1}$	Inverse Debye length
Coulomb cut-off	3.5 nm	-
Neighbor List	Cell List	Exclusions: 1–2, body

Additional files

MDAR checklist: https://cdn.elifesciences.org/articles/111124/elife-111124-mdarchecklist1-v1.pdf
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Kai Zhang
Zhiyu Peng
Wenfei Li
Wei Wang

(2026)

Role of desolvation on biomolecular liquid–liquid phase separation

eLife 15:RP111124.

https://doi.org/10.7554/eLife.111124.3

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Desolvation-related PMF features of intermolecular interactions.

Desolvation-related PMF features and fitted parameters from all-atom analogue simulations.

Thermodynamic regulation and microscopic mechanisms of desolvation-mediated phase separation.

Microscopic residue-pair distributions and integrated effective attraction under varying desolvation parameters.

Effect of desolvation on protein conformations.

Desolvation-mediated modulation of diffusion and coarsening dynamics.

Parameterization of desolvation terms for the HPS and CALVADOS2 models based on IDPs.

Optimization of the CALVADOS2+desolvation energy scale using experimental Rg data.

Global scan of CALVADOS2+desolvation parameter combinations against experimental Rg values.

Single-chain Rg comparison of FUS LC under different coarse-grained model variants.

Phase behavior of the LAF-1 RGG domain simulated with CALVADOS2 and CALVADOS2+desolvation.

Global desolvation coefficients αb and αss used in the HPS and CALVADOS2 frameworks.

Summary of the production run parameters for all-atom molecular dynamics simulations.

Summary of the coarse-grained molecular dynamics simulation parameters used in the slab simulations.

MDAR checklist

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

Optimization of the CALVADOS2+desolvation energy scale using experimental $R_{g}$ data.

Global scan of CALVADOS2+desolvation parameter combinations against experimental $R_{g}$ values.

Single-chain $R_{g}$ comparison of FUS LC under different coarse-grained model variants.

Global desolvation coefficients $α_{b}$ and $α_{s s}$ used in the HPS and CALVADOS2 frameworks.