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

Unveiling Putative Excited State and Transmission of Binding Information in the Fluoride Riboswitch

Riboswitches regulate downstream gene expression by binding to specific small molecules or ions with multiple mechanisms to transfer the binding information. In the case of the fluoride riboswitch, the transcription termination signal is conveyed through a transient excited state (ES). In this work, we performed conventional molecular dynamics (MD) simulations, totaling 180 μs, to obtain the ES structure and investigate the mechanism underlying information transmission in Mg2+/F- binding within the fluoride riboswitch aptamer. The Mg2+/F- binding pocket exhibits various conformations in its apo form. A series of ES structures were extracted from the MD trajectories of the apo form. The dynamics of the Mg2+/F- binding pocket influenced key pair A40-U48 in ES structures. The pathway connecting the binding pocket to the pair involves interactions between the phosphate groups of U7 and G8 and the nucleobases of G8-C47-U48. Our work presents a structural ensemble of the ES and elucidates a pathway for transferring Mg2+/F- binding information, thereby facilitating the understanding of how the holo-like apo state achieves transcriptional repression.

Analysis of proteins in the light of mutations

Proteins have evolved through mutations-amino acid substitutions-since life appeared on Earth, some 109 years ago. The study of these phenomena has been of particular significance because of their impact on protein stability, function, and structure. This study offers a new viewpoint on how the most recent findings in these areas can be used to explore the impact of mutations on protein sequence, stability, and evolvability. Preliminary results indicate that: (1) mutations can be viewed as sensitive probes to identify 'typos' in the amino-acid sequence, and also to assess the resistance of naturally occurring proteins to unwanted sequence alterations; (2) the presence of 'typos' in the amino acid sequence, rather than being an evolutionary obstacle, could promote faster evolvability and, in turn, increase the likelihood of higher protein stability; (3) the mutation site is far more important than the substituted amino acid in terms of the marginal stability changes of the protein, and (4) the unpredictability of protein evolution at the molecular level-by mutations-exists even in the absence of epistasis effects. Finally, the Darwinian concept of evolution "descent with modification" and experimental evidence endorse one of the results of this study, which suggests that some regions of any protein sequence are susceptible to mutations while others are not. This work contributes to our general understanding of protein responses to mutations and may spur significant progress in our efforts to develop methods to accurately forecast changes in protein stability, their propensity for metamorphism, and their ability to evolve.

Integration of a Randomized Sequence Scanning Approach in AlphaFold2 and Local Frustration Profiling of Conformational States Enable Interpretable Atomistic Characterization of Conformational Ensembles and Detection of Hidden Allosteric States in the ABL1 Protein Kinase

Despite the success of AlphaFold methods in predicting single protein structures, these methods showed intrinsic limitations in the characterization of multiple functional conformations of allosteric proteins. The recent NMR-based structural determination of the unbound ABL kinase in the active state and discovery of the inactive low-populated functional conformations that are unique for ABL kinase present an ideal challenge for the AlphaFold2 approaches. In the current study, we employ several adaptations of the AlphaFold2 methodology to predict protein conformational ensembles and allosteric states of the ABL kinase including randomized alanine sequence scanning combined with the multiple sequence alignment subsampling proposed in this study. We show that the proposed new AlphaFold2 adaptation combined with local frustration profiling of conformational states enables accurate prediction of the protein kinase structures and conformational ensembles, also offering a robust approach for interpretable characterization of the AlphaFold2 predictions and detection of hidden allosteric states. We found that the large high frustration residue clusters are uniquely characteristic of the low-populated, fully inactive ABL form and can define energetically frustrated cracking sites of conformational transitions, presenting difficult targets for AlphaFold2. The results of this study uncovered previously unappreciated fundamental connections between local frustration profiles of the functional allosteric states and the ability of AlphaFold2 methods to predict protein structural ensembles of the active and inactive states. This study showed that integration of the randomized sequence scanning adaptation of AlphaFold2 with a robust landscape-based analysis allows for interpretable atomistic predictions and characterization of protein conformational ensembles, providing a physical basis for the successes and limitations of current AlphaFold2 methods in detecting functional allosteric states that play a significant role in protein kinase regulation.

Validating the 15N-1H HSQC-ROESY experiment for detecting 1HN exchange broadening in proteated proteins

It is advantageous to investigate milli-to-micro-second conformational exchange data contained in the solution NMR protein relaxation data other than 15N nuclei. Not only does one search under another lamp post, one also looks at dynamics at other time scales. The HSQC-ROESY 1HN relaxation dispersion experiment for amide protons as introduced by Ishima, et al (1998). J. Am. Soc. 120, 10534-10542, is such an experiment, but has by the authors been advised to only be used for perdeuterated proteins to avoid complication with the 1H-1H multiple-spin effects. This is regretful, since not all proteins can be perdeuterated. Here we analyze in detail the 1HN relaxation terms for this experiment for a fully proteated protein. Indeed, the 1HN relaxation theory is in this case complex and includes dipolar-dipolar relaxation interference and TOCSY transfers. With simulate both of these effects and show that the interference can be exploited for detecting exchange broadening. The TOCSY effect is shown to minor, and when it is not, a solution is provided. We apply the HSQC-ROESY experiment, with a small modification to suppress ROESY crosspeaks, to a 7 kDa GB1 protein that is just 15N and 13C labeled. At 10 °C we cannot detect any conformational exchange broadening: the 1HN R2 relaxation rates with 1.357 kHz spinlock field not larger than those recorded with a 12.136 kHz spinlock field. This means that there is no exchange broadening that can be differentially suppressed with the applied fields. Either there is no broadening, or the broadening is effectively suppressed by all fields, or the broadening cannot be suppressed by either of the fields. While initially this seems to be a disappointing result, we feel that this work establishes that the HSQC-ROESY experiment is very robust. It can indeed be utilized for proteated proteins upto about 30 kDa. This could be opening the study the milli-microsecond conformational dynamics as reported by 1HN exchange broadening for many more proteins.

Prediction of Conformational Ensembles and Structural Effects of State-Switching Allosteric Mutants in the Protein Kinases Using Comparative Analysis of AlphaFold2 Adaptations with Sequence Masking and Shallow Subsampling

Despite the success of AlphaFold2 approaches in predicting single protein structures, these methods showed intrinsic limitations in predicting multiple functional conformations of allosteric proteins and have been challenged to accurately capture of the effects of single point mutations that induced significant structural changes. We systematically examined several implementations of AlphaFold2 methods to predict conformational ensembles for state-switching mutants of the ABL kinase. The results revealed that a combination of randomized alanine sequence masking with shallow multiple sequence alignment subsampling can significantly expand the conformational diversity of the predicted structural ensembles and capture shifts in populations of the active and inactive ABL states. Consistent with the NMR experiments, the predicted conformational ensembles for M309L/L320I and M309L/H415P ABL mutants that perturb the regulatory spine networks featured the increased population of the fully closed inactive state. On the other hand, the predicted conformational ensembles for the G269E/M309L/T334I and M309L/L320I/T334I triple ABL mutants that share activating T334I gate-keeper substitution are dominated by the active ABL form. The proposed adaptation of AlphaFold can reproduce the experimentally observed mutation-induced redistributions in the relative populations of the active and inactive ABL states and capture the effects of regulatory mutations on allosteric structural rearrangements of the kinase domain. The ensemble-based network analysis complemented AlphaFold predictions by revealing allosteric mediating centers that often directly correspond to state-switching mutational sites or reside in their immediate local structural proximity, which may explain the global effect of regulatory mutations on structural changes between the ABL states. This study suggested that attention-based learning of long-range dependencies between sequence positions in homologous folds and deciphering patterns of allosteric interactions may further augment the predictive abilities of AlphaFold methods for modeling of alternative protein sates, conformational ensembles and mutation-induced structural transformations.

Identifying protein conformational states in the Protein Data Bank: Toward unlocking the potential of integrative dynamics studies

Studying protein dynamics and conformational heterogeneity is crucial for understanding biomolecular systems and treating disease. Despite the deposition of over 215 000 macromolecular structures in the Protein Data Bank and the advent of AI-based structure prediction tools such as AlphaFold2, RoseTTAFold, and ESMFold, static representations are typically produced, which fail to fully capture macromolecular motion. Here, we discuss the importance of integrating experimental structures with computational clustering to explore the conformational landscapes that manifest protein function. We describe the method developed by the Protein Data Bank in Europe - Knowledge Base to identify distinct conformational states, demonstrate the resource's primary use cases, through examples, and discuss the need for further efforts to annotate protein conformations with functional information. Such initiatives will be crucial in unlocking the potential of protein dynamics data, expediting drug discovery research, and deepening our understanding of macromolecular mechanisms.

Dominant negative mutations in yeast Hsp90 reveal triage decision mechanism targeting client proteins for degradation

Most of the fundamental processes of cells are mediated by proteins. However, the biologically-relevant mechanism of most proteins are poorly understood. Dominant negative mutations have provided a valuable tool for investigating protein mechanisms but can be difficult to isolate because of their toxic effects. We used a mutational scanning approach to identify dominant negative mutations in yeast Hsp90. Hsp90 is a chaperone that forms dynamic complexes with many co-chaperones and client proteins. In vitro analyses have elucidated some key biochemical states and structures of Hsp90, co-chaperones, and clients; however, the biological mechanism of Hsp90 remains unclear. For example, high throughput studies have found that many E3 ubiquitin ligases bind to Hsp90, but it is unclear if these are primarily clients or acting to tag other clients for degradation. We introduced a library of all point mutations in the ATPase domain of Hsp90 into yeast and noticed that 176 were more than 10-fold depleted at the earliest point that we could analyze. There were two hot spot regions of the depleted mutations that were located at the hinges of a loop that closes over ATP. We quantified the dominant negative growth effects of mutations in the hinge regions using a library of mutations driven by an inducible promoter. We analyzed individual dominant negative mutations in detail and found that addition of the E33A mutation that prevents ATP hydrolysis by Hsp90 abrogated the dominant negative phenotype. Pull-down experiments did not reveal any stable binding partners, indicating that the dominant effects were mediated by dynamic complexes. DN Hsp90 decreased the expression level of two model Hsp90 clients, glucocorticoid receptor (GR) and v-src kinase. Using MG132, we found that GR was rapidly destabilized in a proteasome-dependent fashion. These findings provide evidence that the binding of E3 ligases to Hsp90 may serve a quality control function fundamental to eukaryotes.

Contributions of Hyperactive Mutations in Mpro from SARS-CoV-2 to Drug Resistance

The appearance and spread of mutations that cause drug resistance in rapidly evolving diseases, including infections by the SARS-CoV-2 virus, are major concerns for human health. Many drugs target enzymes, and resistance-conferring mutations impact inhibitor binding or enzyme activity. Nirmatrelvir, the most widely used inhibitor currently used to treat SARS-CoV-2 infections, targets the main protease (Mpro) preventing it from processing the viral polyprotein into active subunits. Our previous work systematically analyzed resistance mutations in Mpro that reduce binding to inhibitors; here, we investigate mutations that affect enzyme function. Hyperactive mutations that increase Mpro activity can contribute to drug resistance but have not been thoroughly studied. To explore how hyperactive mutations contribute to resistance, we comprehensively assessed how all possible individual mutations in Mpro affect enzyme function using a mutational scanning approach with a fluorescence resonance energy transfer (FRET)-based yeast readout. We identified hundreds of mutations that significantly increased the Mpro activity. Hyperactive mutations occurred both proximal and distal to the active site, consistent with protein stability and/or dynamics impacting activity. Hyperactive mutations were observed 3 times more than mutations which reduced apparent binding to nirmatrelvir in recent studies of laboratory-grown viruses selected for drug resistance. Hyperactive mutations were also about three times more prevalent than nirmatrelvir binding mutations in sequenced isolates from circulating SARS-CoV-2. Our findings indicate that hyperactive mutations are likely to contribute to the natural evolution of drug resistance in Mpro and provide a comprehensive list for future surveillance efforts.

Temporal Resolution of Activity-Related Solvation Dynamics in the TIM Barrel Enzyme Murine Adenosine Deaminase

Murine adenosine deaminase (mADA) is a prototypic system for studying the thermal activation of active site chemistry within the TIM barrel family of enzyme reactions. Previous temperature-dependent hydrogen deuterium exchange studies under various conditions have identified interconnected thermal networks for heat transfer from opposing protein-solvent interfaces to active site residues in mADA. One of these interfaces contains a solvent exposed helix-loop-helix moiety that presents the hydrophobic face of its long α-helix to the backside of bound substrate. Herein we pursue the time and temperature dependence of solvation dynamics at the surface of mADA, for comparison to established kinetic parameters that represent active site chemistry. We first created a modified protein devoid of native tryptophans with close to native kinetic behavior. Single site-specific tryptophan mutants were back inserted into each of the four positions where native tryptophans reside. Measurements of nanosecond fluorescence relaxation lifetimes and Stokes shift decays, that reflect time dependent environmental reoroganization around the photo-excited state of Trp*, display minimal temperature dependences. These regions serve as controls for the behavior of a new single tryptophan inserted into a solvent exposed region near the helix-loop-helix moiety located behind the bound substrate, Lys54Trp. This installed Trp displays a significantly elevated value for Ea ( k Stokes shift ) ; further, when Phe61 within the long helix positioned behind bound substrate is replaced by a series of aliphatic hydrophobic side chains, the trends in Ea ( k Stokes shift ) mirror the earlier reported impact of the same series of function-altering hydrophobic side chains on the activation energy of catalysis, Ea ( k cat ) .The reported experimental findings implicate a solvent initiated and rapid (>ns) protein restructuring that contributes to the enthalpic activation barrier to catalysis in mADA.

Optimization of TROSY- and anti-TROSY-based 15N CPMG relaxation dispersion experiments through phase cycling

CPMG relaxation dispersion studies of biomolecular dynamics on the μs-ms timescale can provide detailed kinetic, thermodynamic, and structural insights into function. Frequently, the 15N spin serves as the probe of choice, as uniform incorporation of the 15N isotope is facile and cost-effective, and the interpretation of the resulting data is often relatively straightforward. In conventional CPMG relaxation dispersion experiments the application of CPMG pulses with constant radiofrequency (RF) phase can lead to artifactual dispersion profiles that result from off-resonance effects, RF field inhomogeneity, and pulse miscalibration. The development of CPMG experiments with the [0013]-phase cycle has significantly reduced the impact of pulse imperfections over a greater bandwidth of frequency offsets in comparison to constant phase experiments. Application of 15N-TROSY-based CPMG schemes to studies of the dynamics of large molecules is necessary for high sensitivity, yet the correct incorporation of the [0013]-phase cycle is non-trivial. Here we present TROSY- and anti-TROSY-based 15N CPMG experiments with the [0013]-phase cycling scheme and demonstrate, through comprehensive numerical simulations and experimental validation, enhanced resistance to pulse imperfections relative to traditional schemes utilizing constant phase CPMG pulses. Notably, exchange parameters derived from the new experiments are in good agreement with those obtained using other, more established, 15N-based CPMG approaches.

Switching Go̅-Martini for Investigating Protein Conformational Transitions and Associated Protein-Lipid Interactions

Proteins are dynamic biomolecules that can transform between different conformational states when exerting physiological functions, which is difficult to simulate using all-atom methods. Coarse-grained (CG) Go̅-like models are widely used to investigate large-scale conformational transitions, which usually adopt implicit solvent models and therefore cannot explicitly capture the interaction between proteins and surrounding molecules, such as water and lipid molecules. Here, we present a new method, named Switching Go̅-Martini, to simulate large-scale protein conformational transitions between different states, based on the switching Go̅ method and the CG Martini 3 force field. The method is straightforward and efficient, as demonstrated by the benchmarking applications for multiple protein systems, including glutamine binding protein (GlnBP), adenylate kinase (AdK), and β2-adrenergic receptor (β2AR). Moreover, by employing the Switching Go̅-Martini method, we can not only unveil the conformational transition from the E2Pi-PL state to E1 state of the type 4 P-type ATPase (P4-ATPase) flippase ATP8A1-CDC50 but also provide insights into the intricate details of lipid transport.

Sensitivity-enhanced NMR 15N R1 and R1ρ relaxation experiments for the investigation of intrinsically disordered proteins at high magnetic fields

NMR relaxation experiments provide residue-specific insights into the structural dynamics of proteins. Here, we present an optimized set of sensitivity-enhanced 15N R1 and R1ρ relaxation experiments applicable to fully protonated proteins. The NMR pulse sequences are conceptually similar to the set of TROSY-based sequences and their HSQC counterpart (Lakomek et al., J. Biomol. NMR 2012). Instead of the TROSY read-out scheme, a sensitivity-enhanced HSQC read-out scheme is used, with improved and easier optimized water suppression. The presented pulse sequences are applied on the cytoplasmic domain of the SNARE protein Synpatobrevin-2 (Syb-2), which is intrinsically disordered in its monomeric pre-fusion state. A two-fold increase in the obtained signal-to-noise ratio is observed for this intrinsically disordered protein, therefore offering a four-fold reduction of measurement time compared to the TROSY-detected version. The inter-scan recovery delay can be shortened to two seconds. Pulse sequences were tested at 600 MHz and 1200 MHz 1H Larmor frequency, thus applicable over a wide magnetic field range. A comparison between protonated and deuterated protein samples reveals high agreement, indicating that reliable 15N R1 and R1ρ rate constants can be extracted for fully protonated and deuterated samples. The presented pulse sequences will benefit not only for IDPs but also for an entire range of low and medium-sized proteins.

A unified view on enzyme catalysis by cryo-EM study of a DNA topoisomerase

The theories for substrate recognition in enzyme catalysis have evolved from lock-key to induced fit, then conformational selection, and conformational selection followed by induced fit. However, the prevalence and consensus of these theories require further examination. Here we use cryogenic electron microscopy and African swine fever virus type 2 topoisomerase (AsfvTop2) to demonstrate substrate binding theories in a joint and ordered manner: catalytic selection by the enzyme, conformational selection by the substrates, then induced fit. The apo-AsfvTop2 pre-exists in six conformers that comply with the two-gate mechanism directing DNA passage and release in the Top2 catalytic cycle. The structures of AsfvTop2-DNA-inhibitor complexes show that substantial induced-fit changes occur locally from the closed apo-conformer that however is too far-fetched for the open apo-conformer. Furthermore, the ATPase domain of AsfvTop2 in the MgAMP-PNP-bound crystal structures coexist in reduced and oxidized forms involving a disulfide bond, which can regulate the AsfvTop2 function.

Interpretable Atomistic Prediction and Functional Analysis of Conformational Ensembles and Allosteric States in Protein Kinases Using AlphaFold2 Adaptation with Randomized Sequence Scanning and Local Frustration Profiling

The groundbreaking achievements of AlphaFold2 (AF2) approaches in protein structure modeling marked a transformative era in structural biology. Despite the success of AF2 tools in predicting single protein structures, these methods showed intrinsic limitations in predicting multiple functional conformations of allosteric proteins and fold-switching systems. The recent NMR-based structural determination of the unbound ABL kinase in the active state and two inactive low-populated functional conformations that are unique for ABL kinase presents an ideal challenge for AF2 approaches. In the current study we employ several implementations of AF2 methods to predict protein conformational ensembles and allosteric states of the ABL kinase including (a) multiple sequence alignments (MSA) subsampling approach; (b) SPEACH_AF approach in which alanine scanning is performed on generated MSAs; and (c) introduced in this study randomized full sequence mutational scanning for manipulation of sequence variations combined with the MSA subsampling. We show that the proposed AF2 adaptation combined with local frustration mapping of conformational states enable accurate prediction of the ABL active and intermediate structures and conformational ensembles, also offering a robust approach for interpretable characterization of the AF2 predictions and limitations in detecting hidden allosteric states. We found that the large high frustration residue clusters are uniquely characteristic of the low-populated, fully inactive ABL form and can define energetically frustrated cracking sites of conformational transitions, presenting difficult targets for AF2 methods. This study uncovered previously unappreciated, fundamental connections between distinct patterns of local frustration in functional kinase states and AF2 successes/limitations in detecting low-populated frustrated conformations, providing a better understanding of benefits and limitations of current AF2-based adaptations in modeling of conformational ensembles.

What can molecular assembly learn from catalysed assembly in living organisms?

Molecular assembly is the process of organizing individual molecules into larger structures and complex systems. The self-assembly approach is predominantly utilized in creating artificial molecular assemblies, and was believed to be the primary mode of molecular assembly in living organisms as well. However, it has been shown that the assembly of many biological complexes is "catalysed" by other molecules, rather than relying solely on self-assembly. In this review, we summarize these catalysed-assembly (catassembly) phenomena in living organisms and systematically analyse their mechanisms. We then expand on these phenomena and discuss related concepts, including catalysed-disassembly and catalysed-reassembly. Catassembly proves to be an efficient and highly selective strategy for synergistically controlling and manipulating various noncovalent interactions, especially in hierarchical molecular assemblies. Overreliance on self-assembly may, to some extent, hinder the advancement of artificial molecular assembly with powerful features. Furthermore, inspired by the biological catassembly phenomena, we propose guidelines for designing artificial catassembly systems and developing characterization and theoretical methods, and review pioneering works along this new direction. Overall, this approach may broaden and deepen our understanding of molecular assembly, enabling the construction and control of intelligent assembly systems with advanced functionality.

Bonds and bytes: The odyssey of structural biology

Characterizing structural and dynamic properties of proteins and large macromolecular assemblies is crucial to understand the molecular mechanisms underlying biological functions. In the field of structural biology, no single method comprehensively reveals the behavior of biological systems across various spatiotemporal scales. Instead, we have a versatile toolkit of techniques, each contributing a piece to the overall puzzle. Integrative structural biology combines different techniques to create accurate and precise multi-scale models that expand our understanding of complex biological systems. This review outlines recent advancements in computational and experimental methods in structural biology, with special focus on recent Artificial Intelligence techniques, emphasizes integrative approaches that combine different types of data for precise spatiotemporal modeling, and provides an outlook into future directions of this field.

An RNA excited conformational state at atomic resolution

Sparse and short-lived excited RNA conformational states are essential players in cell physiology, disease, and therapeutic development, yet determining their 3D structures remains challenging. Combining mutagenesis, NMR spectroscopy, and computational modeling, we determined the 3D structural ensemble formed by a short-lived (lifetime ~2.1 ms) lowly-populated (~0.4%) conformational state in HIV-1 TAR RNA. Through a strand register shift, the excited conformational state completely remodels the 3D structure of the ground state (RMSD from the ground state = 7.2 ± 0.9 Å), forming a surprisingly more ordered conformational ensemble rich in non-canonical mismatches. The structure impedes the formation of the motifs recognized by Tat and the super elongation complex, explaining why this alternative TAR conformation cannot activate HIV-1 transcription. The ability to determine the 3D structures of fleeting RNA states using the presented methodology holds great promise for our understanding of RNA biology, disease mechanisms, and the development of RNA-targeting therapeutics.

Rapidly determining the 3D structure of proteins by surface-enhanced Raman spectroscopy

Despite great advances in protein structure analysis, label-free and ultrasensitive methods to obtain the natural and dynamic three-dimensional (3D) structures are still urgently needed. Surface-enhanced Raman spectroscopy (SERS) can be a good candidate, whereas the complexity originated from the interactions between the protein and the gradient surface electric field makes it extremely challenging to determine the protein structure. Here, we propose a deciphering strategy for accurate determination of 3D protein structure from experimental SERS spectra in seconds by simply summing SERS spectra of isolated amino acids in electric fields of different strength with their orientations in protein. The 3D protein structure can be reconstructed by comparing the experimental spectra obtained in a well-defined gap-mode SERS configuration with the simulated spectra. The gradient electric field endows SERS with a unique advantage to section biomolecules with atomic precision, which makes SERS a competent tool for monitoring biomolecular events under physiological conditions.

Tuning sterol extraction kinetics yields a renal-sparing polyene antifungal

Decades of previous efforts to develop renal-sparing polyene antifungals were misguided by the classic membrane permeabilization model1. Recently, the clinically vital but also highly renal-toxic small-molecule natural product amphotericin B was instead found to kill fungi primarily by forming extramembraneous sponge-like aggregates that extract ergosterol from lipid bilayers2-6. Here we show that rapid and selective extraction of fungal ergosterol can yield potent and renal-sparing polyene antifungals. Cholesterol extraction was found to drive the toxicity of amphotericin B to human renal cells. Our examination of high-resolution structures of amphotericin B sponges in sterol-free and sterol-bound states guided us to a promising structural derivative that does not bind cholesterol and is thus renal sparing. This derivative was also less potent because it extracts ergosterol more slowly. Selective acceleration of ergosterol extraction with a second structural modification yielded a new polyene, AM-2-19, that is renal sparing in mice and primary human renal cells, potent against hundreds of pathogenic fungal strains, resistance evasive following serial passage in vitro and highly efficacious in animal models of invasive fungal infections. Thus, rational tuning of the dynamics of interactions between small molecules may lead to better treatments for fungal infections that still kill millions of people annually7,8 and potentially other resistance-evasive antimicrobials, including those that have recently been shown to operate through supramolecular structures that target specific lipids9.

Kinetic Resolution of the Atomic 3D Structures Formed by Ground and Excited Conformational States in an RNA Dynamic Ensemble

Knowing the 3D structures formed by the various conformations populating the RNA free-energy landscape, their relative abundance, and kinetic interconversion rates is required to obtain a quantitative and predictive understanding of how RNAs fold and function at the atomic level. While methods integrating ensemble-averaged experimental data with computational modeling are helping define the most abundant conformations in RNA ensembles, elucidating their kinetic rates of interconversion and determining the 3D structures of sparsely populated short-lived RNA excited conformational states (ESs) remains challenging. Here, we developed an approach integrating Rosetta-FARFAR RNA structure prediction with NMR residual dipolar couplings and relaxation dispersion that simultaneously determines the 3D structures formed by the ground-state (GS) and ES subensembles, their relative abundance, and kinetic rates of interconversion. The approach is demonstrated on HIV-1 TAR, whose six-nucleotide apical loop was previously shown to form a sparsely populated (∼13%) short-lived (lifetime ∼ 45 μs) ES. In the GS, the apical loop forms a broad distribution of open conformations interconverting on the pico-to-nanosecond time scale. Most residues are unpaired and preorganized to bind the Tat-superelongation protein complex. The apical loop zips up in the ES, forming a narrow distribution of closed conformations, which sequester critical residues required for protein recognition. Our work introduces an approach for determining the 3D ensemble models formed by sparsely populated RNA conformational states, provides a rare atomic view of an RNA ES, and kinetically resolves the atomic 3D structures of RNA conformational substates, interchanging on time scales spanning 6 orders of magnitude, from picoseconds to microseconds.

Intrinsic structural dynamics dictate enzymatic activity and inhibition

Enzymes are known to sample various conformations, many of which are critical for their biological function. However, structural characterizations of enzymes predominantly focus on the most populated conformation. As a result, single-point mutations often produce structures that are similar or essentially identical to those of the wild-type enzyme despite large changes in enzymatic activity. Here, we show for mutants of a histone deacetylase enzyme (HDAC8) that reduced enzymatic activities, reduced inhibitor affinities, and reduced residence times are all captured by the rate constants between intrinsically sampled conformations that, in turn, can be obtained independently by solution NMR spectroscopy. Thus, for the HDAC8 enzyme, the dynamic sampling of conformations dictates both enzymatic activity and inhibitor potency. Our analysis also dissects the functional role of the conformations sampled, where specific conformations distinct from those in available structures are responsible for substrate and inhibitor binding, catalysis, and product dissociation. Precise structures alone often do not adequately explain the effect of missense mutations on enzymatic activity and drug potency. Our findings not only assign functional roles to several conformational states of HDAC8 but they also underscore the paramount role of dynamics, which will have general implications for characterizing missense mutations and designing inhibitors.

Pathfinder: Protein folding pathway prediction based on conformational sampling

The study of protein folding mechanism is a challenge in molecular biology, which is of great significance for revealing the movement rules of biological macromolecules, understanding the pathogenic mechanism of folding diseases, and designing protein engineering materials. Based on the hypothesis that the conformational sampling trajectory contain the information of folding pathway, we propose a protein folding pathway prediction algorithm named Pathfinder. Firstly, Pathfinder performs large-scale sampling of the conformational space and clusters the decoys obtained in the sampling. The heterogeneous conformations obtained by clustering are named seed states. Then, a resampling algorithm that is not constrained by the local energy basin is designed to obtain the transition probabilities of seed states. Finally, protein folding pathways are inferred from the maximum transition probabilities of seed states. The proposed Pathfinder is tested on our developed test set (34 proteins). For 11 widely studied proteins, we correctly predicted their folding pathways and specifically analyzed 5 of them. For 13 proteins, we predicted their folding pathways to be further verified by biological experiments. For 6 proteins, we analyzed the reasons for the low prediction accuracy. For the other 4 proteins without biological experiment results, potential folding pathways were predicted to provide new insights into protein folding mechanism. The results reveal that structural analogs may have different folding pathways to express different biological functions, homologous proteins may contain common folding pathways, and α-helices may be more prone to early protein folding than β-strands.

New Insights into the Cooperativity and Dynamics of Dimeric Enzymes

A survey of protein databases indicates that the majority of enzymes exist in oligomeric forms, with about half of those found in the UniProt database being homodimeric. Understanding why many enzymes are in their dimeric form is imperative. Recent developments in experimental and computational techniques have allowed for a deeper comprehension of the cooperative interactions between the subunits of dimeric enzymes. This review aims to succinctly summarize these recent advancements by providing an overview of experimental and theoretical methods, as well as an understanding of cooperativity in substrate binding and the molecular mechanisms of cooperative catalysis within homodimeric enzymes. Focus is set upon the beneficial effects of dimerization and cooperative catalysis. These advancements not only provide essential case studies and theoretical support for comprehending dimeric enzyme catalysis but also serve as a foundation for designing highly efficient catalysts, such as dimeric organic catalysts. Moreover, these developments have significant implications for drug design, as exemplified by Paxlovid, which was designed for the homodimeric main protease of SARS-CoV-2.

Design of stimulus-responsive two-state hinge proteins

In nature, proteins that switch between two conformations in response to environmental stimuli structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Designing proteins with two distinct but fully structured conformations is a challenge for protein design as it requires sculpting an energy landscape with two distinct minima. Here we describe the design of "hinge" proteins that populate one designed state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, double electron-electron resonance spectroscopy, and binding measurements demonstrate that despite the significant structural differences the two states are designed with atomic level accuracy and that the conformational and binding equilibria are closely coupled.

Insights into Enzymatic Catalysis from Binding and Hydrolysis of Diadenosine Tetraphosphate by E. coli Adenylate Kinase

Adenylate kinases play a crucial role in cellular energy homeostasis through the interconversion of ATP, AMP, and ADP in all living organisms. Here, we explore how adenylate kinase (AdK) from Escherichia coli interacts with diadenosine tetraphosphate (AP4A), a putative alarmone associated with transcriptional regulation, stress, and DNA damage response. From a combination of EPR and NMR spectroscopy together with X-ray crystallography, we found that AdK interacts with AP4A with two distinct modes that occur on disparate time scales. First, AdK dynamically interconverts between open and closed states with equal weights in the presence of AP4A. On a much slower time scale, AdK hydrolyses AP4A, and we suggest that the dynamically accessed substrate-bound open AdK conformation enables this hydrolytic activity. The partitioning of the enzyme into open and closed states is discussed in relation to a recently proposed linkage between active site dynamics and collective conformational dynamics.

Protein folding rate evolution upon mutations

Despite the spectacular success of cutting-edge protein fold prediction methods, many critical questions remain unanswered, including why proteins can reach their native state in a biologically reasonable time. A satisfactory answer to this simple question could shed light on the slowest folding rate of proteins as well as how mutations-amino-acid substitutions and/or post-translational modifications-might affect it. Preliminary results indicate that (i) Anfinsen's dogma validity ensures that proteins reach their native state on a reasonable timescale regardless of their sequence or length, and (ii) it is feasible to determine the evolution of protein folding rates without accounting for epistasis effects or the mutational trajectories between the starting and target sequences. These results have direct implications for evolutionary biology because they lay the groundwork for a better understanding of why, and to what extent, mutations-a crucial element of evolution and a factor influencing it-affect protein evolvability. Furthermore, they may spur significant progress in our efforts to solve crucial structural biology problems, such as how a sequence encodes its folding.

Experimental Insights into Conformational Ensembles of Assembled β-Sheet Peptides

Deciphering the conformations and interactions of peptides in their assemblies offers a basis for guiding the rational design of peptide-assembled materials. Here we report the use of scanning tunneling microscopy (STM), a single-molecule imaging method with a submolecular resolution, to distinguish 18 types of coexisting conformational substates of the β-strand of the 8-37 segment of human islet amyloid polypeptide (hIAPP 8-37). We analyzed the pairwise peptide-peptide interactions in the hIAPP 8-37 assembly and found 82 interconformation interactions within a free energy difference of 3.40 k_BT. Besides hIAPP 8-37, this STM method validates the existence of multiple conformations of other β-sheet peptide assemblies, including mutated hIAPP 8-37 and amyloid-β 42. Overall, the results reported in this work provide single-molecule experimental insights into the conformational ensemble and interpeptide interactions in the β-sheet peptide assembly.

Single-molecule visualization determines conformational substate ensembles in β-sheet-rich peptide fibrils

An understanding of protein conformational ensembles is essential for revealing the underlying mechanisms of interpeptide recognition and association. However, experimentally resolving multiple simultaneously existing conformational substates remains challenging. Here, we report the use of scanning tunneling microscopy (STM) to analyze the conformational substate ensembles of β sheet peptides with a submolecular resolution (in-plane <2.6 Å). We observed ensembles of more than 10 conformational substates (with free energy fluctuations between several k_BTs) in peptide homoassemblies of keratin (KRT) and amyloidal peptides (-5Aβ42 and TDP-43 341-357). Furthermore, STM reveals a change in the conformational ensemble of peptide mutants, which is correlated with the macroscopic properties of peptide assemblies. Our results demonstrate that the STM-based single-molecule imaging can capture a thorough picture of the conformational substates with which to build an energetic landscape of interconformational interactions and can rapidly screen conformational ensembles, which can complement conventional characterization techniques.

Reduced dynamic complexity allows structure elucidation of an excited state of KRASG13D

Localized dynamics of RAS, including regions distal to the nucleotide-binding site, is of high interest for elucidating the mechanisms by which RAS proteins interact with effectors and regulators and for designing inhibitors. Among several oncogenic mutants, methyl relaxation dispersion experiments reveal highly synchronized conformational dynamics in the active (GMPPNP-bound) KRAS^G13D, which suggests an exchange between two conformational states in solution. Methyl and ³¹P NMR spectra of active KRAS^G13D in solution confirm a two-state ensemble interconverting on the millisecond timescale, with a major P^γ atom peak corresponding to the dominant State 1 conformation and a secondary peak indicating an intermediate state different from the known State 2 conformation recognized by RAS effectors. High-resolution crystal structures of active KRAS^G13D and KRAS^G13D-RAF1 RBD complex provide snapshots of the State 1 and 2 conformations, respectively. We use residual dipolar couplings to solve and cross-validate the structure of the intermediate state of active KRAS^G13D, showing a conformation distinct from those of States 1 and 2 outside the known flexible switch regions. The dynamic coupling between the conformational exchange in the effector lobe and the breathing motion in the allosteric lobe is further validated by a secondary mutation in the allosteric lobe, which affects the conformational population equilibrium.

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.

Paramagnetic NMR restraints for the characterization of protein structural rearrangements

Mobility is a common feature of biomacromolecules, often fundamental for their function. Thus, in many cases, biomacromolecules cannot be described by a single conformation, but rather by a conformational ensemble. NMR paramagnetic data demonstrated quite informative to monitor this conformational variability, especially when used in conjunction with data from different sources. Due to their long-range nature, paramagnetic data can, for instance, i) clearly demonstrate the occurrence of conformational rearrangements, ii) reveal the presence of minor conformational states, sampled only for a short time, iii) indicate the most representative conformations within the conformational ensemble sampled by the molecule, iv) provide an upper limit to the weight of each conformation.

Protein Dynamics and Enzymatic Catalysis

This Perspective presents a review of our work and that of others in the highly controversial topic of the coupling of protein dynamics to reaction in enzymes. We have been involved in studying this topic for many years. Thus, this perspective will naturally present our own views, but it also is designed to present an overview of the variety of viewpoints of this topic, both experimental and theoretical. This is obviously a large and contentious topic.

Rigidified and Hydrophilic DOTA-like Lanthanoid Ligands: Design, Synthesis, and Dynamic Properties

Limiting the dynamics of paramagnetic tags is crucial for the accuracy of the structural information derived from paramagnetic nuclear magnetic resonance (NMR) experiments. A hydrophilic rigid 2,2',2″,2‴-(1,4,7,10-tetraazacyclododecane-1,4,7,10-tetrayl)tetraacetic acid (DOTA)-like lanthanoid complex was designed and synthesized following a strategy that allows the incorporation of two sets of two adjacent substituents. This resulted in a C₂ symmetric hydrophilic and rigid macrocyclic ring, featuring four chiral hydroxyl-methylene substituents. NMR spectroscopy was used to investigate the conformational dynamics of the novel macrocycle upon complexation with europium and compared to DOTA and its derivatives. The twisted square antiprismatic and square antiprismatic conformers coexist, but the former is favored, which is different from DOTA. Two-dimensional ¹H exchange spectroscopy shows that ring flipping of the cyclen-ring is suppressed due to the presence of the four chiral equatorial hydroxyl-methylene substituents at proximate positions. The reorientation of the pendant arms causes conformational exchange between two conformers. The reorientation of the coordination arms is slower when the ring flipping is suppressed. This indicates that these complexes are suitable scaffolds to develop rigid probes for paramagnetic NMR of proteins. Due to their hydrophilic nature, it is anticipated that they are less likely to cause protein precipitation than their more hydrophobic counterparts.

Designer Nanodiscs to Probe and Reprogram Membrane Biology in Synapses

Signal transduction at the synapse is mediated by a variety of protein-lipid interactions, which are vital for the spatial and temporal regulation of synaptic vesicle biogenesis, neurotransmitter release, and postsynaptic receptor activation. Therefore, our understanding of synaptic transmission cannot be completed until the elucidation of these critical protein-lipid interactions. On this front, recent advances in nanodiscs have vastly expanded our ability to probe and reprogram membrane biology in synapses. Here, we summarize the progress of the nanodisc toolbox and discuss future directions in this exciting field.

The lens epithelium as a major determinant in the development, maintenance, and regeneration of the crystalline lens

The crystalline lens is a transparent and refractive biconvex structure formed by lens epithelial cells (LECs) and lens fibers. Lens opacity, also known as cataracts, is the leading cause of blindness in the world. LECs are the principal cells of lens throughout human life, exhibiting different physiological properties and functions. During the embryonic stage, LECs proliferate and differentiate into lens fibers, which form the crystalline lens. Genetics and environment are vital factors that influence normal lens development. During maturation, LECs help maintain lens homeostasis through material transport, synthesis and metabolism as well as mitosis and proliferation. If disturbed, this will result in loss of lens transparency. After cataract surgery, the repair potential of LECs is activated and the structure and transparency of the regenerative tissue depends on postoperative microenvironment. This review summarizes recent research advances on the role of LECs in lens development, homeostasis, and regeneration, with a particular focus on the role of cholesterol synthesis (eg., lanosterol synthase) in lens development and homeostasis maintenance, and how the regenerative potential of LECs can be harnessed to develop surgical strategies and improve the outcomes of cataract surgery (Fig. 1). These new insights suggest that LECs are a major determinant of the physiological and pathological state of the lens. Further studies on their molecular biology will offer possibility to explore new approaches for cataract prevention and treatment.

Proteins turn "Proteans" - The over 40-year delayed paradigm shift in structural biology: From "native proteins in uniquely defined configurations" to "intrinsically disordered proteins"

The current millennium brought up a revolutionary paradigm shift in molecular biology: many operative proteins, rather than being quasi-rigid polypeptide chains folded into unique configurations - as believed throughout most of the past century - are now known to be intrinsically disordered, dynamic, pleomorphic, and multifunctional structures with stochastic behaviors. Yet, part of this knowledge, including suggestions about possible mechanisms and plenty of evidence for the same, became available by the 1950s and 1960s to remain then nearly forgotten for over 40 years. Here, we review the main steps toward the classic notions about protein structures, as well as the neglected precedents of present views, discuss possible explanations for such long oblivion, and offer a sketch of the current panorama in this field.

Protein dynamics: The future is bright and complicated!

Biological life depends on motion, and this manifests itself in proteins that display motion over a formidable range of time scales spanning from femtoseconds vibrations of atoms at enzymatic transition states, all the way to slow domain motions occurring on micro to milliseconds. An outstanding challenge in contemporary biophysics and structural biology is a quantitative understanding of the linkages among protein structure, dynamics, and function. These linkages are becoming increasingly explorable due to conceptual and methodological advances. In this Perspective article, we will point toward future directions of the field of protein dynamics with an emphasis on enzymes. Research questions in the field are becoming increasingly complex such as the mechanistic understanding of high-order interaction networks in allosteric signal propagation through a protein matrix, or the connection between local and collective motions. In analogy to the solution to the "protein folding problem," we argue that the way forward to understanding these and other important questions lies in the successful integration of experiment and computation, while utilizing the present rapid expansion of sequence and structure space. Looking forward, the future is bright, and we are in a period where we are on the doorstep to, at least in part, comprehend the importance of dynamics for biological function.

Optimizing frequency sampling in CEST experiments

For the past decade chemical exchange saturation transfer (CEST) experiments have been successfully applied to study exchange processes in biomolecules involving sparsely populated, transiently formed conformers. Initial implementations focused on extensive sampling of the CEST frequency domain, requiring significant measurement times. Here we show that the lengthy sampling schemes often used are not optimal and that reduced frequency sampling schedules can be developed without a priori knowledge of the exchange parameters, that only depend on the chosen B₁ field, and, to a lesser extent, on the intrinsic transverse relaxation rates of ground state spins. The reduced sampling approach described here can be used synergistically with other methods for reducing measurement times such as those that excite multiple frequencies in the CEST dimension simultaneously, or make use of non-uniform sampling of indirectly detected time domains, to further decrease measurement times. The proposed approach is validated by analysis of simulated and experimental datasets.

Correlation coefficient-directed label-free characterization of native proteins by surface-enhanced Raman spectroscopy

Investigation of proteins in their native state is the core of proteomics towards better understanding of their structures and functions. Surface-enhanced Raman spectroscopy (SERS) has shown its unique advantages in protein characterization with fingerprint information and high sensitivity, which makes it a promising tool for proteomics. It is still challenging to obtain SERS spectra of proteins in the native state and evaluate the native degree. Here, we constructed 3D physiological hotspots for a label-free dynamic SERS characterization of a native protein with iodide-modified 140 nm Au nanoparticles. We further introduced the correlation coefficient to quantitatively evaluate the variation of the native degree, whose quantitative nature allows us to explicitly investigate the Hofmeister effect on the protein structure. We realized the classification of a protein of SARS-CoV-2 variants in 15 min, which has not been achieved before. This study offers an effective tool for tracking the dynamic structure of proteins and biomedical research.

Role of Repeated Conformational Transitions in Substrate Binding of Adenylate Kinase

The catalytic cycle of the enzyme adenylate kinase involves large conformational motions between open and closed states. A previous single-molecule experiment showed that substrate binding tends to accelerate both the opening and the closing rates and that a single turnover event often involves multiple rounds of conformational switching. In this work, we showed that the repeated conformational transitions of adenylate kinase are essential for the relaxation of incorrectly bound substrates into the catalytically competent conformation by combining all-atom and coarse-grained molecular simulations. In addition, free energy calculations based on all-atom and coarse-grained models demonstrated that the enzyme with incorrectly bound substrates has much a lower free energy barrier for domain opening compared to that with the correct substrate conformation, which may explain the the acceleration of the domain opening rate by substrate binding. The results of this work provide mechanistic understanding to previous experimental observations and shed light onto the interplay between conformational dynamics and enzyme catalysis.

Threading single proteins through pores to compare their energy landscapes

Protein function correlates with its structural dynamics. While theoretical approaches to studying protein energy landscapes are well developed, experimental methods that enable probing these landscapes of proteins remain challenging. We used solid-state nanopores to study the translocation behavior of three mutants of a helix bundle protein and quantified the number of energetically accessible conformational states for each mutant. We found that a slower-folding mutant with access to more conformational states translocates faster than a faster-folding mutant with a smaller number of accessible states, suggesting that ease of folding and ease of translocation are at odds in this case.

Translocation of proteins is correlated with structural fluctuations that access conformational states higher in free energy than the folded state. We use electric fields at the solid-state nanopore to control the relative free energy and occupancy of different protein conformational states at the single-molecule level. The change in occupancy of different protein conformations as a function of electric field gives rise to shifts in the measured distributions of ionic current blockades and residence times. We probe the statistics of the ionic current blockades and residence times for three mutants of the λ-repressor family in order to determine the number of accessible conformational states of each mutant and evaluate the ruggedness of their free energy landscapes. Translocation becomes faster at higher electric fields when additional flexible conformations are available for threading through the pore. At the same time, folding rates are not correlated with ease of translocation; a slow-folding mutant with a low-lying intermediate state translocates faster than a faster-folding two-state mutant. Such behavior allows us to distinguish among protein mutants by selecting for the degree of current blockade and residence time at the pore. Based on these findings, we present a simple free energy model that explains the complementary relationship between folding equilibrium constants and translocation rates.

Spectroscopic studies reveal details of substrate-induced conformational changes distant from the active site in isopenicillin N synthase

Isopenicillin N synthase (IPNS) catalyzes formation of the β-lactam and thiazolidine rings of isopenicillin N from its linear tripeptide l-δ-(α-aminoadipoyl)-l-cysteinyl-d-valine (ACV) substrate in an iron- and dioxygen (O₂)-dependent four-electron oxidation without precedent in current synthetic chemistry. Recent X-ray free-electron laser studies including time-resolved serial femtosecond crystallography show that binding of O₂ to the IPNS–Fe(II)–ACV complex induces unexpected conformational changes in α-helices on the surface of IPNS, in particular in α3 and α10. However, how substrate binding leads to conformational changes away from the active site is unknown. Here, using detailed ¹⁹F NMR and electron paramagnetic resonance experiments with labeled IPNS variants, we investigated motions in α3 and α10 induced by binding of ferrous iron, ACV, and the O₂ analog nitric oxide, using the less mobile α6 for comparison. ¹⁹F NMR studies were carried out on singly and doubly labeled α3, α6, and α10 variants at different temperatures. In addition, double electron–electron resonance electron paramagnetic resonance analysis was carried out on doubly spin-labeled variants. The combined spectroscopic and crystallographic results reveal that substantial conformational changes in regions of IPNS including α3 and α10 are induced by binding of ACV and nitric oxide. Since IPNS is a member of the structural superfamily of 2-oxoglutarate-dependent oxygenases and related enzymes, related conformational changes may be of general importance in nonheme oxygenase catalysis.

A litmus test for classifying recognition mechanisms of transiently binding proteins

Partner recognition in protein binding is critical for all biological functions, and yet, delineating its mechanism is challenging, especially when recognition happens within microseconds. We present a theoretical and experimental framework based on straight-forward nuclear magnetic resonance relaxation dispersion measurements to investigate protein binding mechanisms on sub-millisecond timescales, which are beyond the reach of standard rapid-mixing experiments. This framework predicts that conformational selection prevails on ubiquitin’s paradigmatic interaction with an SH3 (Src-homology 3) domain. By contrast, the SH3 domain recognizes ubiquitin in a two-state binding process. Subsequent molecular dynamics simulations and Markov state modeling reveal that the ubiquitin conformation selected for binding exhibits a characteristically extended C-terminus. Our framework is robust and expandable for implementation in other binding scenarios with the potential to show that conformational selection might be the design principle of the hubs in protein interaction networks.

The authors provide a litmus test for the recognition mechanism of transiently binding proteins based on nuclear magnetic resonance and find a conformational selection binding mechanism through concentration-dependent kinetics of ubiquitin and SH3.

Proteins' Evolution upon Point Mutations

As the reader must be already aware, state-of-the-art protein folding prediction methods have reached a smashing success in their goal of accurately determining the three-dimensional structures of proteins. Yet, a solution to simple problems such as the effects of protein point mutations on their (i) native conformation; (ii) marginal stability; (iii) ensemble of high-energy nativelike conformations; and (iv) metamorphism propensity and, hence, their evolvability, remains as an unsolved problem. As a plausible solution to the latter, some properties of the amide hydrogen-deuterium exchange, a highly sensitive probe of the structure, stability, and folding of proteins, are assessed from a new perspective. The preliminary results indicate that the protein marginal stability change upon point mutations provides the necessary and sufficient information to estimate, through a Boltzmann factor, the evolution of the amide hydrogen exchange protection factors and, consequently, that of the ensemble of folded conformations coexisting with the native state. This work contributes to our general understanding of the effects of point mutations on proteins and may spur significant progress in our efforts to develop methods to determine the appearance of new folds and functions accurately.