A universal code for phase separation of prion-like low complexity domains: Insights from quantitative computer simulations

Maristany, Maria Julia; Aguirre, Anne; Joseph, Jerelle A.; Collepardo-Guevara, Rosana

doi:10.1016/j.bpj.2022.11.960

Cited by 3 publications

(4 citation statements)

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“…3 ). While one could envisage applying our approach to interrogate the underlying molecular grammar associated with phase separation across disordered regions, prior and ongoing work from other groups has exhaustively explored the underlying chemical principles encoded by coarse-grained forcefields ( 24 , 42 , 44 , 88 – 95 ). We build on this prior work, moving away from the need to extrapolate general principles to specific systems and instead enable direct predictions for how mutations are predicted to impact phase diagrams – at least qualitatively – on a case-by-case basis.…”

Section: Discussionmentioning

confidence: 99%

Direct prediction of intermolecular interactions driven by disordered regions

Ginell,

Emenecker,

Lotthammer

et al. 2024

Preprint

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Intrinsically disordered regions (IDRs) are critical for a wide variety of cellular functions, many of which involve interactions with partner proteins. Molecular recognition is typically considered through the lens of sequence-specific binding events. However, a growing body of work has shown that IDRs often interact with partners in a manner that does not depend on the precise order of the amino acid order, instead driven by complementary chemical interactions leading to disordered bound-state complexes. Despite this emerging paradigm, we lack tools to describe, quantify, predict, and interpret these types of structurally heterogeneous interactions from the underlying amino acid sequences. Here, we repurpose the chemical physics developed originally for molecular simulations to develop an approach for predicting intermolecular interactions between IDRs and partner proteins. Our approach enables the direct prediction of phase diagrams, the identification of chemically-specific interaction hotspots on IDRs, and a route to develop and test mechanistic hypotheses regarding IDR function in the context of molecular recognition. We use our approach to examine a range of systems and questions to highlight its versatility and applicability.

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Section: Discussionmentioning

confidence: 99%

Direct prediction of intermolecular interactions driven by disordered regions

Ginell,

Emenecker,

Lotthammer

et al. 2024

Preprint

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“…Previous studies using hnRNP A1 PLD have demonstrated that the distributed aromatic (Y/F) amino acids act as "stickers" that mediate PLD-PLD interactions 18,26 , whereas the polar amino acids (S/G) can be described as "spacers", which regulate chain solvation and cooperativity of sticker-sticker interactions. The importance of tyrosine residues in driving PLD phase separation has been further demonstrated experimentally for FUS 26 and EWSR1 27 , and computationally for a large number of PLD sequence variants 28 . In addition to aromatic residues, charged residues such as arginine (R) and polar amino acids such as glutamine (Q) also play smaller but important roles in PLD phase separation 28 .…”

Section: Introductionmentioning

confidence: 88%

“…The importance of tyrosine residues in driving PLD phase separation has been further demonstrated experimentally for FUS 26 and EWSR1 27 , and computationally for a large number of PLD sequence variants 28 . In addition to aromatic residues, charged residues such as arginine (R) and polar amino acids such as glutamine (Q) also play smaller but important roles in PLD phase separation 28 . Together, the sticker and spacer residues regulate PLD phase separation in a context-dependent manner 19 .…”

Section: Introductionmentioning

confidence: 88%

Heterotypic interactions in the dilute phase can drive co-condensation of prion-like low-complexity domains of FET proteins and mammalian SWI/SNF complex

Davis

Ranganath

Moosa

et al. 2023

Preprint

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Prion-like domains (PLDs) are low-complexity protein sequences enriched within nucleic acid-binding proteins including those involved in transcription and RNA processing. PLDs of FUS and EWSR1 play key roles in recruiting chromatin remodeler mammalian SWI/SNF complex to oncogenic FET fusion protein condensates. Here, we show that disordered low-complexity domains of multiple SWI/SNF subunits are prion-like with a strong propensity to undergo intracellular phase separation. These PLDs engage in sequence-specific heterotypic interactions with the PLD of FUS in the dilute phase at sub-saturation conditions, leading to the formation of PLD co-condensates. In the dense phase, homotypic and heterotypic PLD interactions are highly cooperative, resulting in the co-mixing of individual PLD phases and forming spatially homogeneous ternary co-condensates. Heterotypic PLD-mediated positive cooperativity in protein-protein interaction networks is likely to play key roles in the assembly of SWI/SNF complexes and their co-phase separation with transcription factors containing homologous low-complexity domains.

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“…47 Simulations have also been used to derive rules enabling predictions of variations in PS of specific families of IDRs. 9,48 Despite the many advances highlighted above, it is still challenging to accurately predict the concentrations of the dense and, importantly, the dilute phase, even for in vitro systems of a single species of IDR in solution. In turn, predicting the free energy of transfer from dilute into the dense phase is likewise challenging, in particular due to the sensitivity of the dilute phase (saturation) concentration to sequence changes.…”

Section: Introductionmentioning

confidence: 99%

Prediction of phase separation propensities of disordered proteins from sequence

von Bülow,

Tesei,

Lindorff-Larsen

2024

Preprint

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Phase separation is thought to be one possible mechanism governing the selective cellular enrichment of biomolecular constituents for processes such as transcriptional activation, mRNA regulation, and immune signaling. Phase separation is mediated by multivalent interactions of biological macromolecules including intrinsically disordered proteins and regions (IDRs). Despite considerable advances in experiments, theory and simulations, the prediction of the thermodynamics of IDR phase behaviour remains challenging. We combined coarse-grained molecular dynamics simulations and active learning to develop a fast and accurate machine learning model to predict the free energy and saturation concentration for phase separation directly from sequence. We validate the model using both experimental and computational data. We apply our model to all 27,663 IDRs of chain length up to 800 residues in the human proteome and find that 1,420 of these (5%) are predicted to undergo homotypic phase separation with transfer free energies<−2kBT. We use our model to understand the relationship between single-chain compaction and phase separation, and find that changes from charge-to hydrophobicity-mediated interactions can break the symmetry between intra-and inter-molecular interactions. We also analyse the structural preferences at condensate interfaces and find substantial heterogeneity that is determined by the same sequence properties as phase separation. Our work refines the established rules governing the relationships between sequence features and phase separation propensities, and our prediction models will be useful for interpreting and designing cellular experiments on the role of phase separation, and for the design of IDRs with specific phase separation propensities.

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A universal code for phase separation of prion-like low complexity domains: Insights from quantitative computer simulations

Cited by 3 publications

References 0 publications

Direct prediction of intermolecular interactions driven by disordered regions

Direct prediction of intermolecular interactions driven by disordered regions

Heterotypic interactions in the dilute phase can drive co-condensation of prion-like low-complexity domains of FET proteins and mammalian SWI/SNF complex

Prediction of phase separation propensities of disordered proteins from sequence

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