scholarly journals Fuzzy protein theory for disordered proteins

2020 ◽  
Vol 48 (6) ◽  
pp. 2557-2564
Author(s):  
Monika Fuxreiter
Keyword(s):  
Fuzzy Logic ◽  
Phase Separation ◽  
Liquid Phase ◽  
Disordered Proteins ◽  
Cellular Behavior ◽  
Alternative Pathways ◽  
Conformational Ensembles ◽  
Cellular Environment ◽  
Wide Range ◽  
Liquid Liquid Phase Separation

Why proteins are fuzzy? Constant adaptation to the cellular environment requires a wide range of changes in protein structure and interactions. Conformational ensembles of disordered proteins in particular exhibit large shifts to activate or inhibit alternative pathways. Fuzziness is critical for liquid–liquid phase separation and conversion of biomolecular condensates into fibrils. Interpretation of these phenomena presents a challenge for the classical structure-function paradigm. Here I discuss a multi-valued formalism, based on fuzzy logic, which can be applied to describe complex cellular behavior of proteins.

scholarly journals Structure of biomolecular condensates from dissipative particle dynamics simulations

2019 ◽  
Author(s):  
Julian C. Shillcock ◽  
Maelick Brochut ◽  
Etienne Chénais ◽  
John H. Ipsen
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Intrinsically Disordered Proteins ◽  
Liquid Phase Separation ◽  
Coarse Grained ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Wide Range ◽  
End Caps ◽  
Liquid Liquid Phase Separation

ABSTRACTPhase separation of immiscible fluids is a common phenomenon in polymer chemistry, and is recognized as an important mechanism by which cells compartmentalize their biochemical reactions. Biomolecular condensates are condensed fluid droplets in cells that form by liquid-liquid phase separation of intrinsically-disordered proteins. They have a wide range of functions and are associated with chronic neurodegenerative diseases in which they become pathologically rigid. Intrinsically-disordered proteins are conformationally flexible and possess multiple, distributed binding sites for each other or for RNA. However, it remains unclear how their material properties depend on the molecular structure of the proteins. Here we use coarse-grained simulations to explore the phase behavior and structure of a model biomolecular condensate composed of semi-flexible polymers with attractive end-caps in a good solvent. Although highly simplified, the model contains the minimal molecular features that are sufficient to observe liquid-liquid phase separation of soluble polymers. The polymers condense into a porous, three-dimensional network in which their end-caps reversibly bind at junctions. The spatial separation of connected junctions scales with the polymer backbone length as a self-avoiding random walk over a wide range of concentration with a weak affinity-dependent prefactor. By contrast, the average number of polymers that meet at the junctions depends strongly on the end-cap affinity but only weakly on the polymer length. The regularity and porosity of the condensed network suggests a mechanism for cells to regulate biomolecular condensates. Interaction sites along a protein may be turned on or off to modulate the condensate’s porosity and tune the diffusion and interaction of additional proteins.

scholarly journals Widespread occurrence of the droplet state of proteins in the human proteome

2020 ◽  
Author(s):  
Maarten Hardenberg ◽  
Attila Horvath ◽  
Viktor Ambrus ◽  
Monika Fuxreiter ◽  
Michele Vendruscolo
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Liquid Phase Separation ◽  
Current Evidence ◽  
Cellular Environment ◽  
Wide Range ◽  
Proteome Level ◽  
Client Proteins ◽  
Separation Of Proteins ◽  
Liquid Liquid Phase Separation

AbstractA wide range of proteins have been reported to condensate into a dense liquid phase, forming a reversible droplet state. Failure in the control of the droplet state can lead to the formation of the more stable amyloid state, which is often disease-related. These observations prompt the question of how many proteins can undergo liquid-liquid phase separation. Here, in order to address this problem, we discuss the biophysical principles underlying the droplet state of proteins by analyzing current evidence for droplet-driver and droplet-client proteins. Based on the concept that the droplet state is stabilized by the large conformational entropy associated with non-specific side-chain interactions, we develop the FuzDrop method to predict droplet-promoting regions and proteins, which can spontaneously phase separate. We use this approach to carry out a proteome-level study to rank proteins according to their propensity to form the droplet state, spontaneously or via partner interactions. Our results lead to the conclusion that the droplet state could be, at least transiently, accessible to most proteins under conditions found in the cellular environment.SignificanceLiquid-liquid phase separation of proteins results in biomolecular condensates, which contribute to the organisation of cellular matter into membraneless organelles. It is still unclear, however, whether these condensates represent a common state of proteins. Here, based on biophysical principles driving phase separation, we report a proteome-wide ranking of proteins according to their propensity to condensate into a droplet state. We analyze two mechanisms for droplet formation - driver proteins can spontaneously phase separate, while client proteins require additional components. We conclude that the droplet state, as the native and amyloid states, is a fundamental state of proteins, with most proteins expected to be capable of undergoing liquid-liquid phase separation via either of these two mechanisms.

Charge pattern affects the structure and dynamics of polyampholyte condensates

2020 ◽  
Vol 22 (34) ◽  
pp. 19368-19375 ◽  
Author(s):  
Milan Kumar Hazra ◽  
Yaakov Levy
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Intrinsically Disordered Proteins ◽  
Liquid Phase Separation ◽  
Disordered Proteins ◽  
Internal Diffusion ◽  
Intrinsically Disordered ◽  
Structure And Dynamics ◽  
Liquid Liquid Phase Separation

The charge pattern of intrinsically disordered proteins affects the dynamics and internal diffusion of their condensate formed via liquid–liquid phase separation.

scholarly journals The Dynamism of Intrinsically Disordered Proteins in Liquid-Liquid Phase Separation

2020 ◽  
Vol 118 (3) ◽  
pp. 60a
Author(s):  
Samrat Mukhopadhyay ◽  
Anupa Majumdar ◽  
Priyanka Dogra ◽  
Shiny Maity ◽  
Ashish Joshi
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Intrinsically Disordered Proteins ◽  
Liquid Phase Separation ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Liquid Liquid Phase Separation

scholarly journals Liquid-liquid phase separation and viscosity within secondary organic aerosol generated from diesel fuel vapors

2019 ◽  
Author(s):  
Mijung Song ◽  
Adrian M. Maclean ◽  
Yuanzhou Huang ◽  
Natalie R. Smith ◽  
Sandra L. Blair ◽  
...  
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Diesel Fuel ◽  
Diffusion Coefficients ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Liquid Phase Separation ◽  
Small Diffusion ◽  
Wide Range ◽  
Liquid Liquid Phase Separation

Abstract. Information on liquid-liquid phase separation (LLPS) and viscosity (or diffusion) within secondary organic aerosol (SOA) is needed to improve predictions of particle size, mass, reactivity, and cloud nucleating properties in the atmosphere. Here we report on LLPS and viscosities within SOA generated by the photooxidation of diesel fuel vapors. Diesel fuel contains a wide range of volatile organic compounds, and SOA generated by the photooxidation of diesel fuel vapors may be a good proxy for SOA from anthropogenic emissions. In our experiments, LLPS occurred over the relative humidity (RH) range of ~ 70 % to ~ 100 %, resulting in an organic-rich outer phase and a water-rich inner phase. These results may have implications for predicting the cloud nucleating properties of anthropogenic SOA since the organic-rich outer phase can lower the kinetic barrier for activation to a cloud droplet. At ≤ 10 % RH, the viscosity was in the range of ≥ 1 × 108 Pa s, which corresponds to roughly the viscosity of tar pitch. At 38–50 % RH the viscosity was in the range of 1 × 108–3 × 105 Pa s. These measured viscosities are consistent with predictions based on oxygen to carbon elemental ratio (O : C) and molar mass as well as predictions based on the number of carbon, hydrogen, and oxygen atoms. Based on the measured viscosities and the Stokes–Einstein relation, at ≤ 10 % RH diffusion coefficients of organics within diesel fuel SOA is ≤ 5.4 × 10−17cm2 s−1 and the mixing time of organics within 200 nm diesel fuel SOA particles (τmixing) is ≳ 50 h. These small diffusion coefficients and large mixing times may be important in laboratory experiments, where SOA is often generated and studied using low RH conditions and on time scales of minutes to hours. At 38–50 % RH, the calculated organic diffusion coefficients are in the range of 5.4 × 10−17 to 1.8 × 10−13 cm2 s−1 and calculated τmixing values are in the range of ~ 0.01 h to ~ 50 h. These values provide important constraints for the physicochemical properties of anthropogenic SOA.

scholarly journals Liquid–liquid phase separation and viscosity within secondary organic aerosol generated from diesel fuel vapors

2019 ◽  
Vol 19 (19) ◽  
pp. 12515-12529 ◽  
Author(s):  
Mijung Song ◽  
Adrian M. Maclean ◽  
Yuanzhou Huang ◽  
Natalie R. Smith ◽  
Sandra L. Blair ◽  
...  
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Diesel Fuel ◽  
Diffusion Coefficients ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Liquid Phase Separation ◽  
Small Diffusion ◽  
Wide Range ◽  
Liquid Liquid Phase Separation

Abstract. Information on liquid–liquid phase separation (LLPS) and viscosity (or diffusion) within secondary organic aerosol (SOA) is needed to improve predictions of particle size, mass, reactivity, and cloud nucleating properties in the atmosphere. Here we report on LLPS and viscosities within SOA generated by the photooxidation of diesel fuel vapors. Diesel fuel contains a wide range of volatile organic compounds, and SOA generated by the photooxidation of diesel fuel vapors may be a good proxy for SOA from anthropogenic emissions. In our experiments, LLPS occurred over the relative humidity (RH) range of ∼70 % to ∼100 %, resulting in an organic-rich outer phase and a water-rich inner phase. These results may have implications for predicting the cloud nucleating properties of anthropogenic SOA since the presence of an organic-rich outer phase at high-RH values can lower the supersaturation with respect to water required for cloud droplet formation. At ≤10 % RH, the viscosity was ≥1×108 Pa s, which corresponds to roughly the viscosity of tar pitch. At 38 %–50 % RH, the viscosity was in the range of 1×108 to 3×105 Pa s. These measured viscosities are consistent with predictions based on oxygen to carbon elemental ratio (O:C) and molar mass as well as predictions based on the number of carbon, hydrogen, and oxygen atoms. Based on the measured viscosities and the Stokes–Einstein relation, at ≤10 % RH diffusion coefficients of organics within diesel fuel SOA is ≤5.4×10-17 cm2 s−1 and the mixing time of organics within 200 nm diesel fuel SOA particles (τmixing) is 50 h. These small diffusion coefficients and large mixing times may be important in laboratory experiments, where SOA is often generated and studied using low-RH conditions and on timescales of minutes to hours. At 38 %–50 % RH, the calculated organic diffusion coefficients are in the range of 5.4×10-17 to 1.8×10-13 cm2 s−1 and calculated τmixing values are in the range of ∼0.01 h to ∼50 h. These values provide important constraints for the physicochemical properties of anthropogenic SOA.

Sign in / Sign up

Export Citation Format

Share Document