NMR paves the way for atomic level descriptions of sparsely populated, transiently formed biomolecular conformers

Beyond slow two-state protein conformational exchange using CEST: applications to three-state protein interconversion on the millisecond timescale

Although NMR spectroscopy is routinely used to study the conformational dynamics of biomolecules, robust analyses of the data are challenged in cases where exchange is more complex than two-state, such as when a 'visible' major conformer exchanges with two 'invisible' minor states on the millisecond timescale. It is becoming increasingly clear that chemical exchange saturation transfer (CEST) NMR experiments that were initially developed to study systems undergoing slow interconversion are also sensitive to intermediate-fast timescale biomolecular conformational exchange. Here we investigate the utility of the amide 15N CEST experiment to characterise protein three-state exchange occurring on the millisecond timescale by studying the interconversion between the folded (F) state of the FF domain from human HYPA/FBP11 (WT FF) and two of its folding intermediates I1 and I2. Although 15N CPMG experiments are consistent with the F state interconverting with a single minor state on the millisecond timescale, 15N CEST data clearly establish an exchange process between F and a pair of minor states. A unique three-state exchange model cannot be obtained by analysis of 15N CEST data recorded at a single temperature. However, including the relative sign of the difference in the chemical shifts of the two minor states based on a simple two-state analysis of CEST data recorded at multiple temperatures, results in a robust three-state model in which the F, I1 and I2 states interconvert with each other on the millisecond timescale ( k e x , F I 1 ~ 550 s-1, k e x , F I 2 ~ 1200 s-1, k e x , I 1 I 2 ~ 5000 s-1), with I1 and I2 sparsely populated at ~ 0.15% and ~ 0.35%, respectively, at 15 °C. A computationally demanding grid-search of exchange parameter space is not required to extract the best-fit exchange parameters from the CEST data. The utility of the CEST experiment, thus, extends well beyond studies of conformers in slow exchange on the NMR chemical shift timescale, to include systems with interconversion rates on the order of thousands/second.

MD simulations indicate Omicron P132H of SARS-CoV-2 Mpro is a potential allosteric mutant involved in modulating the dynamics of catalytic site entry loop

The SARS-CoV-2 main protease Mpro, essential for viral replication is an important drug target. It plays a critical role in processing viral polyproteins necessary for viral replication assembly. One of the predominant SARS-CoV-2 Mpro mutations of Omicron variant is Pro132His. Structurally, this mutation site is located ∼22 Å away from the catalytic site. The solved crystal structure of this mutant in complex with inhibitors as well as its reported catalytic efficiency did not show any difference with respect to the wild type. Thus, the mutation was concluded to be non-allosteric. Based on microsecond long MD simulation of the Pro132His mutant and wild type, we show that Pro132His mutation affects the conformational equilibrium with more population of conformational substates having open catalytic site, modulated by the dynamics of the catalytic site entry loop, implying the allosteric nature of this mutation. The structural analysis indicates that rearrangement of hydrogen bonds between His132 and adjacent residues enhances the dynamics of the linker, which in turn is augmented by the inherent dynamic flexibility of the catalytic pocket entry site due to the presence of charged residues. The altered dynamics leading to loss of secondary structures corroborate well with the reported compromised thermal stability.

Measuring Hydroxyl Exchange Rates in Glycans Using a Synergistic Combination of Saturation Transfer and Relaxation Dispersion NMR

Molecular recognition events mediated by glycans play pivotal roles in controlling the fate of diverse biological processes such as cellular communication and the immune response. The affinity of glycans for their target receptors is governed primarily by the hydrogen bonds formed by hydroxyl groups decorating the glycan surface. Hydroxyl exchange rate constants are therefore vital parameters that report on glycan structure and dynamics. Here we present a strategy for characterizing hydroxyl hydrogen/deuterium (H/D) exchange in glycans that employs a synergistic combination of 13C chemical exchange saturation transfer (CEST) and Carr-Purcell-Meiboom-Gill relaxation dispersion (CPMG) NMR methods. We show that the combination of CEST and CPMG experiments facilitates the sensitive detection of the small (∼0.1 ppm) two-bond deuterium isotope shift on a 13C nucleus when the attached hydroxyl group fluctuates between protonated and deuterated states. This shift is leveraged for measuring site-specific kinetic H/D exchange rate constants as well as thermodynamic free energies of isotope fractionation. The CEST and CPMG modules are integrated with a selective J-cross-polarization scheme that provides the flexibility for rapid characterization of H/D exchange at a specific hydroxyl site. Moreover, our approach enables the precise isothermal measurement of hydroxyl exchange rate constants without the need for cumbersome isotope labeling. The H/D exchange rate constants of three different glycans assessed using this method highlight its potential for detecting transient intra- and intermolecular hydrogen bonds. In addition, the trends in H/D exchange rate constants establish site-specific steric accessibility as a key determinant of solvent exchange dynamics in glycans.

Transient excited states of the metamorphic protein Mad2 and their implications for function

The spindle checkpoint complex is a key surveillance mechanism in cell division that prevents premature separation of sister chromatids. Mad2 is an integral component of this spindle checkpoint complex that recognizes cognate substrates such as Mad1 and Cdc20 in its closed (C-Mad2) conformation by fastening a "seatbelt" around short peptide regions that bind to the substrate recognition site. Mad2 is also a metamorphic protein that adopts not only the fold found in C-Mad2, but also a structurally distinct open conformation (O-Mad2) which is incapable of binding substrates. Here, we show using chemical exchange saturation transfer (CEST) and relaxation dispersion (CPMG) NMR experiments that Mad2 transiently populates three other higher free energy states with millisecond lifetimes, two in equilibrium with C-Mad2 (E1 and E2) and one with O-Mad2 (E3). E1 is a mimic of substrate-bound C-Mad2 in which the N-terminus of one C-Mad2 molecule inserts into the seatbelt region of a second molecule of C-Mad2, providing a potential pathway for autoinhibition of C-Mad2. E2 is the "unbuckled" conformation of C-Mad2 that facilitates the triage of molecules along competing fold-switching and substrate binding pathways. The E3 conformation that coexists with O-Mad2 shows fluctuations at a hydrophobic lock that is required for stabilizing the O-Mad2 fold and we hypothesize that E3 represents an early intermediate on-pathway towards conversion to C-Mad2. Collectively, the NMR data highlight the rugged free energy landscape of Mad2 with multiple low-lying intermediates that interlink substrate-binding and fold-switching, and also emphasize the role of molecular dynamics in its function.

Excited States of apo-Guanidine-III Riboswitch Contribute to Guanidinium Binding through Both Conformational and Induced-Fit Mechanisms

Riboswitches are mRNA segments that regulate gene expression through conformational changes driven by their cognate ligand binding. The ykkC motif forms a riboswitch class that selectively senses a guanidinium ion (Gdm+) and regulates the downstream expression of proteins which aid in the efflux of excess Gdm+ from the cells. The aptamer domain (AD) of the guanidine-III riboswitch forms an H-type pseudoknot with a triple helical domain that binds a Gdm+. We studied the binding of Gdm+ to the AD of the guanidine (ykkC)-III riboswitch using computer simulations to probe the specificity of the riboswitch to Gdm+ binding. We show that Gdm+ binding is a fast process occurring on the nanosecond time scale, with minimal conformational changes to the AD. Using machine learning and Markov-state models, we identified the excited conformational states of the AD, which have a high Gdm+ binding propensity, making the Gdm+ binding landscape complex exhibiting both conformational selection and induced-fit mechanisms. The proposed apo-AD excited states and their role in the ligand-sensing mechanism are amenable to experimental verification. Further, targeting these excited-state conformations in discovering new antibiotics can be explored.

BioCARS: Synchrotron facility for probing structural dynamics of biological macromolecules

A major goal in biomedical science is to move beyond static images of proteins and other biological macromolecules to the internal dynamics underlying their function. This level of study is necessary to understand how these molecules work and to engineer new functions and modulators of function. Stemming from a visionary commitment to this problem by Keith Moffat decades ago, a community of structural biologists has now enabled a set of x-ray scattering technologies for observing intramolecular dynamics in biological macromolecules at atomic resolution and over the broad range of timescales over which motions are functionally relevant. Many of these techniques are provided by BioCARS, a cutting-edge synchrotron radiation facility built under Moffat leadership and located at the Advanced Photon Source at Argonne National Laboratory. BioCARS enables experimental studies of molecular dynamics with time resolutions spanning from 100 ps to seconds and provides both time-resolved x-ray crystallography and small- and wide-angle x-ray scattering. Structural changes can be initiated by several methods-UV/Vis pumping with tunable picosecond and nanosecond laser pulses, substrate diffusion, and global perturbations, such as electric field and temperature jumps. Studies of dynamics typically involve subtle perturbations to molecular structures, requiring specialized computational techniques for data processing and interpretation. In this review, we present the challenges in experimental macromolecular dynamics and describe the current state of experimental capabilities at this facility. As Moffat imagined years ago, BioCARS is now positioned to catalyze the scientific community to make fundamental advances in understanding proteins and other complex biological macromolecules.

Dynamic Structures of Bioactive Proteins as Determined by Nuclear Magnetic Resonance

According to "Panta rhei", a phrase by the ancient Greeks, you cannot enter the same river two times [...].

Distinct activation mechanisms of β-arrestin-1 revealed by 19F NMR spectroscopy

β-Arrestins (βarrs) are functionally versatile proteins that play critical roles in the G-protein-coupled receptor (GPCR) signaling pathways. While it is well established that the phosphorylated receptor tail plays a central role in βarr activation, emerging evidence highlights the contribution from membrane lipids. However, detailed molecular mechanisms of βarr activation by different binding partners remain elusive. In this work, we present a comprehensive study of the structural changes in critical regions of βarr1 during activation using 19F NMR spectroscopy. We show that phosphopeptides derived from different classes of GPCRs display different βarr1 activation abilities, whereas binding of the membrane phosphoinositide PIP2 stabilizes a distinct partially activated conformational state. Our results further unveil a sparsely-populated activation intermediate as well as complex cross-talks between different binding partners, implying a highly multifaceted conformational energy landscape of βarr1 that can be intricately modulated during signaling.

Characterization of a transitionally occupied state and thermal unfolding of domain 1.1 of σ A factor of RNA polymerase from Bacillus subtilis

σ factors are essential parts of bacterial RNA polymerase (RNAP) as they allow to recognize promotor sequences and initiate transcription. Domain 1.1 of vegetative σ factors occupies the primary channel of RNAP and also prevents binding of the σ factor to promoter DNA alone. Here, we show that domain 1.1 of Bacillus subtilisσ A exists in more structurally distinct variants in dynamic equilibrium. The major conformation at room temperature is represented by a previously reported well-folded structure solved by nuclear magnetic resonance (NMR), but 4% of the protein molecules are present in a less thermodynamically favorable state. We show that this population increases with temperature and we predict its significant elevation at higher but still biologically relevant temperatures. We characterized the minor state of the domain 1.1 using specialized methods of NMR. We found that, in contrast to the major state, the detected minor state is partially unfolded. Its propensity to form secondary structure elements is especially decreased for the first and third α helices, while the second α helix and β strand close to the C-terminus are more stable. We also analyzed thermal unfolding of the domain 1.1 and performed functional experiments with full lengthσ A and its shortened version lacking domain 1.1 (σ A _ Δ 1.1 ). The results revealed that while full lengthσ A increases transcription activity of RNAP with increasing temperature, transcription withσ A _ Δ 1.1 remains constant. In summary, this study reveals conformational dynamics of domain 1.1 and provides a basis for studies of its interaction with RNAP and effects on transcription regulation.

Studying micro to millisecond protein dynamics using simple amide 15N CEST experiments supplemented with major-state R2 and visible peak-position constraints

Over the last decade amide 15N CEST experiments have emerged as a popular tool to study protein dynamics that involves exchange between a 'visible' major state and sparsely populated 'invisible' minor states. Although initially introduced to study exchange between states that are in slow exchange with each other (typical exchange rates of, 10 to 400 s-1), they are now used to study interconversion between states on the intermediate to fast exchange timescale while still using low to moderate (5 to 350 Hz) 'saturating' B1 fields. The 15N CEST experiment is very sensitive to exchange as the exchange delay TEX can be quite long (~0.5 s) allowing for a large number of exchange events to occur making it a very powerful tool to detect minor sates populated ([Formula: see text]) to as low as 1%. When systems are in fast exchange and the 15N CEST data has to be described using a model that contains exchange, the exchange parameters are often poorly defined because the [Formula: see text] versus [Formula: see text] and [Formula: see text] versus exchange rate ([Formula: see text]) plots can be quite flat with shallow or no minima and the analysis of such 15N CEST data can lead to wrong estimates of the exchange parameters due to the presence of 'spurious' minima. Here we show that the inclusion of experimentally derived constraints on the intrinsic transverse relaxation rates and the inclusion of visible state peak-positions during the analysis of amide 15N CEST data acquired with moderate B1 values (~50 to ~350 Hz) results in convincing minima in the [Formula: see text] versus [Formula: see text] and the [Formula: see text] versus [Formula: see text] plots even when exchange occurs on the 100 μs timescale. The utility of this strategy is demonstrated on the fast-folding Bacillus stearothermophilus peripheral subunit binding domain that folds with a rate constant ~104 s-1. Here the analysis of 15N CEST data alone results in [Formula: see text] versus [Formula: see text] and [Formula: see text] versus [Formula: see text] plots that contain shallow minima, but the inclusion of visible-state peak positions and restraints on the intrinsic transverse relaxation rates of both states during the analysis of the 15N CEST data results in pronounced minima in the [Formula: see text] versus [Formula: see text] and [Formula: see text] versus [Formula: see text] plots and precise exchange parameters even in the fast exchange regime ([Formula: see text]~5). Using this strategy we find that the folding rate constant of PSBD is invariant (~10,500 s-1) from 33.2 to 42.9 °C while the unfolding rates (~70 to ~500 s-1) and unfolded state populations (~0.7 to ~4.3%) increase with temperature. The results presented here show that protein dynamics occurring on the 10 to 104 s-1 timescale can be studied using amide 15N CEST experiments.

Functional regulation of an intrinsically disordered protein via a conformationally excited state

A longstanding goal in the field of intrinsically disordered proteins (IDPs) is to characterize their structural heterogeneity and pinpoint the role of this heterogeneity in IDP function. Here, we use multinuclear chemical exchange saturation (CEST) nuclear magnetic resonance to determine the structure of a thermally accessible globally folded excited state in equilibrium with the intrinsically disordered native ensemble of a bacterial transcriptional regulator CytR. We further provide evidence from double resonance CEST experiments that the excited state, which structurally resembles the DNA-bound form of cytidine repressor (CytR), recognizes DNA by means of a "folding-before-binding" conformational selection pathway. The disorder-to-order regulatory switch in DNA recognition by natively disordered CytR therefore operates through a dynamical variant of the lock-and-key mechanism where the structurally complementary conformation is transiently accessed via thermal fluctuations.

Emerging Time-Resolved X-Ray Diffraction Approaches for Protein Dynamics

Proteins guide the flows of information, energy, and matter that make life possible by accelerating transport and chemical reactions, by allosterically modulating these reactions, and by forming dynamic supramolecular assemblies. In these roles, conformational change underlies functional transitions. Time-resolved X-ray diffraction methods characterize these transitions either by directly triggering sequences of functionally important motions or, more broadly, by capturing the motions of which proteins are capable. To date, most successful have been experiments in which conformational change is triggered in light-dependent proteins. In this review, I emphasize emerging techniques that probe the dynamic basis of function in proteins lacking natively light-dependent transitions and speculate about extensions and further possibilities. In addition, I review how the weaker and more distributed signals in these data push the limits of the capabilities of analytical methods. Taken together, these new methods are beginning to establish a powerful paradigm for the study of the physics of protein function.

From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on "Allosteric Intersection" of Biochemical and Big Data Approaches

The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric regulation, the emerging structural biology technologies and AI approaches remains largely unexplored, calling for the development of AI-augmented integrative structural biology. In this review, we focus on the latest remarkable progress in deep high-throughput mining and comprehensive mapping of allosteric protein landscapes and allosteric regulatory mechanisms as well as on the new developments in AI methods for prediction and characterization of allosteric binding sites on the proteome level. We also discuss new AI-augmented structural biology approaches that expand our knowledge of the universe of protein dynamics and allostery. We conclude with an outlook and highlight the importance of developing an open science infrastructure for machine learning studies of allosteric regulation and validation of computational approaches using integrative studies of allosteric mechanisms. The development of community-accessible tools that uniquely leverage the existing experimental and simulation knowledgebase to enable interrogation of the allosteric functions can provide a much-needed boost to further innovation and integration of experimental and computational technologies empowered by booming AI field.

Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches

Allosteric mechanisms are commonly employed regulatory tools used by proteins to orchestrate complex biochemical processes and control communications in cells. The quantitative understanding and characterization of allosteric molecular events are among major challenges in modern biology and require integration of innovative computational experimental approaches to obtain atomistic-level knowledge of the allosteric states, interactions, and dynamic conformational landscapes. The growing body of computational and experimental studies empowered by emerging artificial intelligence (AI) technologies has opened up new paradigms for exploring and learning the universe of protein allostery from first principles. In this review we analyze recent developments in high-throughput deep mutational scanning of allosteric protein functions; applications and latest adaptations of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems. We also highlight recent computational and experimental studies of the SARS-CoV-2 spike (S) proteins revealing an important and often hidden role of allosteric regulation driving functional conformational changes, binding interactions with the host receptor, and mutational escape mechanisms of S proteins which are critical for viral infection. We conclude with a summary and outlook of future directions suggesting that AI-augmented biophysical and computer simulation approaches are beginning to transform studies of protein allostery toward systematic characterization of allosteric landscapes, hidden allosteric states, and mechanisms which may bring about a new revolution in molecular biology and drug discovery.

Intrinsically Disordered Chromatin Protein NUPR1 Binds to the Enzyme PADI4

The nuclear protein 1 (NUPR1) is an intrinsically disordered protein involved in stress-mediated cellular conditions. Its paralogue nuclear protein 1-like (NUPR1L) is p53-regulated, and its expression down-regulates that of the NUPR1 gene. Peptidyl-arginine deiminase 4 (PADI4) is an isoform of a family of enzymes catalyzing arginine to citrulline conversion; it is also involved in stress-mediated cellular conditions. We characterized the interaction between NUPR1 and PADI4 in vitro, in silico, and in cellulo. The interaction of NUPR1 and PADI4 occurred with a dissociation constant of 18 ± 6 μM. The binding region of NUPR1, mapped by NMR, was a hydrophobic polypeptide patch surrounding the key residue Ala33, as pinpointed by: (i) computational results; and, (ii) site-directed mutagenesis of residues of NUPR1. The association between PADI4 and wild-type NUPR1 was also assessed in cellulo by using proximity ligation assays (PLAs) and immunofluorescence (IF), and it occurred mainly in the nucleus. Moreover, binding between NUPR1L and PADI4 also occurred in vitro with an affinity similar to that of NUPR1. Molecular modelling provided information on the binding hot spot for PADI4. This is an example of a disordered partner of PADI4, whereas its other known interacting proteins are well-folded. Altogether, our results suggest that the NUPR1/PADI4 complex could have crucial functions in modulating DNA-repair, favoring metastasis, or facilitating citrullination of other proteins.

Advances in the exact nuclear Overhauser effect 2018-2022

The introduction of the exact nuclear Overhauser enhancement (eNOE) methodology to solution-state nuclear magnetic resonance (NMR) spectroscopy results in tighter distance restraints from NOEs than in convention analysis. These improved restraints allow for higher resolution in structure calculation and even the disentanglement of different conformations of macromolecules. While initial work primarily focused on technical development of the eNOE, structural studies aimed at the elucidation of spatial sampling in proteins and nucleic acids were published in parallel prior to 2018. The period of 2018-2022 saw a continued series of technical innovation, but also major applications addressing biological questions. Here, we review both aspects, covering topics from the implementation of non-uniform sampling of NOESY buildups, novel pulse sequences, adaption of the eNOE to solid-state NMR, advances in eNOE data analysis, and innovations in structural ensemble calculation, to applications to protein, RNA, and DNA structure elucidation.

Iterative Landmark-Based Umbrella Sampling (ILBUS) Protocol for Sampling of Conformational Space of Biomolecules

Computer simulations of biomolecules such as molecular dynamics often suffer from insufficient sampling. Due to limited computational resources, insufficient sampling prevents obtaining proper equilibrium distributions of observed properties. To deal with this problem, we proposed a simulation protocol for efficient resampling of collected off-equilibrium trajectories. These trajectories are utilized for the initial mapping of the conformational space, which is later properly resampled by the introduced Iterative Landmark-Based Umbrella Sampling (ILBUS) method. Reconstruction of static equilibrium properties is achieved by the multistate Bennett acceptance ratio (MBAR) method, which enables efficient use of simulated data. The ILBUS protocol is geometry-based and does not demand any additional collective variable or a dimensional-reduction technique. The only requirement is a set of suitably spaced reference conformations, which serve as landmarks in the mapped conformational space. Additionally, the ILBUS protocol encompasses an iterative process that optimizes the force constant used in the umbrella sampling simulation. Such tuning is an inherent feature of the protocol and does not need to be performed by the user in advance. Furthermore, even the simulations with suboptimal force constants can be used in estimates by MBAR. We demonstrate the feasibility and the performance of this approach in the study of the conformational landscape of the alanine dipeptide, met-enkephalin, and adenylate kinase.

Crowding-induced protein destabilization in the absence of soft attractions

It is generally assumed that volume exclusion by macromolecular crowders universally stabilizes the native states of proteins and destabilization suggests soft attractions between crowders and protein. Here we show that proteins can be destabilized even by crowders that are purely repulsive. With a coarse-grained sequence-based model, we study the folding thermodynamics of two sequences with different native folds, a helical hairpin and a β-barrel, in a range of crowder volume fractions, φ_c. We find that the native state, N, remains structurally unchanged under crowded conditions, while the size of the unfolded state, U, decreases monotonically with φ_c. Hence, for all φ_c>0, U is entropically disfavored relative to N. This entropy-centric view holds for the helical hairpin protein, which is stabilized under all crowded conditions as quantified by changes in either the folding midpoint temperature, T_m, or the free energy of folding. We find, however, that the β-barrel protein is destabilized under low-T, low-φ_c conditions. This destabilization can be understood from two characteristics of its folding: 1) a relatively compact U at T<T_m, such that U is only weakly disfavored entropically by the crowders; and 2) a transient, compact, and relatively low-energy nonnative state that has a maximum population of only a few percent at φ_c=0, but increasing monotonically with φ_c. Overall, protein destabilization driven by hard-core effects appears possible when a compaction of U leads to even a modest population of compact nonnative states that are energetically competitive with N.

Elucidating the mechanisms underlying protein conformational switching using NMR spectroscopy

How proteins switch between various ligand-free and ligand-bound structures has been a key biophysical question ever since the postulation of the Monod-Wyman-Changeux and Koshland-Nemethy-Filmer models over six decades ago. The ability of NMR spectroscopy to provide structural and kinetic information on biomolecular conformational exchange places it in a unique position as an analytical tool to interrogate the mechanisms of biological processes such as protein folding and biomolecular complex formation. In addition, recent methodological developments in the areas of saturation transfer and relaxation dispersion have expanded the scope of NMR for probing the mechanics of transitions in systems where one or more states constituting the exchange process are sparsely populated and 'invisible' in NMR spectra. In this review, we highlight some of the strategies available from NMR spectroscopy for examining the nature of multi-site conformational exchange, using five case studies that have employed NMR, either in isolation, or in conjunction with other biophysical tools.

Modulation of free energy landscapes as a strategy for the design of antimicrobial peptides

Computational design of antimicrobial peptides (AMPs) is a promising area of research for developing novel agents against drug-resistant bacteria. AMPs are present naturally in many organisms, from bacteria to humans, a time-tested mechanism that makes them attractive as effective antibiotics. Depending on the environment, AMPs can exhibit α-helical or β-sheet conformations, a mix of both, or lack secondary structure; they can be linear or cyclic. Prediction of their structures is challenging but critical for rational design. Promising AMP leads can be developed using essentially two approaches: traditional modeling of the physicochemical mechanisms that determine peptide behavior in aqueous and membrane environments and knowledge-based, e.g., machine learning (ML) techniques, that exploit ever-growing AMP databases. Here, we explore the conformational landscapes of two recently ML-designed AMPs, characterize the dependence of these landscapes on the medium conditions, and identify features in peptide and membrane landscapes that mediate protein-membrane association. For both peptides, we observe greater conformational diversity in an aqueous solvent than in a less polar solvent, and one peptide is seen to alter its conformation more dramatically than the other upon the change of solvent. Our results support the view that structural rearrangement in response to environmental changes is central to the mechanism of membrane-structure disruption by linear peptides. We expect that the design of AMPs by ML will benefit from the incorporation of peptide conformational substates as quantified here with molecular simulations.

AlphaFold 2 and NMR Spectroscopy: Partners to Understand Protein Structure, Dynamics and Function

The artificial intelligence program AlphaFold 2 is revolutionizing the field of protein structure determination as it accurately predicts the 3D structure of two thirds of the human proteome. Its predictions can be used directly as structural models or indirectly as aids for experimental structure determination using X-ray crystallography, CryoEM or NMR spectroscopy. Nevertheless, AlphaFold 2 can neither afford insight into how proteins fold, nor can it determine protein stability or dynamics. Rare folds or minor alternative conformations are also not predicted by AlphaFold 2 and the program does not forecast the impact of post translational modifications, mutations or ligand binding. The remaining third of human proteome which is poorly predicted largely corresponds to intrinsically disordered regions of proteins. Key to regulation and signaling networks, these disordered regions often form biomolecular condensates or amyloids. Fortunately, the limitations of AlphaFold 2 are largely complemented by NMR spectroscopy. This experimental approach provides information on protein folding and dynamics as well as biomolecular condensates and amyloids and their modulation by experimental conditions, small molecules, post translational modifications, mutations, flanking sequence, interactions with other proteins, RNA and virus. Together, NMR spectroscopy and AlphaFold 2 can collaborate to advance our comprehension of proteins.

Rational design of hairpin RNA excited states reveals multi-step transitions

RNA excited states represent a class of high-energy-level and thus low-populated conformational states of RNAs that are sequestered within the free energy landscape until being activated by cellular cues. In recent years, there has been growing interest in structural and functional studies of these transient states, but the rational design of excited states remains unexplored. Here we developed a method to design small hairpin RNAs with predefined excited states that exchange with ground states through base pair reshuffling, and verified these transient states by combining NMR relaxation dispersion technique and imino chemical shift prediction. Using van’t Hoff analysis and accelerated molecular dynamics simulations, a mechanism of multi-step sequential transition has been revealed. The efforts made in this study will expand the scope of RNA rational design, and also contribute towards improved predictions of RNA secondary structure.

RNA molecules exhibit conformational fluctuations between ground states and excited states. Here the authors designed and verified small hairpin RNAs with predefined secondary structure reshufflings. In light of Van’t Hoff analysis and accelerated molecular dynamics simulation, a mechanism of multistep sequential transition has been revealed.

Characterization of protein unfolding by fast cross-linking mass spectrometry using di-ortho-phthalaldehyde cross-linkers

Chemical cross-linking of proteins coupled with mass spectrometry is widely used in protein structural analysis. In this study we develop a class of non-hydrolyzable amine-selective di-ortho-phthalaldehyde (DOPA) cross-linkers, one of which is called DOPA2. Cross-linking of proteins with DOPA2 is 60-120 times faster than that with the N-hydroxysuccinimide ester cross-linker DSS. Compared with DSS cross-links, DOPA2 cross-links show better agreement with the crystal structures of tested proteins. More importantly, DOPA2 has unique advantages when working at low pH, low temperature, or in the presence of denaturants. Using staphylococcal nuclease, bovine serum albumin, and bovine pancreatic ribonuclease A, we demonstrate that DOPA2 cross-linking provides abundant spatial information about the conformations of progressively denatured forms of these proteins. Furthermore, DOPA2 cross-linking allows time-course analysis of protein conformational changes during denaturant-induced unfolding.

Structure determination of high-energy states in a dynamic protein ensemble

Macromolecular function frequently requires that proteins change conformation into high-energy states^1-4. However, methods for solving the structures of these functionally essential, lowly populated states are lacking. Here we develop a method for high-resolution structure determination of minorly populated states by coupling NMR spectroscopy-derived pseudocontact shifts⁵ (PCSs) with Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion⁶ (PCS-CPMG). Our approach additionally defines the corresponding kinetics and thermodynamics of high-energy excursions, thereby characterizing the entire free-energy landscape. Using a large set of simulated data for adenylate kinase (Adk), calmodulin and Src kinase, we find that high-energy PCSs accurately determine high-energy structures (with a root mean squared deviation of less than 3.5 angström). Applying our methodology to Adk during catalysis, we find that the high-energy excursion involves surprisingly small openings of the AMP and ATP lids. This previously unresolved high-energy structure solves a longstanding controversy about conformational interconversions that are rate-limiting for catalysis. Primed for either substrate binding or product release, the high-energy structure of Adk suggests a two-step mechanism combining conformational selection to this state, followed by an induced-fit step into a fully closed state for catalysis of the phosphoryl-transfer reaction. Unlike other methods for resolving high-energy states, such as cryo-electron microscopy and X-ray crystallography, our solution PCS-CPMG approach excels in cases involving domain rearrangements of smaller systems (less than 60 kDa) and populations as low as 0.5%, and enables the simultaneous determination of protein structure, kinetics and thermodynamics while proteins perform their function.

The A39G FF domain folds on a volcano-shaped free energy surface via separate pathways

Conformational dynamics play critical roles in protein folding, misfolding, function, misfunction, and aggregation. While detecting and studying the different conformational states populated by protein molecules on their free energy surfaces (FESs) remain a challenge, NMR spectroscopy has emerged as an invaluable experimental tool to explore the FES of a protein, as conformational dynamics can be probed at atomic resolution over a wide range of timescales. Here, we use chemical exchange saturation transfer (CEST) to detect "invisible" minor states on the energy landscape of the A39G mutant FF domain that exhibited "two-state" folding kinetics in traditional experiments. Although CEST has mostly been limited to studies of processes with rates between ∼5 to 300 s^-1 involving sparse states with populations as low as ∼1%, we show that the line broadening that is often associated with minor state dips in CEST profiles can be exploited to inform on additional conformers, with lifetimes an order of magnitude shorter and populations close to 10-fold smaller than what typically is characterized. Our analysis of CEST profiles that exploits the minor state linewidths of the 71-residue A39G FF domain establishes a folding mechanism that can be described in terms of a four-state exchange process between interconverting states spanning over two orders of magnitude in timescale from ∼100 to ∼15,000 μs. A similar folding scheme is established for the wild-type domain as well. The study shows that the folding of this small domain proceeds through a pair of sparse, partially structured intermediates via two discrete pathways on a volcano-shaped FES.

Hydrogen/Deuterium Exchange Measurements May Provide an Incomplete View of Protein Dynamics: a Case Study on Cytochrome c

Many aspects of protein function rely on conformational fluctuations. Hydrogen/deuterium exchange (HDX) mass spectrometry (MS) provides a window into these dynamics. Despite the widespread use of HDX-MS, it remains unclear whether this technique provides a truly comprehensive view of protein dynamics. HDX is mediated by H-bond-opening/closing events, implying that HDX methods provide an H-bond-centric view. This raises the question if there could be fluctuations that leave the H-bond network unaffected, thereby rendering them undetectable by HDX-MS. We explore this issue in experiments on cytochrome c (cyt c). Compared to the Fe(II) protein, Fe(III) cyt c shows enhanced deuteration on both the distal and proximal sides of the heme. Previous studies have attributed the enhanced dynamics of Fe(III) cyt c to the facile and reversible rupture of the distal M80-Fe(III) bond. Using molecular dynamics (MD) simulations, we conducted a detailed analysis of various cyt c conformers. Our MD data confirm that rupture of the M80-Fe(III) contact triggers major reorientation of the distal Ω loop. Surprisingly, this event takes place with only miniscule H-bonding alterations. In other words, the distal loop dynamics are almost "HDX-silent". Moreover, distal loop movements cannot account for enhanced dynamics on the opposite (proximal) side of the heme. Instead, enhanced deuteration of Fe(III) cyt c is attributed to sparsely populated conformers where both the distal (M80) and proximal (H18) coordination bonds have been ruptured, along with opening of numerous H-bonds on both sides of the heme. We conclude that there can be major structural fluctuations that are only weakly coupled to changes in H-bonding, making them virtually impossible to track by HDX-MS. In such cases, HDX-MS may provide an incomplete view of protein dynamics.

Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins

Intrinsically disordered proteins and intrinsically disordered regions within proteins make up a large and functionally significant part of the human proteome. The highly flexible nature of these sequences allows them to form weak, long-range, and transient interactions with diverse biomolecular partners. Specific yet low-affinity interactions promote promiscuous binding and enable a single intrinsically disordered segment to interact with a multitude of target sites. Because of the transient nature of these interactions, they can be difficult to characterize by structural biology methods that rely on proteins to form a single, predominant conformation. Paramagnetic relaxation enhancement NMR is a useful tool for identifying and defining the structural underpinning of weak and transient interactions. A detailed protocol for using paramagnetic relaxation enhancement to characterize the lowly-populated encounter complexes that form between intrinsically disordered proteins and their protein, nucleic acid, or other biomolecular partners is described.

Identification and characterization of metamorphic proteins: Current and future perspectives

Proteins that can reversibly alternate between distinctly different folds under native conditions are described as being metamorphic. The "metamorphome" is the collection of all metamorphic proteins in the proteome, but it remains unknown the extent to which the proteome is populated by this class of proteins. We propose that uncovering the metamorphome will require a synergy of computational screening of protein sequences to identify potential metamorphic behavior and validation through experimental techniques. This perspective discusses computational and experimental approaches that are currently used to predict and characterize metamorphic proteins as well as the need for developing improved methodologies. Since metamorphic proteins act as molecular switches, understanding their properties and behavior could lead to novel applications of these proteins as sensors in biological or environmental contexts.

Characterization of Mannosyl Dioxanium Ions in Solution Using Chemical Exchange Saturation Transfer NMR

The stereoselective introduction of the glycosidic bond remains one of the main challenges in carbohydrate synthesis. Characterizing the reactive intermediates of this reaction is key to develop stereoselective glycosylation reactions. Herein we report the characterization of low-populated, rapidly equilibrating, mannosyl dioxanium ions that arise from participation of a C-3 acyl group using chemical exchange saturation transfer (CEST) NMR spectroscopy. Dioxanium ion structure and equilibration kinetics were measured under relevant glycosylation conditions and highly α -selective couplings were observed suggesting glycosylation took place via this elusive intermediate.

Advances in the study of GPCRs by 19F NMR

Crystallography and cryo-electron microscopy have advanced atomic resolution perspectives of inactive and active states of G protein-coupled receptors (GPCRs), alone and in complex with G proteins or arrestin. ¹⁹F NMR can play a role in ascertaining activation mechanisms and understanding the complete energy landscape associated with signal transduction. Fluorinated reporters are introduced biosynthetically via fluorinated amino acid analogs or chemically, via thiol-specific fluorinated reporters. The chemical shift sensitivity of these reporters makes it possible to discern details of conformational ensembles. In addition to spectroscopic details, paramagnetic species can be incorporated through orthogonal techniques to obtain distance information on fluorinated reporters, while T₂-and T₁-based relaxation experiments provide details on exchange kinetics in addition to fluctuations within a given state.

A Genetically Encoded Two-Dimensional Infrared Probe for Enzyme Active-Site Dynamics

While two-dimensional infrared (2D-IR) spectroscopy is uniquely suitable for monitoring femtosecond (fs) to picosecond (ps) water dynamics around static protein structures, its utility for probing enzyme active-site dynamics is limited due to the lack of site-specific 2D-IR probes. We demonstrate the genetic incorporation of a novel 2D-IR probe, m-azido-L-tyrosine (N3Y) in the active-site of DddK, an iron-dependent enzyme that catalyzes the conversion of dimethylsulfoniopropionate to dimethylsulphide. Our results show that both the oxidation of active-site iron to Fe^III , and the addition of denaturation reagents, result in significant decrease in enzyme activity and active-site water motion confinement. As tyrosine residues play important roles, including as general acids and bases, and electron transfer agents in many key enzymes, the genetically encoded 2D-IR probe N3Y should be broadly applicable to investigate how the enzyme active-site motions at the fs-ps time scale direct reaction pathways to facilitating specific chemical reactions.

Probing RNA Conformational Equilibria within the Functional Cellular Context

Low-abundance short-lived non-native conformations referred to as excited states (ESs) are increasingly observed in vitro and implicated in the folding and biological activities of regulatory RNAs. We developed an approach for assessing the relative abundance of RNA ESs within the functional cellular context. Nuclear magnetic resonance (NMR) spectroscopy was used to estimate the degree to which substitution mutations bias conformational equilibria toward the inactive ES in vitro. The cellular activity of the ES-stabilizing mutants was used as an indirect measure of the conformational equilibria within the functional cellular context. Compensatory mutations that restore the ground-state conformation were used to control for changes in sequence. Using this approach, we show that the ESs of two regulatory RNAs from HIV-1, the transactivation response element (TAR) and the Rev response element (RRE), likely form in cells with abundances comparable to those measured in vitro, and their targeted stabilization may provide an avenue for developing anti-HIV therapeutics.

Chemical shift prediction of RNA imino groups: application toward characterizing RNA excited states

NH groups in proteins or nucleic acids are the most challenging target for chemical shift prediction. Here we show that the RNA base pair triplet motif dictates imino chemical shifts in its central base pair. A lookup table is established that links each type of base pair triplet to experimental chemical shifts of the central base pair, and can be used to predict imino chemical shifts of RNAs to remarkable accuracy. Strikingly, the semiempirical method can well interpret the variations of chemical shifts for different base pair triplets, and is even applicable to non-canonical motifs. This finding opens an avenue for predicting chemical shifts of more complicated RNA motifs. Furthermore, we combine the imino chemical shift prediction with NMR relaxation dispersion experiments targeting both ¹⁵N and ¹H^N of the imino group, and verify a previously characterized excited state of P5abc subdomain including an earlier speculated non-native G•G mismatch.

Prediction of chemical shifts is critical for extracting structural and dynamic information from biomolecular NMR data. Here the authors report an RNA imino group chemical shift predictor, showing that the imino chemical shifts of a residue are dictated by the surrounding base pair triplet.

Removal of 2H-decoupling sidebands in 13CHD2 13C-CEST profiles

A unique aspect of NMR is its capacity to provide integrated insight into both the structure and intrinsic dynamics of biomolecules. Chemical exchange phenomena that often serve as probes of dynamic processes in biological macromolecules can be quantitatively investigated with chemical exchange saturation transfer (CEST) experiments. ²H-decoupling sidebands, however, always occur in the profiles of ¹³CHD₂ ¹³C-CEST experiments when using the simple CW (continuous wave) method, which may obscure the detection of minor dips of excited states. Traditionally, these sidebands are manually eliminated from the profiles before data analysis by removing experimental points in the range of ²H-decoupling field strength ±50 Hz away from the major dips of the ground state on either side of the dips. Unfortunately, this may also eliminate potential minor dips if they overlap with the decoupling sidebands. Here, we developed methods that use pseudo-continuous waves with variable RF amplitudes distributed onto ramps for ²H decoupling. The new methods were thoroughly validated on Bruker spectrometers at a range of fields (¹H frequencies of 600, 700, and 850 MHz, and 1.1 GHz). By using these methods, we successfully removed the sidebands from the NMR profiles of ¹³CHD₂ ¹³C-CEST experiments.

NMR spectroscopy captures the essential role of dynamics in regulating biomolecular function

Biomolecules are in constant motion. To understand how they function, and why malfunctions can cause disease, it is necessary to describe their three-dimensional structures in terms of dynamic conformational ensembles. Here, we demonstrate how nuclear magnetic resonance (NMR) spectroscopy provides an essential, dynamic view of structural biology that captures biomolecular motions at atomic resolution. We focus on examples that emphasize the diversity of biomolecules and biochemical applications that are amenable to NMR, such as elucidating functional dynamics in large molecular machines, characterizing transient conformations implicated in the onset of disease, and obtaining atomic-level descriptions of intrinsically disordered regions that make weak interactions involved in liquid-liquid phase separation. Finally, we discuss the pivotal role that NMR has played in driving forward our understanding of the biomolecular dynamics-function paradigm.

2'-O-Methylation can increase the abundance and lifetime of alternative RNA conformational states

2'-O-Methyl (Nm) is a highly abundant post-transcriptional RNA modification that plays important biological roles through mechanisms that are not entirely understood. There is evidence that Nm can alter the biological activities of RNAs by biasing the ribose sugar pucker equilibrium toward the C3'-endo conformation formed in canonical duplexes. However, little is known about how Nm might more broadly alter the dynamic ensembles of flexible RNAs containing bulges and internal loops. Here, using NMR and the HIV-1 transactivation response (TAR) element as a model system, we show that Nm preferentially stabilizes alternative secondary structures in which the Nm-modified nucleotides are paired, increasing both the abundance and lifetime of low-populated short-lived excited states by up to 10-fold. The extent of stabilization increased with number of Nm modifications and was also dependent on Mg2+. Through phi-value analysis, the Nm modification also provided rare insights into the structure of the transition state for conformational exchange. Our results suggest that Nm could alter the biological activities of Nm-modified RNAs by modulating their secondary structural ensembles as well as establish the utility of Nm as a tool for the discovery and characterization of RNA excited state conformations.

Visualizing a protonated RNA state that modulates microRNA-21 maturation

MicroRNAs are evolutionarily conserved small, noncoding RNAs that regulate diverse biological processes. Due to their essential regulatory roles, microRNA biogenesis is tightly regulated, where protein factors are often found to interact with specific primary and precursor microRNAs for regulation. Here, using NMR relaxation dispersion spectroscopy and mutagenesis, we reveal that the precursor of oncogenic microRNA-21 exists as a pH-dependent ensemble that spontaneously reshuffles the secondary structure of the entire apical stem-loop region, including the Dicer cleavage site. We show that the alternative excited conformation transiently sequesters the bulged adenine into a noncanonical protonated A⁺-G mismatch, conferring a substantial enhancement in Dicer processing over its ground conformational state. These results indicate that microRNA maturation efficiency may be encoded in the intrinsic dynamic ensemble of primary and precursor microRNAs, providing a potential means of regulating microRNA biogenesis in response to environmental and cellular stimuli.

Probing conformational transitions towards mutagenic Watson-Crick-like G·T mismatches using off-resonance sugar carbon R1ρ relaxation dispersion

NMR off-resonance R_1ρ relaxation dispersion measurements on base carbon and nitrogen nuclei have revealed that wobble G·T/U mismatches in DNA and RNA duplexes exist in dynamic equilibrium with short-lived, low-abundance, and mutagenic Watson-Crick-like conformations. As Watson-Crick-like G·T mismatches have base pairing geometries similar to Watson-Crick base pairs, we hypothesized that they would mimic Watson-Crick base pairs with respect to the sugar-backbone conformation as well. Using off-resonance R_1ρ measurements targeting the sugar C3' and C4' nuclei, a structure survey, and molecular dynamics simulations, we show that wobble G·T mismatches adopt sugar-backbone conformations that deviate from the canonical Watson-Crick conformation and that transitions toward tautomeric and anionic Watson-Crick-like G·T mismatches restore the canonical Watson-Crick sugar-backbone. These measurements also reveal kinetic isotope effects for tautomerization in D₂O versus H₂O, which provide experimental evidence in support of a transition state involving proton transfer. The results provide additional evidence in support of mutagenic Watson-Crick-like G·T mismatches, help rule out alternative inverted wobble conformations in the case of anionic G·T^-, and also establish sugar carbons as new non-exchangeable probes of this exchange process.

Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.

Extending the Sensitivity of CEST NMR Spectroscopy to Micro-to-Millisecond Dynamics in Nucleic Acids Using High-Power Radio-Frequency Fields

Biomolecules undergo motions on the micro-to-millisecond timescale to adopt low-populated transient states that play important roles in folding, recognition, and catalysis. NMR techniques, such as Carr-Purcell-Meiboom-Gill (CPMG), chemical exchange saturation transfer (CEST), and R1ρ are the most commonly used methods for characterizing such transitions at atomic resolution under solution conditions. CPMG and CEST are most effective at characterizing motions on the millisecond timescale. While some implementations of the R1ρ experiment are more broadly sensitive to motions on the micro-to-millisecond timescale, they entail the use of selective irradiation schemes and inefficient 1D data acquisition methods. Herein, we show that high-power radio-frequency fields can be used in CEST experiments to extend the sensitivity to faster motions on the micro-to-millisecond timescale. Given the ease of implementing high-power fields in CEST, this should make it easier to characterize micro-to-millisecond dynamics in biomolecules.

Maturation of the functional mouse CRES amyloid from globular form

The epididymal lumen contains a complex cystatin-rich nonpathological amyloid matrix with putative roles in sperm maturation and sperm protection. Given our growing understanding for the biological function of this and other functional amyloids, the problem still remains: how functional amyloids assemble including their initial transition to early oligomeric forms. To examine this, we developed a protocol for the purification of nondenatured mouse CRES, a component of the epididymal amyloid matrix, allowing us to examine its assembly to amyloid under conditions that may mimic those in vivo. Herein we use X-ray crystallography, solution-state NMR, and solid-state NMR to follow at the atomic level the assembly of the CRES amyloidogenic precursor as it progressed from monomeric folded protein to an advanced amyloid. We show the CRES monomer has a typical cystatin fold that assembles into highly branched amyloid matrices, comparable to those in vivo, by forming β-sheet assemblies that our data suggest occur via two distinct mechanisms: a unique conformational switch of a highly flexible disulfide-anchored loop to a rigid β-strand and by traditional cystatin domain swapping. Our results provide key insight into our understanding of functional amyloid assembly by revealing the earliest structural transitions from monomer to oligomer and by showing that some functional amyloid structures may be built by multiple and distinctive assembly mechanisms.

Unveiling the activation dynamics of a fold-switch bacterial glycosyltransferase by 19F NMR

Fold-switch pathways remodel the secondary structure topology of proteins in response to the cellular environment. It is a major challenge to understand the dynamics of these folding processes. Here, we conducted an in-depth analysis of the α-helix–to–β-strand and β-strand–to–α-helix transitions and domain motions displayed by the essential mannosyltransferase PimA from mycobacteria. Using ¹⁹F NMR, we identified four functionally relevant states of PimA that coexist in dynamic equilibria on millisecond-to-second timescales in solution. We discovered that fold-switching is a slow process, on the order of seconds, whereas domain motions occur simultaneously but are substantially faster, on the order of milliseconds. Strikingly, the addition of substrate accelerated the fold-switching dynamics of PimA. We propose a model in which the fold-switching dynamics constitute a mechanism for PimA activation.

The Conformational Preference of Chemical Cross-linkers Determines the Cross-linking Probability of Reactive Protein Residues

Chemical cross-linking mass spectrometry (XLMS) is an emerging technique in structural biology. Providing the cross-linked peptides are identified by mass spectrometry with high confidence, a distance restraint can be applied between the two reactive protein residues, with the upper bound corresponding to the maximal span of the cross-linker. However, as the upper bound is typically over 20 Å, cross-link distance restraints are unrestrictive and provide a marginal improvement in protein structural refinement. Here we analyze the experimental cross-links for lysine or acidic residues and show that the distribution of Cβ-Cβ' distances can be described with two overlapping Gaussian species. In addition to the pairwise occurrence probability of the reactive protein residues, we show that the distribution profile of the cross-link distances is determined by the intrinsic conformational propensity of the cross-linker. The cross-linker prefers either a compact or extended conformation and, once attached to a reactive protein residue, predominantly an extended conformation. Consequently, the long-distance Gaussian species occurs at a much higher probability than the short-distance species in the observed cross-links. Together, the probabilistic distribution of the cross-link distance allows the construction of a more restrictive restraint for structural modeling and better use of the XLMS data.

The Pierced Lasso Topology Leptin has a Bolt on Dynamic Domain Composed by the Disordered Loops I and III

Leptin is an important signaling hormone, mostly known for its role in energy expenditure and satiety. Furthermore, leptin plays a major role in other proteinopathies, such as cancer, marked hyperphagia, impaired immune function, and inflammation. In spite of its biological relevance in human health, there are no NMR resonance assignments of the human protein available, obscuring high-resolution characterization of the soluble protein and/or its conformational dynamics, suggested as being important for receptor interaction and biological activity. Here, we report the nearly complete backbone resonance assignments of human leptin. Chemical shift-based secondary structure prediction confirms that in solution leptin forms a four-helix bundle including a pierced lasso topology. The conformational dynamics, determined on several timescales, show that leptin is monomeric, has a rigid four-helix scaffold, and a dynamic domain, including a transiently formed helix. The dynamic domain is anchored to the helical scaffold by a secondary hydrophobic core, pinning down the long loops of leptin to the protein body, inducing motional restriction without a well-defined secondary or tertiary hydrogen bond stabilized structure. This dynamic region is well suited for and may be involved in functional allosteric dynamics upon receptor binding.