Accurate Transfer Efficiencies, Distance Distributions, and Ensembles of Unfolded and Intrinsically Disordered Proteins From Single-Molecule FRET

Conformational dynamics of the hepatitis C virus 3'X RNA

The 3' end of the hepatitis C virus genome is terminated by a highly conserved, 98 nt sequence called 3'X. This untranslated structural element is thought to regulate several essential RNA-dependent processes associated with infection. 3'X has two proposed conformations comprised of either three or two stem-loop structures that result from the different base-pairing interactions within the first 55 nt. Here, we used single-molecule Förster resonance energy transfer spectroscopy to monitor the conformational status of fluorescently labeled constructs that isolate this region of the RNA (3'X55). We observed that 3'X55 can adopt both proposed conformations and the relative abundance of them can be modulated by either solution conditions or nucleotide deletions. Furthermore, interconversion between the two conformations takes place over the course of several hours. The simultaneous existence of two slowly interconverting conformations may help prime individual copies of the viral genome for either viral protein or RNA synthesis, thereby minimizing conflicts between these two competing processes.

Field-domain rapid-scan EPR at 240GHz for studies of protein functional dynamics at room temperature

We present field-domain rapid-scan (RS) electron paramagnetic resonance (EPR) at 8.6T and 240GHz. To enable this technique, we upgraded a home-built EPR spectrometer with an FPGA-enabled digitizer and real-time processing software. The software leverages the Hilbert transform to recover the in-phase (I) and quadrature (Q) channels, and therefore the raw absorptive and dispersive signals, χ' and χ'', from their combined magnitude (I2+Q2). Averaging a magnitude is simpler than real-time coherent averaging and has the added benefit of permitting long-timescale signal averaging (up to at least 2.5×106 scans) because it eliminates the effects of source-receiver phase drift. Our rapid-scan (RS) EPR provides a signal-to-noise ratio that is approximately twice that of continuous wave (CW) EPR under the same experimental conditions, after scaling by the square root of acquisition time. We apply our RS EPR as an extension of the recently reported time-resolved Gd-Gd EPR (TiGGER) [Maity et al., 2023], which is able to monitor inter-residue distance changes during the photocycle of a photoresponsive protein through changes in the Gd-Gd dipolar couplings. RS, opposed to CW, returns field-swept spectra as a function of time with 10ms time resolution, and thus, adds a second dimension to the static field transients recorded by TiGGER. We were able to use RS TiGGER to track time-dependent and temperature-dependent kinetics of AsLOV2, a light-activated phototropin domain found in oats. The results presented here combine the benefits of RS EPR with the improved spectral resolution and sensitivity of Gd chelates at high magnetic fields. In the future, field-domain RS EPR at high magnetic fields may enable studies of other real-time kinetic processes with time resolutions that are otherwise difficult to access in the solution state.

Nanosecond chain dynamics of single-stranded nucleic acids

The conformational dynamics of single-stranded nucleic acids are fundamental for nucleic acid folding and function. However, their elementary chain dynamics have been difficult to resolve experimentally. Here we employ a combination of single-molecule Förster resonance energy transfer, nanosecond fluorescence correlation spectroscopy, and nanophotonic enhancement to determine the conformational ensembles and rapid chain dynamics of short single-stranded nucleic acids in solution. To interpret the experimental results in terms of end-to-end distance dynamics, we utilize the hierarchical chain growth approach, simple polymer models, and refinement with Bayesian inference to generate structural ensembles that closely align with the experimental data. The resulting chain reconfiguration times are exceedingly rapid, in the 10-ns range. Solvent viscosity-dependent measurements indicate that these dynamics of single-stranded nucleic acids exhibit negligible internal friction and are thus dominated by solvent friction. Our results provide a detailed view of the conformational distributions and rapid dynamics of single-stranded nucleic acids.

Unraveling Burst Selection Bias in Single-Molecule FRET of Species with Unequal Brightness and Diffusivity

Single-molecule free diffusion experiments enable accurate quantification of coexisting species or states. However, unequal brightness and diffusivity introduce a burst selection bias and affect the interpretation of experimental results. We address this issue with a photon-by-photon maximum likelihood method, burstML, which explicitly considers burst selection criteria. BurstML accurately estimates parameters, including photon count rates, diffusion times, Förster resonance energy transfer (FRET) efficiencies, and population, even in cases where species are poorly distinguished in FRET efficiency histograms. We develop a quantitative theory that determines the fraction of photon bursts corresponding to each species and thus obtain accurate species populations from the measured burst fractions. In addition, we provide a simple approximate formula for burst fractions and establish the range of parameters where unequal brightness and diffusivity can significantly affect the results obtained by conventional methods. The performance of the burstML method is compared with that of a maximum likelihood method that assumes equal species brightness and diffusivity, as well as standard Gaussian fitting of FRET efficiency histograms, using both simulated and real single-molecule data for cold-shock protein, protein L, and protein G. The burstML method enhances the accuracy of parameter estimation in single-molecule fluorescence studies.

Time-heterogeneity of the Förster Radius from Dipole Orientational Dynamics Explains Observed Dynamic Shift

Förster resonance energy transfer (FRET) is a quantum mechanical phenomenon involving the non-radiative transfer of energy between coupled electric dipoles. Due to the strong dependence of FRET on the distance between the dipoles, it is frequently used as a "molecular ruler" in biology, chemistry, and physics. This is done by placing dipolar molecules called dyes on molecules of interest. In time-resolved confocal single-molecule FRET (smFRET) experiments, the joint distribution of the FRET efficiency and the donor fluorescence lifetime can reveal underlying molecular conformational dynamics via deviation from their theoretical Förster relationship. This deviation is referred to as a dynamic shift. Quantifying the dynamic shift caused by the motion of the fluorescent dyes is essential to decoupling the dynamics of the studied molecules and the dyes. We develop novel Langevin models for the dye linker dynamics, including rotational dynamics, based on first physics principles and proper dye linker chemistry to match accessible volumes predicted by molecular dynamics simulations. By simulating the dyes' stochastic translational and rotational dynamics, we show that the observed dynamic shift can largely be attributed to the mutual orientational dynamics of the electric dipole moments associated with the dyes, not their accessible volume.

Hierarchical Assembly of Single-Stranded RNA

Single-stranded RNA (ssRNA) plays a major role in the flow of genetic information-most notably, in the form of messenger RNA (mRNA)-and in the regulation of biological processes. The highly dynamic nature of chains of unpaired nucleobases challenges structural characterizations of ssRNA by experiments or molecular dynamics (MD) simulations alike. Here, we use hierarchical chain growth (HCG) to construct ensembles of ssRNA chains. HCG assembles the structures of protein and nucleic acid chains from fragment libraries created by MD simulations. Applied to homo- and heteropolymeric ssRNAs of different lengths, we find that HCG produces structural ensembles that overall are in good agreement with diverse experiments, including nuclear magnetic resonance (NMR), small-angle X-ray scattering (SAXS), and single-molecule Förster resonance energy transfer (FRET). The agreement can be further improved by ensemble refinement using Bayesian inference of ensembles (BioEn). HCG can also be used to assemble RNA structures that combine base-paired and base-unpaired regions, as illustrated for the 5' untranslated region (UTR) of SARS-CoV-2 RNA.

DNA binding redistributes activation domain ensemble and accessibility in pioneer factor Sox2

More than 1600 human transcription factors orchestrate the transcriptional machinery to control gene expression and cell fate. Their function is conveyed through intrinsically disordered regions (IDRs) containing activation or repression domains but lacking quantitative structural ensemble models prevents their mechanistic decoding. Here we integrate single-molecule FRET and NMR spectroscopy with molecular simulations showing that DNA binding can lead to complex changes in the IDR ensemble and accessibility. The C-terminal IDR of pioneer factor Sox2 is highly disordered but its conformational dynamics are guided by weak and dynamic charge interactions with the folded DNA binding domain. Both DNA and nucleosome binding induce major rearrangements in the IDR ensemble without affecting DNA binding affinity. Remarkably, interdomain interactions are redistributed in complex with DNA leading to variable exposure of two activation domains critical for transcription. Charged intramolecular interactions allowing for dynamic redistributions may be common in transcription factors and necessary for sensitive tuning of structural ensembles.

Single-molecule-binding studies of antivirals targeting the hepatitis C virus core protein

IMPORTANCE

The hepatitis C virus is associated with nearly 300,000 deaths annually. At the core of the virus is an RNA-protein complex called the nucleocapsid, which consists of the viral genome and many copies of the core protein. Because the assembly of the nucleocapsid is a critical step in viral replication, a considerable amount of effort has been devoted to identifying antiviral therapeutics that can bind to the core protein and disrupt assembly. Although several candidates have been identified, little is known about how they interact with the core protein or how those interactions alter the structure and thus the function of this viral protein. Our work biochemically characterizes several of these binding interactions, highlighting both similarities and differences as well as strengths and weaknesses. These insights bolster the notion that this viral protein is a viable target for novel therapeutics and will help to guide future developments of these candidate antivirals.

Nuclear magnetic resonance/single molecule fluorescence combinations to study dynamic protein systems

Many proteins require different structural states or conformations for function, and intrinsically disordered proteins, i.e. proteins without stable three-dimensional structure, are certainly an extreme. Single molecule fluorescence and nuclear magnetic resonance (NMR) spectroscopy are both exceptionally well suited to decipher and describe these states and their interconversion. Different time scales, from picoseconds to several milliseconds, can be addressed by both techniques. The length scales probed and the sample requirements (e.g. concentration, molecular weight, sample complexity) are, however, vastly different, making NMR and single molecule fluorescence an excellent combination for integrated studies. Here, we review recently undertaken approaches for the combined use of NMR and single molecule fluorescence to study protein dynamics.

Rapid droplet-based mixing for single-molecule spectroscopy

Probing non-equilibrium dynamics with single-molecule spectroscopy is important for dissecting biomolecular mechanisms. However, existing microfluidic rapid-mixing systems for this purpose are incompatible with surface-adhesive biomolecules, exhibit undesirable flow dispersion and are often demanding to fabricate. Here we introduce droplet-based microfluidic mixing for single-molecule spectroscopy to overcome these limitations in a wide range of applications. We demonstrate its robust functionality with binding kinetics of even very surface-adhesive proteins on the millisecond timescale.

Extreme dynamics in a biomolecular condensate

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

Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology

Intense study of intrinsically disordered proteins (IDPs) did not begin in earnest until the late 1990s when a few groups, working independently, convinced the community that these 'weird' proteins could have important functions. Over the past two decades, it has become clear that IDPs play critical roles in a multitude of biological phenomena with prominent examples including coordination in signaling hubs, enabling gene regulation, and regulating ion channels, just to name a few. One contributing factor that delayed appreciation of IDP functional significance is the experimental difficulty in characterizing their dynamic conformations. The combined application of multiple methods, termed integrative structural biology, has emerged as an essential approach to understanding IDP phenomena. Here, we review some of the recent applications of the integrative structural biology philosophy to study IDPs.

GPCR-mediated β-arrestin activation deconvoluted with single-molecule precision

β-arrestins bind G protein-coupled receptors to terminate G protein signaling and to facilitate other downstream signaling pathways. Using single-molecule fluorescence resonance energy transfer imaging, we show that β-arrestin is strongly autoinhibited in its basal state. Its engagement with a phosphopeptide mimicking phosphorylated receptor tail efficiently releases the β-arrestin tail from its N domain to assume distinct conformations. Unexpectedly, we find that β-arrestin binding to phosphorylated receptor, with a phosphorylation barcode identical to the isolated phosphopeptide, is highly inefficient and that agonist-promoted receptor activation is required for β-arrestin activation, consistent with the release of a sequestered receptor C tail. These findings, together with focused cellular investigations, reveal that agonism and receptor C-tail release are specific determinants of the rate and efficiency of β-arrestin activation by phosphorylated receptor. We infer that receptor phosphorylation patterns, in combination with receptor agonism, synergistically establish the strength and specificity with which diverse, downstream β-arrestin-mediated events are directed.

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.

Generating Ensembles of Dynamic Misfolding Proteins

The early stages of protein misfolding and aggregation involve disordered and partially folded protein conformers that contain a high degree of dynamic disorder. These dynamic species may undergo large-scale intra-molecular motions of intrinsically disordered protein (IDP) precursors, or flexible, low affinity inter-molecular binding in oligomeric assemblies. In both cases, generating atomic level visualization of the interconverting species that captures the conformations explored and their physico-chemical properties remains hugely challenging. How specific sub-ensembles of conformers that are on-pathway to aggregation into amyloid can be identified from their aggregation-resilient counterparts within these large heterogenous pools of rapidly moving molecules represents an additional level of complexity. Here, we describe current experimental and computational approaches designed to capture the dynamic nature of the early stages of protein misfolding and aggregation, and discuss potential challenges in describing these species because of the ensemble averaging of experimental restraints that arise from motions on the millisecond timescale. We give a perspective of how machine learning methods can be used to extract aggregation-relevant sub-ensembles and provide two examples of such an approach in which specific interactions of defined species within the dynamic ensembles of α-synuclein (αSyn) and β2-microgloblulin (β2m) can be captured and investigated.

Global Structure of the Intrinsically Disordered Protein Tau Emerges from Its Local Structure

The paradigmatic disordered protein tau plays an important role in neuronal function and neurodegenerative diseases. To disentangle the factors controlling the balance between functional and disease-associated conformational states, we build a structural ensemble of the tau K18 fragment containing the four pseudorepeat domains involved in both microtubule binding and amyloid fibril formation. We assemble 129-residue-long tau K18 chains with atomic detail from an extensive fragment library constructed with molecular dynamics simulations. We introduce a reweighted hierarchical chain growth (RHCG) algorithm that integrates experimental data reporting on the local structure into the assembly process in a systematic manner. By combining Bayesian ensemble refinement with importance sampling, we obtain well-defined ensembles and overcome the problem of exponentially varying weights in the integrative modeling of long-chain polymeric molecules. The resulting tau K18 ensembles capture nuclear magnetic resonance (NMR) chemical shift and J-coupling measurements. Without further fitting, we achieve very good agreement with measurements of NMR residual dipolar couplings. The good agreement with experimental measures of global structure such as single-molecule Förster resonance energy transfer (FRET) efficiencies is improved further by ensemble refinement. By comparing wild-type and mutant ensembles, we show that pathogenic single-point P301L, P301S, and P301T mutations shift the population from the turn-like conformations of the functional microtubule-bound state to the extended conformations of disease-associated tau fibrils. RHCG thus provides us with an atomically detailed view of the population equilibrium between functional and aggregation-prone states of tau K18, and demonstrates that global structural characteristics of this intrinsically disordered protein emerge from its local structure.

Databases for intrinsically disordered proteins

Intrinsically disordered regions (IDRs) lacking a fixed three-dimensional protein structure are widespread and play a central role in cell regulation. Only a small fraction of IDRs have been functionally characterized, with heterogeneous experimental evidence that is largely buried in the literature. Predictions of IDRs are still difficult to estimate and are poorly characterized. Here, an overview of the publicly available knowledge about IDRs is reported, including manually curated resources, deposition databases and prediction repositories. The types, scopes and availability of the various resources are analyzed, and their complementarity and overlap are highlighted. The volume of information included and the relevance to the field of structural biology are compared.

Release of linker histone from the nucleosome driven by polyelectrolyte competition with a disordered protein

Highly charged intrinsically disordered proteins are essential regulators of chromatin structure and transcriptional activity. Here we identify a surprising mechanism of molecular competition that relies on the pronounced dynamical disorder present in these polyelectrolytes and their complexes. The highly positively charged human linker histone H1.0 (H1) binds to nucleosomes with ultrahigh affinity, implying residence times incompatible with efficient biological regulation. However, we show that the disordered regions of H1 retain their large-amplitude dynamics when bound to the nucleosome, which enables the highly negatively charged and disordered histone chaperone prothymosin α to efficiently invade the H1-nucleosome complex and displace H1 via a competitive substitution mechanism, vastly accelerating H1 dissociation. By integrating experiments and simulations, we establish a molecular model that rationalizes the remarkable kinetics of this process structurally and dynamically. Given the abundance of polyelectrolyte sequences in the nuclear proteome, this mechanism is likely to be widespread in cellular regulation.

Quantifying charge state heterogeneity for proteins with multiple ionizable residues

Ionizable residues can release and take up protons and this has an influence on protein structure and function. The extent of protonation is linked to the overall pH of the solution and the local environments of ionizable residues. Binding or unbinding of a single proton generates a distinct charge microstate defined by a specific pattern of charges. Accordingly, the overall partition function is a sum over all charge microstates and Boltzmann weights of all conformations associated with each of the charge microstates. This ensemble-of-ensembles description recast as a q-canonical ensemble allows us to analyze and interpret potentiometric titrations that provide information regarding net charge as a function of pH. In the q-canonical ensemble, charge microstates are grouped into mesostates where each mesostate is a collection of microstates of the same net charge. Here, we show that leveraging the structure of the q-canonical ensemble allows us to decouple contributions of net proton binding and release from proton arrangement and conformational considerations. Through application of the q-canonical formalism to analyze potentiometric measurements of net charge in proteins with repetitive patterns of Lys and Glu residues, we determine the underlying mesostate pKa values and, more importantly, we estimate relative mesostate populations as a function of pH. This is a strength of using the q-canonical approach that cannot be replicated using purely site-specific analyses. Overall, our work shows how measurements of charge equilibria, decoupled from measurements of conformational equilibria, and analyzed using the framework of the q-canonical ensemble, provide protein-specific quantitative descriptions of pH-dependent populations of mesostates. This method is of direct relevance for measuring and understanding how different charge states contribute to conformational, binding, and phase equilibria of proteins.

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.

Apolar chemical environments compact unfolded RNAs and can promote folding

It is well documented that the structure, and thus function, of nucleic acids depends on the chemical environment surrounding them, which often includes potential proteinaceous binding partners. The nonpolar amino acid side chains of these proteins will invariably alter the polarity of the local chemical environment around the nucleic acid. However, we are only beginning to understand how environmental polarity generally influences the structural and energetic properties of RNA folding. Here, we use a series of aqueous-organic cosolvent mixtures to systematically modulate the solvent polarity around two different RNA folding constructs that can form either secondary or tertiary structural elements. Using single-molecule Förster resonance energy transfer spectroscopy to simultaneously monitor the structural and energetic properties of these RNAs, we show that the unfolded conformations of both model RNAs become more compact in apolar environments characterized by dielectric constants less than that of pure water. In the case of tertiary structure formation, this compaction also gives rise to more energetically favorable folding. We propose that these physical changes arise from an enhanced accumulation of counterions in the low dielectric environment surrounding the unfolded RNA.

Integrating single-molecule spectroscopy and simulations for the study of intrinsically disordered proteins

Over the last two decades, intrinsically disordered proteins and protein regions (IDRs) have emerged from a niche corner of biophysics to be recognized as essential drivers of cellular function. Various techniques have provided fundamental insight into the function and dysfunction of IDRs. Among these techniques, single-molecule fluorescence spectroscopy and molecular simulations have played a major role in shaping our modern understanding of the sequence-encoded conformational behavior of disordered proteins. While both techniques are frequently used in isolation, when combined they offer synergistic and complementary information that can help uncover complex molecular details. Here we offer an overview of single-molecule fluorescence spectroscopy and molecular simulations in the context of studying disordered proteins. We discuss the various means in which simulations and single-molecule spectroscopy can be integrated, and consider a number of studies in which this integration has uncovered biological and biophysical mechanisms.

The diversity of molecular interactions involving intrinsically disordered proteins: A molecular modeling perspective

Intrinsically Disordered Proteins and Regions (IDPs/IDRs) are key components of a multitude of biological processes. Conformational malleability enables IDPs/IDRs to perform very specialized functions that cannot be accomplished by globular proteins. The functional role for most of these proteins is related to the recognition of other biomolecules to regulate biological processes or as a part of signaling pathways. Depending on the extent of disorder, the number of interacting sites and the type of partner, very different architectures for the resulting assemblies are possible. More recently, molecular condensates with liquid-like properties composed of multiple copies of IDPs and nucleic acids have been proven to regulate key processes in eukaryotic cells. The structural and kinetic details of disordered biomolecular complexes are difficult to unveil experimentally due to their inherent conformational heterogeneity. Computational approaches, alone or in combination with experimental data, have emerged as unavoidable tools to understand the functional mechanisms of this elusive type of assemblies. The level of description used, all-atom or coarse-grained, strongly depends on the size of the molecular systems and on the timescale of the investigated mechanism. In this mini-review, we describe the most relevant architectures found for molecular interactions involving IDPs/IDRs and the computational strategies applied for their investigation.

Combining Rapid Microfluidic Mixing and Three-Color Single-Molecule FRET for Probing the Kinetics of Protein Conformational Changes

Single-molecule Förster resonance energy transfer (FRET) is well suited for studying the kinetics of protein conformational changes, owing to its high sensitivity and ability to resolve individual subpopulations in heterogeneous systems. However, the most common approach employing two fluorophores can only monitor one distance at a time, and the use of three fluorophores for simultaneously monitoring multiple distances has largely been limited to equilibrium fluctuations. Here we show that three-color single-molecule FRET can be combined with rapid microfluidic mixing to investigate conformational changes in a protein from milliseconds to minutes. In combination with manual mixing, we extended the kinetics to 1 h, corresponding to a total range of 5 orders of magnitude in time. We studied the monomer-to-protomer conversion of the pore-forming toxin cytolysin A (ClyA), one of the largest protein conformational transitions known. Site-specific labeling of ClyA with three fluorophores enabled us to follow the kinetics of three intramolecular distances at the same time and revealed a previously undetected intermediate. The combination of three-color single-molecule FRET with rapid microfluidic mixing thus provides an approach for probing the mechanisms of complex biomolecular processes with high time resolution.

Ratiometric Single-Molecule FRET Measurements to Probe Conformational Subpopulations of Intrinsically Disordered Proteins

Over the past few decades, numerous examples have demonstrated that intrinsic disorder in proteins lies at the heart of many vital processes, including transcriptional regulation, stress response, cellular signaling, and most recently protein liquid-liquid phase separation. The so-called intrinsically disordered proteins (IDPs) involved in these processes have presented a challenge to the classic protein "structure-function paradigm," as their functions do not necessarily involve well-defined structures. Understanding the mechanisms of IDP function is likewise challenging because traditional structure determination methods often fail with such proteins or provide little information about the diverse array of structures that can be related to different functions of a single IDP. Single-molecule fluorescence methods can overcome this ensemble-average masking, allowing the resolution of subpopulations and dynamics and thus providing invaluable insights into IDPs and their function. In this protocol, we describe a ratiometric single-molecule Förster resonance energy transfer (smFRET) routine that permits the investigation of IDP conformational subpopulations and dynamics. We note that this is a basic protocol, and we provide brief information and references for more complex analysis schemes available for in-depth characterization. This protocol covers optical setup preparation and protein handling and provides insights into experimental design and outcomes, together with background information about theory and a brief discussion of troubleshooting. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Ratiometric smFRET detection and analysis of IDPs Support Protocol 1: Fluorophore labeling of a protein through maleimide chemistry Support Protocol 2: Sample chamber preparation Support Protocol 3: Determination of direct excitation of acceptor by donor excitation and leakage of donor emission to acceptor emission channel.

Integrating single-molecule FRET and biomolecular simulations to study diverse interactions between nucleic acids and proteins

The conformations of biological macromolecules are intimately related to their cellular functions. Conveniently, the well-characterized dipole-dipole distance-dependence of Förster resonance energy transfer (FRET) makes it possible to measure and monitor the nanoscale spatial dimensions of these conformations using fluorescence spectroscopy. For this reason, FRET is often used in conjunction with single-molecule detection to study a wide range of conformationally dynamic biochemical processes. Written for those not yet familiar with the subject, this review aims to introduce biochemists to the methodology associated with single-molecule FRET, with a particular emphasis on how it can be combined with biomolecular simulations to study diverse interactions between nucleic acids and proteins. In the first section, we highlight several conceptual and practical considerations related to this integrative approach. In the second section, we review a few recent research efforts wherein various combinations of single-molecule FRET and biomolecular simulations were used to study the structural and dynamic properties of biochemical systems involving different types of nucleic acids (e.g., DNA and RNA) and proteins (e.g., folded and disordered).

Physics-based computational and theoretical approaches to intrinsically disordered proteins

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.

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current 'state of the art' from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of 'soft recommendations' about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage 'open science' practices.

Defining the Neuropathological Aggresome across in Silico, in Vitro, and ex Vivo Experiments

The loss of proteostasis over the life course is associated with a wide range of debilitating degenerative diseases and is a central hallmark of human aging. When left unchecked, proteins that are intrinsically disordered can pathologically aggregate into highly ordered fibrils, plaques, and tangles (termed amyloids), which are associated with countless disorders such as Alzheimer's disease, Parkinson's disease, type II diabetes, cancer, and even certain viral infections. However, despite significant advances in protein folding and solution biophysics techniques, determining the molecular cause of these conditions in humans has remained elusive. This has been due, in part, to recent discoveries showing that soluble protein oligomers, not insoluble fibrils or plaques, drive the majority of pathological processes. This has subsequently led researchers to focus instead on heterogeneous and often promiscuous protein oligomers. Unfortunately, significant gaps remain in how to prepare, model, experimentally corroborate, and extract amyloid oligomers relevant to human disease in a systematic manner. This Review will report on each of these techniques and their successes and shortcomings in an attempt to standardize comparisons between protein oligomers across disciplines, especially in the context of neurodegeneration. By standardizing multiple techniques and identifying their common overlap, a clearer picture of the soluble neuropathological aggresome can be constructed and used as a baseline for studying human disease and aging.

PED in 2021: a major update of the protein ensemble database for intrinsically disordered proteins

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

Polyelectrolyte interactions enable rapid association and dissociation in high-affinity disordered protein complexes

Highly charged intrinsically disordered proteins can form complexes with very high affinity in which both binding partners fully retain their disorder and dynamics, exemplified by the positively charged linker histone H1.0 and its chaperone, the negatively charged prothymosin α. Their interaction exhibits another surprising feature: The association/dissociation kinetics switch from slow two-state-like exchange at low protein concentrations to fast exchange at higher, physiologically relevant concentrations. Here we show that this change in mechanism can be explained by the formation of transient ternary complexes favored at high protein concentrations that accelerate the exchange between bound and unbound populations by orders of magnitude. Molecular simulations show how the extreme disorder in such polyelectrolyte complexes facilitates (i) diffusion-limited binding, (ii) transient ternary complex formation, and (iii) fast exchange of monomers by competitive substitution, which together enable rapid kinetics. Biological polyelectrolytes thus have the potential to keep regulatory networks highly responsive even for interactions with extremely high affinities.

Automated and optimally FRET-assisted structural modeling

FRET experiments can provide state-specific structural information of complex dynamic biomolecular assemblies. However, to overcome the sparsity of FRET experiments, they need to be combined with computer simulations. We introduce a program suite with (i) an automated design tool for FRET experiments, which determines how many and which FRET pairs should be used to minimize the uncertainty and maximize the accuracy of an integrative structure, (ii) an efficient approach for FRET-assisted coarse-grained structural modeling, and all-atom molecular dynamics simulations-based refinement, and (iii) a quantitative quality estimate for judging the accuracy of FRET-derived structures as opposed to precision. We benchmark our tools against simulated and experimental data of proteins with multiple conformational states and demonstrate an accuracy of ~3 Å RMSD_Cα against X-ray structures for sets of 15 to 23 FRET pairs. Free and open-source software for the introduced workflow is available at https://github.com/Fluorescence-Tools. A web server for FRET-assisted structural modeling of proteins is available at http://nmsim.de.

To overcome the limitation of FRET data being too sparse to cover all structural details, FRET experiments need to be carefully designed and complemented with simulations. Here the authors present a toolkit for automated design of FRET experiments, which determines how many and which FRET pairs should be used to maximize the accuracy, and for FRET-assisted structural modeling and refinement at the atomistic level.

Single-Molecule FRET of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) are now widely recognized as playing critical roles in a broad range of cellular functions as well as being implicated in diverse diseases. Their lack of stable secondary structure and tertiary interactions, coupled with their sensitivity to measurement conditions, stymies many traditional structural biology approaches. Single-molecule Förster resonance energy transfer (smFRET) is now widely used to characterize the physicochemical properties of these proteins in isolation and is being increasingly applied to more complex assemblies and experimental environments. This review provides an overview of confocal diffusion-based smFRET as an experimental tool, including descriptions of instrumentation, data analysis, and protein labeling. Recent papers are discussed that illustrate the unique capability of smFRET to provide insight into aggregation-prone IDPs, protein–protein interactions involving IDPs, and IDPs in complex experimental milieus.

Emerging consensus on the collapse of unfolded and intrinsically disordered proteins in water

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.

Binding without folding - the biomolecular function of disordered polyelectrolyte complexes

Recent evidence shows that oppositely charged intrinsically disordered proteins (IDPs) can form high-affinity complexes that involve neither the formation of secondary or tertiary structure nor site-specific interactions between individual residues. Similar electrostatically dominated interactions have also been identified for positively charged IDPs binding to nucleic acids. These highly disordered polyelectrolyte complexes constitute an extreme case within the spectrum of biomolecular interactions involving disorder. Such interactions are likely to be widespread, since sequence analysis predicts proteins with highly charged disordered regions to be surprisingly numerous. Here, we summarize the insights that have emerged from the highly disordered polyelectrolyte complexes identified so far, and we highlight recent developments and future challenges in (i) establishing models for the underlying highly dynamic structural ensembles, (ii) understanding the novel binding mechanisms associated with them, and (iii) identifying the functional consequences.

Single-molecule FRET methods to study the dynamics of proteins at work

Feynman commented that "Everything that living things do can be understood in terms of the jiggling and wiggling of atoms". Proteins can jiggle and wiggle large structural elements such as domains and subunits as part of their functional cycles. Single-molecule fluorescence resonance energy transfer (smFRET) is an excellent tool to study conformational dynamics and decipher coordinated large-scale motions within proteins. smFRET methods introduced in recent years are geared toward understanding the time scales and amplitudes of function-related motions. This review discusses the methodology for obtaining and analyzing smFRET temporal trajectories that provide direct dynamic information on transitions between conformational states. It also introduces correlation methods that are useful for characterizing intramolecular motions. This arsenal of techniques has been used to study multiple molecular systems, from membrane proteins through molecular chaperones, and we examine some of these studies here. Recent exciting methodological novelties permit revealing very fast, submillisecond dynamics, whose relevance to protein function is yet to be fully grasped.

An intrinsically disordered proteins community for ELIXIR

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are now recognised as major determinants in cellular regulation. This white paper presents a roadmap for future e-infrastructure developments in the field of IDP research within the ELIXIR framework. The goal of these developments is to drive the creation of high-quality tools and resources to support the identification, analysis and functional characterisation of IDPs. The roadmap is the result of a workshop titled “An intrinsically disordered protein user community proposal for ELIXIR” held at the University of Padua. The workshop, and further consultation with the members of the wider IDP community, identified the key priority areas for the roadmap including the development of standards for data annotation, storage and dissemination; integration of IDP data into the ELIXIR Core Data Resources; and the creation of benchmarking criteria for IDP-related software. Here, we discuss these areas of priority, how they can be implemented in cooperation with the ELIXIR platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for an IDP Community in ELIXIR and is an appeal to identify and involve new stakeholders.

q-Canonical Monte Carlo Sampling for Modeling the Linkage between Charge Regulation and Conformational Equilibria of Peptides

The overall charge content and the patterning of charged residues have a profound impact on the conformational ensembles adopted by intrinsically disordered proteins. These parameters can be altered by charge regulation, which refers to the effects of post-translational modifications, pH-dependent changes to charge, and conformational fluctuations that modify the pKa values of ionizable residues. Although atomistic simulations have played a prominent role in uncovering the major sequence-ensemble relationships of IDPs, most simulations assume fixed charge states for ionizable residues. This may lead to erroneous estimates for conformational equilibria if they are linked to charge regulation. Here, we report the development of a new method we term q-canonical Monte Carlo sampling for modeling the linkage between charge regulation and conformational equilibria. The method, which is designed to be interoperable with the ABSINTH implicit solvation model, operates as follows: For a protein sequence with n ionizable residues, we start with all 2n charge microstates and use a criterion based on model compound pKa values to prune down to a subset of thermodynamically relevant charge microstates. This subset is then grouped into mesostates, where all microstates that belong to a mesostate have the same net charge. Conformational distributions, drawn from a canonical ensemble, are generated for each of the charge microstates that make up a mesostate using a method we designate as proton walk sampling. This method combines Metropolis Monte Carlo sampling in conformational space with an auxiliary Markov process that enables interconversions between charge microstates along a mesostate. Proton walk sampling helps identify the most likely charge microstate per mesostate. We then use thermodynamic integration aided by the multistate Bennett acceptance ratio method to estimate the free energies for converting between mesostates. These free energies are then combined with the per-microstate weights along each mesostate to estimate standard state free energies and pH-dependent free energies for all thermodynamically relevant charge microstates. The results provide quantitative estimates of the probabilities and preferred conformations associated with every thermodynamically accessible charge microstate. We showcase the application of q-canonical sampling using two model systems. The results establish the soundness of the method and the importance of charge regulation in systems characterized by conformational heterogeneity.

Disordered RNA chaperones can enhance nucleic acid folding via local charge screening

RNA chaperones are proteins that aid in the folding of nucleic acids, but remarkably, many of these proteins are intrinsically disordered. How can these proteins function without a well-defined three-dimensional structure? Here, we address this question by studying the hepatitis C virus core protein, a chaperone that promotes viral genome dimerization. Using single-molecule fluorescence spectroscopy, we find that this positively charged disordered protein facilitates the formation of compact nucleic acid conformations by acting as a flexible macromolecular counterion that locally screens repulsive electrostatic interactions with an efficiency equivalent to molar salt concentrations. The resulting compaction can bias unfolded nucleic acids towards folding, resulting in faster folding kinetics. This potentially widespread mechanism is supported by molecular simulations that rationalize the experimental findings by describing the chaperone as an unstructured polyelectrolyte.

RNA chaperones, such as the hepatitic C virus (HCV) core protein, are proteins that aid in the folding of nucleic acids. Here authors use single‐molecule spectroscopy and simulation to show that the HCV core protein acts as a flexible macromolecular counterion which facilitates nucleic acid folding.