Mechanistic View of hnRNPA2 Low-Complexity Domain Structure, Interactions, and Phase Separation Altered by Mutation and Arginine Methylation.

hnRNPA2, a component of RNA-processing membraneless organelles, forms inclusions when mutated in a syndrome characterized by the degeneration of neurons (bearing features of amyotrophic lateral sclerosis [ALS] and frontotemporal dementia), muscle, and bone. Here we provide a unified structural view of hnRNPA2 self-assembly, aggregation, and interaction and the distinct effects of small chemical changes-disease mutations and arginine methylation-on these assemblies. The hnRNPA2 low-complexity (LC) domain is compact and intrinsically disordered as a monomer, retaining predominant disorder in a liquid-liquid phase-separated form. Disease mutations D290V and P298L induce aggregation by enhancing and extending, respectively, the aggregation-prone region. Co-aggregating in disease inclusions, hnRNPA2 LC directly interacts with and induces phase separation of TDP-43. Conversely, arginine methylation reduces hnRNPA2 phase separation, disrupting arginine-mediated contacts. These results highlight the mechanistic role of specific LC domain interactions and modifications conserved across many hnRNP family members but altered by aggregation-causing pathological mutations.

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

Liquid-liquid phase separation (LLPS) is involved in the formation of membraneless organelles (MLOs) associated with RNA processing. The RNA-binding protein TDP-43 is present in several MLOs, undergoes LLPS, and has been linked to the pathogenesis of amyotrophic lateral sclerosis (ALS). While some ALS-associated mutations in TDP-43 disrupt self-interaction and function, here we show that designed single mutations can enhance TDP-43 assembly and function via modulating helical structure. Using molecular simulation and NMR spectroscopy, we observe large structural changes upon dimerization of TDP-43. Two conserved glycine residues (G335 and G338) are potent inhibitors of helical extension and helix-helix interaction, which are removed in part by variants at these positions, including the ALS-associated G335D. Substitution to helix-enhancing alanine at either of these positions dramatically enhances phase separation in vitro and decreases fluidity of phase-separated TDP-43 reporter compartments in cells. Furthermore, G335A increases TDP-43 splicing function in a minigene assay. Therefore, the TDP-43 helical region serves as a short but uniquely tunable module where application of biophysical principles can precisely control assembly and function in cellular and synthetic biology applications of LLPS.

Phosphorylation of the FUS low-complexity domain disrupts phase separation, aggregation, and toxicity.

Neuronal inclusions of aggregated RNA-binding protein fused in sarcoma (FUS) are hallmarks of ALS and frontotemporal dementia subtypes. Intriguingly, FUS's nearly uncharged, aggregation-prone, yeast prion-like, low sequence-complexity domain (LC) is known to be targeted for phosphorylation. Here we map in vitro and in-cell phosphorylation sites across FUS LC We show that both phosphorylation and phosphomimetic variants reduce its aggregation-prone/prion-like character, disrupting FUS phase separation in the presence of RNA or salt and reducing FUS propensity to aggregate. Nuclear magnetic resonance spectroscopy demonstrates the intrinsically disordered structure of FUS LC is preserved after phosphorylation; however, transient domain collapse and self-interaction are reduced by phosphomimetics. Moreover, we show that phosphomimetic FUS reduces aggregation in human and yeast cell models, and can ameliorate FUS-associated cytotoxicity. Hence, post-translational modification may be a mechanism by which cells control physiological assembly and prevent pathological protein aggregation, suggesting a potential treatment pathway amenable to pharmacologic modulation.

Effect of heterochiral inversions on the structure of a ß-hairpin peptide.

We study computationally a family of ß-hairpin peptides with systematically introduced chiral inversions, in explicit water, and we investigate the extent to which the backbone structure is able to fold in the presence of heterochiral perturbations. In contrast to the recently investigated case of a helical peptide, we do not find a monotonic change in secondary structure content as a function of the number of L- to D-inversions. The effects of L- to D-inversions are instead found to be highly position-specific. Additionally, in contrast to the helical peptide, some inversions increase the stability of the folded peptide: in such cases, we compute an increase in ß-sheet content in the aqueous solution equilibrium ensemble. However, the tertiary structures of the stable (folded) configurations for peptides for which inversions cause an increase in ß-sheet content show differences from one another, as well as from the native fold of the nonchirally perturbed ß-hairpin. Our results suggest that although some chiral perturbations can increase folding stability, chirally perturbed proteins may still underperform functionally, given the relationship between structure and function.

Surface force measurements and simulations of mussel-derived peptide adhesives on wet organic surfaces.

Translating sticky biological molecules-such as mussel foot proteins (MFPs)-into synthetic, cost-effective underwater adhesives with adjustable nano- and macroscale characteristics requires an intimate understanding of the glue's molecular interactions. To help facilitate the next generation of aqueous adhesives, we performed a combination of surface forces apparatus (SFA) measurements and replica-exchange molecular dynamics (REMD) simulations on a synthetic, easy to prepare, Dopa-containing peptide (MFP-3s peptide), which adheres to organic surfaces just as effectively as its wild-type protein analog. Experiments and simulations both show significant differences in peptide adsorption on CH3-terminated (hydrophobic) and OH-terminated (hydrophilic) self-assembled monolayers (SAMs), where adsorption is strongest on hydrophobic SAMs because of orientationally specific interactions with Dopa. Additional umbrella-sampling simulations yield free-energy profiles that quantitatively agree with SFA measurements and are used to extract the adhesive properties of individual amino acids within the context of MFP-3s peptide adhesion, revealing a delicate balance between van der Waals, hydrophobic, and electrostatic forces.

Highly Disordered Amyloid-ß Monomer Probed by Single-Molecule FRET and MD Simulation.

Monomers of amyloid-ß (Aß) protein are known to be disordered, but there is considerable controversy over the existence of residual or transient conformations that can potentially promote oligomerization and fibril formation. We employed single-molecule Förster resonance energy transfer (FRET) spectroscopy with site-specific dye labeling using an unnatural amino acid and molecular dynamics simulations to investigate conformations and dynamics of Aß isoforms with 40 (Aß40) and 42 residues (Aß42). The FRET efficiency distributions of both proteins measured in phosphate-buffered saline at room temperature show a single peak with very similar FRET efficiencies, indicating there is apparently only one state. 2D FRET efficiency-donor lifetime analysis reveals, however, that there is a broad distribution of rapidly interconverting conformations. Using nanosecond fluorescence correlation spectroscopy, we measured the timescale of the fluctuations between these conformations to be ∼35 ns, similar to that of disordered proteins. These results suggest that both Aß40 and Aß42 populate an ensemble of rapidly reconfiguring unfolded states, with no long-lived conformational state distinguishable from that of the disordered ensemble. To gain molecular-level insights into these observations, we performed molecular dynamics simulations with a force field optimized to describe disordered proteins. We find, as in experiments, that both peptides populate configurations consistent with random polymer chains, with the vast majority of conformations lacking significant secondary structure, giving rise to very similar ensemble-averaged FRET efficiencies.

Inferring properties of disordered chains from FRET transfer efficiencies.

Förster resonance energy transfer (FRET) is a powerful tool for elucidating both structural and dynamic properties of unfolded or disordered biomolecules, especially in single-molecule experiments. However, the key observables, namely, the mean transfer efficiency and fluorescence lifetimes of the donor and acceptor chromophores, are averaged over a broad distribution of donor-acceptor distances. The inferred average properties of the ensemble therefore depend on the form of the model distribution chosen to describe the distance, as has been widely recognized. In addition, while the distribution for one type of polymer model may be appropriate for a chain under a given set of physico-chemical conditions, it may not be suitable for the same chain in a different environment so that even an apparently consistent application of the same model over all conditions may distort the apparent changes in chain dimensions with variation of temperature or solution composition. Here, we present an alternative and straightforward approach to determining ensemble properties from FRET data, in which the polymer scaling exponent is allowed to vary with solution conditions. In its simplest form, it requires either the mean FRET efficiency or fluorescence lifetime information. In order to test the accuracy of the method, we have utilized both synthetic FRET data from implicit and explicit solvent simulations for 30 different protein sequences, and experimental single-molecule FRET data for an intrinsically disordered and a denatured protein. In all cases, we find that the inferred radii of gyration are within 10% of the true values, thus providing higher accuracy than simpler polymer models. In addition, the scaling exponents obtained by our procedure are in good agreement with those determined directly from the molecular ensemble. Our approach can in principle be generalized to treating other ensemble-averaged functions of intramolecular distances from experimental data.

Diffusive Dynamics of Contact Formation in Disordered Polypeptides.

Experiments measuring contact formation between probes in disordered chains provide information on the fundamental time scales relevant to protein folding. However, their interpretation usually relies on one-dimensional (1D) diffusion models, as do many experiments probing a single distance. Here, we use all-atom molecular simulations to capture both the time scales of contact formation, as well as the scaling with peptide length for tryptophan triplet quenching experiments, revealing the sensitivity of the experimental quenching times to the configurational space explored by the chain. We find a remarkable consistency between the results of the full calculation and from Szabo-Schulten-Schulten theory applied to a 1D diffusion model, supporting the validity of such models. The significant reduction in diffusion coefficient at the small probe separations which most influence quenching rate, suggests that contact formation and Förster resonance energy transfer correlation experiments provide complementary information on diffusivity.

Folding thermodynamics of ß-hairpins studied by replica-exchange molecular dynamics simulations.

We study the differences in folding stability of ß-hairpin peptides, including GB1 hairpin and a point mutant GB1 K10G, as well as tryptophan zippers (TrpZips): TrpZip1, TrpZip2, TrpZip3-1, and TrpZip4. By performing replica-exchange molecular dynamics simulations with Amber03* force field (a modified version of Amber ff03) in explicit solvent, we observe ab initio folding of all the peptides except TrpZip3-1, which is experimentally known to be the least stable among the peptides studied here. By calculating the free energies of unfolding of the peptides at room temperature and folding midpoint temperatures for thermal unfolding of peptides, we find that TrpZip4 and GB1 K10G peptides are the most stable ß-hairpins followed by TrpZip1, GB1, and TrpZip2 in the given order. Hence, the proposed K10G mutation of GB1 peptide results in enhanced stability compared to wild-type GB1. An important goal of our study is to test whether simulations with Amber 03* model can reproduce experimentally predicted folding stability differences between these peptides. While the stabilities of GB1 and TrpZip1 yield close agreement with experiment, TrpZip2 is found to be less stable than predicted by experiment. However, as heterogenous folding of TrpZip2 may yield divergent thermodynamic parameters by different spectroscopic methods, mismatching of results with previous experimental values are not conclusive of model shortcomings. For most of the cases, molecular simulations with Amber03* can successfully reproduce experimentally known differences between the mutated peptides, further highlighting the predictive capabilities of current state-of-the-art all-atom protein force fields.

To What Extent Does Surface Hydrophobicity Dictate Peptide Folding and Stability near Surfaces?

Protein-surface interactions are ubiquitous in both the cellular setting and in modern bioengineering devices, but how such interactions impact protein stability is not well understood. We investigate the folding of the GB1 hairpin peptide in the presence of self-assembled monolayers and graphite like surfaces using replica exchange molecular dynamics simulations. By varying surface hydrophobicity, and decoupling direct protein-surface interactions from water-mediated interactions, we show that surface wettability plays a surprisingly minor role in dictating protein stability. For both the ß-hairpin GB1 and the helical miniprotein TrpCage, adsorption and stability is largely dictated by the nature of the direct chemical interactions between the protein and the surface. Independent of the surface hydrophobicity profile, strong protein-surface interactions destabilize the folded structure while weak interactions stabilize it.

Modest influence of FRET chromophores on the properties of unfolded proteins.

Single-molecule Förster resonance energy transfer (FRET) experiments are often used to study the properties of unfolded and intrinsically disordered proteins. Because of their large extinction coefficients and quantum yields, synthetic heteroaromatic chromophores covalently linked to the protein are often used as donor and acceptor fluorophores. A key issue in the interpretation of such experiments is the extent to which the properties of the unfolded chain may be affected by the presence of these chromophores. In this article, we investigate this question using all-atom explicit solvent replica exchange molecular dynamics simulations of three different unfolded or intrinsically disordered proteins. We find that the secondary structure and long-range contacts are largely the same in the presence or absence of the fluorophores, and that the dimensions of the chain with and without chromophores are similar. This suggests that, at least in the cases studied, extrinsic fluorophores have little effect on the structural properties of unfolded or disordered proteins. We also find that the critical FRET orientational factor κ(2), has an average value and equilibrium distribution very close to that expected for isotropic orientations, which supports one of the assumptions frequently made when interpreting FRET efficiency in terms of distances.

Optimizing the Martini 3 Force Field Reveals the Effects of the Intricate Balance between Protein-Water Interaction Strength and Salt Concentration on Biomolecular Condensate Formation.

Condensation/dissolution has become a widely acknowledged biological macromolecular assembly phenomenon in subcellular compartmentalization. The MARTINI force field offers a coarse-grained protein model with a resolution that preserves molecular details with an explicit (CG) solvent. Despite its relatively higher resolution, it can still achieve condensate formation in a reasonable computing time with explicit solvent and ionic species. Therefore, it is highly desirable to tune this force field to be able to reproduce the experimentally observed properties of the condensate formation. In this work, we studied the condensate formation of the low-sequence complexity domain of fused in sarcoma protein using a MARTINI 3 force field by systematically modifying (increasing) the protein-water interaction strength and varying the salt concentration. We found that the condensate formation is sensitive both to the protein-water interaction strength and the presence of salt. While the unmodified MARTINI force field yields a complete collapse of proteins into one dense phase (i.e., no dilute phase), we reported a range of modified protein-water interaction strength that is capable of capturing the experimentally found transfer free energy between dense and dilute phases. We also found that the condensates lose their spherical shape upon the addition of salt, especially when the protein-water interactions are weak. Interchain amino acid contact map analysis showed one explanation for this observation: the protein-protein contact fraction reduces as salt is added to systems (when the protein-water interactions are weak), consistent with electrostatic screening effects. This reduction might be responsible for the condensates becoming nonspherical upon the addition of salt by reducing the need for minimizing the interfacial area. However, as the protein-water interactions become stronger to the extent that makes the transfer free energy agree well with experimentally observed transfer free energy, we found an increase in the protein-protein contact fraction upon the addition of salt, consistent with the salting-out effects. Therefore, we concluded that there is an intricate balance between screening effects and salting-out effects upon the addition of salt and this balance is highly sensitive to the strength of protein-water interactions.

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop.

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. We also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

The molecular picture of the local environment in a stable model coacervate.

Complex coacervates play essential roles in various biological processes and applications. Although substantial progress has been made in understanding the molecular interactions driving complex coacervation, the mechanisms stabilizing coacervates against coalescence remain experimentally challenging and not fully elucidated. We recently showed that polydiallyldimethylammonium chloride (PDDA) and adenosine triphosphate (ATP) coacervates stabilize upon their transfer to deionized (DI) water. Here, we perform molecular dynamics simulations of PDDA-ATP coacervates in supernatant and DI water, to understand the ion dynamics and structure within stable coacervates. We found that transferring the coacervates to DI water results in an immediate ejection of a significant fraction of small ions (Na+ and Cl-) from the surface of the coacervates to DI water. We also observed a notable reduction in the mobility of these counterions in coacervates when in DI water, both in the cluster-forming and slab simulations, together with a lowered displacement of PDDA and ATP. These results suggest that the initial ejection of the ions from the coacervates in DI water may induce an interfacial skin layer formation, inhibiting further mobility of ions in the skin layer.

Comparison of On-the-Fly Probability Enhanced Sampling and Parallel Tempering Combined with Metadynamics for Atomistic Simulations of RNA Tetraloop Folding.

Atomistic simulations with reliable models are extremely useful in providing exquisitely detailed pictures of biomolecular phenomena that are not always accessible to experiments. One such biomolecular phenomenon is RNA folding, which often requires exhaustive simulations with combined advanced sampling techniques. In this work, we employed the multithermal-multiumbrella on-the-fly probability enhanced sampling (MM-OPES) technique and compared it against combined parallel tempering and metadynamics simulations. We found that MM-OPES simulations were successful in reproducing the free energy surfaces from combined parallel tempering and metadynamics simulations. Importantly, we also investigated a wide range of temperature sets (minimum and maximum temperatures) for MM-OPES simulations in order to identify some guidelines for deciding the temperature limits for an accurate and efficient exploration of the free energy landscapes. We found that most temperature sets yielded almost the same accuracy in reproducing the free energy surface at the ambient conditions as long as (i) the maximum temperature is reasonably high, (ii) the temperature at which we run the simulation is reasonably high (in our simulations, running temperature is defined as [minimum temperature + maximum temperature]/2), and (iii) the effective sample size at the temperature of interest is statistically reasonable. In terms of the computational cost, all MM-OPES simulations were nearly 4 times less costly than the combined parallel tempering and metadynamics simulations. We concluded that the demanding combined parallel tempering and metadynamics simulations can safely be replaced with approximately 4 times less costly MM-OPES simulations (with carefully selected temperature limits) to obtain the same information.

Thermodynamics of DNA Hybridization from Atomistic Simulations.

Studying DNA hybridization equilibrium at atomistic length scales, either via molecular dynamics (MD) or through commonly used advanced sampling approaches, is notoriously difficult. In this work, we describe an order-parameter-based advanced sampling technique to calculate the free energy of hybridization, and estimate the melting temperature of DNA oligomers at atomistic resolution. The free energy landscapes are reported as a function of a native-topology-based order parameter for the Drew-Dickerson dodecamer and for a range of DNA decamer sequences of different GC content. Our estimated melting temperatures match the experimental numbers within ±15 °C. As a test of the numerical reliability of the procedures employed, it was verified that the predicted free energy surfaces and melting temperatures of the d- and l-enantiomers of the Drew-Dickerson dodecamer were indistinguishable within numerical accuracy.

A Computational Study of RNA Tetraloop Thermodynamics, Including Misfolded States.

An important characteristic of RNA folding is the adoption of alternative configurations of similar stability, often referred to as misfolded configurations. These configurations are considered to compete with correctly folded configurations, although their rigorous thermodynamic and structural characterization remains elusive. Tetraloop motifs found in large ribozymes are ideal systems for an atomistically detailed computational quantification of folding free energy landscapes and the structural characterization of their constituent free energy basins, including nonnative states. In this work, we studied a group of closely related 10-mer tetraloops using a combined parallel tempering and metadynamics technique that allows a reliable sampling of the free energy landscapes, requiring only knowledge that the stem folds into a canonical A-RNA configuration. We isolated and analyzed unfolded, folded, and misfolded populations that correspond to different free energy basins. We identified a distinct misfolded state that has a stability very close to that of the correctly folded state. This misfolded state contains a predominant population that shares the same structural features across all tetraloops studied here and lacks the noncanonical A-G base pair in its loop portion. Further analysis performed with biased trajectories showed that although this competitive misfolded state is not an essential intermediate, it is visited in most of the transitions from unfolded to correctly folded states. Moreover, the tetraloops can transition from this misfolded state to the correctly folded state without requiring extensive unfolding.

Second critical point in two realistic models of water.

The hypothesis that water has a second critical point at deeply supercooled conditions was formulated to provide a thermodynamically consistent interpretation of numerous experimental observations. A large body of work has been devoted to verifying or falsifying this hypothesis, but no unambiguous experimental proof has yet been found. Here, we use histogram reweighting and large-system scattering calculations to investigate computationally two molecular models of water, TIP4P/2005 and TIP4P/Ice, widely regarded to be among the most accurate classical force fields for this substance. We show that both models have a metastable liquid-liquid critical point at deeply supercooled conditions and that this critical point is consistent with the three-dimensional Ising universality class.

Computational investigation of retro-isomer equilibrium structures: Intrinsically disordered, foldable, and cyclic peptides.

We use all-atom modeling and advanced-sampling molecular dynamics simulations to investigate quantitatively the effect of peptide bond directionality on the equilibrium structures of four linear (two foldable, two disordered) and two cyclic peptides. We find that the retro forms of cyclic and foldable linear peptides adopt distinctively different conformations compared to their parents. While the retro form of a linear intrinsically disordered peptide with transient secondary structure fails to reproduce a secondary structure content similar to that of its parent, the retro form of a shorter disordered linear peptide shows only minor differences compared to its parent.

The Handedness of DNA Assembly around Carbon Nanotubes Is Determined by the Chirality of DNA.

Single-stranded DNA chains enable postsynthesis sorting of single-walled carbon nanotubes (CNTs) according to their diameter and helicity by wrapping helically around CNT surfaces. Both DNA chains and CNTs in these CNT-DNA conjugates are intrinsically chiral. Using a single-stranded DNA chain in both of its chiral realizations, we systematically study cross-chiral interactions between DNA and CNTs by varying the helicity of CNTs within a relatively narrow range of diameters. We find that regardless of the helicity or handedness of the carbon nanotube, the chirality of DNA dictates the handedness of its predominant helical wrap around carbon nanotubes.