Improved coarse‐grained model for studying sequence dependent phase separation of disordered proteins

2021 ◽  
Author(s):  
Roshan Mammen Regy ◽  
Jacob Thompson ◽  
Young C. Kim ◽  
Jeetain Mittal
Author(s):  
T. M. Perdikari ◽  
N. Jovic ◽  
G. L. Dignon ◽  
Y. C. Kim ◽  
N. L. Fawzi ◽  
...  

AbstractBiomolecules undergo liquid-liquid phase separation (LLPS) resulting in the formation of multicomponent protein-RNA membraneless organelles in cells. However, the physiological and pathological role of post translational modifications (PTMs) on the biophysics of phase behavior is only beginning to be probed. To study the effect of PTMs on LLPS in silico, we extend our transferable coarse-grained model of intrinsically disordered proteins to include phosphorylated and acetylated amino acids. Using the parameters for modified amino acids available for fixed charge atomistic forcefields, we parameterize the size and atomistic hydropathy of the coarse-grained modified amino acid beads, and hence the interactions between the modified and natural amino acids. We then elucidate how the number and position of phosphorylated and acetylated residues alter the protein’s single chain compactness and its propensity to phase separate. We show that both the number and the position of phosphorylated threonines/serines or acetylated lysines can serve as a molecular on/off switch for phase separation in the well-studied disordered regions of FUS and DDX3X, respectively. We also compare modified residues to their commonly used PTM mimics for their impact on chain properties. Importantly, we show that the model can predict and capture experimentally measured differences in the phase behavior for position-specific modifications, showing that the position of modifications can dictate phase separation. In sum, this model will be useful for studying LLPS of post-translationally modified intrinsically disordered proteins and predicting how modifications control phase behavior with position-specific resolution.Statement of SignificancePost-translational modifications are important regulators of liquid-liquid phase separation (LLPS) which drives the formation of biomolecular condensates. Theoretical methods can be used to characterize the biophysical properties of intrinsically disordered proteins (IDPs). Our recent framework for molecular simulations using a Cα-centered coarse-grained model can predict the effect of various perturbations such as mutations (Dignon et al. PloS Comput. Biol, 2018) and temperature (Dignon et al, ACS Cent. Sci., 2019) on LLPS. Here, we expand this framework to incorporate modified residues like phosphothreonine, phosphoserine and acetylysine. This model will prove useful for simulating the phase separation of post-translationally modified IDPs and predicting how position-specific modifications can control phase behavior across the large family of proteins known to be phosphorylated and acetylated.


2020 ◽  
Vol 117 (46) ◽  
pp. 28795-28805
Author(s):  
Suman Das ◽  
Yi-Hsuan Lin ◽  
Robert M. Vernon ◽  
Julie D. Forman-Kay ◽  
Hue Sun Chan

Endeavoring toward a transferable, predictive coarse-grained explicit-chain model for biomolecular condensates underlain by liquid–liquid phase separation (LLPS) of proteins, we conducted multiple-chain simulations of the N-terminal intrinsically disordered region (IDR) of DEAD-box helicase Ddx4, as a test case, to assess roles of electrostatic, hydrophobic, cation–π, and aromatic interactions in amino acid sequence-dependent LLPS. We evaluated three different residue–residue interaction schemes with a shared electrostatic potential. Neither a common hydrophobicity scheme nor one augmented with arginine/lysine-aromatic cation–π interactions consistently accounted for available experimental LLPS data on the wild-type, a charge-scrambled, a phenylalanine-to-alanine (FtoA), and an arginine-to-lysine (RtoK) mutant of Ddx4 IDR. In contrast, interactions based on contact statistics among folded globular protein structures reproduce the overall experimental trend, including that the RtoK mutant has a much diminished LLPS propensity. Consistency between simulation and experiment was also found for RtoK mutants of P-granule protein LAF-1, underscoring that, to a degree, important LLPS-driving π-related interactions are embodied in classical statistical potentials. Further elucidation is necessary, however, especially of phenylalanine’s role in condensate assembly because experiments on FtoA and tyrosine-to-phenylalanine mutants suggest that LLPS-driving phenylalanine interactions are significantly weaker than posited by common statistical potentials. Protein–protein electrostatic interactions are modulated by relative permittivity, which in general depends on aqueous protein concentration. Analytical theory suggests that this dependence entails enhanced interprotein interactions in the condensed phase but more favorable protein–solvent interactions in the dilute phase. The opposing trends lead to only a modest overall impact on LLPS.


2020 ◽  
Author(s):  
Zakarya Benayad ◽  
Sören von Bülow ◽  
Lukas S. Stelzl ◽  
Gerhard Hummer

AbstractDisordered proteins and nucleic acids can condense into droplets that resemble the membraneless organelles observed in living cells. MD simulations offer a unique tool to characterize the molecular interactions governing the formation of these biomolecular condensates, their physico-chemical properties, and the factors controlling their composition and size. However, biopolymer condensation depends sensitively on the balance between different energetic and entropic contributions. Here, we develop a general strategy to fine-tune the potential energy function for molecular dynamics simulations of biopolymer phase separation. We rebalance protein-protein interactions against solvation and entropic contributions to match the excess free energy of transferring proteins between dilute solution and condensate. We illustrate this formalism by simulating liquid droplet formation of the FUS low complexity domain (LCD) with a rebalanced MARTINI model. By scaling the strength of the nonbonded interactions in the coarse-grained MARTINI potential energy function, we map out a phase diagram in the plane of protein concentration and interaction strength. Above a critical scaling factor of αc ≈ 0.6, FUS LCD condensation is observed, where α = 1 and 0 correspond to full and repulsive interactions in the MARTINI model, respectively. For a scaling factor α = 0.65, we recover the experimental densities of the dilute and dense phases, and thus the excess protein transfer free energy into the droplet and the saturation concentration where FUS LCD condenses. In the region of phase separation, we simulate FUS LCD droplets of four different sizes in stable equilibrium with the dilute phase and slabs of condensed FUS LCD for tens of microseconds, and over one millisecond in aggregate. We determine surface tensions in the range of 0.01 to 0.4mN/m from the fluctuations of the droplet shape and from the capillary-wave-like broadening of the interface between the two phases. From the dynamics of the protein end-to-end distance, we estimate shear viscosities from 0.001 to 0.02Pas for the FUS LCD droplets with scaling factors α in the range of 0.625 to 0.75, where we observe liquid droplets. Significant hydration of the interior of the droplets keeps the proteins mobile and the droplets fluid.


2020 ◽  
Vol 117 (21) ◽  
pp. 11421-11431 ◽  
Author(s):  
Benjamin S. Schuster ◽  
Gregory L. Dignon ◽  
Wai Shing Tang ◽  
Fleurie M. Kelley ◽  
Aishwarya Kanchi Ranganath ◽  
...  

Phase separation of intrinsically disordered proteins (IDPs) commonly underlies the formation of membraneless organelles, which compartmentalize molecules intracellularly in the absence of a lipid membrane. Identifying the protein sequence features responsible for IDP phase separation is critical for understanding physiological roles and pathological consequences of biomolecular condensation, as well as for harnessing phase separation for applications in bioinspired materials design. To expand our knowledge of sequence determinants of IDP phase separation, we characterized variants of the intrinsically disordered RGG domain from LAF-1, a model protein involved in phase separation and a key component of P granules. Based on a predictive coarse-grained IDP model, we identified a region of the RGG domain that has high contact probability and is highly conserved between species; deletion of this region significantly disrupts phase separation in vitro and in vivo. We determined the effects of charge patterning on phase behavior through sequence shuffling. We designed sequences with significantly increased phase separation propensity by shuffling the wild-type sequence, which contains well-mixed charged residues, to increase charge segregation. This result indicates the natural sequence is under negative selection to moderate this mode of interaction. We measured the contributions of tyrosine and arginine residues to phase separation experimentally through mutagenesis studies and computationally through direct interrogation of different modes of interaction using all-atom simulations. Finally, we show that despite these sequence perturbations, the RGG-derived condensates remain liquid-like. Together, these studies advance our fundamental understanding of key biophysical principles and sequence features important to phase separation.


2021 ◽  
Author(s):  
Ushnish Rana ◽  
Clifford P Brangwynne ◽  
Athanassios Z Panagiotopoulos

Liquid-liquid phase separation (LLPS) is widely utilized by the cell to organize and regulate various biochemical processes. Although the LLPS of proteins is known to occur in a sequence dependent manner, it is unclear how sequence properties dictate the nature of the phase transition and thereby influence condensed phase morphology. In this work, we have utilized grand canonical Monte Carlo simulations for a simple coarse-grained model of disordered proteins to systematically investigate how sequence distribution, sticker fraction and chain length influence the phase behavior and regulate the formation of finite-size aggregates preempting macroscopic phase separation for some sequences. We demonstrate that a normalized sequence charge decoration (SCD) parameter establishes a ``soft" criterion for predicting the underlying phase transition of a model protein. Additionally, we find that this order parameter is strongly correlated to the critical density for phase separation, highlighting an unambiguous connection between sequence distribution and condensed phase density. Results obtained from an analysis of the order parameter reveals that at sufficiently long chain lengths, the vast majority of sequences are likely to phase separate. Our results predict that classical LLPS should be the dominant phase transition for disordered proteins and suggests a possible reason behind recent findings of widespread phase separation throughout living cells.


Membranes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 17
Author(s):  
Julian C. Shillcock ◽  
David B. Thomas ◽  
Jonathan R. Beaumont ◽  
Graeme M. Bragg ◽  
Mark L. Vousden ◽  
...  

Phospholipid membranes surround the cell and its internal organelles, and their multicomponent nature allows the formation of domains that are important in cellular signalling, the immune system, and bacterial infection. Cytoplasmic compartments are also created by the phase separation of intrinsically disordered proteins into biomolecular condensates. The ubiquity of lipid membranes and protein condensates raises the question of how three-dimensional droplets might interact with two-dimensional domains, and whether this coupling has physiological or pathological importance. Here, we explore the equilibrium morphologies of a dilute phase of a model disordered protein interacting with an ideal-mixing, two-component lipid membrane using coarse-grained molecular simulations. We find that the proteins can wet the membrane with and without domain formation, and form phase separated droplets bound to membrane domains. Results from much larger simulations performed on a novel non-von-Neumann compute architecture called POETS, which greatly accelerates their execution compared to conventional hardware, confirm the observations. Reducing the wall clock time for such simulations requires new architectures and computational techniques. We demonstrate here an inter-disciplinary approach that uses real-world biophysical questions to drive the development of new computing hardware and simulation algorithms.


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