Ensemble models of proteins and protein domains based on distance distribution restraints

Ensemble structure of the N-terminal domain (1-267) of FUS in a biomolecular condensate

Solutions of some proteins phase separate into a condensed state of high protein concentration and a dispersed state of low concentration. Such behavior is observed in living cells for a number of RNA-binding proteins that feature intrinsically disordered domains. It is relevant for cell function via the formation of membraneless organelles and transcriptional condensates. On a basic level, the process can be studied in vitro on protein domains that are necessary and sufficient for liquid-liquid phase separation (LLPS). We have performed distance distribution measurements by electron paramagnetic resonance for 13 sections in an N-terminal domain (NTD) construct of the protein fused in sarcoma (FUS), consisting of the QGSY-rich domain and the RGG1 domain, in the denatured, dispersed, and condensed state. Using 10 distance distribution restraints for ensemble modeling and three such restraints for model validation, we have found that FUS NTD behaves as a random-coil polymer under good-solvent conditions in both the dispersed and condensed state. Conformation distribution in the biomolecular condensate is virtually indistinguishable from the one in an unrestrained ensemble, with the latter one being based on only residue-specific Ramachandran angle distributions. Over its whole length, FUS NTD is slightly more compact in the condensed than in the dispersed state, which is in line with the theory for random coils in good solvent proposed by de Gennes, Daoud, and Jannink. The estimated concentration in the condensate exceeds the overlap concentration resulting from this theory. The QGSY-rich domain is slightly more extended, slightly more hydrated, and has slightly higher propensity for LLPS than the RGG1 domain. Our results support previous suggestions that LLPS of FUS is driven by multiple transient nonspecific hydrogen bonding and π-sp2 interactions.

Protein ensemble modeling and analysis with MMMx

Proteins, especially of eukaryotes, often have disordered domains and may contain multiple folded domains whose relative spatial arrangement is distributed. The MMMx ensemble modeling and analysis toolbox (https://github.com/gjeschke/MMMx) can support the design of experiments to characterize the distributed structure of such proteins, starting from AlphaFold2 predictions or folded domain structures. Weak order can be analyzed with reference to a random coil model or to peptide chains that match the residue-specific Ramachandran angle distribution of the loop regions and are otherwise unrestrained. The deviation of the mean square end-to-end distance of chain sections from their average over sections of the same sequence length reveals localized compaction or expansion of the chain. The shape sampled by disordered chains is visualized by superposition in the principal axes frame of their inertia tensor. Ensembles of different sizes and with weighted conformers can be compared based on a similarity parameter that abstracts from the ensemble width.

Integrative solution structure of PTBP1-IRES complex reveals strong compaction and ordering with residual conformational flexibility

RNA-binding proteins (RBPs) are crucial regulators of gene expression, often composed of defined domains interspersed with flexible, intrinsically disordered regions. Determining the structure of ribonucleoprotein (RNP) complexes involving such RBPs necessitates integrative structural modeling due to their lack of a single stable state. In this study, we integrate magnetic resonance, mass spectrometry, and small-angle scattering data to determine the solution structure of the polypyrimidine-tract binding protein 1 (PTBP1/hnRNP I) bound to an RNA fragment from the internal ribosome entry site (IRES) of the encephalomyocarditis virus (EMCV). This binding, essential for enhancing the translation of viral RNA, leads to a complex structure that demonstrates RNA and protein compaction, while maintaining pronounced conformational flexibility. Acting as an RNA chaperone, PTBP1 orchestrates the IRES RNA into a few distinct conformations, exposing the RNA stems outward. This conformational diversity is likely common among RNP structures and functionally important. Our approach enables atomic-level characterization of heterogeneous RNP structures.

Phase Separation of Heterogeneous Nuclear Ribonucleoprotein A1 upon Specific RNA-Binding Observed by Magnetic Resonance

Interaction of heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) with specific single-stranded RNA and its relation to liquid-liquid phase separation (LLPS) were studied in vitro by magnetic resonance based on site-directed spin labelling. An ensemble model of dispersed hnRNP A1 in the absence of RNA was derived from distance distributions between spin labelled sites and small angle X-ray scattering. This model revealed a compact state of the low-complexity domain and its interaction with the RNA recognition motifs. Paramagnetic relaxation enhancement NMR spectroscopy confirmed this interaction. Addition of RNA to dispersed hnRNP A1 induced liquid-droplet formation. Such LLPS depended on RNA concentration and sequence, with continuous wave EPR spectroscopy showing an influence of RNA point mutations on local protein dynamics. We propose that an interplay of sequence-specific RNA binding and LLPS contributes to regulation of specific RNA segregation during stress response.

Integrative ensemble modeling of proteins and their complexes with distance distribution restraints

Many proteins and protein complexes exhibit regions that are intrinsically disordered. Whereas an arsenal of techniques exists to characterize structured proteins or protein regions, characterization of the vast conformational space occupied by intrinsically disordered regions remains a challenging task due the ensemble-averaging nature of many techniques that provide mean value restraints. More representative information can be gained in the form of distribution restraints, such as EPR-derived distance distributions. Previously we developed the ensemble modeling tool MMM, where we partition the macromolecule into structured and unstructured domains and utilize an integrative structural approach with a focus on EPR-derived distance restraints. Here we present the successor program of MMM: MMMx. All the modeling functionality was ported to MMMx and is now accessed by a uniform script format, allowing to combine the different modules at will to modeling pipelines. During the conception of MMMx many of the tools were improved or updated. We discuss the general functionality of MMMx and its modules, and illustrate some of the modeling tools by application examples.

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.

Protein functional dynamics from the rigorous global analysis of DEER data: Conditions, components, and conformations

The potential of spin labeling to reveal the dynamic dimension of macromolecules has been recognized since the dawn of the methodology in the 1960s. However, it was the development of pulsed electron paramagnetic resonance spectroscopy to detect dipolar coupling between spin labels and the availability of turnkey instrumentation in the 21st century that realized the full promise of spin labeling. Double electron-electron resonance (DEER) spectroscopy has seen widespread applications to channels, transporters, and receptors. In these studies, distance distributions between pairs of spin labels obtained under different biochemical conditions report the conformational states of macromolecules, illuminating the key movements underlying biological function. These experimental studies have spurred the development of methods for the rigorous analysis of DEER spectroscopic data along with methods for integrating these distributions into structural models. In this tutorial, we describe a model-based approach to obtaining a minimum set of components of the distance distribution that correspond to functionally relevant protein conformations with a set of fractional amplitudes that define the equilibrium between these conformations. Importantly, we review and elaborate on the error analysis reflecting the uncertainty in the various parameters, a critical step in rigorous structural interpretation of the spectroscopic data.

Characterization of Weak Protein Domain Structure by Spin-Label Distance Distributions

Function of intrinsically disordered proteins may depend on deviation of their conformational ensemble from that of a random coil. Such deviation may be hard to characterize and quantify, if it is weak. We explored the potential of distance distributions between spin labels, as they can be measured by electron paramagnetic resonance techniques, for aiding such characterization. On the example of the intrinsically disordered N-terminal domain 1-267 of fused in sarcoma (FUS) we examined what such distance distributions can and cannot reveal on the random-coil reference state. On the example of the glycine-rich domain 188-320 of heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) we studied whether deviation from a random-coil ensemble can be robustly detected with 19 distance distribution restraints. We discuss limitations imposed by ill-posedness of the conversion of primary data to distance distributions and propose overlap of distance distributions as a fit criterion that can tackle this problem. For testing consistency and size sufficiency of the restraint set, we propose jack-knife resampling. At current desktop computers, our approach is expected to be viable for domains up to 150 residues and for between 10 and 50 distance distribution restraints.

MMM: Integrative ensemble modeling and ensemble analysis

Proteins and their complexes can be heterogeneously disordered. In ensemble modeling of such systems with restraints from several experimental techniques the following problems arise: (a) integration of diverse restraints obtained on different samples under different conditions; (b) estimation of a realistic ensemble width; (c) sufficient sampling of conformational space; (d) representation of the ensemble by an interpretable number of conformers; (e) recognition of weak order with site resolution. Here, I introduce several tools that address these problems, focusing on utilization of distance distribution information for estimating ensemble width. The RigiFlex approach integrates such information with high-resolution structures of ordered domains and small-angle scattering data. The EnsembleFit module provides moderately sized ensembles by fitting conformer populations and discarding conformers with low population. EnsembleFit balances the loss in fit quality upon combining restraint subsets from different techniques. Pair correlation analysis for residues and local compaction analysis help in feature detection. The RigiFlex pipeline is tested on data simulated from the structure 70 kDa protein-RNA complex RsmE/RsmZ. It recovers this structure with ensemble width and difference from ground truth both being on the order of 4.2 Å. EnsembleFit reduces the ensemble of the proliferating-cell-nuclear-antigen-associated factor p15PAF from 4,939 to 75 conformers while maintaining good fit quality of restraints. Local compaction analysis for the PaaA2 antitoxin from E. coli O157 revealed correlations between compactness and enhanced residual dipolar couplings in the original NMR restraint set.

A Unified De Novo Approach for Predicting the Structures of Ordered and Disordered Proteins

As recognition of the abundance and relevance of intrinsically disordered proteins (IDPs) continues to grow, demand increases for methods that can rapidly predict the conformational ensembles populated by these proteins. To date, IDP simulations have largely been dominated by molecular dynamics (MD) simulations, which require significant compute times and/or complex hardware. Recent developments in MD have afforded methods capable of simulating both ordered and disordered proteins, yet to date, accurate fold prediction from a sequence has been dominated by Monte Carlo (MC)-based methods such as Rosetta. To overcome the limitations of current approaches in IDP simulation using Rosetta while maintaining its utility for modeling folded domains, we developed PyRosetta-based algorithms that allow for the accurate de novo prediction of proteins across all degrees of foldedness along with structural ensembles of disordered proteins. Our simulations have accuracy comparable to state-of-the-art MD with vastly reduced computational demands.

Positional Distributions of the Tethered Modules in Nitric Oxide Synthase: Monte Carlo Calculations and Pulsed EPR Measurements

The nitric oxide synthase (NOS) enzyme consists of multiple domains connected by flexible random coil tethers. In a catalytic cycle, the NOS domains move within the limits determined by the length and flexibility of the interdomain tethers and form docking complexes with each other. This process represents a key component of the electron transport from the flavin adenine dinucleotide/reduced nicotinamide adenine dinucleotide phosphate binding domain to the catalytic heme centers located in the oxygenase domain. Studying the conformational behavior of NOS is therefore imperative for a full understanding of the overall catalytic mechanism. In this work, we have investigated the equilibrium positional distributions of the NOS domains and the bound calmodulin (CaM) by using Monte Carlo calculations of the NOS conformations. As a main experimental reference, we have used the magnetic dipole interaction between a bifunctional spin label attached to T34C/S38C mutant CaM and the NOS heme centers, which was measured by pulsed electron paramagnetic resonance. In general, the calculations of the conformational distributions allow one to determine the range and statistics of positions occupied by the tethered protein domains, assess the crowding effect of the multiple domains on each other, evaluate the accessibility of various potential domain docking sites, and estimate the interaction energies required to achieve target populations of the docked states. In the particular application described here, we have established the specific mechanisms by which the bound CaM facilitates the flavin mononucleotide (FMN)/heme interdomain docking in NOS. We have also shown that the intersubunit FMN/heme domain docking and electron transfer in the homodimeric NOS protein are dictated by the existing structural makeup of the protein. Finally, from comparison of the calculated and experimental docking probabilities, the characteristic stabilization energies for the CaM/heme domain and the FMN domain/heme domain docking complexes have been estimated as -4.5kT and -10.5kT, respectively.

Using a FRET Library with Multiple Probe Pairs To Drive Monte Carlo Simulations of α-Synuclein

We describe a strategy for experimentally-constraining computational simulations of intrinsically disordered proteins (IDPs), using α-synuclein, an IDP with a central role in Parkinson's disease pathology, as an example. Previously, data from single-molecule Förster Resonance Energy Transfer (FRET) experiments have been effectively utilized to generate experimentally constrained computational models of IDPs. However, the fluorophores required for single-molecule FRET experiments are not amenable to the study of short-range (<30 Å) interactions. Using ensemble FRET measurements allows one to acquire data from probes with multiple distance ranges, which can be used to constrain Monte Carlo simulations in PyRosetta. To appropriately employ ensemble FRET data as constraints, we optimized the shape and weight of constraining potentials to afford ensembles of structures that are consistent with experimental data. We also used this approach to examine the structure of α-synuclein in the presence of the compacting osmolyte trimethylamine-N-oxide. Despite significant compaction imparted by 2 M trimethylamine-N-oxide, the underlying ensemble of α-synuclein remains largely disordered and capable of aggregation, also in agreement with experimental data. These proof-of-concept experiments demonstrate that our modeling protocol enables one to efficiently generate experimentally constrained models of IDPs that incorporate atomic-scale detail, allowing one to study an IDP under a variety of conditions.

Spontaneous Switching among Conformational Ensembles in Intrinsically Disordered Proteins

The common conception of intrinsically disordered proteins (IDPs) is that they stochastically sample all possible configurations driven by thermal fluctuations. This is certainly true for many IDPs, which behave as swollen random coils that can be described using polymer models developed for homopolymers. However, the variability in interaction energy between different amino acid sequences provides the possibility that some configurations may be strongly preferred while others are forbidden. In compact globular IDPs, core hydration and packing density can vary between segments of the polypeptide chain leading to complex conformational dynamics. Here, we describe a growing number of proteins that appear intrinsically disordered by biochemical and bioinformatic characterization but switch between restricted regions of conformational space. In some cases, spontaneous switching between conformational ensembles was directly observed, but few methods can identify when an IDP is acting as a restricted chain. Such switching between disparate corners of conformational space could bias ligand binding and regulate the volume of IDPs acting as structural or entropic elements. Thus, mapping the accessible energy landscape and capturing dynamics across a wide range of timescales are essential to recognize when an IDP is acting as such a switch.

Refinement of Highly Flexible Protein Structures using Simulation-Guided Spectroscopy

Highly flexible proteins present a special challenge for structure determination because they are multi-structured yet not disordered, so their conformational ensembles are essential for understanding function. Because spectroscopic measurements of multiple conformational populations often provide sparse data, experiment selection is a limiting factor in conformational refinement. A molecular simulations- and information-theory based approach to select which experiments best refine conformational ensembles has been developed. This approach was tested on three flexible proteins. For proteins where a clear mechanistic hypothesis exists, experiments that test this hypothesis were systematically identified. When available data did not yield such mechanistic hypotheses, experiments that significantly outperform structure-guided approaches in conformational refinement were identified. This approach offers a particular advantage when refining challenging, underdetermined protein conformational ensembles.

Single Molecule FRET: A Powerful Tool to Study Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) are often modeled using ideas from polymer physics that suggest they smoothly explore all corners of configuration space. Experimental verification of this random, dynamic behavior is difficult as random fluctuations of IDPs cannot be synchronized across an ensemble. Single molecule fluorescence (or Förster) resonance energy transfer (smFRET) is one of the few approaches that are sensitive to transient populations of sub-states within molecular ensembles. In some implementations, smFRET has sufficient time resolution to resolve transitions in IDP behaviors. Here we present experimental issues to consider when applying smFRET to study IDP configuration. We illustrate the power of applying smFRET to IDPs by discussing two cases in the literature of protein systems for which smFRET has successfully reported phosphorylation-induced modification (but not elimination) of the disordered properties that have been connected to impacts on the related biological function. The examples we discuss, PAGE4 and a disordered segment of the GluN2B subunit of the NMDA receptor, illustrate the great potential of smFRET to inform how IDP function can be regulated by controlling the detailed ensemble of disordered states within biological networks.

Membrane Active Peptides and Their Biophysical Characterization

In the last 20 years, an increasing number of studies have been reported on membrane active peptides. These peptides exert their biological activity by interacting with the cell membrane, either to disrupt it and lead to cell lysis or to translocate through it to deliver cargos into the cell and reach their target. Membrane active peptides are attractive alternatives to currently used pharmaceuticals and the number of antimicrobial peptides (AMPs) and peptides designed for drug and gene delivery in the drug pipeline is increasing. Here, we focus on two most prominent classes of membrane active peptides; AMPs and cell-penetrating peptides (CPPs). Antimicrobial peptides are a group of membrane active peptides that disrupt the membrane integrity or inhibit the cellular functions of bacteria, virus, and fungi. Cell penetrating peptides are another group of membrane active peptides that mainly function as cargo-carriers even though they may also show antimicrobial activity. Biophysical techniques shed light on peptide–membrane interactions at higher resolution due to the advances in optics, image processing, and computational resources. Structural investigation of membrane active peptides in the presence of the membrane provides important clues on the effect of the membrane environment on peptide conformations. Live imaging techniques allow examination of peptide action at a single cell or single molecule level. In addition to these experimental biophysical techniques, molecular dynamics simulations provide clues on the peptide–lipid interactions and dynamics of the cell entry process at atomic detail. In this review, we summarize the recent advances in experimental and computational investigation of membrane active peptides with particular emphasis on two amphipathic membrane active peptides, the AMP melittin and the CPP pVEC.

Spin labelling for integrative structure modelling: a case study of the polypyrimidine-tract binding protein 1 domains in complexes with short RNAs

A combined method, employing NMR and EPR spectroscopies, has demonstrated its strength in solving structures of protein/RNA and other types of biomolecular complexes. This method works particularly well when the large biomolecular complex consists of a limited number of rigid building blocks, such as RNA-binding protein domains (RBDs). A variety of spin labels is available for such studies, allowing for conventional as well as spectroscopically orthogonal double electron-electron resonance (DEER) measurements in EPR. In this work, we compare different types of nitroxide-based and Gd(iii)-based spin labels attached to isolated RBDs of the polypyrimidine-tract binding protein 1 (PTBP1) and to short RNA fragments. In particular, we demonstrate experiments on spectroscopically orthogonal labelled RBD/RNA complexes. For all experiments we analyse spin labelling, DEER method performance, resulting distance distributions, and their consistency with the predictions from the spin label rotamers analysis. This work provides a set of intra-domain calibration DEER data, which can serve as a basis to start structure determination of the full length PTBP1 complex with an RNA derived from encephalomycarditis virus (EMCV) internal ribosomal entry site (IRES). For a series of tested labelling sites, we discuss their particular advantages and drawbacks in such a structure determination approach.

A Structural Model of a P450-Ferredoxin Complex from Orientation-Selective Double Electron-Electron Resonance Spectroscopy

Cytochrome P450 (CYP) monooxygenases catalyze the oxidation of chemically inert carbon-hydrogen bonds in diverse endogenous and exogenous organic compounds by atmospheric oxygen. This C-H bond oxy-functionalization activity has huge potential in biotechnological applications. Class I CYPs receive the two electrons required for oxygen activation from NAD(P)H via a ferredoxin reductase and ferredoxin. The interaction of Class I CYPs with their cognate ferredoxin is specific. In order to reconstitute the activity of diverse CYPs, structural characterization of CYP-ferredoxin complexes is necessary, but little structural information is available. Here we report a structural model of such a complex (CYP199A2-HaPux) in frozen solution derived from distance and orientation restraints gathered by the EPR technique of orientation-selective double electron-electron resonance (os-DEER). The long-lived oscillations in the os-DEER spectra were well modeled by a single orientation of the CYP199A2-HaPux complex. The structure is different from the two known Class I CYP-Fdx structures: CYP11A1-Adx and CYP101A1-Pdx. At the protein interface, HaPux residues in the [Fe₂S₂] cluster-binding loop and the α3 helix and the C-terminus residue interact with CYP199A2 residues in the proximal loop and the C helix. These residue contacts are consistent with biochemical data on CYP199A2-ferredoxin binding and electron transfer. Electron-tunneling calculations indicate an efficient electron-transfer pathway from the [Fe₂S₂] cluster to the heme. This new structural model of a CYP-Fdx complex provides the basis for tailoring CYP enzymes for which the cognate ferredoxin is not known, to accept electrons from HaPux and display monooxygenase activity.

The contribution of modern EPR to structural biology

Electron paramagnetic resonance (EPR) spectroscopy combined with site-directed spin labelling is applicable to biomolecules and their complexes irrespective of system size and in a broad range of environments. Neither short-range nor long-range order is required to obtain structural restraints on accessibility of sites to water or oxygen, on secondary structure, and on distances between sites. Many of the experiments characterize a static ensemble obtained by shock-freezing. Compared with characterizing the dynamic ensemble at ambient temperature, analysis is simplified and information loss due to overlapping timescales of measurement and system dynamics is avoided. The necessity for labelling leads to sparse restraint sets that require integration with data from other methodologies for building models. The double electron–electron resonance experiment provides distance distributions in the nanometre range that carry information not only on the mean conformation but also on the width of the native ensemble. The distribution widths are often inconsistent with Anfinsen's concept that a sequence encodes a single native conformation defined at atomic resolution under physiological conditions.

MMM: A toolbox for integrative structure modeling

Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples.

Reliable nanometre-range distance distributions from 5-pulse double electron electron resonance

The partial excitation artefact in 5-pulse DEER data can be eliminated by experimental time shifting and signal processing.