Relation between single-molecule properties and phase behavior of intrinsically disordered proteins

Abstract

Proteins that undergo liquid-liquid phase separation (LLPS) have been shown to play a critical role in many physiological functions through formation of condensed liquid-like assemblies that function as membraneless organelles within biological systems. To understand how different proteins may contribute differently to these assemblies and their functions, it is important to understand the molecular driving forces of phase separation and characterize their phase boundaries and material properties. Experimental studies have shown that intrinsically disordered regions of these proteins are a major driving force, as many of them undergo LLPS in isolation. Previous work on polymer solution phase behavior suggests a potential correspondence between intramolecular and intermolecular interactions that can be leveraged to discover relationships between single-molecule properties and phase boundaries. Here, we take advantage of a recently developed coarse-grained framework to calculate the θ temperature [Formula: see text], the Boyle temperature [Formula: see text], and the critical temperature [Formula: see text] for 20 diverse protein sequences, and we show that these three properties are highly correlated. We also highlight that these correlations are not specific to our model or simulation methodology by comparing between different pairwise potentials and with data from other work. We, therefore, suggest that smaller simulations or experiments to determine [Formula: see text] or [Formula: see text] can provide useful insights into the corresponding phase behavior.

Temperature, Hydrostatic Pressure, and Osmolyte Effects on Liquid–Liquid Phase Separation in Protein Condensates: Physical Chemistry and Biological Implications

“…[129][130][131] In this context, progress has nonetheless been made in theoreticalp hysical understanding of how LLPS of IPDs might depend on their amino acid sequences by using coarse-grained approaches. These include analytical theory, [33,38,61,132,133] lattice [134] and continuum [9,135,136] residuebased explicit-chain models, [137] and field theory simulations. [138,139] These studies indicate that LLPS is sensitiven ot only to the net electric charge of an IDP buta lso the pattern of charged istribution along its sequence.…”

TDP-43 α-helical structure tunes liquid-liquid phase separation and function

“…To further elucidate the potential contributions of hydrophobicity vs. helicity to TDP-43 phase separation, we conducted coarse-grained simulations of TDP-43 CTD coexistence following the simulation model and framework from our previous work [46][47][48] . Because this coarse-grained model treats protein chains as flexible polymers and secondary structure is not directly captured, this allows us to decouple the mutational change in hydrophobicity from the changes in helicity, which are inseparable in experiment and traditional all-atom molecular simulation.…”

Hydropathy patterning complements charge patterning to describe conformational preferences of disordered proteins

“…20,28,[34][35][36] We also found that the θ-temperature (T θ ) of a single chain, the temperature at which ν=0.5, is strongly correlated with the critical temperature (T c ) of liquid-liquid phase separation (LLPS) of disordered proteins. 37,38 This relationship provides a rapid method for approximating the behavior of IDPs in the context of LLPS, and aided in the development of a novel temperature-dependent interaction potential that explained upper-and lower critical solution temperature phase transitions based on temperature-dependent solvent-mediated interactions. 39 Given the role of polymer scaling properties in dictating the conformational behavior of IDPs, there have been significant efforts to predict ν as a function of the protein sequence or order parameters representing important sequence characteristics.…”

“…The advantage of using ν as opposed to R g to characterize a protein's size is to eliminate the chain length dependence and to provide meaningful information on the solvent quality that can be useful in predicting protein LLPS. 37 We have recently shown that R g of a single protein can be used to estimate the scaling exponent (ν Rg ): 33,50,51…”

“…Motivated by the success of the SCD parameter in capturing the charge patterning effects on protein behavior, 37,43,58,59 we propose a similar strategy to describe effects of hydropathy patterning, terming the new parameter sequence hydropathy decoration (SHD). To derive SHD, we adopt the theoretical approach presented in detail by Sawle and Ghosh 43 for charged polymers.…”