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Highly disordered complexes between oppositely charged intrinsically disordered proteins present a new paradigm of biomolecular interactions. Here, we investigate the driving forces of such interactions for the example of the highly positively charged linker histone H1 and its highly negatively charged chaperone, prothymosin α (ProTα). Temperature-dependent single-molecule Förster resonance energy transfer (FRET) experiments and isothermal titration calorimetry reveal ProTα-H1 binding to be enthalpically unfavorable, and salt-dependent affinity measurements suggest counterion release entropy to be an important thermodynamic driving force. Using single-molecule FRET, we also identify ternary complexes between ProTα and H1 in addition to the heterodimer at equilibrium and show how they contribute to the thermodynamics observed in ensemble experiments. Finally, we explain the observed thermodynamics quantitatively with a mean-field polyelectrolyte theory that treats counterion release explicitly. ProTα-H1 complex formation resembles the interactions between synthetic polyelectrolytes, and the underlying principles are likely to be of broad relevance for interactions between charged biomolecules in general.

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Proteins and nucleic acids can phase-separate in the cell to form concentrated biomolecular condensates1-4. The functions of condensates span many length scales: they modulate interactions and chemical reactions at the molecular scale5, organize biochemical processes at the mesoscale6 and compartmentalize cells4. Understanding the underlying mechanisms of these processes will require detailed knowledge of the rich dynamics across these scales7. The mesoscopic dynamics of biomolecular condensates have been extensively characterized8, but their behaviour at the molecular scale has remained more elusive. Here, as an example of biomolecular phase separation, we study complex coacervates of two highly and oppositely charged disordered human proteins9. Their dense phase is 1,000 times more concentrated than the dilute phase, and the resulting percolated interaction network10 leads to a bulk viscosity 300 times greater than that of water. However, single-molecule spectroscopy optimized for measurements within individual droplets reveals that at the molecular scale, the disordered proteins remain exceedingly dynamic, with their chain configurations interconverting on submicrosecond timescales. Massive all-atom molecular dynamics simulations reproduce the experimental observations and explain this apparent discrepancy: the underlying interactions between individual charged side chains are short-lived and exchange on a pico- to nanosecond timescale. Our results indicate that, despite the high macroscopic viscosity of phase-separated systems, local biomolecular rearrangements required for efficient reactions at the molecular scale can remain rapid.

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Single-molecule Förster resonance energy transfer (FRET) is a versatile technique for probing the structure and dynamics of biomolecules even in heterogeneous ensembles. However, because of the limited fluorescence brightness per molecule and the relatively long fluorescence lifetimes, probing ultrafast structural dynamics in the nanosecond time scale has thus far been very challenging. Here, we demonstrate that nanophotonic fluorescence enhancement in zero-mode waveguides enables measurements of previously inaccessible low-nanosecond dynamics by dramatically improving time resolution and reduces data acquisition times by more than an order of magnitude. As a prototypical example, we use this approach to probe the dynamics of a short intrinsically disordered peptide that were previously inaccessible with single-molecule FRET measurements. We show that we are now able to detect the low-nanosecond correlations in this peptide, and we obtain a detailed interpretation of the underlying distance distributions and dynamics in conjunction with all-atom molecular dynamics simulations, which agree remarkably well with the experiments. We expect this combined approach to be widely applicable to the investigation of very rapid biomolecular dynamics.

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A key regulatory process during Drosophila development is the localized suppression of the hunchback mRNA translation at the posterior, which gives rise to a hunchback gradient governing the formation of the anterior-posterior body axis. This suppression is achieved by a concerted action of Brain Tumour (Brat), Pumilio (Pum) and Nanos. Each protein is necessary for proper Drosophila development. The RNA contacts have been elucidated for the proteins individually in several atomic-resolution structures. However, the interplay of all three proteins during RNA suppression remains a long-standing open question. Here, we characterize the quaternary complex of the RNA-binding domains of Brat, Pum and Nanos with hunchback mRNA by combining NMR spectroscopy, SANS/SAXS, XL/MS with MD simulations and ITC assays. The quaternary hunchback mRNA suppression complex comprising the RNA binding domains is flexible with unoccupied nucleotides functioning as a flexible linker between the Brat and Pum-Nanos moieties of the complex. Moreover, the presence of the Pum-HD/Nanos-ZnF complex has no effect on the equilibrium RNA binding affinity of the Brat RNA binding domain. This is in accordance with previous studies, which showed that Brat can suppress mRNA independently and is distributed uniformly throughout the embryo.

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Small-angle X-ray scattering (SAXS) is a widely used experimental technique, providing structural and dynamic insight into soft-matter complexes and biomolecules under near-native conditions. However, interpreting the one-dimensional scattering profiles in terms of three-dimensional structures and ensembles remains challenging, partly because it is poorly understood how structural information is encoded along the measured scattering angle. We combined all-atom SAXS-restrained ensemble simulations, simplified continuum models, and SAXS experiments of a n-dodecyl-ß-d-maltoside (DDM) micelle to decipher the effects of model asymmetry, shape fluctuations, atomic disorder, and atomic details on SAXS curves. Upon interpreting the small-angle regime, we find remarkable agreement between (i) a two-component triaxial ellipsoid model fitted against the data and (ii) a SAXS-refined all-atom ensemble. However, continuum models fail at wider angles, even if they account for shape fluctuations, disorder, and asymmetry of the micelle. We conclude that modeling atomic details is mandatory for explaining SAXS curves at wider angles.

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Small-angle X-ray scattering (SAXS) is a popular experimental technique used to obtain structural information on biomolecules in solution. SAXS is sensitive to the overall electron density contrast between the biomolecule and the buffer, including contrast contributions from the hydration layer and the ion cloud. This property may be used advantageously to probe the properties of the ion cloud around charged biomolecules. However, in turn, contributions from the hydration layer and ion cloud may complicate the interpretation of the data, because these contributions must be modelled during structure validation and refinement. In this work, we quantified the influence of the ion cloud on SAXS curves of two charged proteins, bovine serum albumin (BSA) and glucose isomerase (GI), solvated in five different alkali chloride buffers of 100 mM or 500 mM concentrations. We compared three computational methods of varying physical detail, for deriving the ion cloud effect on the radius of gyration Rg of the proteins, namely (i) atomistic molecular dynamics simulations in conjunction with explicit-solvent SAXS calculations, (ii) non-linear Poisson-Boltzmann calculations, and (iii) a simple spherical model in conjunction with linearized Poisson-Boltzmann theory. The calculations for BSA are validated against experimental data. We find favorable agreement among the three computational methods and the experiment, suggesting that the influence of the ion cloud on Rg, as detected by SAXS, may be predicted with nearly analytic calculations. Our analysis further suggests that the ion cloud effect on Rg is dominated by the long-range distribution of the ions around the proteins, as described by Debye-Hückel theory, whereas the local salt structure near the protein surface plays a minor role.

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In-solution small-angle X-ray and neutron scattering (SAXS/SANS) have become popular methods to characterize the structure of membrane proteins, solubilized by either detergents or nanodiscs. SANS studies of protein-detergent complexes usually require deuterium-labeled proteins or detergents, which in turn often lead to problems in their expression or purification. Here, we report an approach whose novelty is the combined analysis of SAXS and SANS data from an unlabeled membrane protein complex in solution in two complementary ways. First, an explicit atomic analysis, including both protein and detergent molecules, using the program WAXSiS, which has been adapted to predict SANS data. Second, the use of MONSA which allows one to discriminate between detergent head- and tail-groups in an ab initio approach. Our approach is readily applicable to any detergent-solubilized protein and provides more detailed structural information on protein-detergent complexes from unlabeled samples than SAXS or SANS alone.

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Surfactants have found a wide range of industrial and scientific applications. In particular, detergent micelles are used as lipid membrane mimics to solubilize membrane proteins for functional and structural characterization. However, an atomic-level understanding of surfactants remains limited because many experiments provide only low-resolution structural information on surfactant aggregates. In this work, small-angle X-ray scattering is combined with molecular dynamics simulations to derive fully atomic models of two maltoside micelles at temperatures between 10 °C and 70 °C. The micelles take the shape of general tri-axial ellipsoids and decrease in size and aggregation number with increasing temperature. Density profiles of hydrophobic groups and water along the three principal axes reveal that the minor micelle axis closely mimics lipid membranes. The results suggest that coupling atomic simulations with low-resolution data allows the structural characterization of surfactant aggregates.