Capturing chemical reactions inside biomolecular condensates with reactive Martini simulations

Biomolecular condensates are phase separated systems that play an important role in the spatio-temporal organisation of cells. Their distinct physico-chemical nature offers a unique environment for chemical reactions to occur. The compartmentalisation of chemical reactions is also believed to be central to the development of early life. To demonstrate how molecular dynamics may be used to capture chemical reactions in condensates, here we perform reactive molecular dynamics simulations using the coarse-grained Martini forcefield. We focus on the formation of rings of benzene-1,3-dithiol inside a synthetic peptide-based condensate, and find that the ring size distribution shifts to larger macrocycles compared to when the reaction takes place in an aqueous environment. Moreover, reaction rates are noticeably increased when the peptides simultaneously undergo phase separation, hinting that condensates may act as chaperones in recruiting molecules to reaction hubs.

below, and the fitting statistics for single and double exponential models in table S2.
Table S1.Diffusion coefficients for the water and peptide components of the LFssFL/water system at neutral and high pH, as measured from the fits to the incoherent scattering functions in the Figure S1.S5.Reaction rates for each system, denoted by the region of the system the reaction is taking place in.Note for co-formation simulations, the dense and dilute regions are not well defined, and it is not possible to distinguish where a reaction specifically occurs.

Figure S1 :
Figure S1: Incoherent scattering function data, and fitted curves in the LFssFL peptide systems for water (left) and peptide (right) components.The top row shows the systems at neutral pH, and the bottom row at high pH, with N termini deprotonated.The fitted results are summarised in tableS1below, and the fitting statistics for single and double exponential models in tableS2.

Figure S2 .
Figure S2.Comparing systems with increased peptide-water interactions.Data for native systems are taken from the main text and replotted here for clarity of comparison.a) PMF of a benzene-1,3-diol molecule moving from the dense to dilute region of a condensate at high pH, comparing the native Martini model of LFssFL (blue) with a model with slightly stronger peptidewater interactions (purple).b) density profiles of the condensates of the two models showing the protein (dashed lines) and water (solid lines) components of the two systems.The weight proportion of water inside the condensate has been increased from around 17% to around 22%. c,d) ring size changes between the two condensate systems with native and stronger peptidewater interactions.

Figure S3 .
Figure S3.Potential of mean force of a molecule of XGLKFK across the interface of a LFssFL condensate.

Figure S4 :
Figure S4: initial and final configurations of simulations as described in the main text.Water removed for clarity.Peptides shown as transparent surfaces, and the reactive molecules shown in yellow and black.All scale bars are 100 A.

Figure S5 :
Figure S5: Reactions of benzene-1,3-dithiol do not affect condensate formation.a) System potential energy for unreactive and reactive systems.b) Simulation snapshot of LFssFL peptides having formed a condensate with unreactive benzene-1,3-dithiol molecules

Figure S6 :
Figure S6: Change in ring sizes across each simulation, median taken from 3 repeats.

Figure S7 :
Figure S7: Ring size counts using smaller reactive potential well.a) Ring counts for reactive Martini simulations with a potential well of 20 kJ/mol, as compared to the default 60 kJ/mol potential.b) Ring size counts in the native potential systems taken from the main text and replotted here for clarity of comparison.

Figure S8 .
Figure S8.Illustration of reversible bond formation using a smaller reactive potential.a) Three monomers come together to form a strand.b) The strand self-completes and forms a ring.c) The ring breaks apart again.d) One monomer breaks away from the strand.

Figure S9 .
Figure S9.Ring size counts over a longer simulation trajectory of 500 ns.

Figure S10 .
Figure S10.Simulations of WGR-1 peptide condensate systems.a) The chemical structure of the WGR-1 peptide.b) Martini coarse grained representation of the WGR-1 peptide.c) A condensate of WGR-1 peptides in a slab configuration.d) Density profiles of the water and protein components of the system in a slab configuration.e) Final ring size distributions in reactive Martini simulations.

Figure S11 .
Figure S11.Partitioning experiment of 1mer in LFssFL condensates (a) UPLC chromatograms obtained from the condensate solution before centrifugation (b) UPLC chromatograms obtained from the supernatant solution after centrifugation (c) superimposed chromatograms of (a) and (b).

Figure S12 .
Figure S12.Partitioning experiment of 3mer and 4mer in LFssFL condensates (a) UPLC chromatograms obtained from the condensate solution before centrifugation (b) UPLC chromatograms obtained from the supernatant solution after centrifugation (c) superimposed chromatograms of (a) and (b).

Table S2 .
Akaike information criterion values for single and double exponential model fits to the incoherent scattering function data shown in figure S1.

Table S3 .
The initial prepared conditions for the reactive simulations performed in this work.

Table S4 .
Final ring counts for each system.

Table S5 .
Experimentally measured partition coefficients of unassembled macrocycles between the dense and dilute regions of LFssFL condensates.