Macromolecular condensation organizes nucleolar sub-phases to set up a pH gradient.

Nucleoli are multicomponent condensates defined by coexisting sub-phases. We identified distinct intrinsically disordered regions (IDRs), including acidic (D/E) tracts and K-blocks interspersed by E-rich regions, as defining features of nucleolar proteins. We show that the localization preferences of nucleolar proteins are determined by their IDRs and the types of RNA or DNA binding domains they encompass. In vitro reconstitutions and studies in cells showed how condensation, which combines binding and complex coacervation of nucleolar components, contributes to nucleolar organization. D/E tracts of nucleolar proteins contribute to lowering the pH of co-condensates formed with nucleolar RNAs in vitro. In cells, this sets up a pH gradient between nucleoli and the nucleoplasm. By contrast, juxta-nucleolar bodies, which have different macromolecular compositions, featuring protein IDRs with very different charge profiles, have pH values that are equivalent to or higher than the nucleoplasm. Our findings show that distinct compositional specificities generate distinct physicochemical properties for condensates.

A molten globule ensemble primes Arf1-GDP for the nucleotide switch.

The adenosine di-phosphate (ADP) ribosylation factor (Arf) small guanosine tri-phosphate (GTP)ases function as molecular switches to activate signaling cascades that control membrane organization in eukaryotic cells. In Arf1, the GDP/GTP switch does not occur spontaneously but requires guanine nucleotide exchange factors (GEFs) and membranes. Exchange involves massive conformational changes, including disruption of the core ß-sheet. The mechanisms by which this energetically costly switch occurs remain to be elucidated. To probe the switch mechanism, we coupled pressure perturbation with nuclear magnetic resonance (NMR), Fourier Transform infra-red spectroscopy (FTIR), small-angle X-ray scattering (SAXS), fluorescence, and computation. Pressure induced the formation of a classical molten globule (MG) ensemble. Pressure also favored the GDP to GTP transition, providing strong support for the notion that the MG ensemble plays a functional role in the nucleotide switch. We propose that the MG ensemble allows for switching without the requirement for complete unfolding and may be recognized by GEFs. An MG-based switching mechanism could constitute a pervasive feature in Arfs and Arf-like GTPases, and more generally, the evolutionarily related (Ras-like small GTPases) Rags and Gα GTPases.

Uncovering the Contributions of Charge Regulation to the Stability of Single Alpha Helices.

The single alpha helix (SAH) is a recurring motif in biology. The consensus sequence has a di-block architecture that includes repeats of four consecutive glutamate residues followed by four consecutive lysine residues. Measurements show that the overall helicity of sequences with consensus E4 K4 repeats is insensitive to a wide range of pH values. Here, we use the recently introduced q-canonical ensemble, which allows us to decouple measurements of charge state and conformation, to explain the observed insensitivity of SAH helicity to pH. We couple the outputs from separate measurements of charge and conformation with atomistic simulations to derive residue-specific quantifications of preferences for being in an alpha helix and for the ionizable residues to be charged vs. uncharged. We find a clear preference for accommodating uncharged Glu residues within internal positions of SAH-forming sequences. The stabilities of alpha helical conformations increase with the number of E4 K4 repeats and so do the numbers of accessible charge states that are compatible with forming conformations of high helical content. There is conformational buffering whereby charge state heterogeneity buffers against large-scale conformational changes thus making the overall helicity insensitive to large changes in pH. Further, the results clearly argue against a single, rod-like alpha helical conformation being the only or even dominant conformation in the ensembles of so-called SAH sequences.

Quantifying charge state heterogeneity for proteins with multiple ionizable residues.

Ionizable residues can release and take up protons and this has an influence on protein structure and function. The extent of protonation is linked to the overall pH of the solution and the local environments of ionizable residues. Binding or unbinding of a single proton generates a distinct charge microstate defined by a specific pattern of charges. Accordingly, the overall partition function is a sum over all charge microstates and Boltzmann weights of all conformations associated with each of the charge microstates. This ensemble-of-ensembles description recast as a q-canonical ensemble allows us to analyze and interpret potentiometric titrations that provide information regarding net charge as a function of pH. In the q-canonical ensemble, charge microstates are grouped into mesostates where each mesostate is a collection of microstates of the same net charge. Here, we show that leveraging the structure of the q-canonical ensemble allows us to decouple contributions of net proton binding and release from proton arrangement and conformational considerations. Through application of the q-canonical formalism to analyze potentiometric measurements of net charge in proteins with repetitive patterns of Lys and Glu residues, we determine the underlying mesostate pKa values and, more importantly, we estimate relative mesostate populations as a function of pH. This is a strength of using the q-canonical approach that cannot be replicated using purely site-specific analyses. Overall, our work shows how measurements of charge equilibria, decoupled from measurements of conformational equilibria, and analyzed using the framework of the q-canonical ensemble, provide protein-specific quantitative descriptions of pH-dependent populations of mesostates. This method is of direct relevance for measuring and understanding how different charge states contribute to conformational, binding, and phase equilibria of proteins.

The consequences of cavity creation on the folding landscape of a repeat protein depend upon context.

The effect of introducing internal cavities on protein native structure and global stability has been well documented, but the consequences of these packing defects on folding free-energy landscapes have received less attention. We investigated the effects of cavity creation on the folding landscape of the leucine-rich repeat protein pp32 by high-pressure (HP) and urea-dependent NMR and high-pressure small-angle X-ray scattering (HPSAXS). Despite a modest global energetic perturbation, cavity creation in the N-terminal capping motif (N-cap) resulted in very strong deviation from two-state unfolding behavior. In contrast, introduction of a cavity in the most stable, C-terminal half of pp32 led to highly concerted unfolding, presumably because the decrease in stability by the mutations attenuated the N- to C-terminal stability gradient present in WT pp32. Interestingly, enlarging the central cavity of the protein led to the population under pressure of a distinct intermediate in which the N-cap and repeats 1-4 were nearly completely unfolded, while the fifth repeat and the C-terminal capping motif remained fully folded. Thus, despite modest effects on global stability, introducing internal cavities can have starkly distinct repercussions on the conformational landscape of a protein, depending on their structural and energetic context.

High-Resolution Mapping of a Repeat Protein Folding Free Energy Landscape.

A complete description of the pathways and mechanisms of protein folding requires a detailed structural and energetic characterization of the conformational ensemble along the entire folding reaction coordinate. Simulations can provide this level of insight for small proteins. In contrast, with the exception of hydrogen exchange, which does not monitor folding directly, experimental studies of protein folding have not yielded such structural and energetic detail. NMR can provide residue specific atomic level structural information, but its implementation in protein folding studies using chemical or temperature perturbation is problematic. Here we present a highly detailed structural and energetic map of the entire folding landscape of the leucine-rich repeat protein, pp32 (Anp32), obtained by combining pressure-dependent site-specific 1H-15N HSQC data with coarse-grained molecular dynamics simulations. The results obtained using this equilibrium approach demonstrate that the main barrier to folding of pp32 is quite broad and lies near the unfolded state, with structure apparent only in the C-terminal region. Significant deviation from two-state unfolding under pressure reveals an intermediate on the folded side of the main barrier in which the N-terminal region is disordered. A nonlinear temperature dependence of the population of this intermediate suggests a large heat capacity change associated with its formation. The combination of pressure, which favors the population of folding intermediates relative to chemical denaturants; NMR, which allows their observation; and constrained structure-based simulations yield unparalleled insight into protein folding mechanisms.

MEDOC: A fast, scalable and mathematically exact algorithm for the site-specific prediction of the protonation degree in large disordered proteins.

Intrinsically disordered regions are found in most eukaryotic proteins and are enriched in positively and negatively charged residues. While it is often convenient to assume these residues follow their model-compound pKa values, recent work has shown that local charge effects (charge regulation) can upshift or downshift sidechain pKa values with major consequences for molecular function. Despite this, charge regulation is rarely considered when investigating disordered regions. The number of potential charge microstates that can be populated through acid/base regulation of a given number of ionizable residues in a sequence, N , scales as ~ 2 N . This exponential scaling makes the assessment of the full charge landscape of most proteins computationally intractable. To address this problem, we developed MEDOC (Multisite Extent of Deprotonation Originating from Context) to determine the degree of protonation of a protein based on the local sequence context of each ionizable residue. We show that we can drastically reduce the number of parameters necessary to determine the full, analytic, Boltzmann partition function of the charge landscape at both global and site-specific levels. Our algorithm applies the structure of the q-canonical ensemble, combined with novel strategies to rapidly obtain the minimal set of parameters, thereby circumventing the combinatorial explosion of the number of charge microstates even for proteins containing a large number of ionizable amino acids. We apply MEDOC to several sequences, including a global analysis of the distribution of pKa values across the entire DisProt database. Our results show differences in the distribution of predicted pKa values for different amino acids, in agreement with NMR-measured distributions in proteins.

Phosphorylation of disordered proteins tunes local and global intramolecular interactions.

Protein post-translational modifications, such as phosphorylation, are important regulatory signals for diverse cellular functions. In particular, intrinsically disordered protein regions (IDRs) are subject to phosphorylation as a means to modulate their interactions and functions. Toward understanding the relationship between phosphorylation in IDRs and specific functional outcomes, we must consider how phosphorylation affects the IDR conformational ensemble. Various experimental techniques are suited to interrogate the features of IDR ensembles; molecular simulations can provide complementary insights and even illuminate ensemble features that may be experimentally inaccessible. Therefore, we sought to expand the tools available to study phosphorylated IDRs by all-atom Monte Carlo simulations. To this end, we implemented parameters for phosphoserine (pSer) and phosphothreonine (pThr) into the OPLS version of the continuum solvent model, ABSINTH, and assessed their performance in all-atom simulations compared to published findings. We simulated short (< 20 residues) and long (> 80 residues) phospho-IDRs that, collectively, survey both local and global phosphorylation-induced changes to the ensemble. Our simulations of four well-studied phospho-IDRs show near-quantitative agreement with published findings for these systems via metrics including changes to radius of gyration, transient helicity, and persistence length. We also leveraged the inherent advantage of sequence control in molecular simulations to explore the conformational effects of diverse combinations of phospho-sites in two multi-phosphorylated IDRs. Our results support and expand on prior observations that connect phosphorylation to changes in the IDR conformational ensemble. Herein, we describe phosphorylation as a means to alter sequence chemistry, net charge and charge patterning, and intramolecular interactions, which can collectively modulate the local and global IDR ensemble features.

Uncovering Differences in Hydration Free Energies and Structures for Model Compound Mimics of Charged Side Chains of Amino Acids.

Free energies of hydration are of fundamental interest for modeling and understanding conformational and phase equilibria of macromolecular solutes in aqueous phases. Of particular relevance to systems such as intrinsically disordered proteins are the free energies of hydration and hydration structures of model compounds that mimic charged side chains of Arg, Lys, Asp, and Glu. Here, we deploy a Thermodynamic Cycle-based Proton Dissociation (TCPD) approach in conjunction with data from direct measurements to obtain estimates for the free energies of hydration for model compounds that mimic the side chains of Arg+, Lys+, Asp-, and Glu-. Irrespective of the choice made for the hydration free energy of the proton, the TCPD approach reveals clear trends regarding the free energies of hydration for Arg+, Lys+, Asp-, and Glu-. These trends include asymmetries between the hydration free energies of acidic (Asp- and Glu-) and basic (Arg+ and Lys+) residues. Further, the TCPD analysis, which relies on a combination of experimental data, shows that the free energy of hydration of Arg+ is less favorable than that of Lys+. We sought a physical explanation for the TCPD-derived trends in free energies of hydration. To this end, we performed temperature-dependent calculations of free energies of hydration and analyzed hydration structures from simulations that use the polarizable Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field and water model. At 298 K, the AMOEBA model generates estimates of free energies of hydration that are consistent with TCPD values with a free energy of hydration for the proton of ca. -259 kcal/mol. Analysis of temperature-dependent simulations leads to a structural explanation for the observed differences in free energies of hydration of ionizable residues and reveals that the heat capacity of hydration is positive for Arg+ and Lys+ and negative for Asp- and Glu-.

Design of intrinsically disordered proteins that undergo phase transitions with lower critical solution temperatures.

Many naturally occurring elastomers are intrinsically disordered proteins (IDPs) built up of repeating units and they can demonstrate two types of thermoresponsive phase behavior. Systems characterized by lower critical solution temperatures (LCST) undergo phase separation above the LCST whereas systems characterized by upper critical solution temperatures (UCST) undergo phase separation below the UCST. There is congruence between thermoresponsive coil-globule transitions and phase behavior whereby the theta temperatures above or below which the IDPs transition from coils to globules serve as useful proxies for the LCST / UCST values. This implies that one can design sequences with desired values for the theta temperature with either increasing or decreasing radii of gyration above the theta temperature. Here, we show that the Monte Carlo simulations performed in the so-called intrinsic solvation (IS) limit version of the temperature-dependent the ABSINTH (self-Assembly of Biomolecules Studied by an Implicit, Novel, Tunable Hamiltonian) implicit solvation model, yields a useful heuristic for discriminating between sequences with known LCST versus UCST phase behavior. Accordingly, we use this heuristic in a supervised approach, integrate it with a genetic algorithm, combine this with IS limit simulations, and demonstrate that novel sequences can be designed with LCST phase behavior. These calculations are aided by direct estimates of temperature dependent free energies of solvation for model compounds that are derived using the polarizable AMOEBA (atomic multipole optimized energetics for biomolecular applications) forcefield. To demonstrate the validity of our designs, we calculate coil-globule transition profiles using the full ABSINTH model and combine these with Gaussian Cluster Theory calculations to establish the LCST phase behavior of designed IDPs.

q-Canonical Monte Carlo Sampling for Modeling the Linkage between Charge Regulation and Conformational Equilibria of Peptides.

The overall charge content and the patterning of charged residues have a profound impact on the conformational ensembles adopted by intrinsically disordered proteins. These parameters can be altered by charge regulation, which refers to the effects of post-translational modifications, pH-dependent changes to charge, and conformational fluctuations that modify the pKa values of ionizable residues. Although atomistic simulations have played a prominent role in uncovering the major sequence-ensemble relationships of IDPs, most simulations assume fixed charge states for ionizable residues. This may lead to erroneous estimates for conformational equilibria if they are linked to charge regulation. Here, we report the development of a new method we term q-canonical Monte Carlo sampling for modeling the linkage between charge regulation and conformational equilibria. The method, which is designed to be interoperable with the ABSINTH implicit solvation model, operates as follows: For a protein sequence with n ionizable residues, we start with all 2n charge microstates and use a criterion based on model compound pKa values to prune down to a subset of thermodynamically relevant charge microstates. This subset is then grouped into mesostates, where all microstates that belong to a mesostate have the same net charge. Conformational distributions, drawn from a canonical ensemble, are generated for each of the charge microstates that make up a mesostate using a method we designate as proton walk sampling. This method combines Metropolis Monte Carlo sampling in conformational space with an auxiliary Markov process that enables interconversions between charge microstates along a mesostate. Proton walk sampling helps identify the most likely charge microstate per mesostate. We then use thermodynamic integration aided by the multistate Bennett acceptance ratio method to estimate the free energies for converting between mesostates. These free energies are then combined with the per-microstate weights along each mesostate to estimate standard state free energies and pH-dependent free energies for all thermodynamically relevant charge microstates. The results provide quantitative estimates of the probabilities and preferred conformations associated with every thermodynamically accessible charge microstate. We showcase the application of q-canonical sampling using two model systems. The results establish the soundness of the method and the importance of charge regulation in systems characterized by conformational heterogeneity.

NMR and Computation Reveal a Pressure-Sensitive Folded Conformation of Trp-Cage.

Beyond defining the structure and stability of folded states of proteins, primary amino acid sequences determine all of the features of their conformational landscapes. Characterizing how sequence modulates the population of protein excited states or folding pathways requires atomic level detailed structural and energetic information. Such insight is essential for improving protein design strategies, as well as for interpreting protein evolution. Here, high pressure NMR and molecular dynamics simulations were combined to probe the conformational landscape of a small model protein, the tryptophan cage variant, Tc5b. Pressure effects on protein conformation are based on volume differences between states, providing a subtle continuous variable for perturbing conformations. 2D proton TOCSY spectra of Tc5b were acquired as a function of pressure at different temperature, pH, and urea concentration. In contrast to urea and pH which lead to unfolding of Tc5b, pressure resulted in modulation of the structures that are populated within the folded state basin. The results of molecular dynamics simulations on Tc5b displayed remarkable agreement with the NMR data. Principal component analysis identified two structural subensembles in the folded state basin, one of which was strongly destabilized by pressure. The pressure-dependent structural perturbations observed by NMR coincided precisely with the changes in secondary structure associated with the shifting populations in the folded state basin observed in the simulations. These results highlight the deep structural insight afforded by pressure perturbation in conjunction with high resolution experimental and advanced computational tools.