Resolving dynamics and function of transient states in single enzyme molecules

Labelizer: systematic selection of protein residues for covalent fluorophore labeling

Attaching fluorescent dyes to biomolecules is essential for assays in biology, biochemistry, biophysics, biomedicine and imaging. A systematic approach for the selection of suitable labeling sites in macromolecules, particularly proteins, is missing. We present a quantitative strategy to identify such protein residues using a naïve Bayes classifier. Analysis of >100 proteins with ~400 successfully labeled residues allows to identify four parameters, which can rank residues via a single metric (the label score). The approach is tested and benchmarked by inspection of literature data and experiments on the expression level, degree of labelling, and success in FRET assays of different bacterial substrate binding proteins. With the paper, we provide a python package and webserver ( https://labelizer.bio.lmu.de/ ), that performs an analysis of a pdb-structure (or model), label score calculation, and FRET assay scoring. The approach can facilitate to build up a central open-access database to continuously refine the label-site selection in proteins.

Accounting for Fast vs Slow Exchange in Single Molecule FRET Experiments Reveals Hidden Conformational States

Proteins are dynamic systems whose structural preferences determine their function. Unfortunately, building atomically detailed models of protein structural ensembles remains challenging, limiting our understanding of the relationships between sequence, structure, and function. Combining single molecule Förster resonance energy transfer (smFRET) experiments with molecular dynamics simulations could provide experimentally grounded, all-atom models of a protein's structural ensemble. However, agreement between the two techniques is often insufficient to achieve this goal. Here, we explore whether accounting for important experimental details like averaging across structures sampled during a given smFRET measurement is responsible for this apparent discrepancy. We present an approach to account for this time-averaging by leveraging the kinetic information available from Markov state models of a protein's dynamics. This allows us to accurately assess which time scales are averaged during an experiment. We find this approach significantly improves agreement between simulations and experiments in proteins with varying degrees of dynamics, including the well-ordered protein T4 lysozyme, the partially disordered protein apolipoprotein E (ApoE), and a disordered amyloid protein (Aβ40). We find evidence for hidden states that are not apparent in smFRET experiments because of time averaging with other structures, akin to states in fast exchange in nuclear magnetic resonance, and evaluate different force fields. Finally, we show how remaining discrepancies between computations and experiments can be used to guide additional simulations and build structural models for states that were previously unaccounted for. We expect our approach will enable combining simulations and experiments to understand the link between sequence, structure, and function in many settings. Understanding protein dynamics is crucial for understanding protein function, yet few methodologies report on protein motion at an atomic level. Combining single molecule Förster resonance energy transfer (smFRET) experiments with computer simulations could provide atomistic models of protein ensembles which are grounded in experiments, however, there has been limited agreement between the two methods to date. Here, we present an algorithm to recapitulate smFRET experiments from molecular dynamics simulations. This approach significantly improves agreement between simulations and experiments for proteins across the ordered spectrum. Moreover, with this approach we can confidently create atomic models for states observed during smFRET experiments which were otherwise difficult to model due to high amounts of flexibility, disorder, or large deviations from crystal-like states.

Time-heterogeneity of the Förster Radius from Dipole Orientational Dynamics Impacts Single-Molecule FRET Experiments

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 principle physics 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. Our models provide the most up-to-date and accurate estimation of FRET.

Accurate estimation of the normalized mutual information of multidimensional data

While the linear Pearson correlation coefficient represents a well-established normalized measure to quantify the inter-relation of two stochastic variables X and Y, it fails for multidimensional variables, such as Cartesian coordinates. Avoiding any assumption about the underlying data, the mutual information I(X, Y) does account for multidimensional correlations. However, unlike the normalized Pearson correlation, it has no upper bound (I ∈ [0, ∞)), i.e., it is not clear if say, I = 0.4 corresponds to a low or a high correlation. Moreover, the mutual information (MI) involves the estimation of high-dimensional probability densities (e.g., six-dimensional for Cartesian coordinates), which requires a k nearest-neighbor algorithm, such as the estimator by Kraskov et al. [Phys. Rev. E 69, 066138 (2004)]. As existing methods to normalize the MI cannot be used in connection with this estimator, a new approach is presented, which uses an entropy estimation method that is invariant under variable transformations. The algorithm is numerically efficient and does not require more effort than the calculation of the (un-normalized) MI. After validating the method by applying it to various toy models, the normalized MI between the Cα-coordinates of T4 lysozyme is considered and compared to a correlation analysis of inter-residue contacts.

FRET-guided modeling of nucleic acids

The functional diversity of RNAs is encoded in their innate conformational heterogeneity. The combination of single-molecule spectroscopy and computational modeling offers new attractive opportunities to map structural transitions within nucleic acid ensembles. Here, we describe a framework to harmonize single-molecule Förster resonance energy transfer (FRET) measurements with molecular dynamics simulations and de novo structure prediction. Using either all-atom or implicit fluorophore modeling, we recreate FRET experiments in silico, visualize the underlying structural dynamics and quantify the reaction coordinates. Using multiple accessible-contact volumes as a post hoc scoring method for fragment assembly in Rosetta, we demonstrate that FRET can be used to filter a de novo RNA structure prediction ensemble by refuting models that are not compatible with in vitro FRET measurement. We benchmark our FRET-assisted modeling approach on double-labeled DNA strands and validate it against an intrinsically dynamic manganese(II)-binding riboswitch. We show that a FRET coordinate describing the assembly of a four-way junction allows our pipeline to recapitulate the global fold of the riboswitch displayed by the crystal structure. We conclude that computational fluorescence spectroscopy facilitates the interpretability of dynamic structural ensembles and improves the mechanistic understanding of nucleic acid interactions.

NMR and Single-Molecule FRET Insights into Fast Protein Motions and Their Relation to Function

Proteins often undergo large-scale conformational transitions, in which secondary and tertiary structure elements (loops, helices, and domains) change their structures or their positions with respect to each other. Simple considerations suggest that such dynamics should be relatively fast, but the functional cycles of many proteins are often relatively slow. Sophisticated experimental methods are starting to tackle this dichotomy and shed light on the contribution of large-scale conformational dynamics to protein function. In this review, we focus on the contribution of single-molecule Förster resonance energy transfer and nuclear magnetic resonance (NMR) spectroscopies to the study of conformational dynamics. We briefly describe the state of the art in each of these techniques and then point out their similarities and differences, as well as the relative strengths and weaknesses of each. Several case studies, in which the connection between fast conformational dynamics and slower function has been demonstrated, are then introduced and discussed. These examples include both enzymes and large protein machines, some of which have been studied by both NMR and fluorescence spectroscopies.

Absorption-Based Rapid Acquisition of Single-Molecule Kinetics from Unstable Enzymes in Microdroplets

Single-molecule catalysis reflects the heterogeneity of each molecule, providing a unique insight into the complex catalytic mechanism through the statistics of stochastic individuals. However, the present study methods for single-molecule catalysis are either complicated or have low throughput, limiting their rapid acquisition of single-molecule reaction kinetics with statistical significance. Here, a label-free imaging method is developed for the study of single-molecule catalysis in microdroplets with high throughput based on the absorption of the reaction molecules. A wide distribution of the catalytic reaction rate constant value of 238-2026 molecules s-1 is observed from 68 single enzymes. Interestingly, an exponential decayed distribution of the enzyme activity can be clearly observed due to the rapid denaturation of the enzymes. The denaturation mechanism of the Horse Radish Peroxidase (HRP) enzyme is clarified. It is revealed that the denaturation of each enzyme goes through a gradual decay rather than a truncated turn-off process from a single molecule point of view. This absorption-based method can be applied to most of the catalytic reactions with high throughput, which offers an indispensable route for the rapid statistical analysis of various single-molecule catalytic reactions, making it particularly suitable for the acquisition of catalytic kinetics from highly unstable enzymes.

Accounting for fast vs slow exchange in single molecule FRET experiments reveals hidden conformational states

Proteins are dynamic systems whose structural preferences determine their function. Unfortunately, building atomically detailed models of protein structural ensembles remains challenging, limiting our understanding of the relationships between sequence, structure, and function. Combining single molecule Förster resonance energy transfer (smFRET) experiments with molecular dynamics simulations could provide experimentally grounded, all-atom models of a protein's structural ensemble. However, agreement between the two techniques is often insufficient to achieve this goal. Here, we explore whether accounting for important experimental details like averaging across structures sampled during a given smFRET measurement is responsible for this apparent discrepancy. We present an approach to account for this time-averaging by leveraging the kinetic information available from Markov state models of a protein's dynamics. This allows us to accurately assess which timescales are averaged during an experiment. We find this approach significantly improves agreement between simulations and experiments in proteins with varying degrees of dynamics, including the well-ordered protein T4 lysozyme, the partially disordered protein apolipoprotein E (ApoE), and a disordered amyloid protein (Aβ40). We find evidence for hidden states that are not apparent in smFRET experiments because of time averaging with other structures, akin to states in fast exchange in NMR, and evaluate different force fields. Finally, we show how remaining discrepancies between computations and experiments can be used to guide additional simulations and build structural models for states that were previously unaccounted for. We expect our approach will enable combining simulations and experiments to understand the link between sequence, structure, and function in many settings.

DNA controls the dimerization of the human FoxP1 forkhead domain

Transcription factors (TFs) regulate gene expression by binding to specific DNA sequences and gating access to genes. Even when the binding of TFs and their cofactors to DNA is reversible, indicating a reversible control of gene expression, there is little knowledge about the molecular effect DNA has on TFs. Using single-molecule multiparameter fluorescence spectroscopy, molecular dynamics simulations, and biochemical assays, we find that the monomeric form of the forkhead (FKH) domain of the human FoxP1 behaves as a disordered protein and increases its folded population when it dimerizes. Notably, DNA binding promotes a disordered FKH dimer bound to DNA, negatively controlling the stability of the dimeric FoxP1:DNA complex. The DNA-mediated reversible regulation on FKH dimers suggests that FoxP1-dependent gene suppression is unstable, and it must require the presence of other dimerization domains or cofactors to revert the negative impact exerted by the DNA.

Diameter dependence of transport through nuclear pore complex mimics studied using optical nanopores

The nuclear pore complex (NPC) regulates the selective transport of large biomolecules through the nuclear envelope. As a model system for nuclear transport, we construct NPC mimics by functionalizing the pore walls of freestanding palladium zero-mode waveguides with the FG-nucleoporin Nsp1. This approach enables the measurement of single-molecule translocations through individual pores using optical detection. We probe the selectivity of Nsp1-coated pores by quantitatively comparing the translocation rates of the nuclear transport receptor Kap95 to the inert probe BSA over a wide range of pore sizes from 35 nm to 160 nm. Pores below 55 ± 5 nm show significant selectivity that gradually decreases for larger pores. This finding is corroborated by coarse-grained molecular dynamics simulations of the Nsp1 mesh within the pore, which suggest that leakage of BSA occurs by diffusion through transient openings within the dynamic mesh. Furthermore, we experimentally observe a modulation of the BSA permeation when varying the concentration of Kap95. The results demonstrate the potential of single-molecule fluorescence measurements on biomimetic NPCs to elucidate the principles of nuclear transport.

Integrating Electron Paramagnetic Resonance Spectroscopy and Computational Modeling to Measure Protein Structure and Dynamics

Electron paramagnetic resonance (EPR) has become a powerful probe of conformational heterogeneity and dynamics of biomolecules. In this Review, we discuss different computational modeling techniques that enrich the interpretation of EPR measurements of dynamics or distance restraints. A variety of spin labels are surveyed to provide a background for the discussion of modeling tools. Molecular dynamics (MD) simulations of models containing spin labels provide dynamical properties of biomolecules and their labels. These simulations can be used to predict EPR spectra, sample stable conformations and sample rotameric preferences of label sidechains. For molecular motions longer than milliseconds, enhanced sampling strategies and de novo prediction software incorporating or validated by EPR measurements are able to efficiently refine or predict protein conformations, respectively. To sample large-amplitude conformational transition, a coarse-grained or an atomistic weighted ensemble (WE) strategy can be guided with EPR insights. Looking forward, we anticipate an integrative strategy for efficient sampling of alternate conformations by de novo predictions, followed by validations by systematic EPR measurements and MD simulations. Continuous pathways between alternate states can be further sampled by WE-MD including all intermediate states.

Investigation of Rare Protein Conformational Transitions via Dissipation-Corrected Targeted Molecular Dynamics

To sample rare events, dissipation-corrected targeted molecular dynamics (dcTMD) applies a constant velocity constraint along a one-dimensional reaction coordinate s, which drives an atomistic system from an initial state into a target state. Employing a cumulant approximation of Jarzynski's identity, the free energy ΔG(s) is calculated from the mean external work and dissipated work of the process. By calculating the friction coefficient Γ(s) from the dissipated work, in a second step, the equilibrium dynamics of the process can be studied by propagating a Langevin equation. While so far dcTMD has been mostly applied to study the unbinding of protein-ligand complexes, here its applicability to rare conformational transitions within a protein and the prediction of their kinetics are investigated. As this typically requires the introduction of multiple collective variables {xj} = x, a theoretical framework is outlined to calculate the associated free energy ΔG(x) and friction Γ(x) from dcTMD simulations along coordinate s. Adopting the α-β transition of alanine dipeptide as well as the open-closed transition of T4 lysozyme as representative examples, the virtues and shortcomings of dcTMD to predict protein conformational transitions and the related kinetics are studied.

The Onset of Molecule-Spanning Dynamics in Heat Shock Protein Hsp90

Protein dynamics have been investigated on a wide range of time scales. Nano- and picosecond dynamics have been assigned to local fluctuations, while slower dynamics have been attributed to larger conformational changes. However, it is largely unknown how fast (local) fluctuations can lead to slow global (allosteric) changes. Here, fast molecule-spanning dynamics on the 100 to 200 ns time scale in the heat shock protein 90 (Hsp90) are shown. Global real-space movements are assigned to dynamic modes on this time scale, which is possible by a combination of single-molecule fluorescence, quasi-elastic neutron scattering and all-atom molecular dynamics (MD) simulations. The time scale of these dynamic modes depends on the conformational state of the Hsp90 dimer. In addition, the dynamic modes are affected to various degrees by Sba1, a co-chaperone of Hsp90, depending on the location within Hsp90, which is in very good agreement with MD simulations. Altogether, this data is best described by fast molecule-spanning dynamics, which precede larger conformational changes in Hsp90 and might be the molecular basis for allostery. This integrative approach provides comprehensive insights into molecule-spanning dynamics on the nanosecond time scale for a multi-domain protein.

Mapping protein dynamics at high spatial resolution with temperature-jump X-ray crystallography

Understanding and controlling protein motion at atomic resolution is a hallmark challenge for structural biologists and protein engineers because conformational dynamics are essential for complex functions such as enzyme catalysis and allosteric regulation. Time-resolved crystallography offers a window into protein motions, yet without a universal perturbation to initiate conformational changes the method has been limited in scope. Here we couple a solvent-based temperature jump with time-resolved crystallography to visualize structural motions in lysozyme, a dynamic enzyme. We observed widespread atomic vibrations on the nanosecond timescale, which evolve on the submillisecond timescale into localized structural fluctuations that are coupled to the active site. An orthogonal perturbation to the enzyme, inhibitor binding, altered these dynamics by blocking key motions that allow energy to dissipate from vibrations into functional movements linked to the catalytic cycle. Because temperature jump is a universal method for perturbing molecular motion, the method demonstrated here is broadly applicable for studying protein dynamics.

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.

DNA facilitates heterodimerization between human transcription factors FoxP1 and FoxP2 by increasing their conformational flexibility

Transcription factors regulate gene expression by binding to DNA. They have disordered regions and specific DNA-binding domains. Binding to DNA causes structural changes, including folding and interactions with other molecules. The FoxP subfamily of transcription factors in humans is unique because they can form heterotypic interactions without DNA. However, it is unclear how they form heterodimers and how DNA binding affects their function. We used computational and experimental methods to study the structural changes in FoxP1's DNA-binding domain when it forms a heterodimer with FoxP2. We found that FoxP1 has complex and diverse conformational dynamics, transitioning between compact and extended states. Surprisingly, DNA binding increases the flexibility of FoxP1, contrary to the typical folding-upon-binding mechanism. In addition, we observed a 3-fold increase in the rate of heterodimerization after FoxP1 binds to DNA. These findings emphasize the importance of structural flexibility in promoting heterodimerization to form transcriptional complexes.

Local Xenon-Protein Interaction Produces Global Conformational Change and Allosteric Inhibition in Lysozyme

Noble gases have well-established biological effects, yet their molecular mechanisms remain poorly understood. Here, we investigated, both experimentally and computationally, the molecular modes of xenon (Xe) action in bacteriophage T4 lysozyme (T4L). By combining indirect gassing methods with a colorimetric lysozyme activity assay, a reversible, Xe-specific (20 ± 3)% inhibition effect was observed. Accelerated molecular dynamic simulations revealed that Xe exerts allosteric inhibition on the protein by expanding a C-terminal hydrophobic cavity. Xe-induced cavity expansion results in global conformational changes, with long-range transduction distorting the active site where peptidoglycan binds. Interestingly, the peptide substrate binding site that enables lysozyme specificity does not change conformation. Two T4L mutants designed to reshape the C-terminal Xe cavity established a correlation between cavity expansion and enzyme inhibition. This work also highlights the use of Xe flooding simulations to identify new cryptic binding pockets. These results enrich our understanding of Xe-protein interactions at the molecular level and inspire further biochemical investigations with noble gases.

Perspective: How Fast Dynamics Affect Slow Function in Protein Machines

Internal motions in proteins take place on a broad range of time- and space-scales. The potential roles of these dynamics in the biochemical functions of proteins have intrigued biophysicists for many years, and multiple mechanisms to couple motions to function have been proposed. Some of these mechanisms have relied on equilibrium concepts. For example, the modulation of dynamics was proposed to change the entropy of a protein, hence affecting processes such as binding. This so-called dynamic allostery scenario has been demonstrated in several recent experiments. Perhaps even more intriguing may be models that involve out-of-equilibrium operation, which by necessity require the input of energy. We discuss several recent experimental studies that expose such potential mechanisms for coupling dynamics and function. In Brownian ratchets, for example, directional motion is promoted by switching a protein between two free energy surfaces. An additional example involves the effect of microsecond domain-closure dynamics of an enzyme on its much slower chemical cycle. These observations lead us to propose a novel two-time-scale paradigm for the activity of protein machines: fast equilibrium fluctuations take place on the microsecond-millisecond time scale, while on a slower time scale, free energy is invested in order to push the system out of equilibrium and drive functional transitions. Motions on the two time scales affect each other and are essential for the overall function of these machines.

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins

Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology.

Shrinking gate fluorescence correlation spectroscopy yields equilibrium constants and separates photophysics from structural dynamics

Fluorescence correlation spectroscopy is a versatile tool for studying fast conformational changes of biomolecules especially when combined with Förster resonance energy transfer (FRET). Despite the many methods available for identifying structural dynamics in FRET experiments, the determination of the forward and backward transition rate constants and thereby also the equilibrium constant is difficult when two intensity levels are involved. Here, we combine intensity correlation analysis with fluorescence lifetime information by including only a subset of photons in the autocorrelation analysis based on their arrival time with respect to the excitation pulse (microtime). By fitting the correlation amplitude as a function of microtime gate, the transition rate constants from two fluorescence-intensity level systems and the corresponding equilibrium constants are obtained. This shrinking-gate fluorescence correlation spectroscopy (sg-FCS) approach is demonstrated using simulations and with a DNA origami-based model system in experiments on immobilized and freely diffusing molecules. We further show that sg-FCS can distinguish photophysics from dynamic intensity changes even if a dark quencher, in this case graphene, is involved. Finally, we unravel the mechanism of a FRET-based membrane charge sensor indicating the broad potential of the method. With sg-FCS, we present an algorithm that does not require prior knowledge and is therefore easily implemented when an autocorrelation analysis is carried out on time-correlated single-photon data.

Challenges in Inferring the Directionality of Active Molecular Processes from Single-Molecule Fluorescence Resonance Energy Transfer Trajectories

We discuss some of the practical challenges that one faces in using stochastic thermodynamics to infer directionality of molecular machines from experimental single-molecule trajectories. Because of the limited spatiotemporal resolution of single-molecule experiments and because both forward and backward transitions between the same pairs of states cannot always be detected, differentiating between the forward and backward directions of, e.g., an ATP-consuming molecular machine that operates periodically, turns out to be a nontrivial task. Using a simple extension of a Markov-state model that is commonly employed to analyze single-molecule transition-path measurements, we illustrate how irreversibility can be hidden from such measurements but in some cases can be uncovered when non-Markov effects in low-dimensional single-molecule trajectories are considered.

Automated Path Searching Reveals the Mechanism of Hydrolysis Enhancement by T4 Lysozyme Mutants

Bacteriophage T4 lysozyme (T4L) is a glycosidase that is widely applied as a natural antimicrobial agent in the food industry. Due to its wide applications and small size, T4L has been regarded as a model system for understanding protein dynamics and for large-scale protein engineering. Through structural insights from the single conformation of T4L, a series of mutations (L99A,G113A,R119P) have been introduced, which have successfully raised the fractional population of its only hydrolysis-competent excited state to 96%. However, the actual impact of these substitutions on its dynamics remains unclear, largely due to the lack of highly efficient sampling algorithms. Here, using our recently developed travelling-salesman-based automated path searching (TAPS), we located the minimum-free-energy path (MFEP) for the transition of three T4L mutants from their ground states to their excited states. All three mutants share a three-step transition: the flipping of F114, the rearrangement of α0/α1 helices, and final refinement. Remarkably, the MFEP revealed that the effects of the mutations are drastically beyond the expectations of their original design: (a) the G113A substitution not only enhances helicity but also fills the hydrophobic Cavity I and reduces the free energy barrier for flipping F114; (b) R119P barely changes the stability of the ground state but stabilizes the excited state through rarely reported polar contacts S117_OG:N132_ND2, E11_OE1:R145_NH1, and E11_OE2:Q105_NE2; (c) the residue W138 flips into Cavity I and further stabilizes the excited state for the triple mutant L99A,G113A,R119P. These novel insights that were unexpected in the original mutant design indicated the necessity of incorporating path searching into the workflow of rational protein engineering.

Detecting Förster resonance energy transfer in living cells by conventional and spectral flow cytometry

Assays based on Förster resonance energy transfer (FRET) can be used to study many processes in cell biology. Although this is most often done with microscopy for fluorescence detection, we report two ways to measure FRET in living cells by flow cytometry. Using a conventional flow cytometer and the "3-cube method" for intensity-based calculation of FRET efficiency, we measured the enzymatic activity of specific kinases in cells expressing a genetically-encoded reporter. For both AKT and protein kinase A, the method measured kinase activity in time-course, dose-response, and kinetic assays. Using the Cytek Aurora spectral flow cytometer, which applies linear unmixing to emission measured in multiple wavelength ranges, FRET from the same reporters was measured with greater single-cell precision, in real time and in the presence of other fluorophores. Results from gene-knockout studies suggested that spectral flow cytometry might enable the sorting of cells on the basis of FRET. The methods we present provide convenient and flexible options for using FRET with flow cytometry in studies of cell biology.

Differential modulation of collybistin conformational dynamics by the closely related GTPases Cdc42 and TC10

Interneuronal synaptic transmission relies on the proper spatial organization of presynaptic neurotransmitter release and its reception on the postsynaptic side by cognate neurotransmitter receptors. Neurotransmitter receptors are incorporated into and arranged within the plasma membrane with the assistance of scaffolding and adaptor proteins. At inhibitory GABAergic postsynapses, collybistin, a neuronal adaptor protein, recruits the scaffolding protein gephyrin and interacts with various neuronal factors including cell adhesion proteins of the neuroligin family, the GABA A receptor α2-subunit and the closely related small GTPases Cdc42 and TC10 (RhoQ). Most collybistin splice variants harbor an N-terminal SH3 domain and exist in an autoinhibited/closed state. Cdc42 and TC10, despite sharing 67.4% amino acid sequence identity, interact differently with collybistin. Here, we delineate the molecular basis of the collybistin conformational activation induced by TC10 with the aid of recently developed collybistin FRET sensors. Time-resolved fluorescence-based FRET measurements reveal that TC10 binds to closed/inactive collybistin leading to relief of its autoinhibition, contrary to Cdc42, which only interacts with collybistin when forced into an open state by the introduction of mutations destabilizing the closed state of collybistin. Taken together, our data describe a TC10-driven signaling mechanism in which collybistin switches from its autoinhibited closed state to an open/active state.

Cross-validation of distance measurements in proteins by PELDOR/DEER and single-molecule FRET

Pulsed electron-electron double resonance spectroscopy (PELDOR/DEER) and single-molecule Förster resonance energy transfer spectroscopy (smFRET) are frequently used to determine conformational changes, structural heterogeneity, and inter probe distances in biological macromolecules. They provide qualitative information that facilitates mechanistic understanding of biochemical processes and quantitative data for structural modelling. To provide a comprehensive comparison of the accuracy of PELDOR/DEER and smFRET, we use a library of double cysteine variants of four proteins that undergo large-scale conformational changes upon ligand binding. With either method, we use established standard experimental protocols and data analysis routines to determine inter-probe distances in the presence and absence of ligands. The results are compared to distance predictions from structural models. Despite an overall satisfying and similar distance accuracy, some inconsistencies are identified, which we attribute to the use of cryoprotectants for PELDOR/DEER and label-protein interactions for smFRET. This large-scale cross-validation of PELDOR/DEER and smFRET highlights the strengths, weaknesses, and synergies of these two important and complementary tools in integrative structural biology.

Reduction of protein disulfide isomerase results in open conformations and stimulates dynamic exchange between structural ensembles

Human protein disulfide isomerase (PDI) is an essential redox-regulated enzyme required for oxidative protein folding. It comprises four thioredoxin domains, two catalytically active (a, a’) and two inactive (b, b’), organized to form a flexible abb’a’ U-shape. Snapshots of unbound oxidized and reduced PDI have been obtained by X-ray crystallography. Yet, how PDI’s structure changes in response to the redox environment and inhibitor binding remains controversial. Here, we used multiparameter confocal single-molecule FRET to track the movements of the two catalytic domains with high temporal resolution. We found that at equilibrium, PDI visits three structurally distinct conformational ensembles, two “open” (O₁ and O₂) and one “closed” (C). We show that the redox environment dictates the time spent in each ensemble and the rate at which they exchange. While oxidized PDI samples O₁, O₂, and C more evenly and in a slower fashion, reduced PDI predominantly populates O₁ and O₂ and exchanges between them more rapidly, on the submillisecond timescale. These findings were not expected based on crystallographic data. Using mutational analyses, we further demonstrate that the R300-W396 cation-π interaction and active site cysteines dictate, in unexpected ways, how the catalytic domains relocate. Finally, we show that irreversible inhibitors targeting the active sites of reduced PDI did not abolish these protein dynamics but rather shifted the equilibrium toward the closed ensemble. This work introduces a new structural framework that challenges current views of PDI dynamics, helps rationalize its multifaceted role in biology, and should be considered when designing PDI-targeted therapeutics.

Cooperative Protein Allosteric Transition Mediated by a Fluctuating Transmission Network

Allosteric communication between distant protein sites represents a key mechanism of biomolecular regulation and signal transduction. Compared to other processes such as protein folding, however, the dynamical evolution of allosteric transitions is still not well understood. As an example of allosteric coupling between distant protein regions, we consider the global open-closed motion of the two domains of T4 lysozyme, which is triggered by local motion in the hinge region. Combining extensive molecular dynamics simulations with a correlation analysis of interresidue contacts, we identify a network of interresidue distances that move in a concerted manner. The cooperative process originates from a cogwheel-like motion of the hydrophobic core in the hinge region, which constitutes an evolutionary conserved and flexible transmission network. Through rigid contacts and the protein backbone, the small local changes of the hydrophobic core are passed on to the distant terminal domains and lead to the emergence of a rare global conformational transition. As in an Ising-type model, the cooperativity of the allosteric transition can be explained via the interaction of local fluctuations.

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.

Quantitative Description of Intrinsically Disordered Proteins Using Single-Molecule FRET, NMR, and SAXS

Studying the conformational landscape of intrinsically disordered and partially folded proteins is challenging and only accessible to a few solution state techniques, such as nuclear magnetic resonance (NMR), small-angle scattering techniques, and single-molecule Förster resonance energy transfer (smFRET). While each of the techniques is sensitive to different properties of the disordered chain, such as local structural propensities, overall dimension, or intermediate- and long-range contacts, conformational ensembles describing intrinsically disordered proteins (IDPs) accurately should ideally respect all of these properties. Here we develop an integrated approach using a large set of FRET efficiencies and fluorescence lifetimes, NMR chemical shifts, and paramagnetic relaxation enhancements (PREs), as well as small-angle X-ray scattering (SAXS) to derive quantitative conformational ensembles in agreement with all parameters. Our approach is tested using simulated data (five sets of PREs and 15 FRET efficiencies) and validated experimentally on the example of the disordered domain of measles virus phosphoprotein, providing new insights into the conformational landscape of this viral protein that comprises transient structural elements and is more compact than an unfolded chain throughout its length. Rigorous cross-validation using FRET efficiencies, fluorescence lifetimes, and SAXS demonstrates the predictive nature of the calculated conformational ensembles and underlines the potential of this strategy in integrative dynamic structural biology.

Integrative structural dynamics probing of the conformational heterogeneity in synaptosomal-associated protein 25

SNAP-25 (synaptosomal-associated protein of 25 kDa) is a prototypical intrinsically disordered protein (IDP) that is unstructured by itself but forms coiled-coil helices in the SNARE complex. With high conformational heterogeneity, detailed structural dynamics of unbound SNAP-25 remain elusive. Here, we report an integrative method to probe the structural dynamics of SNAP-25 by combining replica-exchange discrete molecular dynamics (rxDMD) simulations and label-based experiments at ensemble and single-molecule levels. The rxDMD simulations systematically characterize the coil-to-molten globular transition and reconstruct structural ensemble consistent with prior ensemble experiments. Label-based experiments using Förster resonance energy transfer and double electron-electron resonance further probe the conformational dynamics of SNAP-25. Agreements between simulations and experiments under both ensemble and single-molecule conditions allow us to assign specific helix-coil transitions in SNAP-25 that occur in submillisecond timescales and potentially play a vital role in forming the SNARE complex. We expect that this integrative approach may help further our understanding of IDPs.

Microscopy imaging of living cells in metabolic engineering

Microscopy imaging of living cells is becoming a pivotal, noninvasive, and highly specific tool in metabolic engineering to visualize molecular dynamics in industrial microorganisms. This review describes the different microscopy methods, from fluorescence to super resolution, with application in microbial bioengineering. Firstly, the role and importance of microscopy imaging is analyzed in the context of strain design. Then, the advantages and disadvantages of different microscopy technologies are discussed, including confocal laser scanning microscopy (CLSM), spatial light interference microscopy (SLIM), and super-resolution microscopy, followed by their applications in synthetic biology. Finally, the future perspectives of live-cell imaging and their potential to transform microbial systems are analyzed. This review provides theoretical guidance and highlights the importance of microscopy in understanding and engineering microbial metabolism.

Structure dynamics of HIV-1 Env trimers on native virions engaged with living T cells

The HIV-1 envelope glycoprotein (Env) mediates viral entry into the host cell. Although the highly dynamic nature of Env intramolecular conformations has been shown with single molecule spectroscopy in vitro, the bona fide Env intra- and intermolecular mechanics when engaged with live T cells remains unknown. We used two photon fast fluorescence lifetime imaging detection of single-molecule Förster Resonance Energy Transfer occurring between fluorescent labels on HIV-1 Env on native virions. Our observations reveal Env dynamics at two levels: transitions between different intramolecular conformations and intermolecular interactions between Env within the viral membrane. Furthermore, we show that three broad neutralizing anti-Env antibodies directed to different epitopes restrict Env intramolecular dynamics and interactions between adjacent Env molecules when engaged with living T cells. Importantly, our results show that Env-Env interactions depend on efficient virus maturation, and that is disrupted upon binding of Env to CD4 or by neutralizing antibodies. Thus, this study illuminates how different intramolecular conformations and distribution of Env molecules mediate HIV-1 Env-T cell interactions in real time and therefore might control immune evasion.

Critical issues in molecular recognition: the enzyme-substrate association

Chemical and shape recognition are the main assembling mechanisms of complex bio-structures. A refined assessment of relevant thermodynamic parameters includes the consideration of a variety of contributions from different molecular motions and electronic interactions. An additional refinement includes the analysis of recognition involving multiple distant partners. This perspective note highlights some of the above issues in the cases of fibrillogenesis, and enzyme-substrate and antigen-antibody associations. Translational motions are found to be particularly relevant to the fibrillogenesis process. The assembly of enzyme-substrate complexes is discussed in terms of a dynamic equilibrium process.

Out-of-Equilibrium Biophysical Chemistry: The Case for Multidimensional, Integrated Single-Molecule Approaches

Out-of-equilibrium processes are ubiquitous across living organisms and all structural hierarchies of life. At the molecular scale, out-of-equilibrium processes (for example, enzyme catalysis, gene regulation, and motor protein functions) cause biological macromolecules to sample an ensemble of conformations over a wide range of time scales. Quantifying and conceptualizing the structure–dynamics to function relationship is challenging because continuously evolving multidimensional energy landscapes are necessary to describe nonequilibrium biological processes in biological macromolecules. In this perspective, we explore the challenges associated with state-of-the-art experimental techniques to understanding biological macromolecular function. We argue that it is time to revisit how we probe and model functional out-of-equilibrium biomolecular dynamics. We suggest that developing integrated single-molecule multiparametric force–fluorescence instruments and using advanced molecular dynamics simulations to study out-of-equilibrium biomolecules will provide a path towards understanding the principles of and mechanisms behind the structure–dynamics to function paradigm in biological macromolecules.

FRETraj: Integrating single-molecule spectroscopy with molecular dynamics

SUMMARY

Quantitative interpretation of single-molecule FRET experiments requires a model of the dye dynamics to link experimental energy transfer efficiencies to distances between atom positions. We have developed FRETraj, a Python module to predict FRET distributions based on accessible-contact volumes (ACV) and simulated photon statistics. FRETraj helps to identify optimal fluorophore positions on a biomolecule of interest by rapidly evaluating donor-acceptor distances. FRETraj is scalable and fully integrated into PyMOL and the Jupyter ecosystem. Here we describe the conformational dynamics of a DNA hairpin by computing multiple ACVs along a molecular dynamics trajectory and compare the predicted FRET distribution with single-molecule experiments. FRET-assisted modeling will accelerate the analysis of structural ensembles in particular dynamic, non-coding RNAs and transient protein-nucleic acid complexes.

AVAILABILITY

FRETraj is implemented as a cross-platform Python package available under the GPL-3.0 on Github (https://github.com/RNA-FRETools/fretraj) and is documented at https://RNA-FRETools.github.io/fretraj.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Rapid protein delivery to living cells for biomolecular investigation

The lack of a simple, fast and efficient method for protein delivery is limiting the widespread application of in-cell experiments, which are crucial for understanding the cellular function. We present here an innovative strategy to deliver proteins into both prokaryotic and eukaryotic cells, exploiting thermal vesiculation. This method allows to internalize substantial amounts of proteins, with different molecular weight and conformation, without compromising the structural properties and cell viability. Characterizing proteins in a physiological environment is essential as the environment can dramatically affect the conformation and dynamics of biomolecules as shown by in-cell EPR spectra vs those acquired in buffer solution. Considering its versatility, this method opens the possibility to scientists to study proteins directly in living cells through a wide range of techniques.

Fundamental photophysics of isomorphic and expanded fluorescent nucleoside analogues

Fluorescent nucleoside analogues (FNAs) are structurally diverse mimics of the natural essentially non-fluorescent nucleosides which have found numerous applications in probing the structure and dynamics of nucleic acids as well as their interactions with various biomolecules. In order to minimize disturbance in the labelled nucleic acid sequences, the FNA chromophoric groups should resemble the natural nucleobases in size and hydrogen-bonding patterns. Isomorphic and expanded FNAs are the two groups that best meet the criteria of non-perturbing fluorescent labels for DNA and RNA. Significant progress has been made over the past decades in understanding the fundamental photophysics that governs the spectroscopic and environmentally sensitive properties of these FNAs. Herein, we review recent advances in the spectroscopic and computational studies of selected isomorphic and expanded FNAs. We also show how this information can be used as a rational basis to design new FNAs, select appropriate sequences for optimal spectroscopic response and interpret fluorescence data in FNA applications.

Canonical T cell receptor docking on peptide-MHC is essential for T cell signaling

T cell receptor (TCR) recognition of peptide-major histocompatibility complexes (pMHCs) is characterized by a highly conserved docking polarity. Whether this polarity is driven by recognition or signaling constraints remains unclear. Using "reversed-docking" TCRβ-variable (TRBV) 17⁺ TCRs from the naïve mouse CD8⁺ T cell repertoire that recognizes the H-2D^b-NP₃₆₆ epitope, we demonstrate that their inability to support T cell activation and in vivo recruitment is a direct consequence of reversed docking polarity and not TCR-pMHCI binding or clustering characteristics. Canonical TCR-pMHCI docking optimally localizes CD8/Lck to the CD3 complex, which is prevented by reversed TCR-pMHCI polarity. The requirement for canonical docking was circumvented by dissociating Lck from CD8. Thus, the consensus TCR-pMHC docking topology is mandated by T cell signaling constraints.

Epistasis and intramolecular networks in protein evolution

Proteins are molecular machines composed of complex, highly connected amino acid networks. Their functional optimization requires the reorganization of these intramolecular networks by evolution. In this review, we discuss the mechanisms by which epistasis, that is, the dependence of the effect of a mutation on the genetic background, rewires intramolecular interactions to alter protein function. Deciphering the biophysical basis of epistasis is crucial to our understanding of evolutionary dynamics and the elucidation of sequence-structure-function relationships. We featured recent studies that provide insights into the molecular mechanisms giving rise to epistasis, particularly at the structural level. These studies illustrate the convoluted and fascinating nature of the intramolecular networks co-opted by epistasis during the evolution of protein function.

Different Single-Enzyme Conformational Dynamics upon Binding Hydrolyzable or Nonhydrolyzable Ligands

Single-molecule measurements of protein dynamics help unveil the complex conformational changes and transitions that occur during ligand binding and catalytic processes. Using high-resolution single-molecule nanocircuit techniques, we have investigated differences in the conformational dynamics and transitions of lysozyme interacting with three ligands: peptidoglycan substrate, substrate-based chitin analogue, and indole derivative inhibitors. While processing peptidoglycan, lysozyme followed one of the two mechanistic pathways for the hydrolysis of the glycosidic bonds: a concerted mechanism inducing direct conformational changes from open to fully closed conformations or a nonconcerted mechanism involving transient pauses in intermediate conformations between the open and closed conformations. In the presence of either chitin or an indole inhibitor, lysozyme was unable to access the fully closed conformation where catalysis occurs. Instead, lysozymes' conformational closures terminated at slightly closed, "excited" conformations that were approximately one-quarter of the full hinge-bending range. With the indole inhibitor, lysozyme reached this excited conformation in a single step without any evidence of rate-liming intermediates, but the same conformational motions with chitin involved three hidden, intermediate processes and features similar to the nonconcerted peptidoglycan mechanism. The similarities suggest that these hidden processes involve attempts to accommodate imperfectly aligned polysaccharides in the active site. The results provide a detailed glimpse of the enzyme-ligand interplay at the crux of molecular recognition, enzyme specificity, and catalysis.

Ensemble Switching Unveils a Kinetic Rheostat Mechanism of the Eukaryotic Thiamine Pyrophosphate Riboswitch

Thiamine pyrophosphate (TPP) riboswitches regulate thiamine metabolism by inhibiting the translation of enzymes essential to thiamine synthesis pathways upon binding to thiamine pyrophosphate in cells across all domains of life. Recent work on the Arabidopsis thaliana TPP riboswitch suggests a multi-step TPP binding process involving multiple riboswitch configurational ensembles and that Mg2+ dependence underlies the mechanism of TPP recognition and subsequent transition to the expression-inhibiting state of the aptamer domain followed by changes in the expression platform. However, details of the relationship between TPP riboswitch conformational changes and interactions with TPP and Mg2+ ¬¬in the aptamer domain constituting this mechanism are unknown. Therefore, we integrated single-molecule multiparameter fluorescence and force spectroscopy with atomistic molecular dynamics simulations and found that conformational transitions within the aptamer domain's sensor helices associated with TPP and Mg2+ ligand binding occurred between at least five different ensembles on timescales ranging from µs to ms. These dynamics are orders of magnitude faster than the 10 second-timescale folding kinetics associated with expression-state switching in the switch sequence. Together, our results show that a TPP and Mg2+ dependent mechanism determines dynamic configurational state ensemble switching of the aptamer domain's sensor helices that regulates the stability of the switch helix, which ultimately may lead to the expression-inhibiting state of the riboswitch. Additionally, we propose that two pathways exist for ligand recognition and that this mechanism underlies a kinetic rheostat-like behavior of the Arabidopsis thaliana TPP riboswitch.

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).

A general model to optimise CuII labelling efficiency of double-histidine motifs for pulse dipolar EPR applications

Electron paramagnetic resonance (EPR) distance measurements are making increasingly important contributions to studies of biomolecules underpinning health and disease by providing highly accurate and precise geometric constraints. Combining double-histidine (dH) motifs with CuII spin labels shows promise for further increasing the precision of distance measurements, and for investigating subtle conformational changes. However, non-covalent coordination-based spin labelling is vulnerable to low binding affinity. Dissociation constants of dH motifs for CuII-nitrilotriacetic acid were previously investigated via relaxation induced dipolar modulation enhancement (RIDME), and demonstrated the feasibility of exploiting the dH motif for EPR applications at sub-μM protein concentrations. Herein, the feasibility of using modulation depth quantitation in CuII-CuII RIDME to simultaneously estimate a pair of non-identical independent KD values in such a tetra-histidine model protein is addressed. Furthermore, we develop a general speciation model to optimise CuII labelling efficiency, depending upon pairs of identical or disparate KD values and total CuII label concentration. We find the dissociation constant estimates are in excellent agreement with previously determined values, and empirical modulation depths support the proposed model.

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.

Pulse Dipolar EPR Reveals Double-Histidine Motif CuII-NTA Spin-Labeling Robustness against Competitor Ions

Pulse-dipolar EPR is an appealing strategy for structural characterization of complex systems in solution that complements other biophysical techniques. Significantly, the emergence of genetically encoded self-assembling spin labels exploiting exogenously introduced double-histidine motifs in conjunction with Cu^II-chelates offers high precision distance determination in systems nonpermissive to thiol-directed spin labeling. However, the noncovalency of this interaction exposes potential vulnerabilities to competition from adventitious divalent metal ions, and pH sensitivity. Herein, a combination of room-temperature isothermal titration calorimetry (ITC) and cryogenic relaxation-induced dipolar modulation enhancement (RIDME) measurements are applied to the model protein Streptococcus sp. group G. protein G, B1 domain (GB1). Results demonstrate double-histidine motif spin labeling using Cu^II-nitrilotriacetic acid (Cu^II-NTA) is robust against the competitor ligand Zn^II-NTA at >1000-fold molar excess, and high nM binding affinity is surprisingly retained under acidic and basic conditions even though room temperature affinity shows a stronger pH dependence. This indicates the strategy is well-suited for diverse biological applications, with the requirement of other metal ion cofactors or slightly acidic pH not necessarily being prohibitive.

Pulse Dipolar EPR Reveals Double-Histidine Motif CuII-NTA Spin-Labeling Robustness against Competitor Ions

Pulse-dipolar EPR is an appealing strategy for structural characterization of complex systems in solution that complements other biophysical techniques. Significantly, the emergence of genetically encoded self-assembling spin labels exploiting exogenously introduced double-histidine motifs in conjunction with Cu^II-chelates offers high precision distance determination in systems nonpermissive to thiol-directed spin labeling. However, the noncovalency of this interaction exposes potential vulnerabilities to competition from adventitious divalent metal ions, and pH sensitivity. Herein, a combination of room-temperature isothermal titration calorimetry (ITC) and cryogenic relaxation-induced dipolar modulation enhancement (RIDME) measurements are applied to the model protein Streptococcus sp. group G. protein G, B1 domain (GB1). Results demonstrate double-histidine motif spin labeling using Cu^II-nitrilotriacetic acid (Cu^II-NTA) is robust against the competitor ligand Zn^II-NTA at >1000-fold molar excess, and high nM binding affinity is surprisingly retained under acidic and basic conditions even though room temperature affinity shows a stronger pH dependence. This indicates the strategy is well-suited for diverse biological applications, with the requirement of other metal ion cofactors or slightly acidic pH not necessarily being prohibitive.

Reaction Pathway Sampling and Free-Energy Analyses for Multimeric Protein Complex Disassembly by Employing Hybrid Configuration Bias Monte Carlo/Molecular Dynamics Simulation

Physicochemical characterization of multimeric biomacromolecule assembly and disassembly processes is a milestone to understand the mechanisms for biological phenomena at the molecular level. Mass spectroscopy (MS) and structural bioinformatics (SB) approaches have become feasible to identify subcomplexes involved in assembly and disassembly, while they cannot provide atomic information sufficient for free-energy calculation to characterize transition mechanism between two different sets of subcomplexes. To combine observations derived from MS and SB approaches with conventional free-energy calculation protocols, we here designed a new reaction pathway sampling method by employing hybrid configuration bias Monte Carlo/molecular dynamics (hcbMC/MD) scheme and applied it to simulate the disassembly process of serum amyloid P component (SAP) pentamer. The results we obtained are consistent with those of the earlier MS and SB studies with respect to SAP subcomplex species and the initial stage of SAP disassembly processes. Furthermore, we observed a novel dissociation event, ring-opening reaction of SAP pentamer. Employing free-energy calculation combined with the hcbMC/MD reaction pathway trajectories, we moreover obtained experimentally testable observations on (1) reaction time of the ring-opening reaction and (2) importance of Asp42 and Lys117 for stable formation of SAP oligomer.

Unraveling protein's structural dynamics: from configurational dynamics to ensemble switching guides functional mesoscale assemblies

Evidence regarding protein structure and function manifest the imperative role that dynamics play in proteins, underlining reconsideration of the unanimated sequence-to-structure-to-function paradigm. Structural dynamics portray a heterogeneous energy landscape described by conformational ensembles where each structural representation can be responsible for unique functions or enable macromolecular assemblies. Using the human p27/Cdk2/Cyclin A ternary complex as an example, we highlight the vital role of intramolecular and intermolecular dynamics for target recognition, binding, and inhibition as a critical modulator of cell division. Rapidly sampling configurations is critical for the population of different conformational ensembles encoding functional roles. To garner this knowledge, we present how the integration of (sub)ensemble and single-molecule fluorescence spectroscopy with molecular dynamic simulations can characterize structural dynamics linking the heterogeneous ensembles to function. The incorporation of dynamics into the sequence-to-structure-to-function paradigm promises to assist in tackling various challenges, including understanding the formation and regulation of mesoscale assemblies inside cells.