Crossover in aromatic amino acid interaction strength between tyrosine and phenylalanine in biomolecular condensates
- Polimero eta Material Aurreratuak: Fisika, Kimika eta Teknologia, Kimika Fakultatea, UPV/EHU & Donostia International Physics Center (DIPC), Spain
Figures
Figure 1
Bibliographic values for different properties of phenylalanine and tyrosine.
(A) Solvation free energy (Chang et al., 2007). (B) Probability distributions of min-maxed normalized hydropathy values from bibliographic hydrophobicity scales (Tesei et al., 2021). (C) Self-interaction energy from the Miyazawa-Jernigan contact matrix (Miyazawa and Jernigan, 1996). (D) Solubility in water at 25°C (Nozaki and Tanford, 1971).
Figure 2
Computational approach to estimate differences in phase separation propensity between tyrosine and phenylalanine.
(A) Thermodynamic cycle used in this study for the estimation of free energy differences upon mutation for the insertion of a peptide in a molecular condensate. (B) Schematic of the process of contact formation between two molecules and used in the quantum chemical calculations. We consider that contact formation involves the transfer from water (blue) to a different medium (orange) and the interaction in this medium between the entities involved.
Figure 3 with 5 supplements
Molecular simulations of the GG(F/Y)GG peptide in a GSY peptide slab.
(A) Representative simulation box with a fully solvated GSY condensate in slab geometry, including a GGXGG peptide (spheres) and the capped amino acid mixture (G: white, S: yellow, and Y: green). (B) Time series for the solvent accessible surface area in a representative trajectory of the GGXGG peptide within the GSY condensate for different values of . (C) Time evolution of the density profiles calculated across the longest dimension of the simulation box in the coexistence simulations. In blue, we show the density in mg/mL of all the peptides, and in dark red that of the F/Y residue in the GGXGG peptide.
Figure 3—figure supplement 1
Replicates of the GGXGG peptide simulations in the GSY condensate.
(A) Time series for the accessible surface area for different values of . (B) Density profiles of peptide (solid lines) and F/Y residue (right Y-axis) averaged over the simulation runs. (C) Time series for the density profiles of all peptides (blue) and the F2Y residue (red).
Figure 3—figure supplement 2
Work values for the forward and reverse alchemical transitions for different initial snapshots (bottom) and their distributions (top).
The BAR estimator is shown in the legend. Each panel corresponds to a different solvent. (A) TIP3P water. (B) Replicates of GSY condensates. (C) Replicates of GSF condensates.
Figure 3—figure supplement 3
Results for the GSY condensate in the TIP4P-Ew water model.
(A) Representative simulation box with a fully solvated GSY condensate in slab geometry including a GGXGG peptide (spheres) and the capped amino acid mixture (G: white, S: yellow, and Y: green). (B) Time series for the solvent accessible surface area for different values of . (C) Time evolution of the density profiles calculated across the longest dimension of the simulation box in the coexistence simulations.
Figure 3—figure supplement 4
Results for the GSY condensate in the TIP4P-Ew water model.
Work values and their distribution for forward and backward transitions within water (A) and the GSY condensate (B).
Figure 3—figure supplement 5
Replicates of the GGXGG peptide simulations in the GSF condensate.
(A) Time series for the accessible surface area for different values of . (B) Density profiles of peptide (solid lines) and F/Y residue (right Y-axis) averaged over the simulation runs. (C) Time series for the density profiles of all peptides (blue) and the F2Y residue (red).
Figure 4
Interaction patterns in dense phases of peptide condensates.
(A) Representative snapshots from the simulations of dense phases. G/S/F/Y dipeptides are shown as transparent surfaces (G: white, S: yellow, Y: green, F: purple). (B) Interaction matrix for the normalized number of contacts between different pairs of amino acid residues in the condensates (top) and for each type of amino acid (bottom). (C) Density plots for side chain interactions between aromatic side chains, as characterized by the mean inter-residue distance and the angle between the vectors normal to the rings (Calinsky and Levy, 2024). (D) Density plots for sp2- interactions between amide bonds and aromatic side chains, as characterized by the mean inter-group distance and the angle between the vectors normal to the peptide bond and ring planes. In all panels, results for GSY and GSF condensates are shown on the top and bottom, respectively. Representative snapshots of relevant interactions for each type of pair are shown.
Figure 5 with 2 supplements
Estimation of phase diagrams from atomistic simulations.
(A) Representative snapshots of replica exchange method (REMD) simulations of the GSY condensate at high (top) and low (bottom) temperatures. Color code as in Figure 3. (B) Same for the GSF condensate. (C) Phase diagrams for GSY (green) and GSF (purple). Empty circles correspond to simulations and filled circles correspond to fitted critical temperatures and densities .
Figure 5—figure supplement 1
Density profiles at different temperatures for the GSY (A) and GSF (B) condensates.
Figure 5—figure supplement 2
Density profiles for sticker residues across the simulation box from the replica exchange method (REMD) simulations at room temperature.
Figure 6 with 1 supplement
Comparison of peptide condensates with organic solvents.
(A) Radial distribution function for water oxygen around the in Phe/Tyr for GSF and GSY condensates.We show a representative overlay of simulation snapshots where water molecules are hydrogen-bonded to the Tyr side chain. (B) Transfer free energy differences from water to a different medium between Tyr and Phe. We consider condensates (green), polar solvents (orange) and apolar solvents (blue). (C) Same as a function of calculated dielectric constant, .
Figure 6—figure supplement 1
Work values for the forward and reverse alchemical transitions for different initial snapshots (left) and their distributions (right).
The BAR estimator is shown in the legend. Each panel corresponds to a different solvent: (A) Acetone. (B) Benzene. (C) Cyclohexane. (D) Ethanol. (E) Hexanol. (F) Methanol. (G) Octanol. (H) Toluene.
Figure 7
Contact energies from quantum chemical calculations.
(A) and (B) for different interaction pairs and different solvents as a function of the dielectric constant, . (C) Optimized geometries from quantum chemical calculations for Phe and Tyr interaction pairs. (D) with respect to the cross-F-F interaction for different solvents as a function of the dielectric. Different symbols correspond to the different solvent types. Filled: alcohols; empty: alkanes/benzenes; lines: water with different dielectric.
Additional files
-
MDAR checklist
- https://cdn.elifesciences.org/articles/104950/elife-104950-mdarchecklist1-v1.docx
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Supplementary file 1
Supporting Tables with additional details of the molecular simulations.
- https://cdn.elifesciences.org/articles/104950/elife-104950-supp1-v1.pdf
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Crossover in aromatic amino acid interaction strength between tyrosine and phenylalanine in biomolecular condensates
eLife 14:RP104950.
https://doi.org/10.7554/eLife.104950.3
