Physics-driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy

Joseph, Jerelle A.; Reinhardt, Aleks; Aguirre, Anne; Chew, Pin Yu; Russell, Kieran O.; Espinosa, Jorge R.; Garaizar, Adiran; Collepardo-Guevara, Rosana

doi:10.1016/j.bpj.2021.11.1214

Cited by 27 publications

(64 citation statements)

References 87 publications

(223 reference statements)

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“…In our evolution runs, we evolve either the inner sequence or the outer sequence whilst keeping the other sequence unchanged in order to simplify the subsequent analysis of driving forces. To evolve the sequence, we apply the genetic algorithm as described above (and in the Methods section), computing a sequence’s fitness by performing direct-coexistence moleculardynamics simulations of the two-component mixture using our residue-resolution coarse-grained model, Mpipi, 83 at a fixed temperature.…”

Section: Resultsmentioning

confidence: 99%

“…The phase diagrams of a set of A1 LCD variants have recently been determined both experimentally 95 and computationally using the same coarsegrained model that we have used in this work. 83 We consider sequences with similar, higher and lower upper critical solution temperatures compared to the wild type (WT), ensuring that sequences with distinct features are represented. In particular, we focus on two aromatic variants, +7F−7Y and −12F+12Y, two mixed-charged variants, +7R+12D and +7K+12D, and two arginine–lysine variants, −6R+6K and −3R+3K.…”

Section: Resultsmentioning

confidence: 99%

“…Motivated by these ideas, here we develop an evolutionary algorithm that goes beyond manipulating the stability of condensates and allows us to enforce or inhibit a desired spatial organisation of biomolecules inside multi-component condensates. We couple molecular-dynamics simulations of a residue-resolution coarse-grained protein model that achieves near quantitative agreement with experiments 83 with a genetic algorithm 70 to evolve protein sequences towards increasing ‘multiphasicity’, which we define to be the difference in compositions of the two coexisting phases of a multiphase condensate. The multiphasicity of a condensate increases with the purity of the two coexisting phases.…”

Section: Introductionmentioning

confidence: 99%

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Designing multiphase biomolecular condensates by coevolution of protein mixtures

Chew

Joseph

Collepardo-Guevara

et al. 2022

Preprint

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Control of biomolecular condensates may hold considerable therapeutic potential. Intracellular condensates are highly multi-component systems in which complex phase behaviour can ensue, including the formation of architectures comprising multiple immiscible condensed phases. Conceivable avenues for manipulating condensates to bypass pathologies thus extend beyond merely controlling their stability and material properties, and relying solely on physical intuition to manipulate them is difficult because of the complexity of their composition. We address this challenge by developing an efficient computational approach to design pairs of protein sequences that result in well-separated multilayered condensates. Our method couples a genetic algorithm to a residue-resolution coarse-grained protein model. We demonstrate that we can design protein partners to form multiphase condensates containing naturally occurring proteins, such as the low-complexity domain of hnRNPA1 and its mutants, and show how homo- and heterotypic interactions must differ between proteins to result in multiphasicity.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Designing multiphase biomolecular condensates by coevolution of protein mixtures

Chew

Joseph

Collepardo-Guevara

et al. 2022

Preprint

Self Cite

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“…Coarse-grained simulation techniques simplify the atomic details of proteins in order to simulate thousands of molecules. (50)(51)(52)(53)(54)(55) A minimal model of the phase separation of multivalent proteins is the patchy particle scheme in which proteins are treated as spheres with attractive sites on their surface. (56,57) These models, however, ignore conformational fluctuations that may be important for flexible proteins.…”

Section: Introductionmentioning

confidence: 99%

Model biomolecular condensates have heterogeneous structure quantitatively dependent on the interaction profile of their constituent macromolecules

Shillcock

Lagisquet

Alexandre

et al. 2022

Preprint

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Biomolecular condensates play numerous roles in cells by selectively concentrating client proteins while excluding others. These functions are likely to be sensitive to the spatial organization of the scaffold proteins forming the condensate. We use coarse- grained molecular simulations to show that model intrinsically-disordered proteins phase separate into a heterogeneous, structured fluid characterized by a well-defined length scale. The proteins are modelled as semi-flexible polymers with punctate, multifunctional binding sites in good solvent conditions. Their dense phase is highly solvated with a spatial structure that is more sensitive to the separation of the binding sites than their affinity. We introduce graph theoretic measures to show that the proteins are heterogeneously distributed throughout the dense phase, an effect that increases with increasing binding site number, and exhibit multi-timescale dynamics. The simulations predict that the structure of the dense phase is modulated by the location and affinity of binding sites distant from the termini of the proteins, while sites near the termini more strongly affect its phase behaviour. The relations uncovered between the arrangement of weak interaction sites on disordered proteins and the material properties of their dense phase can be experimentally tested to give insight into the biophysical properties and rational design of biomolecular condensates.

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“…[13][14][15] Unfortunately, these simulations often involve multiple protein chains and large simulation boxes, which cannot be run for sufficiently long timescales for observing LLPS. Alternatively, much more computationally cheap coarse-grained simulation models can recapitulate general principles of phase separation of disordered proteins, 6,[16][17][18] although details of chemical interactions are inevitably lost. In this work we run atomistic MD simulations of amino acid mixtures as a minimal, albeit detailed, model for LLPS in protein-like systems.…”

mentioning

confidence: 99%

Phase separation in amino acid mixtures is governed by composition

Sancho

2022

Preprint

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Liquid-liquid phase separation (LLPS) has recently come to immense prominence as it is central to the formation of membraneless organelles, leading to a new paradigm of cellular organization. This type of phase transition is mediated by molecular interactions between biomolecules, including nucleic acids and both ordered and disordered proteins. In the latter case, the separation between protein-dense and dilute phases is often interpreted using models adapted from polymer theory. Specifically, the "stickers and spacers" model proposes that LLPS originates from the interplay between two classes of residues and that the main determinants for phase separation are multivalency and sequence patterning. The duality of roles of stickers (aromatics like Phe and Tyr) and spacers (Gly and polar residues) may apply more broadly in protein-like mixtures, and the presence of these two types of components alone may suffice for LLPS to take place. In order to explore this hypothesis, we use atomistic molecular dynamics simulations of capped amino-acid residues as a minimal model system. We study the behaviour of pure amino acids in water for three types of residues that are thought to play critical roles in LLPS, corresponding to the spacer and sticker categories, and their multicomponent mixtures. In agreement with previous observations, we find that the spacer type amino acids fail to phase-separate on their own, while the sticker is prone to aggregation. However, ternary amino acid mixtures involving both types of amino acids phase-separate into two phases that retain intermediate degrees of compaction and considerable fluidity. Our results suggest that LLPS is an emergent property of amino acid mixtures determined by composition.

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Physics-driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy

Cited by 27 publications

References 87 publications

Designing multiphase biomolecular condensates by coevolution of protein mixtures

Designing multiphase biomolecular condensates by coevolution of protein mixtures

Model biomolecular condensates have heterogeneous structure quantitatively dependent on the interaction profile of their constituent macromolecules

Phase separation in amino acid mixtures is governed by composition

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