Single-molecule spectroscopy of protein folding dynamics—expanding scope and timescales

Transient Structural Properties of the Rho GDP-Dissociation Inhibitor

Rho GTPases, master spatial regulators of a wide range of cellular processes, are orchestrated by complex formation with guanine nucleotide dissociation inhibitors (RhoGDIs). These have been thought to possess an unstructured N-terminus that inhibits nucleotide exchange of their client upon binding/folding. Via NMR analyses, molecular dynamics simulations, and biochemical assays, we reveal instead pertinent structural properties transiently maintained both, in the presence and absence of the client, imposed onto the terminus context-specifically by modulating interactions with the surface of the folded C-terminal domain. These observations revise the long-standing textbook picture of the GTPases' mechanism of membrane extraction. Rather than by a disorder-to-order transition upon binding of an inhibitory peptide, the intricate and highly selective extraction process of RhoGTPases is orchestrated via a dynamic ensemble bearing preformed transient structural properties, suitably modulated by the specific surrounding along the multi-step process.

Information-theoretical limit on the estimates of dissipation by molecular machines using single-molecule fluorescence resonance energy transfer experiments

Single-molecule fluorescence resonance energy transfer (FRET) experiments are commonly used to study the dynamics of molecular machines. While in vivo molecular processes often break time-reversal symmetry, the temporal directionality of cyclically operating molecular machines is often not evident from single-molecule FRET trajectories, especially in the most common two-color FRET studies. Solving a more quantitative problem of estimating the energy dissipation/entropy production by a molecular machine from single-molecule data is even more challenging. Here, we present a critical assessment of several practical methods of doing so, including Markov-model-based methods and a model-free approach based on an information-theoretical measure of entropy production that quantifies how (statistically) dissimilar observed photon sequences are from their time reverses. The Markov model approach is computationally feasible and may outperform model free approaches, but its performance strongly depends on how well the assumed model approximates the true microscopic dynamics. Markov models are also not guaranteed to give a lower bound on dissipation. Meanwhile, model-free, information-theoretical methods systematically underestimate entropy production at low photoemission rates, and long memory effects in the photon sequences make these methods demanding computationally. There is no clear winner among the approaches studied here, and all methods deserve to belong to a comprehensive data analysis toolkit.

Transient Non-local Interactions Dominate the Dynamics of Measles Virus NTAIL

The RNA genome of measles virus is encapsidated by the nucleoprotein within a helical nucleocapsid that serves as template for both transcription and replication. The intrinsically disordered domain of the nucleoprotein (NTAIL), partly protruding outward from the nucleocapsid, is essential for binding the polymerase complex responsible for viral transcription and replication. As for many IDPs, binding of NTAIL occurs through a short molecular recognition element (MoRE) that folds upon binding, with the majority of NTAIL remaining disordered. Though NTAIL regions far from the MoRE influence the binding affinity, interactions between them and the MoRE have not been investigated in depth. Using an integrated approach, relying on photo-induced electron transfer (PET) experiments between tryptophan and cysteine pairs placed at different positions in the protein under varying salt and pH conditions, combined with simulations and analytical models, we identified transient interactions between two disordered regions distant in sequence, which dominate NTAIL dynamics, and regulate the conformational preferences of both the MoRE and the entire NTAIL domain. Co-evolutionary analysis corroborates our findings, and suggests an important functional role for the same intramolecular interactions. We propose mechanisms by which these non-local interactions may regulate binding to the phosphoprotein, polymerase recruitment, and ultimately viral transcription and replication. Our findings may be extended to other IDPs, where non-local intra-protein interactions affect the conformational preferences of intermolecular binding sites.

Full-length single-molecule protein fingerprinting

Proteins are the primary functional actors of the cell. While proteoform diversity is known to be highly biologically relevant, current protein analysis methods are of limited use for distinguishing proteoforms. Mass spectrometric methods, in particular, often provide only ambiguous information on post-translational modification sites, and sequences of co-existing modifications may not be resolved. Here we demonstrate fluorescence resonance energy transfer (FRET)-based single-molecule protein fingerprinting to map the location of individual amino acids and post-translational modifications within single full-length protein molecules. Our data show that both intrinsically disordered proteins and folded globular proteins can be fingerprinted with a subnanometer resolution, achieved by probing the amino acids one by one using single-molecule FRET via DNA exchange. This capability was demonstrated through the analysis of alpha-synuclein, an intrinsically disordered protein, by accurately quantifying isoforms in mixtures using a machine learning classifier, and by determining the locations of two O-GlcNAc moieties. Furthermore, we demonstrate fingerprinting of the globular proteins Bcl-2-like protein 1, procalcitonin and S100A9. We anticipate that our ability to perform proteoform identification with the ultimate sensitivity may unlock exciting new venues in proteomics research and biomarker-based diagnosis.

Experimental methods to study the structure and dynamics of intrinsically disordered regions in proteins

Eukaryotic proteins often feature long stretches of amino acids that lack a well-defined three-dimensional structure and are referred to as intrinsically disordered proteins (IDPs) or regions (IDRs). Although these proteins challenge conventional structure-function paradigms, they play vital roles in cellular processes. Recent progress in experimental techniques, such as NMR spectroscopy, single molecule FRET, high speed AFM and SAXS, have provided valuable insights into the biophysical basis of IDP function. This review discusses the advancements made in these techniques particularly for the study of disordered regions in proteins. In NMR spectroscopy new strategies such as 13C detection, non-uniform sampling, segmental isotope labeling, and rapid data acquisition methods address the challenges posed by spectral overcrowding and low stability of IDPs. The importance of various NMR parameters, including chemical shifts, hydrogen exchange rates, and relaxation measurements, to reveal transient secondary structures within IDRs and IDPs are presented. Given the high flexibility of IDPs, the review outlines NMR methods for assessing their dynamics at both fast (ps-ns) and slow (μs-ms) timescales. IDPs exert their functions through interactions with other molecules such as proteins, DNA, or RNA. NMR-based titration experiments yield insights into the thermodynamics and kinetics of these interactions. Detailed study of IDPs requires multiple experimental techniques, and thus, several methods are described for studying disordered proteins, highlighting their respective advantages and limitations. The potential for integrating these complementary techniques, each offering unique perspectives, is explored to achieve a comprehensive understanding of IDPs.

Sequence-dependent material properties of biomolecular condensates and their relation to dilute phase conformations

Material properties of phase-separated biomolecular condensates, enriched with disordered proteins, dictate many cellular functions. Contrary to the progress made in understanding the sequence-dependent phase separation of proteins, little is known about the sequence determinants of condensate material properties. Using the hydropathy scale and Martini models, we computationally decipher these relationships for charge-rich disordered protein condensates. Our computations yield dynamical, rheological, and interfacial properties of condensates that are quantitatively comparable with experimentally characterized condensates. Interestingly, we find that the material properties of model and natural proteins respond similarly to charge segregation, despite different sequence compositions. Molecular interactions within the condensates closely resemble those within the single-chain ensembles. Consequently, the material properties strongly correlate with molecular contact dynamics and single-chain structural properties. We demonstrate the potential to harness the sequence characteristics of disordered proteins for predicting and engineering the material properties of functional condensates, with insights from the dilute phase properties.

Single-molecule FRET unmasks structural subpopulations and crucial molecular events during FUS low-complexity domain phase separation

Biomolecular condensates formed via phase separation of proteins and nucleic acids are thought to be associated with a wide range of cellular functions and dysfunctions. We dissect critical molecular events associated with phase separation of an intrinsically disordered prion-like low-complexity domain of Fused in Sarcoma by performing single-molecule studies permitting us to access the wealth of molecular information that is skewed in conventional ensemble experiments. Our single-molecule FRET experiments reveal the coexistence of two conformationally distinct subpopulations in the monomeric form. Single-droplet single-molecule FRET studies coupled with fluorescence correlation spectroscopy, picosecond time-resolved fluorescence anisotropy, and vibrational Raman spectroscopy indicate that structural unwinding switches intramolecular interactions into intermolecular contacts allowing the formation of a dynamic network within condensates. A disease-related mutation introduces enhanced structural plasticity engendering greater interchain interactions that can accelerate pathological aggregation. Our findings provide key mechanistic underpinnings of sequence-encoded dynamically-controlled structural unzipping resulting in biological phase separation.

An automated single-molecule FRET platform for high-content, multiwell plate screening of biomolecular conformations and dynamics

Single-molecule FRET (smFRET) has become a versatile tool for probing the structure and functional dynamics of biomolecular systems, and is extensively used to address questions ranging from biomolecular folding to drug discovery. Confocal smFRET measurements are amongst the widely used smFRET assays and are typically performed in a single-well format. Thus, sampling of many experimental parameters is laborious and time consuming. To address this challenge, we extend here the capabilities of confocal smFRET beyond single-well measurements by integrating a multiwell plate functionality to allow for continuous and automated smFRET measurements. We demonstrate the broad applicability of the multiwell plate assay towards DNA hairpin dynamics, protein folding, competitive and cooperative protein-DNA interactions, and drug-discovery, revealing insights that would be very difficult to achieve with conventional single-well format measurements. For the adaptation into existing instrumentations, we provide a detailed guide and open-source acquisition and analysis software.

Time-resolved burst variance analysis

Quantifying biomolecular dynamics has become a major task of single-molecule fluorescence spectroscopy methods. In single-molecule Förster resonance energy transfer (smFRET), kinetic information is extracted from the stream of photons emitted by attached donor and acceptor fluorophores. Here, we describe a time-resolved version of burst variance analysis that can quantify kinetic rates at microsecond to millisecond timescales in smFRET experiments of diffusing molecules. Bursts are partitioned into segments with a fixed number of photons. The FRET variance is computed from these segments and compared with the variance expected from shot noise. By systematically varying the segment size, dynamics at different timescales can be captured. We provide a theoretical framework to extract kinetic rates from the decay of the FRET variance with increasing segment size. Compared to other methods such as filtered fluorescence correlation spectroscopy, recurrence analysis of single particles, and two-dimensional lifetime correlation spectroscopy, fewer photons are needed to obtain reliable timescale estimates, which reduces the required measurement time.

Single-molecule FRET and molecular diffusion analysis characterize stable oligomers of amyloid-β 42 of extremely low population

Soluble oligomers produced during protein aggregation have been thought to be toxic species causing various diseases. Characterization of these oligomers is difficult because oligomers are a heterogeneous mixture, which is not readily separable, and may appear transiently during aggregation. Single-molecule spectroscopy can provide valuable information by detecting individual oligomers, but there have been various problems in determining the size and concentration of oligomers. In this work, we develop and use a method that analyzes single-molecule fluorescence burst data of freely diffusing molecules in solution based on molecular diffusion theory and maximum likelihood method. We demonstrate that the photon count rate, diffusion time, population, and Förster resonance energy transfer (FRET) efficiency can be accurately determined from simulated data and the experimental data of a known oligomerization system, the tetramerization domain of p53. We used this method to characterize the oligomers of the 42-residue amyloid-β (Aβ42) peptide. Combining peptide incubation in a plate reader and single-molecule free-diffusion experiments allows for the detection of stable oligomers appearing at various stages of aggregation. We find that the average size of these oligomers is 70-mer and their overall population is very low, less than 1 nM, in the early and middle stages of aggregation of 1 µM Aβ42 peptide. Based on their average size and long diffusion time, we predict the oligomers have a highly elongated rod-like shape.

Evidence of microplastics release from polythene and paper cups exposed to hot and cold: A case study on the compromised kinetics of catalase

Microplastics (MPs) have become widespread in the modern world posing a hidden threat to the global environment. However, growing accumulation and devastating impact of MPs on human health and the environment have received least attention. In the current investigation, for the first time MPs have been identified which are released from the daily usable materials like polythene bags (PB) and paper cups (PC) in response to hot and cold water exposure at different time intervals. The impact of these MPs has been assessed on the major antioxidant enzyme, bovine liver catalase (BLC). The binding of MPs caused conformational changes in BLC by decreasing the α-helical content, which results in reduction of the enzymatic activity. Kinetics study revealed nearly ∼1.4-fold compromised catalytic efficiency of catalase in response to MPs. Nevertheless, hepatic catalase activity was also significantly decreased in presence of MPs. Further, materials like glass, porcelain, stainless steel, and high-grade plastics are discovered as greener alternatives to PB and PC.

Polyprotein synthesis: a journey from the traditional pre-translational method to modern post-translational approaches for single-molecule force spectroscopy

Polyproteins, an array of protein units of similar or differential functions in tandem, have been extensively utilized by organisms, unicellular or multicellular, as concentrators of the myriad of molecular activities. Most eukaryotic proteins, two-thirds in unicellular organisms, and more than 80% in metazoans, are polyproteins. Although the use of polyproteins continues to evolve in nature, our understanding of the structure-function-property of polyproteins is still limited. Cumbersome recombinant strategies and the lack of convenient in vitro synthetic routes of polyproteins have been rate-determining factors in the progress. However, in this review we have discussed the revolutionary journey of polyprotein synthesis with a major focus on surface-based structure-function-property studies, especially using force spectroscopy at the single-molecule level.

Liquid-Liquid Phase Separation Modifies the Dynamic Properties of Intrinsically Disordered Proteins

Liquid-liquid phase separation of flexible biomolecules has been identified as a ubiquitous phenomenon underlying the formation of membraneless organelles that harbor a multitude of essential cellular processes. We use nuclear magnetic resonance (NMR) spectroscopy to compare the dynamic properties of an intrinsically disordered protein (measles virus N_TAIL) in the dilute and dense phases at atomic resolution. By measuring ¹⁵N NMR relaxation at different magnetic field strengths, we are able to characterize the dynamics of the protein in dilute and crowded conditions and to compare the amplitude and timescale of the different motional modes to those present in the membraneless organelle. Although the local backbone conformational sampling appears to be largely retained, dynamics occurring on all detectable timescales, including librational, backbone dihedral angle dynamics and segmental, chainlike motions, are considerably slowed down. Their relative amplitudes are also drastically modified, with slower, chain-like motions dominating the dynamic profile. In order to provide additional mechanistic insight, we performed extensive molecular dynamics simulations of the protein under self-crowding conditions at concentrations comparable to those found in the dense liquid phase. Simulation broadly reproduces the impact of formation of the condensed phase on both the free energy landscape and the kinetic interconversion between states. In particular, the experimentally observed reduction in the amplitude of the fastest component of backbone dynamics correlates with higher levels of intermolecular contacts or entanglement observed in simulations, reducing the conformational space available to this mode under strongly self-crowding conditions.

Artificial intelligence-based HDX (AI-HDX) prediction reveals fundamental characteristics to protein dynamics: Mechanisms on SARS-CoV-2 immune escape

Three-dimensional structure and dynamics are essential for protein function. Advancements in hydrogen-deuterium exchange (HDX) techniques enable probing protein dynamic information in physiologically relevant conditions. HDX-coupled mass spectrometry (HDX-MS) has been broadly applied in pharmaceutical industries. However, it is challenging to obtain dynamics information at the single amino acid resolution and time consuming to perform the experiments and process the data. Here, we demonstrate the first deep learning model, artificial intelligence-based HDX (AI-HDX), that predicts intrinsic protein dynamics based on the protein sequence. It uncovers the protein structural dynamics by combining deep learning, experimental HDX, sequence alignment, and protein structure prediction. AI-HDX can be broadly applied to drug discovery, protein engineering, and biomedical studies. As a demonstration, we elucidated receptor-binding domain structural dynamics as a potential mechanism of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody efficacy and immune escape. AI-HDX fundamentally differs from the current AI tools for protein analysis and may transform protein design for various applications.

Spectroelectrochemical behavior of parallel arrays of single vertically oriented Pseudomonas aeruginosa cells

Pseudomonas aeruginosa is a Gram-negative opportunistic human pathogen responsible for a number of healthcare-associated infection. It is currently difficult to assess single cell behaviors of P. aeruginosa that might contribute to acquisition of antibiotic resistance, intercellular communication, biofilm development, or virulence, because mechanistic behavior is inferred from ensemble collections of cells, thus averaging effects over a population. Here, we develop and characterize a device that can capture and trap arrays of single P. aeruginosa cells in individual micropores in order to study their behaviors using spectroelectrochemistry. Focused ion beam milling is used to fabricate an array of micropores in a Au/dielectric/Au/SiO₂-containing multilayer substrate, in which individual micropores are formed with dimensions that facilitate the capture of single P. aeruginosa cells in a predominantly vertical orientation. The bottom Au ring is then used as a working electrode to explore the spectroelectrochemical behavior of parallel arrays of individual P. aeruginosa cells. Application of step-potential or swept-potential waveforms produces changes in the fluorescence emission that can be imaged and correlated with applied potential. Arrays of P. aeruginosa cells typically exhibit three characteristic fluorescence behaviors that are sensitive to nutritional stress and applied potential. The device developed here enables the study of parallel collections of single bacterial cells with well-defined orientational order and should facilitate efforts to elucidate methods of bacterial communication and multidrug resistance at the single cell level.

Single-photon smFRET. I: Theory and conceptual basis

We present a unified conceptual framework and the associated software package for single-molecule Förster resonance energy transfer (smFRET) analysis from single-photon arrivals leveraging Bayesian nonparametrics, BNP-FRET. This unified framework addresses the following key physical complexities of a single-photon smFRET experiment, including: 1) fluorophore photophysics; 2) continuous time kinetics of the labeled system with large timescale separations between photophysical phenomena such as excited photophysical state lifetimes and events such as transition between system states; 3) unavoidable detector artefacts; 4) background emissions; 5) unknown number of system states; and 6) both continuous and pulsed illumination. These physical features necessarily demand a novel framework that extends beyond existing tools. In particular, the theory naturally brings us to a hidden Markov model with a second-order structure and Bayesian nonparametrics on account of items 1, 2, and 5 on the list. In the second and third companion articles, we discuss the direct effects of these key complexities on the inference of parameters for continuous and pulsed illumination, respectively.

Single-photon smFRET: II. Application to continuous illumination

Here we adapt the Bayesian nonparametrics (BNP) framework presented in the first companion article to analyze kinetics from single-photon, single-molecule Förster resonance energy transfer (smFRET) traces generated under continuous illumination. Using our sampler, BNP-FRET, we learn the escape rates and the number of system states given a photon trace. We benchmark our method by analyzing a range of synthetic and experimental data. Particularly, we apply our method to simultaneously learn the number of system states and the corresponding kinetics for intrinsically disordered proteins using two-color FRET under varying chemical conditions. Moreover, using synthetic data, we show that our method can deduce the number of system states even when kinetics occur at timescales of interphoton intervals.

Transient On- and Off-Pathway Protein Folding Intermediate States Characterized with NMR Relaxation Dispersion

The earliest events in the folding of a protein are in general poorly understood. We used NMR R2 relaxation dispersion experiments to study transient local collapse events in the unfolded-state (U) conformational ensemble of apomyoglobin (apoMb). Local residual secondary structure (seen in regions corresponding to the A, D, E, and H helices of the folded protein) is largely unchanged over the pH range of 2.3-2.75, yet a significant pH-dependent increase in the conformational exchange contribution to the R2 relaxation rate (Rex) indicates that transient intramolecular contacts occur on a microsecond to millisecond time scale at pH 2.75. A comparison of 15N and 13CO relaxation dispersion data at pH 2.75 for residues in the A, B, G, and H regions, which participate in the earliest folding intermediates, indicates that chain collapse and secondary structure formation are rapid and concomitant. Increasingly stabilizing conditions (lower temperature, higher pH) result in the observation of a relaxation dispersion in the C, CD, and E regions of the protein, which are known to fold at later stages. Mutation of Trp14 in the A-helix region to Ala eliminates conformational exchange throughout the protein, and the mutation of hydrophobic residues in other regions results in the selective inhibition of conformational exchange in the B, G, or H regions. The R2 dispersion data for WT apoMb at pH 2.75 and 10 °C are best fit to a four-state model ABGH ⇆ AGH ⇆ U ⇆ ABCD that includes on-pathway (AGH and ABGH) and off-pathway (ABCD) transiently folded states, both of which are required to explain the behavior of the mutant proteins. The off-pathway intermediate is destabilized at higher temperatures. Our analysis provides insights into the earliest stages of apoMb folding where the collapsing polypeptide chain samples both productive and nonproductive states with stabilized secondary structure.

Measuring Photophysical Transition Rates with Fluorescence Correlation Spectroscopy and Antibunching

We present a new method that combines fluorescence correlation spectroscopy (FCS) on the microsecond time scale with fluorescence antibunching measurements on the nanosecond time scale for measuring photophysical rate constants of fluorescent molecules. The antibunching measurements allow us to quantify the average excitation rate of fluorescent molecules within the confocal detection volume of the FCS measurement setup. Knowledge of this value allows us then to quantify, in an absolute manner, the intersystem crossing rate and triplet state lifetime from the microsecond temporal decay of the FCS curves. We present a theoretical analysis of the method and estimate the maximum bias caused by the averaging of all quantities (excitation rate and photophysical rates) over the confocal detection volume, and we show that this bias is smaller than 5% in most cases. We apply the method for measuring the photophysical rate constants of the widely used dyes Rhodamine 110 and ATTO 655.

Combining Coarse-Grained Simulations and Single Molecule Analysis Reveals a Three-State Folding Model of the Guanidine-II Riboswitch

Riboswitch RNAs regulate gene expression by conformational changes induced by environmental conditions and specific ligand binding. The guanidine-II riboswitch is proposed to bind the small molecule guanidinium and to subsequently form a kissing loop interaction between the P1 and P2 hairpins. While an interaction was shown for isolated hairpins in crystallization and electron paramagnetic resonance experiments, an intrastrand kissing loop formation has not been demonstrated. Here, we report the first evidence of this interaction in cis in a ligand and Mg²⁺ dependent manner. Using single-molecule FRET spectroscopy and detailed structural information from coarse-grained simulations, we observe and characterize three interconvertible states representing an open and kissing loop conformation as well as a novel Mg²⁺ dependent state for the guanidine-II riboswitch from E. coli. The results further substantiate the proposed switching mechanism and provide detailed insight into the regulation mechanism for the guanidine-II riboswitch class. Combining single molecule experiments and coarse-grained simulations therefore provides a promising perspective in resolving the conformational changes induced by environmental conditions and to yield molecular insights into RNA regulation.

Linker Molecules Convert Commercial Fluorophores into Tailored Functional Probes during Biolabelling

Many life‐science techniques and assays rely on selective labeling of biological target structures with commercial fluorophores that have specific yet invariant properties. Consequently, a fluorophore (or dye) is only useful for a limited range of applications, e.g., as a label for cellular compartments, super‐resolution imaging, DNA sequencing or for a specific biomedical assay. Modifications of fluorophores with the goal to alter their bioconjugation chemistry, photophysical or functional properties typically require complex synthesis schemes. We here introduce a general strategy that allows to customize these properties during biolabelling with the goal to introduce the fluorophore in the last step of biolabelling. For this, we present the design and synthesis of ‘linker’ compounds, that bridge biotarget, fluorophore and a functional moiety via well‐established labeling protocols. Linker molecules were synthesized via the Ugi four‐component reaction (Ugi‐4CR) which facilitates a modular design of linkers with diverse functional properties and bioconjugation‐ and fluorophore attachment moieties. To demonstrate the possibilities of different linkers experimentally, we characterized the ability of commercial fluorophores from the classes of cyanines, rhodamines, carbopyronines and silicon‐rhodamines to become functional labels on different biological targets in vitro and in vivo via thiol‐maleimide chemistry. With our strategy, we showed that the same commercial dye can become a photostable self‐healing dye or a sensor for bivalent ions subject to the linker used. Finally, we quantified the photophysical performance of different self‐healing linker–fluorophore conjugates and demonstrated their applications in super‐resolution imaging and single‐molecule spectroscopy.

NMR Provides Unique Insight into the Functional Dynamics and Interactions of Intrinsically Disordered Proteins

Intrinsically disordered proteins are ubiquitous throughout all known proteomes, playing essential roles in all aspects of cellular and extracellular biochemistry. To understand their function, it is necessary to determine their structural and dynamic behavior and to describe the physical chemistry of their interaction trajectories. Nuclear magnetic resonance is perfectly adapted to this task, providing ensemble averaged structural and dynamic parameters that report on each assigned resonance in the molecule, unveiling otherwise inaccessible insight into the reaction kinetics and thermodynamics that are essential for function. In this review, we describe recent applications of NMR-based approaches to understanding the conformational energy landscape, the nature and time scales of local and long-range dynamics and how they depend on the environment, even in the cell. Finally, we illustrate the ability of NMR to uncover the mechanistic basis of functional disordered molecular assemblies that are important for human health.

Unraveling multi-state molecular dynamics in single-molecule FRET experiments. I. Theory of FRET-lines

Conformational dynamics of biomolecules are of fundamental importance for their function. Single-molecule studies of Förster Resonance Energy Transfer (smFRET) between a tethered donor and acceptor dye pair are a powerful tool to investigate the structure and dynamics of labeled molecules. However, capturing and quantifying conformational dynamics in intensity-based smFRET experiments remains challenging when the dynamics occur on the sub-millisecond timescale. The method of multiparameter fluorescence detection addresses this challenge by simultaneously registering fluorescence intensities and lifetimes of the donor and acceptor. Together, two FRET observables, the donor fluorescence lifetime τD and the intensity-based FRET efficiency E, inform on the width of the FRET efficiency distribution as a characteristic fingerprint for conformational dynamics. We present a general framework for analyzing dynamics that relates average fluorescence lifetimes and intensities in two-dimensional burst frequency histograms. We present parametric relations of these observables for interpreting the location of FRET populations in E-τD diagrams, called FRET-lines. To facilitate the analysis of complex exchange equilibria, FRET-lines serve as reference curves for a graphical interpretation of experimental data to (i) identify conformational states, (ii) resolve their dynamic connectivity, (iii) compare different kinetic models, and (iv) infer polymer properties of unfolded or intrinsically disordered proteins. For a simplified graphical analysis of complex kinetic networks, we derive a moment-based representation of the experimental data that decouples the motion of the fluorescence labels from the conformational dynamics of the biomolecule. Importantly, FRET-lines facilitate exploring complex dynamic models via easily computed experimental observables. We provide extensive computational tools to facilitate applying FRET-lines.

Heterogeneity in Protein Folding and Unfolding Reactions

Proteins have dynamic structures that undergo chain motions on time scales spanning from picoseconds to seconds. Resolving the resultant conformational heterogeneity is essential for gaining accurate insight into fundamental mechanistic aspects of the protein folding reaction. The use of high-resolution structural probes, sensitive to population distributions, has begun to enable the resolution of site-specific conformational heterogeneity at different stages of the folding reaction. Different states populated during protein folding, including the unfolded state, collapsed intermediate states, and even the native state, are found to possess significant conformational heterogeneity. Heterogeneity in protein folding and unfolding reactions originates from the reduced cooperativity of various kinds of physicochemical interactions between various structural elements of a protein, and between a protein and solvent. Heterogeneity may arise because of functional or evolutionary constraints. Conformational substates within the unfolded state and the collapsed intermediates that exchange at rates slower than the subsequent folding steps give rise to heterogeneity on the protein folding pathways. Multiple folding pathways are likely to represent distinct sequences of structure formation. Insight into the nature of the energy barriers separating different conformational states populated during (un)folding can also be obtained by resolving heterogeneity.

Single-Molecule Kinetic Studies of Nucleic Acids by Förster Resonance Energy Transfer

Single-molecule microscopy is often used to observe and characterize the conformational dynamics of nucleic acids (NA). Due to the large variety of NA structures and the challenges specific to single-molecule observation techniques, the data recorded in such experiments must be processed via multiple statistical treatments to finally yield a reliable mechanistic view of the NA dynamics. In this chapter, we propose a comprehensive protocol to analyze single-molecule trajectories in the scope of single-molecule Förster resonance energy transfer (FRET) microscopy. The suggested protocol yields the conformational states common to all molecules in the investigated sample, together with the associated conformational transition kinetics. The given model resolves states that are indistinguishable by their observed FRET signals and is estimated with 95% confidence using error calculations on FRET states and transition rate constants. In the end, a step-by-step user guide is given to reproduce the protocol with the Multifunctional Analysis Software to Handle single-molecule FRET data (MASH-FRET).

Extraction of kinetics from equilibrium distributions of states using the Metropolis Monte Carlo method

The Metropolis Monte Carlo (MMC) method is used to extract reaction kinetics from a given equilibrium distribution of states of a complex system. The approach is illustrated by the folding/unfolding reaction for two proteins: a model β-hairpin and α-helical protein α_{3}D. For the β-hairpin, the free energy surfaces (FESs) and free energy profiles (FEPs) are employed as the equilibrium distributions of states, playing a role of the potentials of mean force to determine the acceptance probabilities of new states in the MMC simulations. Based on the FESs and PESs for a set of temperatures that were simulated with the molecular dynamics (MD) method, the MMC simulations are performed to extract folding/unfolding rates. It has been found that the rate constants and first-passage time (FPT) distributions obtained in the MMC simulations change with temperature in good agreement with those from the MD simulations. For α_{3}D protein, whose equilibrium folding/unfolding was studied with the single-molecule FRET method [Chung et al., J. Phys. Chem. A 115, 3642 (2011)1089-563910.1021/jp1009669], the FRET-efficiency histograms at different denaturant concentrations were used as the equilibrium distributions of protein states. It has been found that the rate constants for folding and unfolding obtained in the MMC simulations change with denaturant concentration in reasonable agreement with the constants that were extracted from the photon trajectories on the basis of theoretical models. The simulated FPT distributions are single-exponential, which is consistent with the assumption of two-state kinetics that was made in the theoretical models. The promising feature of the present approach is that it is based solely on the equilibrium distributions of states, without introducing any additional parameters to perform simulations, which suggests its applicability to other complex systems.

Chaperones Skp and SurA dynamically expand unfolded OmpX and synergistically disassemble oligomeric aggregates

Outer membrane proteins (OMPs) are crucial for the survival of bacteria. The two chaperones 17-kilodalton protein (Skp) and survival factor A (SurA) play key roles in OMP maturation by keeping unfolded OMP proteins soluble in the periplasm. However, their functionalities are incompletely understood. Here, we establish connections between structural and energetic features employed by the two chaperones when interacting with unfolded OmpX. We find that expansion, accompanied with fast polypeptide chain reconfiguration, prevents unfolded OmpX from misfolding and aggregating. Moreover, chaperone interaction with unfolded OmpX is thermodynamically calibrated, allowing for a fine-tuned association of chaperones with OMPs in the adenosine triphosphate-depleted periplasm. We further discovered that Skp and SurA act together as disaggregases and are able to disassemble oligomeric OMP aggregates, revealing remarkable functionalities of this periplasmic chaperone system.

Periplasmic chaperones 17-kilodalton protein (Skp) and survival factor A (SurA) are essential players in outer membrane protein (OMP) biogenesis. They prevent unfolded OMPs from misfolding during their passage through the periplasmic space and aid in the disassembly of OMP aggregates under cellular stress conditions. However, functionally important links between interaction mechanisms, structural dynamics, and energetics that underpin both Skp and SurA associations with OMPs have remained largely unresolved. Here, using single-molecule fluorescence spectroscopy, we dissect the conformational dynamics and thermodynamics of Skp and SurA binding to unfolded OmpX and explore their disaggregase activities. We show that both chaperones expand unfolded OmpX distinctly and induce microsecond chain reconfigurations in the client OMP structure. We further reveal that Skp and SurA bind their substrate in a fine-tuned thermodynamic process via enthalpy–entropy compensation. Finally, we observed synergistic activity of both chaperones in the disaggregation of oligomeric OmpX aggregates. Our findings provide an intimate view into the multifaceted functionalities of Skp and SurA and the fine-tuned balance between conformational flexibility and underlying energetics in aiding chaperone action during OMP biogenesis.

Multi-parameter photon-by-photon hidden Markov modeling

Single molecule Förster resonance energy transfer (smFRET) is a unique biophysical approach for studying conformational dynamics in biomacromolecules. Photon-by-photon hidden Markov modeling (H2MM) is an analysis tool that can quantify FRET dynamics of single biomolecules, even if they occur on the sub-millisecond timescale. However, dye photophysical transitions intertwined with FRET dynamics may cause artifacts. Here, we introduce multi-parameter H2MM (mpH2MM), which assists in identifying FRET dynamics based on simultaneous observation of multiple experimentally-derived parameters. We show the importance of using mpH2MM to decouple FRET dynamics caused by conformational changes from photophysical transitions in confocal-based smFRET measurements of a DNA hairpin, the maltose binding protein, MalE, and the type-III secretion system effector, YopO, from Yersinia species, all exhibiting conformational dynamics ranging from the sub-second to microsecond timescales. Overall, we show that using mpH2MM facilitates the identification and quantification of biomolecular sub-populations and their origin.

New Horizons in Structural Biology of Membrane Proteins: Experimental Evaluation of the Role of Conformational Dynamics and Intrinsic Flexibility

A plethora of membrane proteins are found along the cell surface and on the convoluted labyrinth of membranes surrounding organelles. Since the advent of various structural biology techniques, a sub-population of these proteins has become accessible to investigation at near-atomic resolutions. The predominant bona fide methods for structure solution, X-ray crystallography and cryo-EM, provide high resolution in three-dimensional space at the cost of neglecting protein motions through time. Though structures provide various rigid snapshots, only an amorphous mechanistic understanding can be inferred from interpolations between these different static states. In this review, we discuss various techniques that have been utilized in observing dynamic conformational intermediaries that remain elusive from rigid structures. More specifically we discuss the application of structural techniques such as NMR, cryo-EM and X-ray crystallography in studying protein dynamics along with complementation by conformational trapping by specific binders such as antibodies. We finally showcase the strength of various biophysical techniques including FRET, EPR and computational approaches using a multitude of succinct examples from GPCRs, transporters and ion channels.

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.

Labeling of Proteins for Single-Molecule Fluorescence Spectroscopy

Single-molecule fluorescence spectroscopy has become an important technique for studying the conformational dynamics and folding of proteins. A key step for performing such experiments is the availability of high-quality samples. This chapter describes a simple and widely applicable strategy for preparing proteins that are site-specifically labeled with a donor and an acceptor dye for single-molecule Förster resonance energy transfer (FRET) experiments. The method is based on introducing two cysteine residues that are labeled with maleimide-functionalized fluorophores, combined with high-resolution chromatography. We discuss how to optimize site-specific labeling even in the absence of orthogonal coupling chemistry and present purification strategies that are suitable for samples ranging from intrinsically disordered proteins to large folded proteins. We also discuss common problems in protein labeling, how to avoid them, and how to stringently control sample quality.

Theory and Analysis of Single-Molecule FRET Experiments

Inter-dye distances and conformational dynamics can be studied using single-molecule FRET measurements. We consider two approaches to analyze sequences of photons with recorded photon colors and arrival times. The first approach is based on FRET efficiency histograms obtained from binned photon sequences. The experimental histograms are compared with the theoretical histograms obtained using the joint distribution of acceptor and donor photons or the Gaussian approximation. In the second approach, a photon sequence is analyzed without binning. The parameters of a model describing conformational dynamics are found by maximizing the appropriate likelihood function. The first approach is simpler, while the second one is more accurate, especially when the population of species is small and transition rates are fast. The likelihood-based analysis as well as the recoloring method has the advantage that diffusion of molecules through the laser focus can be rigorously handled.

Measuring the Size and Spontaneous Fluctuations of Amyloid Aggregates with Fluorescence Correlation Spectroscopy

Bacterial amyloids decorate the cell surface of many bacteria by forming functional amyloid fibers. These amyloids have structural and biochemical similarities with many disease-related amyloids in eukaryotes. Amyloid aggregation starts at the individual monomer level, and the end product is the amyloid fibril. The process of amyloid aggregation involves a continuous increase of the aggregate size, and therefore size is a critical parameter to measure in aggregation experiments. Also, our understanding of the aggregation process, and our ability to design interventions, can benefit from a measurement of the conformational dynamics of proteins undergoing aggregation. Fluorescence correlation spectroscopy (FCS) is perhaps the most sensitive and rapid technique available currently for this purpose. It can measure the average size and the size distribution of molecules and aggregates down to sub-nm length scales and can also measure fast nanosecond time-scale conformational dynamics, all in an equilibrium solution. FCS achieves this by measuring the fluorescence intensity fluctuations of freely diffusing protein molecules in an optically defined microscopic probe volume in a solution. Here, we present a set of instructions for effectively measuring the size and dynamics of amyloid aggregates with FCS.

Structural dynamics in the evolution of a bilobed protein scaffold

Proteins conduct numerous complex biological functions by use of tailored structural dynamics. The molecular details of how these emerged from ancestral peptides remains mysterious. How does nature utilize the same repertoire of folds to diversify function? To shed light on this, we analyzed bilobed proteins with a common structural core, which is spread throughout the tree of life and is involved in diverse biological functions such as transcription, enzymatic catalysis, membrane transport, and signaling. We show here that the structural dynamics of the structural core differentiate predominantly via terminal additions during a long-period evolution. This diversifies substrate specificity and, ultimately, biological function.

Novel biophysical tools allow the structural dynamics of proteins and the regulation of such dynamics by binding partners to be explored in unprecedented detail. Although this has provided critical insights into protein function, the means by which structural dynamics direct protein evolution remain poorly understood. Here, we investigated how proteins with a bilobed structure, composed of two related domains from the periplasmic-binding protein–like II domain family, have undergone divergent evolution, leading to adaptation of their structural dynamics. We performed a structural analysis on ∼600 bilobed proteins with a common primordial structural core, which we complemented with biophysical studies to explore the structural dynamics of selected examples by single-molecule Förster resonance energy transfer and Hydrogen–Deuterium exchange mass spectrometry. We show that evolutionary modifications of the structural core, largely at its termini, enable distinct structural dynamics, allowing the diversification of these proteins into transcription factors, enzymes, and extracytoplasmic transport-related proteins. Structural embellishments of the core created interdomain interactions that stabilized structural states, reshaping the active site geometry, and ultimately altered substrate specificity. Our findings reveal an as-yet-unrecognized mechanism for the emergence of functional promiscuity during long periods of evolution and are applicable to a large number of domain architectures.

Evolution of CPEB4 Dynamics Across its Liquid-Liquid Phase Separation Transition

Knowledge about the structural and dynamic properties of proteins that form membrane-less organelles in cells via liquid-liquid phase separation (LLPS) is required for understanding the process at a molecular level. We used spin labeling and electron paramagnetic resonance (EPR) spectroscopy to investigate the dynamic properties (rotational diffusion) of the low complexity N-terminal domain of cytoplasmic polyadenylation element binding-4 protein (CPEB4NTD) across its LLPS transition, which takes place with increasing temperature. We report the coexistence of three spin labeled CPEB4NTD (CPEB4*) populations with distinct dynamic properties representing different conformational spaces, both before and within the LLPS state. Monomeric CPEB4* exhibiting fast motion defines population I and shows low abundance prior to and following LLPS. Populations II and III are part of CPEB4* assemblies where II corresponds to loose conformations with intermediate range motions and population III represents compact conformations with strongly attenuated motions. As the temperature increased the population of component II increased reversibly at the expense of component III, indicating the existence of an III ⇌ II equilibrium. We correlated the macroscopic LLPS properties with the III ⇌ II exchange process upon varying temperature and CPEB4* and salt concentrations. We hypothesized that weak transient intermolecular interactions facilitated by component II lead to LLPS, with the small assemblies integrated within the droplets. The LLPS transition, however, was not associated with a clear discontinuity in the correlation times and populations of the three components. Importantly, CPEB4NTD exhibits LLPS properties where droplet formation occurs from a preformed microscopic assembly rather than the monomeric protein molecules.

Two-colour single-molecule photoinduced electron transfer fluorescence imaging microscopy of chaperone dynamics

Many proteins are molecular machines, whose function is dependent on multiple conformational changes that are initiated and tightly controlled through biochemical stimuli. Their mechanistic understanding calls for spectroscopy that can probe simultaneously such structural coordinates. Here we present two-colour fluorescence microscopy in combination with photoinduced electron transfer (PET) probes as a method that simultaneously detects two structural coordinates in single protein molecules, one colour per coordinate. This contrasts with the commonly applied resonance energy transfer (FRET) technique that requires two colours per coordinate. We demonstrate the technique by directly and simultaneously observing three critical structural changes within the Hsp90 molecular chaperone machinery. Our results reveal synchronicity of conformational motions at remote sites during ATPase-driven closure of the Hsp90 molecular clamp, providing evidence for a cooperativity mechanism in the chaperone’s catalytic cycle. Single-molecule PET fluorescence microscopy opens up avenues in the multi-dimensional exploration of protein dynamics and allosteric mechanisms.

Revealing mechanisms of complex protein machines requires simultaneous exploration of multiple structural coordinates. Here the authors report two-colour fluorescence microscopy combined with photoinduced electron transfer probes to simultaneously detect two structural coordinates in single protein molecules.

Resolving distance variations by single-molecule FRET and EPR spectroscopy using rotamer libraries

Förster resonance energy transfer (FRET) and electron paramagnetic resonance (EPR) spectroscopy are complementary techniques for quantifying distances in the nanometer range. Both approaches are commonly employed for probing the conformations and conformational changes of biological macromolecules based on site-directed fluorescent or paramagnetic labeling. FRET can be applied in solution at ambient temperature and thus provides direct access to dynamics, especially if used at the single-molecule level, whereas EPR requires immobilization or work at cryogenic temperatures but provides data that can be more reliably used to extract distance distributions. However, a combined analysis of the complementary data from the two techniques has been complicated by the lack of a common modeling framework. Here, we demonstrate a systematic analysis approach based on rotamer libraries for both FRET and EPR labels to predict distance distributions between two labels from a structural model. Dynamics of the fluorophores within these distance distributions are taken into account by diffusional averaging, which improves the agreement with experiment. Benchmarking this methodology with a series of surface-exposed pairs of sites in a structured protein domain reveals that the lowest resolved distance differences can be as small as ∼0.25 nm for both techniques, with quantitative agreement between experimental and simulated transfer efficiencies within a range of ±0.045. Rotamer library analysis thus establishes a coherent way of treating experimental data from EPR and FRET and provides a basis for integrative structural modeling, including studies of conformational distributions and dynamics of biological macromolecules using both techniques.

Structural Ensemble of the Insulin Monomer

Experimental evidence suggests that monomeric insulin exhibits significant conformational heterogeneity, and modifications of apparently disordered regions affect both biological activity and the longevity of pharmaceutical formulations, presumably through receptor binding and fibrillation/degradation, respectively. However, a microscopic understanding of conformational heterogeneity has been lacking. Here, we integrate all-atom molecular dynamics simulations with an analysis pipeline to investigate the structural ensemble of human insulin monomers. We find that 60% of the structures present at least one of the following elements of disorder: melting of the A-chain N-terminal helix, detachment of the B-chain N-terminus, and detachment of the B-chain C-terminus. We also observe partial melting and extension of the B-chain helix and significant conformational heterogeneity in the region containing the B-chain β-turn. We then estimate hydrogen-exchange protection factors for the sampled ensemble and find them in line with experimental results for KP-insulin, although the simulations underestimate the importance of unfolded states. Our results help explain the ready exchange of specific amide sites that appear to be protected in crystal structures. Finally, we discuss the implications for insulin function and stability.

Probing the Internal Dynamics and Shape of Simple Peptides in Urea, Guanidinium Hydrochloride, and Proline Solutions with Time-Resolved Fluorescence Anisotropy and Atomistic Cosolvent Simulations

Picosecond time-resolved fluorescence anisotropy was used to measure the effect of denaturants and osmolytes on the reorientation dynamics of the simplest dipeptide. The solvent denaturants guanidinium hydrochloride (gdm), urea, and the osmolyte proline were used at several concentrations. Analysis of the concentration dependence of denaturants at a fixed temperature showed faster and slower reorientation time in two different denaturants at a nearly identical solvent viscosity (η). The reorientation time τ significantly deviates from Kramers' theory (τ ∝ η¹) in the high friction limit for guanidinium and urea with r ≈ 0.4 and r ≈ 0.6 at pH 7.2, respectively. In proline, τ is nearly proportional to η. Atomistic molecular dynamics simulations of the dipeptide in identical cosolvents showed excellent agreement with the measured rotational orientation time. The dipeptide dihedral (ϕ, ψ) isomerization times in water and 6 M urea are almost identical and significantly slower in guanidinium. If a faster and slower reorientation time can be associated with the compact and expanded shapes, the fractional viscosity dependence for guanidinium and urea may result from the fact that internal dynamics of peptides in these cosolvents involve higher and lower internal friction within the dynamic elements.

Markov State Models to Study the Functional Dynamics of Proteins in the Wake of Machine Learning

Markov state models (MSMs) based on molecular dynamics (MD) simulations are routinely employed to study protein folding, however, their application to functional conformational changes of biomolecules is still limited. In the past few years, the field of computational chemistry has experienced a surge of advancements stemming from machine learning algorithms, and MSMs have not been left out. Unlike global processes, such as protein folding, the application of MSMs to functional conformational changes is challenging because they mostly consist of localized structural transitions. Therefore, it is critical to properly select a subset of structural features that can describe the slowest dynamics of these functional conformational changes. To address this challenge, we recommend several automatic feature selection methods such as Spectral-OASIS. To identify states in MSMs, the chosen features can be subject to dimensionality reduction methods such as TICA or deep learning based VAMPNets to project MD conformations onto a few collective variables for subsequent clustering. Another challenge for the application of MSMs to the study of functional conformational changes is the ability to comprehend their biophysical mechanisms, as MSMs built for these processes often require a large number of states. We recommend the recently developed quasi-MSMs (qMSMs) to address this issue. Compared to MSMs, qMSMs encode the non-Markovian dynamics via the generalized master equation and can significantly reduce the number of states. As a result, qMSMs can be built with a handful of states to facilitate the interpretation of functional conformational changes. In the wake of machine learning, we believe that the rapid advancement in the MSM methodology will lead to their wider application in studying functional conformational changes of biomolecules.

Allosteric coupling of sub-millisecond clamshell motions in ionotropic glutamate receptor ligand-binding domains

Ionotropic glutamate receptors (iGluRs) mediate signal transmission in the brain and are important drug targets. Structural studies show snapshots of iGluRs, which provide a mechanistic understanding of gating, yet the rapid motions driving the receptor machinery are largely elusive. Here we detect kinetics of conformational change of isolated clamshell-shaped ligand-binding domains (LBDs) from the three major iGluR sub-types, which initiate gating upon binding of agonists. We design fluorescence probes to measure domain motions through nanosecond fluorescence correlation spectroscopy. We observe a broad kinetic spectrum of LBD dynamics that underlie activation of iGluRs. Microsecond clamshell motions slow upon dimerization and freeze upon binding of full and partial agonists. We uncover allosteric coupling within NMDA LBD hetero-dimers, where binding of L-glutamate to the GluN2A LBD stalls clamshell motions of the glycine-binding GluN1 LBD. Our results reveal rapid LBD dynamics across iGluRs and suggest a mechanism of negative allosteric cooperativity in NMDA receptors.

Rajab et al. study the dynamics of closure of ligand binding domains (LBD) of the three major ionotropic glutamate receptor subtypes. They find pronounced sub-millisecond fluctuations in the apo state of LBDs from all three sub-types and reveal a pathway of allosteric communication in LBD dynamics across the dimerization interface

Single-Molecule FRET of Membrane Transport Proteins

Uncovering the structure and function of biomolecules is a fundamental goal in structural biology. Membrane-embedded transport proteins are ubiquitous in all kingdoms of life. Despite structural flexibility, their mechanisms are typically studied by ensemble biochemical methods or by static high-resolution structures, which complicate a detailed understanding of their dynamics. Here, we review the recent progress of single molecule Förster Resonance Energy Transfer (smFRET) in determining mechanisms and timescales of substrate transport across membranes. These studies do not only demonstrate the versatility and suitability of state-of-the-art smFRET tools for studying membrane transport proteins but they also highlight the importance of membrane mimicking environments in preserving the function of these proteins. The current achievements advance our understanding of transport mechanisms and have the potential to facilitate future progress in drug design.

Slow Escape from a Helical Misfolded State of the Pore-Forming Toxin Cytolysin A

The pore-forming toxin cytolysin A (ClyA) is expressed as a large α-helical monomer that, upon interaction with membranes, undergoes a major conformational rearrangement into the protomer conformation, which then assembles into a cytolytic pore. Here, we investigate the folding kinetics of the ClyA monomer with single-molecule Förster resonance energy transfer spectroscopy in combination with microfluidic mixing, stopped-flow circular dichroism experiments, and molecular simulations. The complex folding process occurs over a broad range of time scales, from hundreds of nanoseconds to minutes. The very slow formation of the native state occurs from a rapidly formed and highly collapsed intermediate with large helical content and nonnative topology. Molecular dynamics simulations suggest pronounced non-native interactions as the origin of the slow escape from this deep trap in the free-energy surface, and a variational enhanced path-sampling approach enables a glimpse of the folding process that is supported by the experimental data.

Protein intrinsic disorder on a dynamic nucleosomal landscape

The complex nucleoprotein landscape of the eukaryotic cell nucleus is rich in dynamic proteins that lack a stable three-dimensional structure. Many of these intrinsically disordered proteins operate directly on the first fundamental level of genome compaction: the nucleosome. Here we give an overview of how disordered interactions with and within nucleosomes shape the dynamics, architecture, and epigenetic regulation of the genetic material, controlling cellular transcription patterns. We highlight experimental and computational challenges in the study of protein disorder and illustrate how integrative approaches are increasingly unveiling the fine details of nuclear interaction networks. We finally dissect sequence properties encoded in disordered regions and assess common features of disordered nucleosome-binding proteins. As drivers of many critical biological processes, disordered proteins are integral to a comprehensive molecular view of the dynamic nuclear milieu.