Extreme dynamics in a biomolecular condensate.

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.

On the role of native contact cooperativity in protein folding.

The consistency of energy landscape theory predictions with available experimental data, as well as direct evidence from molecular simulations, have shown that protein folding mechanisms are largely determined by the contacts present in the native structure. As expected, native contacts are generally energetically favorable. However, there are usually at least as many energetically favorable nonnative pairs owing to the greater number of possible nonnative interactions. This apparent frustration must therefore be reduced by the greater cooperativity of native interactions. In this work, we analyze the statistics of contacts in the unbiased all-atom folding trajectories obtained by Shaw and coworkers, focusing on the unfolded state. By computing mutual cooperativities between contacts formed in the unfolded state, we show that native contacts form the most cooperative pairs, while cooperativities among nonnative or between native and nonnative contacts are typically much less favorable or even anticooperative. Furthermore, we show that the largest network of cooperative interactions observed in the unfolded state consists mainly of native contacts, suggesting that this set of mutually reinforcing interactions has evolved to stabilize the native state.

Theoretical and Data-Driven Approaches for Biomolecular Condensates.

Biomolecular condensation processes are increasingly recognized as a fundamental mechanism that living cells use to organize biomolecules in time and space. These processes can lead to the formation of membraneless organelles that enable cells to perform distinct biochemical processes in controlled local environments, thereby supplying them with an additional degree of spatial control relative to that achieved by membrane-bound organelles. This fundamental importance of biomolecular condensation has motivated a quest to discover and understand the molecular mechanisms and determinants that drive and control this process. Within this molecular viewpoint, computational methods can provide a unique angle to studying biomolecular condensation processes by contributing the resolution and scale that are challenging to reach with experimental techniques alone. In this Review, we focus on three types of dry-lab approaches: theoretical methods, physics-driven simulations and data-driven machine learning methods. We review recent progress in using these tools for probing biomolecular condensation across all three fields and outline the key advantages and limitations of each of the approaches. We further discuss some of the key outstanding challenges that we foresee the community addressing next in order to develop a more complete picture of the molecular driving forces behind biomolecular condensation processes and their biological roles in health and disease.

Martini 3: a general purpose force field for coarse-grained molecular dynamics.

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

Extreme disorder in an ultrahigh-affinity protein complex.

Molecular communication in biology is mediated by protein interactions. According to the current paradigm, the specificity and affinity required for these interactions are encoded in the precise complementarity of binding interfaces. Even proteins that are disordered under physiological conditions or that contain large unstructured regions commonly interact with well-structured binding sites on other biomolecules. Here we demonstrate the existence of an unexpected interaction mechanism: the two intrinsically disordered human proteins histone H1 and its nuclear chaperone prothymosin-α associate in a complex with picomolar affinity, but fully retain their structural disorder, long-range flexibility and highly dynamic character. On the basis of closely integrated experiments and molecular simulations, we show that the interaction can be explained by the large opposite net charge of the two proteins, without requiring defined binding sites or interactions between specific individual residues. Proteome-wide sequence analysis suggests that this interaction mechanism may be abundant in eukaryotes.

Atomic view of cosolute-induced protein denaturation probed by NMR solvent paramagnetic relaxation enhancement.

The cosolvent effect arises from the interaction of cosolute molecules with a protein and alters the equilibrium between native and unfolded states. Denaturants shift the equilibrium toward the latter, while osmolytes stabilize the former. The molecular mechanism whereby cosolutes perturb protein stability is still the subject of considerable debate. Probing the molecular details of the cosolvent effect is experimentally challenging as the interactions are very weak and transient, rendering them invisible to most conventional biophysical techniques. Here, we probe cosolute-protein interactions by means of NMR solvent paramagnetic relaxation enhancement together with a formalism we recently developed to quantitatively describe, at atomic resolution, the energetics and dynamics of cosolute-protein interactions in terms of a concentration normalized equilibrium average of the interspin distance, [Formula: see text], and an effective correlation time, τc The system studied is the metastable drkN SH3 domain, which exists in dynamic equilibrium between native and unfolded states, thereby permitting us to probe the interactions of cosolutes with both states simultaneously under the same conditions. Two paramagnetic cosolute denaturants were investigated, one neutral and the other negatively charged, differing in the presence of a carboxyamide group versus a carboxylate. Our results demonstrate that attractive cosolute-protein backbone interactions occur largely in the unfolded state and some loop regions in the native state, electrostatic interactions reduce the [Formula: see text] values, and temperature predominantly impacts interactions with the unfolded state. Thus, destabilization of the native state in this instance arises predominantly as a consequence of interactions of the cosolutes with the unfolded state.

Treatment of sickle cell disease by increasing oxygen affinity of hemoglobin.

The issue of treating sickle cell disease with drugs that increase hemoglobin oxygen affinity has come to the fore with the US Food and Drug Administration approval in 2019 of voxelotor, the only antisickling drug approved since hydroxyurea in 1998. Voxelotor reduces sickling by increasing the concentration of the nonpolymerizing, high oxygen affinity R (oxy) conformation of hemoglobin S (HbS). Treatment of sickle cell patients with voxelotor increases Hb levels and decreases indicators of hemolysis, but with no indication as yet that it reduces the frequency of pain episodes. In this study, we used the allosteric model of Monod, Wyman, and Changeux to simulate whole-blood oxygen dissociation curves and red cell sickling in the absence and presence of voxelotor under the in vivo conditions of rapid oxygen pressure decreases. Our modeling agrees with results of experiments using a new robust assay, which shows the large, expected decrease in sickling from the drug. The modeling indicates, however, that the increase in oxygen delivery from reduced sickling is largely offset by the increase in oxygen affinity. The net result is that the drug increases overall oxygen delivery only at the very lowest oxygen pressures. However, reduction of sickling mitigates red cell damage and explains the observed decrease in hemolysis. More importantly, our modeling of in vivo oxygen dissociation, sickling, and oxygen delivery suggests that drugs that increase fetal Hb or decrease mean corpuscular hemoglobin concentration (MCHC) should be more therapeutically effective than drugs that increase oxygen affinity.

Cotranslational folding cooperativity of contiguous domains of α-spectrin.

Proteins synthesized in the cell can begin to fold during translation before the entire polypeptide has been produced, which may be particularly relevant to the folding of multidomain proteins. Here, we study the cotranslational folding of adjacent domains from the cytoskeletal protein α-spectrin using force profile analysis (FPA). Specifically, we investigate how the cotranslational folding behavior of the R15 and R16 domains are affected by their neighboring R14 and R16, and R15 and R17 domains, respectively. Our results show that the domains impact each other's folding in distinct ways that may be important for the efficient assembly of α-spectrin, and may reduce its dependence on chaperones. Furthermore, we directly relate the experimentally observed yield of full-length protein in the FPA assay to the force exerted by the folding protein in piconewtons. By combining pulse-chase experiments to measure the rate at which the arrested protein is converted into full-length protein with a Bell model of force-induced rupture, we estimate that the R16 domain exerts a maximal force on the nascent chain of ∼15 pN during cotranslational folding.

Single-molecule Detection of Ultrafast Biomolecular Dynamics with Nanophotonics.

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.

Design of a Protein with Improved Thermal Stability by an Evolution-Based Generative Model.

Efficient design of functional proteins with higher thermal stability remains challenging especially for highly diverse sequence variants. Considering the evolutionary pressure on protein folds, sequence design optimizing evolutionary fitness could help designing folds with higher stability. Using a generative evolution fitness model trained to capture variation patterns in natural sequences, we designed artificial sequences of a proteinaceous inhibitor of pectin methylesterase enzymes. These inhibitors have considerable industrial interest to avoid phase separation in fruit juice manufacturing or reduce methanol in distillates, averting chromatographic passages triggering unwanted aroma loss. Six out of seven designs with up to 30 % divergence to other inhibitor sequences are functional and two have improved thermal stability. This method can improve protein stability expanding functional protein sequence space, with traits valuable for industrial applications and scientific research.

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.

Biomolecular Phase Separation: From Molecular Driving Forces to Macroscopic Properties.

Biological phase separation is known to be important for cellular organization, which has recently been extended to a new class of biomolecules that form liquid-like droplets coexisting with the surrounding cellular or extracellular environment. These droplets are termed membraneless organelles, as they lack a dividing lipid membrane, and are formed through liquid-liquid phase separation (LLPS). Elucidating the molecular determinants of phase separation is a critical challenge for the field, as we are still at the early stages of understanding how cells may promote and regulate functions that are driven by LLPS. In this review, we discuss the role that disorder, perturbations to molecular interactions resulting from sequence, posttranslational modifications, and various regulatory stimuli play on protein LLPS, with a particular focus on insights that may be obtained from simulation and theory. We finally discuss how these molecular driving forces alter multicomponent phase separation and selectivity.

Exploring the sequence fitness landscape of a bridge between protein folds.

Most foldable protein sequences adopt only a single native fold. Recent protein design studies have, however, created protein sequences which fold into different structures apon changes of environment, or single point mutation, the best characterized example being the switch between the folds of the GA and GB binding domains of streptococcal protein G. To obtain further insight into the design of sequences which can switch folds, we have used a computational model for the fitness landscape of a single fold, built from the observed sequence variation of protein homologues. We have recently shown that such coevolutionary models can be used to design novel foldable sequences. By appropriately combining two of these models to describe the joint fitness landscape of GA and GB, we are able to describe the propensity of a given sequence for each of the two folds. We have successfully tested the combined model against the known series of designed GA/GB hybrids. Using Monte Carlo simulations on this landscape, we are able to identify pathways of mutations connecting the two folds. In the absence of a requirement for domain stability, the most frequent paths go via sequences in which neither domain is stably folded, reminiscent of the propensity for certain intrinsically disordered proteins to fold into different structures according to context. Even if the folded state is required to be stable, we find that there is nonetheless still a wide range of sequences which are close to the transition region and therefore likely fold switches, consistent with recent estimates that fold switching may be more widespread than had been thought.

Atomistic mechanism of transmembrane helix association.

Transmembrane helix association is a fundamental step in the folding of helical membrane proteins. The prototypical example of this association is formation of the glycophorin dimer. While its structure and stability have been well-characterized experimentally, the detailed assembly mechanism is harder to obtain. Here, we use all-atom simulations within phospholipid membrane to study glycophorin association. We find that initial association results in the formation of a non-native intermediate, separated by a significant free energy barrier from the dimer with a native binding interface. We have used transition-path sampling to determine the association mechanism. We find that the mechanism of the initial bimolecular association to form the intermediate state can be mediated by many possible contacts, but seems to be particularly favoured by formation of non-native contacts between the C-termini of the two helices. On the other hand, the contacts which are key to determining progression from the intermediate to the native state are those which define the native binding interface, reminiscent of the role played by native contacts in determining folding of globular proteins. As a check on the simulations, we have computed association and dissociation rates from the transition-path sampling. We obtain results in reasonable accord with available experimental data, after correcting for differences in native state stability. Our results yield an atomistic description of the mechanism for a simple prototype of helical membrane protein folding.

Estimating transition path times and shapes from single-molecule photon trajectories: A simulation analysis.

In a two-state molecular system, transition paths comprise the portions of trajectories during which the system transits from one stable state to the other. Because of their low population, it is essentially impossible to obtain information on transition paths from experiments on a large sample of molecules. However, single-molecule experiments such as laser optical tweezers or Förster resonance energy transfer (FRET) spectroscopy have allowed transition-path durations to be estimated. Here, we use molecular simulations to test the methodology for obtaining information on transition paths in single-molecule FRET by generating photon trajectories from the distance trajectories obtained in the simulation. Encouragingly, we find that this maximum likelihood analysis yields transition-path times within a factor of 2-4 of the values estimated using a good coordinate for folding, but tends to systematically underestimate them. The underestimation can be attributed partly to the fact that the large changes in the end-end distance occur mostly early in a folding trajectory. However, even if the transfer efficiency is a good reaction coordinate for folding, the assumption that the transition-path shape is a step function still leads to an underestimation of the transition-path time as defined here. We find that allowing more flexibility in the form of the transition path model allows more accurate transition-path times to be extracted and points the way toward further improvements in methods for estimating transition-path time and transition-path shape.

A small single-domain protein folds through the same pathway on and off the ribosome.

In vivo, proteins fold and function in a complex environment subject to many stresses that can modulate a protein's energy landscape. One aspect of the environment pertinent to protein folding is the ribosome, since proteins have the opportunity to fold while still bound to the ribosome during translation. We use a combination of force and chemical denaturant (chemomechanical unfolding), as well as point mutations, to characterize the folding mechanism of the src SH3 domain both as a stalled ribosome nascent chain and free in solution. Our results indicate that src SH3 folds through the same pathway on and off the ribosome. Molecular simulations also indicate that the ribosome does not affect the folding pathway for this small protein. Taken together, we conclude that the ribosome does not alter the folding mechanism of this small protein. These results, if general, suggest the ribosome may exert a bigger influence on the folding of multidomain proteins or protein domains that can partially fold before the entire domain sequence is outside the ribosome exit tunnel.

Relation between single-molecule properties and phase behavior of intrinsically disordered proteins.

Proteins that undergo liquid-liquid phase separation (LLPS) have been shown to play a critical role in many physiological functions through formation of condensed liquid-like assemblies that function as membraneless organelles within biological systems. To understand how different proteins may contribute differently to these assemblies and their functions, it is important to understand the molecular driving forces of phase separation and characterize their phase boundaries and material properties. Experimental studies have shown that intrinsically disordered regions of these proteins are a major driving force, as many of them undergo LLPS in isolation. Previous work on polymer solution phase behavior suggests a potential correspondence between intramolecular and intermolecular interactions that can be leveraged to discover relationships between single-molecule properties and phase boundaries. Here, we take advantage of a recently developed coarse-grained framework to calculate the θ temperature [Formula: see text], the Boyle temperature [Formula: see text], and the critical temperature [Formula: see text] for 20 diverse protein sequences, and we show that these three properties are highly correlated. We also highlight that these correlations are not specific to our model or simulation methodology by comparing between different pairwise potentials and with data from other work. We, therefore, suggest that smaller simulations or experiments to determine [Formula: see text] or [Formula: see text] can provide useful insights into the corresponding phase behavior.

Folding pathway of an Ig domain is conserved on and off the ribosome.

Proteins that fold cotranslationally may do so in a restricted configurational space, due to the volume occupied by the ribosome. How does this environment, coupled with the close proximity of the ribosome, affect the folding pathway of a protein? Previous studies have shown that the cotranslational folding process for many proteins, including small, single domains, is directly affected by the ribosome. Here, we investigate the cotranslational folding of an all-ß Ig domain, titin I27. Using an arrest peptide-based assay and structural studies by cryo-EM, we show that I27 folds in the mouth of the ribosome exit tunnel. Simulations that use a kinetic model for the force dependence of escape from arrest accurately predict the fraction of folded protein as a function of length. We used these simulations to probe the folding pathway on and off the ribosome. Our simulations-which also reproduce experiments on mutant forms of I27-show that I27 folds, while still sequestered in the mouth of the ribosome exit tunnel, by essentially the same pathway as free I27, with only subtle shifts of critical contacts from the C to the N terminus.

TADOSS: computational estimation of tandem domain swap stability.

SUMMARY: Proteins with highly similar tandem domains have shown an increased propensity for misfolding and aggregation. Several molecular explanations have been put forward, such as swapping of adjacent domains, but there is a lack of computational tools to systematically analyze them. We present the TAndem DOmain Swap Stability predictor (TADOSS), a method to computationally estimate the stability of tandem domain-swapped conformations from the structures of single domains, based on previous coarse-grained simulation studies. The tool is able to discriminate domains susceptible to domain swapping and to identify structural regions with high propensity to form hinge loops. TADOSS is a scalable method and suitable for large scale analyses. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are freely available under an MIT license on GitHub at https://github.com/lafita/tadoss. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sequence determinants of protein phase behavior from a coarse-grained model.

Membraneless organelles important to intracellular compartmentalization have recently been shown to comprise assemblies of proteins which undergo liquid-liquid phase separation (LLPS). However, many proteins involved in this phase separation are at least partially disordered. The molecular mechanism and the sequence determinants of this process are challenging to determine experimentally owing to the disordered nature of the assemblies, motivating the use of theoretical and simulation methods. This work advances a computational framework for conducting simulations of LLPS with residue-level detail, and allows for the determination of phase diagrams and coexistence densities of proteins in the two phases. The model includes a short-range contact potential as well as a simplified treatment of electrostatic energy. Interaction parameters are optimized against experimentally determined radius of gyration data for multiple unfolded or intrinsically disordered proteins (IDPs). These models are applied to two systems which undergo LLPS: the low complexity domain of the RNA-binding protein FUS and the DEAD-box helicase protein LAF-1. We develop a novel simulation method to determine thermodynamic phase diagrams as a function of the total protein concentration and temperature. We show that the model is capable of capturing qualitative changes in the phase diagram due to phosphomimetic mutations of FUS and to the presence or absence of the large folded domain in LAF-1. We also explore the effects of chain-length, or multivalency, on the phase diagram, and obtain results consistent with Flory-Huggins theory for polymers. Most importantly, the methodology presented here is flexible so that it can be easily extended to other pair potentials, be used with other enhanced sampling methods, and may incorporate additional features for biological systems of interest.