Macromolecular crowding and intrinsically disordered proteins: a polymer physics perspective

Clustering of RNA Polymerase II C-Terminal Domain Models upon Phosphorylation

RNA polymerase II (Pol II) C-terminal domain (CTD) is known to have crucial roles in regulating transcription. CTD has also been highly recognized for undergoing phase separation, which is further associated with its regulatory functions. However, the molecular interactions that the CTD forms to induce clustering to drive phase separations and how the phosphorylation of the CTD affects clustering are not entirely known. In this work, we studied the concentrated solutions of two heptapeptide repeat (2CTD) models at different phosphorylation patterns and protein and ion concentrations using all-atom molecular dynamics simulations to investigate clustering behavior and molecular interactions driving the cluster formation. Our results show that salt concentration and phosphorylation patterns play an important role in determining the clustering pattern, specifically at low protein concentrations. The balance between inter- and intrapeptide interactions and counterion coordination together impact the clustering behavior upon phosphorylation.

Crowder titrations enable the quantification of driving forces for macromolecular phase separation

Macromolecular solubility is an important contributor to the driving forces for phase separation. Formally, the driving forces in a binary mixture comprising a macromolecule dissolved in a solvent can be quantified in terms of the saturation concentration, which is the threshold macromolecular concentration above which the mixture separates into coexisting dense and dilute phases. In addition, the second virial coefficient, which measures the effective strength of solvent-mediated intermolecular interactions provides direct assessments of solvent quality. The sign and magnitude of second virial coefficients will be governed by a combination of solution conditions and the nature of the macromolecule of interest. Here, we show, using a combination of theory, simulation, and in vitro experiments, that titrations of crowders, providing they are true depletants, can be used to extract the intrinsic driving forces for macromolecular phase separation. This refers to saturation concentrations in the absence of crowders and the second virial coefficients that quantify the magnitude of the incompatibility between macromolecules and the solvent. Our results show how the depletion-mediated attractions afforded by crowders can be leveraged to obtain comparative assessments of macromolecule-specific, intrinsic driving forces for phase separation.

Design of functional intrinsically disordered proteins

Many proteins do not fold into a fixed three-dimensional structure, but rather function in a highly disordered state. These intrinsically disordered proteins pose a unique challenge to protein engineering and design: How can proteins be designed de novo if not by tailoring their structure? Here, we will review the nascent field of design of intrinsically disordered proteins with focus on applications in biotechnology and medicine. The design goals should not necessarily be the same as for de novo design of folded proteins as disordered proteins have unique functional strengths and limitations. We focus on functions where intrinsically disordered proteins are uniquely suited including disordered linkers, desiccation chaperones, sensors of the chemical environment, delivery of pharmaceuticals, and constituents of biomolecular condensates. Design of functional intrinsically disordered proteins relies on a combination of computational tools and heuristics gleaned from sequence-function studies. There are few cases where intrinsically disordered proteins have made it into industrial applications. However, we argue that disordered proteins can perform many roles currently performed by organic polymers, and that these proteins might be more designable due to their modularity.

Design and Characterization of Model Systems that Promote and Disrupt Transparency of Vertebrate Crystallins In Vitro

Positioned within the eye, the lens supports vision by transmitting and focusing light onto the retina. As an adaptive glassy material, the lens is constituted primarily by densely-packed, polydisperse crystallin proteins that organize to resist aggregation and crystallization at high volume fractions, yet the details of how crystallins coordinate with one another to template and maintain this transparent microstructure remain unclear. The role of individual crystallin subtypes (α, β, and γ) and paired subtype compositions, including how they experience and resist crowding-induced turbidity in solution, is explored using combinations of spectrophotometry, hard-sphere simulations, and surface pressure measurements. After assaying crystallin combinations, β-crystallins emerged as a principal component in all mixtures that enabled dense fluid-like packing and short-range order necessary for transparency. These findings helped inform the design of lens-like hydrogel systems, which are used to monitor and manipulate the loss of transparency under different crowding conditions. When taken together, the findings illustrate the design and characterization of adaptive materials made from lens proteins that can be used to better understand mechanisms regulating transparency.

SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins

Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite simulation analysis of unfolded regions of proteins (SOURSOP), an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.

Condensation Goes Viral: A Polymer Physics Perspective

The past decade has seen a revolution in our understanding of how the cellular environment is organized, where an incredible body of work has provided new insights into the role played by membraneless organelles. These rapid advancements have been made possible by an increasing awareness of the peculiar physical properties that give rise to such bodies and the complex biology that enables their function. Viral infections are not extraneous to this. Indeed, in host cells, viruses can harness existing membraneless compartments or, even, induce the formation of new ones. By hijacking the cellular machinery, these intracellular bodies can assist in the replication, assembly, and packaging of the viral genome as well as in the escape of the cellular immune response. Here, we provide a perspective on the fundamental polymer physics concepts that may help connect and interpret the different observed phenomena, ranging from the condensation of viral genomes to the phase separation of multicomponent solutions. We complement the discussion of the physical basis with a description of biophysical methods that can provide quantitative insights for testing and developing theoretical and computational models.

Excluded Volume and Weak Interactions in Crowded Solutions Modulate Conformations and RNA Binding of an Intrinsically Disordered Tail

The cellular milieu is a solution crowded with a significant concentration of different components (proteins, nucleic acids, metabolites, etc.). Such a crowded environment affects protein conformations, dynamics, and interactions. Intrinsically disordered proteins and regions are particularly sensitive to these effects. Here, we investigate the impact on an intrinsically disordered tail that flanks a folded domain, the N-terminal domain, and the RNA-binding domain of the SARS-CoV-2 nucleocapsid protein. We mimic the crowded environment of the cell using polyethylene glycol (PEG) and study its impact on protein conformations using single-molecule Förster resonance energy transfer. We found that high-molecular-weight PEG induces a collapse of the disordered N-terminal tail, whereas low-molecular-weight PEG induces a chain expansion. Our data can be explained by accounting for two opposing contributions: favorable interactions between the protein and crowder molecules and screening of excluded volume interactions. We further characterized the interaction between protein and RNA in the presence of crowding agents. While for all PEG molecules tested, we observed an increase in the binding affinity, the trend is not monotonic as a function of the degree of PEG polymerization. This points to the role of nonspecific protein-PEG interactions on binding in addition to the entropic effects due to crowding. To separate the enthalpic and entropic components of the effects, we investigated the temperature dependence of the association constants in the absence and presence of crowders. Finally, we compared the effects of crowding across mutations in the disordered region and found that the threefold difference in association constants for two naturally occurring variants of the SARS-CoV-2 nucleocapsid protein is reduced to almost identical affinities in the presence of crowders. Overall, our data provide new insights into understanding and modeling the contribution of crowding effects on disordered regions, including the impact of interactions between proteins and crowders and their interplay when binding a ligand.

The Analytical Flory Random Coil Is a Simple-to-Use Reference Model for Unfolded and Disordered Proteins

Denatured, unfolded, and intrinsically disordered proteins (collectively referred to here as unfolded proteins) can be described using analytical polymer models. These models capture various polymeric properties and can be fit to simulation results or experimental data. However, the model parameters commonly require users' decisions, making them useful for data interpretation but less clearly applicable as stand-alone reference models. Here we use all-atom simulations of polypeptides in conjunction with polymer scaling theory to parameterize an analytical model of unfolded polypeptides that behave as ideal chains (ν = 0.50). The model, which we call the analytical Flory random coil (AFRC), requires only the amino acid sequence as input and provides direct access to probability distributions of global and local conformational order parameters. The model defines a specific reference state to which experimental and computational results can be compared and normalized. As a proof-of-concept, we use the AFRC to identify sequence-specific intramolecular interactions in simulations of disordered proteins. We also use the AFRC to contextualize a curated set of 145 different radii of gyration obtained from previously published small-angle X-ray scattering experiments of disordered proteins. The AFRC is implemented as a stand-alone software package and is also available via a Google Colab notebook. In summary, the AFRC provides a simple-to-use reference polymer model that can guide intuition and aid in interpreting experimental or simulation results.

The analytical Flory random coil is a simple-to-use reference model for unfolded and disordered proteins

Denatured, unfolded, and intrinsically disordered proteins (collectively referred to here as unfolded proteins) can be described using analytical polymer models. These models capture various polymeric properties and can be fit to simulation results or experimental data. However, the model parameters commonly require users' decisions, making them useful for data interpretation but less clearly applicable as stand-alone reference models. Here we use all-atom simulations of polypeptides in conjunction with polymer scaling theory to parameterize an analytical model of unfolded polypeptides that behave as ideal chains (ν = 0.50). The model, which we call the analytical Flory Random Coil (AFRC), requires only the amino acid sequence as input and provides direct access to probability distributions of global and local conformational order parameters. The model defines a specific reference state to which experimental and computational results can be compared and normalized. As a proof-of-concept, we use the AFRC to identify sequence-specific intramolecular interactions in simulations of disordered proteins. We also use the AFRC to contextualize a curated set of 145 different radii of gyration obtained from previously published small-angle X-ray scattering experiments of disordered proteins. The AFRC is implemented as a stand-alone software package and is also available via a Google colab notebook. In summary, the AFRC provides a simple-to-use reference polymer model that can guide intuition and aid in interpreting experimental or simulation results.

SOURSOP: A Python package for the analysis of simulations of intrinsically disordered proteins

Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite SOURSOP, an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.

The biophysics of disordered proteins from the point of view of single-molecule fluorescence spectroscopy

Intrinsically disordered proteins (IDPs) and regions (IDRs) have emerged as key players across many biological functions and diseases. Differently from structured proteins, disordered proteins lack stable structure and are particularly sensitive to changes in the surrounding environment. Investigation of disordered ensembles requires new approaches and concepts for quantifying conformations, dynamics, and interactions. Here, we provide a short description of the fundamental biophysical properties of disordered proteins as understood through the lens of single-molecule fluorescence observations. Single-molecule Förster resonance energy transfer (FRET) and fluorescence correlation spectroscopy (FCS) provides an extensive and versatile toolbox for quantifying the characteristics of conformational distributions and the dynamics of disordered proteins across many different solution conditions, both in vitro and in living cells.

Structure and Transition Dynamics of Intrinsically Disordered Proteins Probed by Single-Molecule Spectroscopy

Intrinsically disordered proteins (IDPs) are a class of proteins that do not follow the unanimated perspective of the structure-function paradigm. IDPs enunciate the dynamics of motions which are often difficult to characterize by a particular experimental or theoretical approach. The chameleon nature of the IDPs is a result of an alteration or transition in their conformation upon binding with ligands. Experimental investigations via ensemble-average approaches to probe this randomness are often difficult to synchronize. Thus, to sense the substates of different conformational ensembles of IDPs, researchers have often targeted approaches based on single-molecule measurements. In this Perspective, we will discuss various single-molecule approaches to explore the conformational transitions of IDPs in different scenarios, the outcome, challenges, and future prospects.