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Here, we introduce FRETpredict, a Python software program to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses an established Rotamer Library Approach to describe the FRET probes covalently bound to the protein. The software efficiently operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We demonstrate the performance and accuracy of the software for different types of systems: a relatively structured peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). We also describe a general approach to generate new rotamer libraries for FRET probes of interest. FRETpredict is open source (GPLv3) and is available atgithub.com/KULL-Centre/FRETpredictand as a Python PyPI package atpypi.org/project/FRETpredict.Author SummaryWe present FRETpredict, an open-source software to calculate FRET observables from protein structures. Using a previously developed Rotamer Library Approach, FRETpredict helps place multiple conformations of the selected FRET probes at the labeled sites, and use these to calculate FRET efficiencies. Through several case studies, we illustrate the ability of FRETpredict to interpret experimental results and validate protein conformations. We also explain a methodology for generating new rotamer libraries of FRET probes of interest.

Many biological macromolecules can phase-separate in the cell and form highly concentrated condensates. The mesoscopic dynamics of these assemblies have been widely characterized, but their behavior at the molecular scale has remained more elusive. Here we investigate condensates of two highly charged disordered human proteins as a characteristic example of liquid-liquid phase separation. The dense phase is 1000 times more concentrated and has 300 times higher bulk viscosity than the dilute phase. However, single-molecule spectroscopy in individual droplets reveals that the polypeptide chains are remarkably dynamic, with sub-microsecond reconfiguration times. We rationalize this behavior with large-scale all-atom molecular-dynamics simulations, which reveal an unexpectedly similar short-range molecular environment in the dense and dilute phases, suggesting that local biochemical processes and interactions can remain exceedingly rapid in phase-separated systems.

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.

The envelope glycoprotein gp41 of the HIV-1 virus mediates its entry into the host cell. During this process, gp41 undergoes large conformational changes and the energy released in the remodeling events is utilized to overcome the barrier associated with fusing the viral and host membranes. Although the structural intermediates of this fusion process are attractive targets for drug development, no detailed high-resolution structural information or quantitative thermodynamic characterization are available. By measuring the dynamic equilibrium between the lipid-bound intermediate and the post-fusion six-helical bundle (6HB) states of the gp41 ectodomain in the presence of bilayer membrane mimetics, we derived both the reaction kinetics and energies associated with these two states by solution NMR spectroscopy. At equilibrium, an exchange time constant of about 12 seconds at 38 °C is observed, and the post-fusion conformation is energetically more stable than the lipid-bound state by 3.4 kcal mol

The formation of membraneless organelles in cells commonly occurs via liquid-liquid phase separation (LLPS), and is in many cases driven by multivalent interactions between intrinsically disordered proteins (IDPs). Investigating the nature of these interactions, and their effect on dynamics within the condensed phase, is therefore of critical importance, but very challenging for either simulation or experiment. Here, we study these interactions and their dynamics by pairing a novel multiscale simulation strategy with microsecond all-atom MD simulations of a condensed, IDP-rich phase.We simulate two IDPs this way, the low complexity domain of FUS and the N-terminal disordered domain of LAF-1, and find good agreement with experimental information on average density, water content and residue-residue contacts. We go significantly beyond what is known from experiments by showing that ion partitioning within the condensed phase is largely driven by the charge distribution of the proteins and - in the cases considered - shows little evidence of preferential interactions of the ions with the proteins. Furthermore, we are able to probe the microscopic diffusive dynamics within the condensed phase, showing that water and ions are in dynamic equilibrium between dense and dilute phases, and their diffusion reduces by a factor of 2–3 in the dense phase. Despite their high concentration in the condensate, the proteins also remain mobile, explaining the observed liquid-like properties of this phase. We finally show that IDP self-association is driven by a combination of non-specific hydrophobic interactions, as well as hydrogen bonds, salt bridges, π−π and cation-π interactions. The simulation approach presented here allows the structural and dynamical properties of biomolecular condensates to be studied in microscopic detail, and is generally applicable to single and multi-component systems of proteins and nucleic acids involved in LLPS.

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.

Establishing the degree of collapse of unfolded or disordered proteins is a fundamental problem in biophysics, because of its relation to protein folding and to the function of intrinsically disordered proteins. However, until recently, different experiments gave qualitatively different results on collapse and there were large discrepancies between experiments and all-atom simulations. New methodology introduced in the past three years has helped to resolve the differences between experiments, and improvements in simulations have closed the gap between experiment and simulation. These advances have led to an emerging consensus on the collapse of disordered proteins in water.

The high concentration of nucleic acids and positively charged proteins in the cell nucleus provides many possibilities for complex coacervation. We consider a prototypical mixture of nucleic acids together with the polycationic C-terminus of histone H1 (CH1). Using a minimal coarse-grained model that captures the shape, flexibility, and charge distributions of the molecules, we find that coacervates are readily formed at physiological ionic strengths, in agreement with experiment, with a progressive increase in local ordering at low ionic strength. Variation of the positions of charged residues in the protein tunes phase separation: for well-mixed or only moderately blocky distributions of charge, there is a modest increase of local ordering with increasing blockiness that is also associated with an increased propensity to phase separate. This ordering is also associated with a slowdown of rotational and translational diffusion in the dense phase. However, for more extreme blockiness (and consequently higher local charge density), we see a qualitative change in the condensed phase to become a segregated structure with a dramatically increased ordering of the DNA. Naturally occurring proteins with these sequence properties, such as protamines in sperm cells, are found to be associated with very dense packing of nucleic acids.

International audience; Single-molecule Förster resonance energy transfer (FRET) is a versatile technique for probing the structure and dynamics of biomolecules even in heterogeneous ensembles. However, due to the limited fluorescence brightness per molecule and the relatively long fluorescence lifetimes, probing ultrafast structural dynamics in the nanosecond timescale 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.

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.

Unbiased molecular dynamics simulations of proteins can now capture spontaneous folding events. This provides a wealth of data reflecting information on folding mechanism, but raises the challenge of interpreting it in a meaningful way. Here, I describe how such simulations can be used to identify reactive states and reaction coordinates for describing folding, and how folding dynamics can be captured by projection onto those coordinates. Methods are described for quantifying the interactions important for defining the folding mechanism, and for comparison of simulations with experimental mechanistic probes, such as ϕ-values.

Unbiased molecular dynamics simulations of proteins can now capture spontaneous folding events. This provides a wealth of data reflecting information on folding mechanism, but raises the challenge of interpreting it in a meaningful way. Here, I describe how such simulations can be used to identify reactive states and reaction coordinates for describing folding, and how folding dynamics can be captured by projection onto those coordinates. Methods are described for quantifying the interactions important for defining the folding mechanism, and for comparison of simulations with experimental mechanistic probes, such as ϕ-values.

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, τ(c). 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.

Intrinsically disordered proteins (IDPs) are a class of protein that, in the native state, possess no well-defined secondary or tertiary structure, existing instead as dynamic ensembles of conformations. They are biologically important, with approximately 20% of all eukaryotic proteins disordered, and found at the heart of many biochemical networks. To fulfil their biological roles, many IDPs need to bind to proteins and/or nucleic acids. And while unstructured in solution, IDPs typically fold into a well-defined three-dimensional structure upon interaction with a binding partner. The flexibility and structural diversity inherent to IDPs makes this coupled folding and binding difficult to study at atomic resolution by experiment alone, and computer simulation currently offers perhaps the best opportunity to understand this process. But simulation of coupled folding and binding is itself extremely challenging; these molecules are large and highly flexible, and their binding partners, such as DNA or cyclins, are also often large. Therefore, their study requires either or both simplified representations and advanced enhanced sampling schemes. It is not always clear that existing simulation techniques, optimized for studying folded proteins, are well-suited to IDPs. In this article, we examine the progress that has been made in the study of coupled folding and binding using molecular dynamics simulation. We summarise what has been learnt, and examine the state of the art in terms of both methodologies and models. We also consider the lessons to be learnt from advances in other areas of simulation and highlight the issues that remain of be addressed.

Graphical abstract, Highlights • Domain swapping refers to the exchange of structural elements between protein domains. • Experiments show that tandem homologous domains are prone to domain swapping. • Recent studies establish a framework to understand the formation of tandem domain swaps. • Prediction of tandem domain swaps is possible but hindered by the amount of available data., Tandem homologous domains in proteins are susceptible to misfolding through the formation of domain swaps, non-native conformations involving the exchange of equivalent structural elements between adjacent domains. Cutting-edge biophysical experiments have recently allowed the observation of tandem domain swapping events at the single molecule level. In addition, computer simulations have shed light into the molecular mechanisms of domain swap formation and serve as the basis for methods to systematically predict them. At present, the number of studies on tandem domain swaps is still small and limited to a few domain folds, but they offer important insights into the folding and evolution of multidomain proteins with applications in the field of protein design.

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.

An accurate model for macroscale disordered assemblies of biological macromolecules such as those formed in so-called membraneless organelles would greatly assist in studying their structure, function, and dynamics. Recent evidence has suggested that liquid-liquid phase separation (LLPS) underlies the formation of membraneless organelles. While the general mechanism of exchange of macromolecule/water for macromolecule/macromolecule interactions is known to be the driving force for LLPS, the specific interactions involved are not well understood. One way that protein-water and protein-protein interactions have been understood historically is via hydrophobicity scales. However, these scales are typically optimized for describing these relative interactions in certain cases, such as protein folding or insertion of proteins into membranes. To better describe the relative interactions of proteins that undergo LLPS, we have developed a new, data-driven hydrophobicity scale. To determine the new scale, we used coarse-grained molecular dynamics simulations using the hydrophobicity scale coarse-grained model, which relates the interactions between amino acids to their hydrophobicity. Hydrophobicity values were determined via the force-balance method on a library of proteins that includes unfolded, intrinsically disordered, and phase-separating proteins (PSP). The resulting hydrophobicity scale can better predict whether a given protein will undergo LLPS at physiological conditions by using coarse-grained molecular dynamics simulations than existing hydrophobicity scales. This new scale confirms the importance of π-π interactions between amino acids as important drivers of LLPS. This new hydrophobicity scale provides a convenient and compact description of protein-protein interactions for proteins that undergo LLPS and could be used to develop new models to describe interactions between PSP and other components, such as nucleic acids.

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 Forster 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.

Intrinsically disordered proteins (IDPs) are an important class of proteins that do not fold to a well-defined three-dimensional shape but rather adopt an ensemble of inter-converting conformations. This feature makes their experimental characterization challenging and invites a theoretical and computational approach to complement experimental studies. In this review, we highlight the recent progress in developing new computational and theoretical approaches to study the structure and dynamics of monomeric and order higher assemblies of IDPs, with a particular emphasis on their phase separation into protein-rich condensates.

International audience; The so-called FeFe hydrogenases catalyze H2 production and oxidation at a dinuclear inorganic active site. Some of them can be natively purified in an overoxidized, O2-resistant “Hinact” state, recently identified by Rodríguez-Maciá et al. as the product of the reaction of the enzyme with sulfide [Rodríguez-Maciá, P.; J. Am. Chem. Soc. 2018, 140, 9346]. We used a combination of direct electrochemistry experiments with the FeFe hydrogenase from Chlamydomonas reinhardtii, site-directed mutagenesis, molecular dynamics and density functional theory (DFT) calculations to describe the mechanism of inhibition: the diffusion of the inhibitor in the enzyme and its subsequent reaction at the active site H-cluster. We conclude that hydrogen sulfide (H2S) inhibits the enzyme noncompetitively, in a first step by replacing a conserved water molecule that is involved in proton transfer, and then binding to the active site as a hydrosulfide ligand (HS–). DFT calculations with the PBE0-D3 functional successfully describe the redox state of the cubane fragment of the H-cluster in the resulting “Htrans” state. Our experimental and theoretical results are consistent with the reactivation involving the reduction of the H-cluster in the Htrans state, followed by the potentiometric or catalytic reoxidation of the enzyme. This mechanism reconciles all experimental observations, and we suggest that it is common to all FeFe hydrogenases. In addition, we observe that the hydrogenases from Megasphaera elsdenii, Clostridium acetobutylicum (CaI), and Clostridium pasteurianum (CpI) are also inhibited by sulfide, but with very slow kinetics. Although sulfide inhibition is fully reversible, we observed an irreversible inactivation by polysulfide contaminants, which should be avoided if the hydrogenase is exposed to sulfide to prepare samples that are protected from air, e.g., for transport or storage.*

Proteins carry out a wide range of functions that are tightly regulated in space and time. Protein phosphorylation is the most common post-translation modification of proteins and plays a key role in the regulation of many biological processes. The finding that many phosphorylated residues are not solvent exposed in the unphosphorylated state opens several questions for understanding the mechanism that underlies phosphorylation and how phosphorylation may affect protein structures. First, because kinases need access to the phosphorylated residue, how do such buried residues become modified? Second, once phosphorylated, what are the structural effects of phosphorylation of buried residues, and do they lead to changed conformational dynamics? We have used the ternary complex between p27(Kip1) (p27), Cdk2, and cyclin A to study these questions using enhanced sampling molecular dynamics simulations. In line with previous NMR and single-molecule fluorescence experiments, we observe transient exposure of Tyr88 in p27, even in its unphosphorylated state. Once Tyr88 is phosphorylated, we observe a coupling to a second site, thus making Tyr74 more easily exposed and thereby the target for a second phosphorylation step. Our observations provide atomic details on how protein dynamics plays a role in modulating multisite phosphorylation in p27, thus supplementing previous experimental observations. More generally, we discuss how the observed phenomenon of transient exposure of buried residues may play a more general role in regulating protein function.

The formation of membraneless organelles in cells commonly occurs via liquid-liquid phase separation (LLPS), and is in many cases driven by multivalent interactions between intrinsically disordered proteins (IDPs). Molecular simulations can reveal the specific amino acid interactions driving LLPS, which is hard to obtain from experiment. Coarse-grained simulations have been used to directly observe the sequence determinants of phase separation but have limited spatial resolution, while all-atom simulations have yet to be applied to LLPS due to the challenges of large system sizes and long time scales relevant to phase separation. We present a novel multiscale computational framework by obtaining initial molecular configurations of a condensed protein-rich phase from equilibrium coarse-grained simulations, and back mapping to an all-atom representation. Using the specialized Anton 2 supercomputer, we resolve microscopic structural and dynamical details of protein condensates through microsecond-scale all-atom explicit-solvent simulations. We have studied two IDPs which phase separatein vitro: the low complexity domain of FUS and the N-terminal disordered domain of LAF-1. Using this approach, we explain the partitioning of ions between phases with low and high protein density, demonstrate that the proteins are remarkably dynamic within the condensed phase, identify the key residue-residue interaction modes stabilizing the dense phase, all while showing good agreement with experimental observations. Our approach is generally applicable to all-atom studies of other single and multi-component systems of proteins and nucleic acids involved in the formation of membraneless organelles.

Mitochondrial ribosomes (mitoribosomes) are tethered to the mitochondrial inner membrane to facilitate the cotranslational membrane insertion of the synthesized proteins. We report cryo-electron microscopy structures of human mitoribosomes with nascent polypeptide, bound to the insertase oxidase assembly 1-like (OXA1L) through three distinct contact sites. OXA1L binding is correlated with a series of conformational changes in the mitoribosomal large subunit that catalyze the delivery of newly synthesized polypeptides. The mechanism relies on the folding of mL45 inside the exit tunnel, forming two specific constriction sites that would limit helix formation of the nascent chain. A gap is formed between the exit and the membrane, making the newly synthesized proteins accessible. Our data elucidate the basis by which mitoribosomes interact with the OXA1L insertase to couple protein synthesis and membrane delivery.

In modelling experimental measurements from intrinsically disordered proteins, it is essential to account for the very broad distribution of structures which they populate. A natural method for doing this is via computer simulations, particularly those that generate a reasonably accurate initial molecular ensemble. In this chapter, I present a reweighting approach that may be used to determine a conformational ensemble by combining experimental information with molecular simulations. The advantages and difficulties associated with this approach are briefly discussed.

Proteins commonly fold cotranslationally on the ribosome, while the nascent chain emerges from the ribosomal tunnel. Protein domains that are sufficiently small can even fold while still located inside the tunnel. However, the effect of the tunnel on the folding dynamics of these domains is still not well understood. Here, we combine optical tweezers with single-molecule FRET and molecular dynamics simulations to investigate folding of the small zinc-finger domain ADR1a inside and at the vestibule of the ribosomal tunnel. The tunnel is found to accelerate folding and stabilize the folded state, reminiscent of the effects of chaperonins. However, a simple mechanism involving stabilization by confinement does not reproduce the results. Instead, it appears that electrostatic interactions between the protein and ribosome contribute to the observed folding acceleration and stabilization of ADR1a.

Molecular simulations reveal that multiple lipid interactions are needed for high-affinity binding of protein domains to membranes., Association of peripheral proteins with lipid bilayers regulates membrane signaling and dynamics. Pleckstrin homology (PH) domains bind to phosphatidylinositol phosphate (PIP) molecules in membranes. The effects of local PIP enrichment on the interaction of PH domains with membranes is unclear. Molecular dynamics simulations allow estimation of the binding energy of GRP1 PH domain to PIP3-containing membranes. The free energy of interaction of the PH domain with more than two PIP3 molecules is comparable to experimental values, suggesting that PH domain binding involves local clustering of PIP molecules within membranes. We describe a mechanism of PH binding proceeding via an encounter state to two bound states which differ in the orientation of the protein relative to the membrane, these orientations depending on the local PIP concentration. These results suggest that nanoscale clustering of PIP molecules can control the strength and orientation of PH domain interaction in a concentration-dependent manner.

In modelling experimental measurements from intrinsically disordered proteins, it is essential to account for the very broad distribution of structures which they populate. A natural method for doing this is via computer simulations, particularly those that generate a reasonably accurate initial molecular ensemble. In this chapter, I present a reweighting approach that may be used to determine a conformational ensemble by combining experimental information with molecular simulations. The advantages and difficulties associated with this approach are briefly discussed.