Modeling concentration-dependent phase separation processes involving peptides and RNA via residue-based coarse-graining

Abstract

Biomolecular condensation, especially liquid-liquid phase separation, is an important physical process with relevance for a number of different aspects of biological functions. Key questions of what drives such condensation, especially in terms of molecular composition, can be addressed via computer simulations, but the development of computationally efficient, yet physically realistic models has been challenging. Here, the coarse-grained model COCOMO is introduced that balances the polymer behavior of peptides and RNA chains with their propensity to phase separate as a function of composition and concentration. COCOMO is a residue-based model that combines bonded terms with short- and long-range terms, including a Debye-Hückel solvation term. The model is highly predictive of experimental data on phase-separating model systems. It is also computationally efficient and can reach the spatial and temporal scales on which biomolecular condensation is observed with moderate computational resources.

The Effect of Polymer Length in Phase Separation

“…Using COCOMO, our recently-developed CG model 20 , simulations were performed for various lengths of adenine polymers (polyA N ) and different repetitions, M, of the [RGRGG] M peptide for a fixed volume fraction of 0.13% of each polymer ( Table S2 ). Snapshots shown at the end of the simulations indicate system-dependent condensation ( Fig.…”

“…The remarkable agreement between experiment and CG simulations suggests that the computational approach could be extended to other sequences and systems as well as other dimensions in phase space, such as concentration or peptide content. The parameterization of the CG model 20 explored a wide range of sequences and concentrations and accounts, for example, for the higher condensation propensity of arginine with nucleotides than lysine, as was observed by Fisher and Elbaum–Garfinkle 18 . However, the relative simplicity of the CG model neglects counterion effects that are known to be important factors during condensation 31-32 and does not consider partial secondary structures that are present in many IDPs.…”

“…We recently developed a coarse-grained (CG) computational model that reduces each amino acid or base to a single bead 20 . The interactions between beads were systematically parameterized to match experimental observations of both polymer characteristics and LLPS for many different systems.…”

Complex Conformational Space of RNA Polymerase II C-Terminal Domain upon Phosphorylation

“…To investigate phase separation by CTD, coarse-grained models in conjunction with enhanced simulation techniques can be applied as done extensively in recent studies for similar systems. [67][68][69] However, available coarse-grained models may need to be finetuned for CTD sequences and especially for the phosphorylated serine residues. One way to do this is to parameterize a coarse-grained model against all-atom MD simulations of concentrated CTD systems, which will be one of our future research directions.…”

The effect of polymer length in liquid-liquid phase separation

“…We recently developed a coarse-grained (CG) computational model that reduces each amino acid or base to a single bead (see supplemental experimental procedures and Table S1 for details). 20 The interactions between beads were systematically parameterized to match experimental observations of polymer characteristics and LLPS for many different systems. The model was also developed to accurately account for concentration dependence of LLPS, which allowed quantitative prediction of the length dependence under real experimental conditions.…”