Intrinsic dynamics of enzymes in the unbound state and relation to allosteric regulation

Applications of the Newly Developed Force-Field Parameters Uncover a Dynamic Nature of Ω-Loop C in the Lys-Ligated Alkaline Form of Cytochrome c

Lys-ligated cytochromes make up an emerging family of heme proteins. Density functional theory calculations on the amine/imidazole-ligated c-type ferric heme were employed to develop force-field parameters for molecular dynamics (MD) simulations of structural and dynamic features of these proteins. The new force-field parameters were applied to the alkaline form of yeast iso-1 cytochrome c to rationalize discrepancies resulting from distinct experimental conditions in prior structural studies and to provide insights into the mechanisms of the alkaline transition. Our simulations have revealed the dynamic nature of Ω-loop C in the Lys-ligated protein and its unfolding in the Lys-ligated conformer having this loop in the same position as in the native Met-ligated protein. The proximity of Tyr67 or Tyr74 to the Lys ligand of ferric heme iron suggests a possible mechanism of the backward alkaline transition where a proton donor Tyr assists in Lys dissociation. The developed force-field parameters will be useful in structural and dynamic characterization of other native or engineered Lys-ligated heme proteins.

An In Silico Analysis of Genetic Variants and Structural Modeling of the Human Frataxin Protein in Friedreich's Ataxia

Friedreich's Ataxia (FRDA) stands out as the most prevalent form of hereditary ataxias, marked by progressive movement ataxia, loss of vibratory sensitivity, and skeletal deformities, severely affecting daily functioning. To date, the only medication available for treating FRDA is Omaveloxolone (Skyclarys®), recently approved by the FDA. Missense mutations within the human frataxin (FXN) gene, responsible for intracellular iron homeostasis regulation, are linked to FRDA development. These mutations induce FXN dysfunction, fostering mitochondrial iron accumulation and heightened oxidative stress, ultimately triggering neuronal cell death pathways. This study amalgamated 226 FXN genetic variants from the literature and database searches, with only 18 previously characterized. Predictive analyses revealed a notable prevalence of detrimental and destabilizing predictions for FXN mutations, predominantly impacting conserved residues crucial for protein function. Additionally, an accurate, comprehensive three-dimensional model of human FXN was constructed, serving as the basis for generating genetic variants I154F and W155R. These variants, selected for their severe clinical implications, underwent molecular dynamics (MD) simulations, unveiling flexibility and essential dynamic alterations in their N-terminal segments, encompassing FXN42, FXN56, and FXN78 domains pivotal for protein maturation. Thus, our findings indicate potential interaction profile disturbances in the FXN42, FXN56, and FXN78 domains induced by I154F and W155R mutations, aligning with the existing literature.

Whispering-Gallery Mode Optoplasmonic Microcavities: From Advanced Single-Molecule Sensors and Microlasers to Applications in Synthetic Biology

Optical microcavities, specifically, whispering-gallery mode (WGM) microcavities, with their remarkable sensitivity to environmental changes, have been extensively employed as biosensors, enabling the detection of a wide range of biomolecules and nanoparticles. To push the limits of detection down to the most sensitive single-molecule level, plasmonic nanorods are strategically introduced to enhance the evanescent fields of WGM microcavities. This advancement of optoplasmonic WGM sensors allows for the detection of single molecules of a protein, conformational changes, and even atomic ions, marking significant contributions in single-molecule sensing. This Perspective discusses the exciting research prospects in optoplasmonic WGM sensing of single molecules, including the study of enzyme thermodynamics and kinetics, the emergence of thermo-optoplasmonic sensing, the ultrasensitive single-molecule sensing on WGM microlasers, and applications in synthetic biology.

Insight into the Nucleotide Based Modulation of the Grp94 Molecular Chaperone Using Multiscale Dynamics

Grp94, an ER-localized molecular chaperone, is required for the folding and activation of many membrane and secretory proteins. Client activation by Grp94 is mediated by nucleotide and conformational changes. In this work, we aim to understand how microscopic changes from nucleotide hydrolysis can potentiate large-scale conformational changes of Grp94. We performed all-atom molecular dynamics simulations on the ATP-hydrolysis competent state of the Grp94 dimer in four different nucleotide bound states. We found that Grp94 was the most rigid when ATP was bound. ATP hydrolysis or nucleotide removal enhanced mobility of the N-terminal domain and ATP lid, resulting in suppression of interdomain communication. In an asymmetric conformation with one hydrolyzed nucleotide, we identified a more compact state, similar to experimental observations. We also identified a potential regulatory role of the flexible linker, as it formed electrostatic interactions with the Grp94 M-domain helix near the region where BiP is known to bind. These studies were complemented with normal-mode analysis of an elastic network model to investigate Grp94's large-scale conformational changes. SPM analysis identified residues that are important in signaling conformational change, many of which have known functional relevance in ATP coordination and catalysis, client binding, and BiP binding. Our findings suggest that ATP hydrolysis in Grp94 alters allosteric wiring and facilitates conformational changes.

Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase

Allosteric drugs have the potential to revolutionize biomedicine due to their enhanced selectivity and protection against overdosage. However, we need to better understand allosteric mechanisms in order to fully harness their potential in drug discovery. In this study, molecular dynamics simulations and nuclear magnetic resonance spectroscopy are used to investigate how increases in temperature affect allostery in imidazole glycerol phosphate synthase. Results demonstrate that temperature increase triggers a cascade of local amino acid-to-amino acid dynamics that remarkably resembles the allosteric activation that takes place upon effector binding. The differences in the allosteric response elicited by temperature increase as opposed to effector binding are conditional to the alterations of collective motions induced by either mode of activation. This work provides an atomistic picture of temperature-dependent allostery, which could be harnessed to more precisely control enzyme function.

Statistical Learning of Protein Elastic Network from Positional Covariance Matrix

Positional fluctuation and covariance during protein dynamics are key observables for understanding the molecular origin of biological functions. A frequently employed potential energy function for describing protein structural variation at the coarse-gained level is elastic network model (ENM). A long-standing issue in biomolecular simulation is thus the parametrization of ENM spring constants from the components of positional covariance matrix (PCM). Based on sensitivity analysis of PCM, the direct-coupling statistics of each spring, which is a specific combination of position fluctuation and covariance, is found to exhibit prominent signal of parameter dependence. This finding provides the basis for devising the objective function and the scheme of running through the effective one-dimensional optimization of every spring by self-consistent iteration. Formal derivation of the positional covariance statistical learning (PCSL) method also motivates the necessary data regularization for stable calculations. Robust convergence of PCSL is achieved in taking an all-atom molecular dynamics trajectory or an ensemble of homologous structures as input data. The PCSL framework can also be generalized with mixed objective functions to capture specific property such as the residue flexibility profile. Such physical chemistry-based statistical learning thus provides a useful platform for integrating the mechanical information encoded in various experimental or computational data.

Effector Regulated Catalytic Cyclization of Alkynoic Acids Using Pt2 L4 Cages

Metabolic pathways are highly regulated by effector molecules that influences the rate of enzymatic reactions. Inspired by the catalytic regulation found in living cells, we report a Pt₂ L₄ cage of which the activity can be controlled by effectors that bind inside the cage. The cage shows catalytic activity in the lactonization of alkynoic acids, with the reaction rates dependent on the effector guest bound in the cage. Some effector guests enhance the rate of the lactonization by up to 19-fold, whereas one decreases it by 5-fold. When mixtures of specific substrates are used, both starting materials and products act as guests for the Pt₂ L₄ cage, enhancing its catalytic activity for one substrate while reducing its activity for the other. The reported regulatory behavior obtained by the addition of effector molecules paves the way to the development of more complex, metabolic-like catalyst systems.

Nonequilibrium Modeling of the Elementary Step in PDZ3 Allosteric Communication

While allostery is of paramount importance for protein signaling and regulation, the underlying dynamical process of allosteric communication is not well understood. The PDZ3 domain represents a prime example of an allosteric single-domain protein, as it features a well-established long-range coupling between the C-terminal α₃-helix and ligand binding. In an intriguing experiment, Hamm and co-workers employed photoswitching of the α₃-helix to initiate a conformational change of PDZ3 that propagates from the C-terminus to the bound ligand within 200 ns. Performing extensive nonequilibrium molecular dynamics simulations, the modeling of the experiment reproduces the measured time scales and reveals a detailed picture of the allosteric communication in PDZ3. In particular, a correlation analysis identifies a network of contacts connecting the α₃-helix and the core of the protein, which move in a concerted manner. Representing a one-step process and involving direct α₃-ligand contacts, this cooperative transition is considered as the elementary step in the propagation of conformational change.

Structure and diffusive dynamics of aspartate α-decarboxylase (ADC) liganded with D-serine in aqueous solution

Incoherent neutron spectroscopy, in combination with dynamic light scattering, was used to investigate the effect of ligand binding on the center-of-mass self-diffusion and internal diffusive dynamics of Escherichia coli aspartate α-decarboxylase (ADC). The X-ray crystal structure of ADC in complex with the d-serine inhibitor was also determined, and molecular dynamics simulations were used to further probe the structural rearrangements that occur as a result of ligand binding. These experiments reveal that d-serine forms hydrogen bonds with some of the active site residues, that higher order oligomers of the ADC tetramer exist on ns–ms time-scales, and also show that ligand binding both affects the ADC internal diffusive dynamics and appears to further increase the size of the higher order oligomers.

Neutron spectroscopy, dynamic light scattering, X-ray diffraction, and MD-simulations were used to investigate the effect of ligand binding on the structure and diffusive dynamics of Escherichia coli aspartate alpha-decarboxylase.

Using Atomistic Simulations to Explore the Role of Methylation and ATP in Chemotaxis Signal Transduction

A bacterial chemotaxis mechanism is activated when nutrients bind to surface receptors. The sequence of intra- and interprotein events in this signal cascade from the receptors to the eventual molecular motors has been clearly identified. However, the atomistic details remain elusive, as in general may be expected of intraprotein signal transduction pathways, especially when fibrillar proteins are involved. We performed atomistic calculations of the methyl accepting chemoprotein (MCP)-CheA-CheW multidomain complex from Escherichia coli, simulating the methylated and unmethylated conditions in the chemoreceptors and the ATP-bound and apo conditions of the CheA. Our results indicate that these atomistic simulations, especially with one of the two force fields we tried, capture several relevant features of the downstream effects, such as the methylation favoring an intermediate structure that is more toward a dipped state and increases the chance of ATP hydrolysis. The results thus suggest the sensitivity of the model to reflect the nutrient signal response, a nontrivial validation considering the complexity of the system, encouraging even more detailed studies on the thermodynamic quantification of the effects and the identification of the signaling networks.

Impact of Host Flexibility on Selectivity in a Supramolecular Host-Catalyzed Enantioselective aza-Darzens Reaction

A highly enantioselective aza-Darzens reaction (up to 99% ee) catalyzed by an enantiopure supramolecular host has been discovered. To understand the role of host structure on reaction outcome, nine new gallium(III)-based enantiopure supramolecular assemblies were prepared via substitution of the external chiral amide. Despite the distal nature of the substitution in these catalysts, changes in enantioselectivity (61 to 90% ee) in the aziridine product were observed. The enantioselectivities were correlated to the flexibility of the supramolecular host scaffold as measured by the kinetics of exchange of a model cationic guest. This correlation led to the development of a best-in-class catalyst by substituting the gallium(III)-based host with one based on indium(III), which generated the most flexible and selective catalyst.

Cooperative Protein Allosteric Transition Mediated by a Fluctuating Transmission Network

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

The effect of dimerization and ligand binding on the dynamics of Kaposi's sarcoma‐associated herpesvirus protease

The Kaposi's sarcoma‐associated herpesvirus protease is essential for virus maturation. This protease functions under allosteric regulation that establishes its enzymatic activity upon dimerization. It exists in equilibrium between an inactive monomeric state and an active, weakly associating, dimeric state that is stabilized upon ligand binding. The dynamics of the protease dimer and its monomer were studied using the Gaussian network model and the anisotropic network model , and its role in mediating the allosteric regulation is demonstrated. We show that the dimer is composed of five dynamical domains. The central domain is formed upon dimerization and composed of helix five of each monomer, in addition to proximal and distal domains of each monomer. Dimerization reduces the mobility of the central domains and increases the mobility of the distal domains, in particular the binding site within them. The three slowest ANM modes of the dimer assist the protease in ligand binding, motion of the conserved Arg142 and Arg143 toward the oxyanion, and reducing the activation barrier for the tetrahedral transition state by stretching the bond that is cleaved by the protease. In addition, we show that ligand binding reduces the motion of helices α1 and α5 at the interface and explain how ligand binding can stabilize the dimer.

Rethinking the MtInhA tertiary and quaternary structure flexibility: a molecular dynamics view

Flexibility and function are related properties in the study of protein dynamics. Flexibility reflects in the conformational potential of proteins and thus in their functionalities. The presence of interactions between protein-ligands and protein-protein complexes, substrates, and environmental changes can alter protein plasticity, acting from the rearrangement of the side chains of amino acids to the folding/unfolding of large structural motifs. To evaluate the effects of the flexibility in protein systems, we defined the enzyme 2-trans-enoyl-ACP (CoA) reductase from Mycobacterium tuberculosis, or MtInhA, as our target system. MtInhA is biologically active as a tetramer in solution; however, computational studies commonly use the monomer justifying the independence of its active sites due to their distances. However, differences in flexibility between tertiary and quaternary structures could present impact on the size of the active site, influencing the drug discovery process. In this study, we investigated the influence of flexibility restrictions in A- and B-loops of the MtInhA in order to suggest a monomeric structure that describes the conformational behavior of the tetrameric system. Overall, we observed that simulations where restrictions were applied to the A- and B-loops present a more similar behavior to the native structure when compared to unrestricted simulations. Therefore, our work presents a monomeric model of MtInhA, which has conformational characteristics of the biologically active structure. Thus, the data obtained in this work can be applied to the MtInhA system for the generation of more reliable flexible models for molecular docking experiments, and also for the performance of longer simulations by molecular dynamics and with a lower computational cost.

Response of Terahertz Protein Vibrations to Ligand Binding: Calmodulin-Peptide Complexes as a Case Study

Terahertz vibrations are sensitive reporters of the structure and interactions of proteins. Ligand binding alters the nature and distribution of these collective vibrations. The ligand-induced changes in the terahertz protein vibrations contribute to the binding entropy and to the overall thermodynamic stability of the resultant protein-ligand complexes. Here, we have examined the response of the low-frequency (below 6 terahertz) collective vibrations of the calcium-loaded calmodulin (CaM) to binding to five different ligands, both in the presence and absence of water, using normal-mode analysis and molecular dynamics simulations. A comparison of the vibrational spectra of hydrated and dry systems reveals that protein-solvent interactions stiffen the terahertz protein vibrations and that these solvent-coupled collective vibrations contribute significantly to the hydration-sensitive variation in the vibrational entropy of CaM. In the absence of water, the low-frequency vibrations of CaM are stiffened by ligand binding. On the contrary, the number and the cumulative vibrational entropy of low-frequency vibrational modes (ω < 200 cm^-1) of the hydrated CaM are increased noticeably after binding to the peptides, indicating binding-induced softening of collective vibrations of the protein. Although the calculated and experimental binding affinities of the chosen complexes correlated reasonably well, no systematic correlation was observed between the protein vibrational entropy and the binding affinity. The results underscored the importance of the interplay of protein-ligand and solvent interactions in modulating the low-frequency vibrations of proteins.

Why are large conformational changes well described by harmonic normal modes?

Low-frequency normal modes generated by elastic network models tend to correlate strongly with large conformational changes of proteins, despite their reliance on the harmonic approximation, which is only valid in close proximity of the native structure. We consider 12 variants of the torsional network model (TNM), an elastic network model in torsion angle space, that adopt different sets of torsion angles as degrees of freedom and reproduce with similar quality the thermal fluctuations of proteins but present drastic differences in their agreement with conformational changes. We show that these differences are related to the extent of the deviations from the harmonic approximation, assessed through an anharmonic energy function whose harmonic approximation coincides with the TNM. Our results indicate that mode anharmonicity is more strongly related to its collectivity, i.e., the number of atoms displaced by the mode, than to its amplitude; low-frequency modes can remain harmonic even at large amplitudes, provided they are sufficiently collective. Finally, we assess the potential benefits of different strategies to minimize the impact of anharmonicity. The reduction of the number of degrees of freedom or their regularization by a torsional harmonic potential significantly improves the collectivity and harmonicity of normal modes and the agreement with conformational changes. In contrast, the correction of normal mode frequencies to partially account for anharmonicity does not yield substantial benefits. The TNM program is freely available at https://github.com/ugobas/tnm.

Structural dynamics in the evolution of a bilobed protein scaffold

Proteins conduct numerous complex biological functions by use of tailored structural dynamics. The molecular details of how these emerged from ancestral peptides remains mysterious. How does nature utilize the same repertoire of folds to diversify function? To shed light on this, we analyzed bilobed proteins with a common structural core, which is spread throughout the tree of life and is involved in diverse biological functions such as transcription, enzymatic catalysis, membrane transport, and signaling. We show here that the structural dynamics of the structural core differentiate predominantly via terminal additions during a long-period evolution. This diversifies substrate specificity and, ultimately, biological function.

Novel biophysical tools allow the structural dynamics of proteins and the regulation of such dynamics by binding partners to be explored in unprecedented detail. Although this has provided critical insights into protein function, the means by which structural dynamics direct protein evolution remain poorly understood. Here, we investigated how proteins with a bilobed structure, composed of two related domains from the periplasmic-binding protein–like II domain family, have undergone divergent evolution, leading to adaptation of their structural dynamics. We performed a structural analysis on ∼600 bilobed proteins with a common primordial structural core, which we complemented with biophysical studies to explore the structural dynamics of selected examples by single-molecule Förster resonance energy transfer and Hydrogen–Deuterium exchange mass spectrometry. We show that evolutionary modifications of the structural core, largely at its termini, enable distinct structural dynamics, allowing the diversification of these proteins into transcription factors, enzymes, and extracytoplasmic transport-related proteins. Structural embellishments of the core created interdomain interactions that stabilized structural states, reshaping the active site geometry, and ultimately altered substrate specificity. Our findings reveal an as-yet-unrecognized mechanism for the emergence of functional promiscuity during long periods of evolution and are applicable to a large number of domain architectures.

Dissecting the role of interprotomer cooperativity in the activation of oligomeric high-temperature requirement A2 protein

The human high-temperature requirement A2 (HtrA2) mitochondrial protease is critical for cellular proteostasis, with mutations in this enzyme closely associated with the onset of neurodegenerative disorders. HtrA2 forms a homotrimeric structure, with each subunit composed of protease and PDZ (PSD-95, DLG, ZO-1) domains. Although we had previously shown that successive ligand binding occurs with increasing affinity, and it has been suggested that allostery plays a role in regulating catalysis, the molecular details of how this occurs have not been established. Here, we use cysteine-based chemistry to generate subunits in different conformational states along with a protomer mixing strategy, biochemical assays, and methyl-transverse relaxation optimized spectroscopy-based NMR studies to understand the role of interprotomer allostery in regulating HtrA2 function. We show that substrate binding to a PDZ domain of one protomer increases millisecond-to-microsecond timescale dynamics in neighboring subunits that prime them for binding substrate molecules. Only when all three PDZ-binding sites are substrate bound can the enzyme transition into an active conformation that involves significant structural rearrangements of the protease domains. Our results thus explain why when one (or more) of the protomers is fixed in a ligand-binding-incompetent conformation or contains the inactivating S276C mutation that is causative for a neurodegenerative phenotype in mouse models of Parkinson's disease, transition to an active state cannot be formed. In this manner, wild-type HtrA2 is only active when substrate concentrations are high and therefore toxic and unregulated proteolysis of nonsubstrate proteins can be suppressed.

The hairpin extension controls solvent access to the chromophore binding pocket in a bacterial phytochrome: a UV-vis absorption spectroscopy study

Solvent access to the protein interior plays an important role in the function of many proteins. Phytochromes contain a specific structural feature, a hairpin extension that appears to relay structural information from the chromophore to the rest of the protein. The extension interacts with amino acids near the chromophore, and hence shields the chromophore from the surrounding solvent. We envision that the detachment of the extension from the protein surface allows solvent exchange reactions in the vicinity of the chromophore. This can facilitate for example, proton transfer processes between solvent and the protein interior. To test this hypothesis, the kinetics of the protonation state of the biliverdin chromophore from Deinococcus radiodurans bacteriophytchrome, and thus, the pH of the surrounding solution, is determined. The observed absorbance changes are related to the solvent access of the chromophore binding pocket, gated by the hairpin extension. We therefore propose a model with an "open" (solvent-exposed, deprotonation-active on a (sub)second time-scale) state and a "closed" (solvent-gated, deprotonation inactive) state, where the hairpin fluctuates slowly between these conformations thereby controlling the deprotonation process of the chromophore on a minute time scale. When the connection between the hairpin and the biliverdin surroundings is destabilized by a point mutation, the amplitude of the deprotonation phase increases considerably. In the absence of the extension, the chromophore deprotonates essentially without any "gating". Hence, we introduce a straightforward method to study the stability and fluctuation of the phytochrome hairpin in its photostationary state. This approach can be extended to other chromophore-protein systems where absorption changes reflect dynamic processes of the protein.

Role of bacterial RNA polymerase gate opening dynamics in DNA loading and antibiotics inhibition elucidated by quasi-Markov State Model

To initiate transcription, the holoenzyme (RNA polymerase [RNAP] in complex with σ factor) loads the promoter DNA via the flexible loading gate created by the clamp and β-lobe, yet their roles in DNA loading have not been characterized. We used a quasi-Markov State Model (qMSM) built from extensive molecular dynamics simulations to elucidate the dynamics of Thermus aquaticus holoenzyme's gate opening. We showed that during gate opening, β-lobe oscillates four orders of magnitude faster than the clamp, whose opening depends on the Switch 2's structure. Myxopyronin, an antibiotic that binds to Switch 2, was shown to undergo a conformational selection mechanism to inhibit clamp opening. Importantly, we reveal a critical but undiscovered role of β-lobe, whose opening is sufficient for DNA loading even when the clamp is partially closed. These findings open the opportunity for the development of antibiotics targeting β-lobe of RNAP. Finally, we have shown that our qMSMs, which encode non-Markovian dynamics based on the generalized master equation formalism, hold great potential to be widely applied to study biomolecular dynamics.

Critical assessment of protein intrinsic disorder prediction

Intrinsically disordered proteins, defying the traditional protein structure-function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has F_max = 0.483 on the full dataset and F_max = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F_max = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

Experimentally based structural model of Yih1 provides insight into its function in controlling the key translational regulator Gcn2

Yeast impact homolog 1 (Yih1), or IMPACT in mammals, is part of a conserved regulatory module controlling the activity of General Control Nonderepressible 2 (Gcn2), a protein kinase that regulates protein synthesis. Yih1/IMPACT is implicated not only in many essential cellular processes, such as neuronal development, immune system regulation and the cell cycle, but also in cancer. Gcn2 must bind to Gcn1 in order to impair the initiation of protein translation. Yih1 hinders this key Gcn1-Gcn2 interaction by binding to Gcn1, thus preventing Gcn2-mediated inhibition of protein synthesis. Here, we solved the structures of the two domains of Saccharomyces cerevisiae Yih1 separately using Nuclear Magnetic Resonance and determined the relative positions of the two domains using a range of biophysical methods. Our findings support a compact structural model of Yih1 in which the residues required for Gcn1 binding are buried in the interface. This model strongly implies that Yih1 undergoes a large conformational rearrangement from a latent closed state to a primed open state to bind Gcn1. Our study provides structural insight into the interactions of Yih1 with partner molecules.

Capturing the Conformational Ensemble of the Mixed Folded Polyglutamine Protein Ataxin-3

Ataxin-3 is a deubiquitinase involved in protein quality control and other essential cellular functions. It preferentially interacts with polyubiquitin chains of four or more units attached to proteins delivered to the ubiquitin-proteasome system. Ataxin-3 is composed of an N-terminal Josephin domain and a flexible C terminus that contains two or three ubiquitin-interacting motifs (UIMs) and a polyglutamine tract, which, when expanded beyond a threshold, leads to protein aggregation and misfolding and causes spinocerebellar ataxia type 3. The high-resolution structure of the Josephin domain is available, but the structural and dynamical heterogeneity of ataxin-3 has so far hindered the structural description of the full-length protein. Here, we characterize non-expanded and expanded variants of ataxin-3 in terms of conformational ensembles adopted by the proteins in solution by jointly using experimental data from nuclear magnetic resonance and small-angle X-ray scattering with coarse-grained simulations. Our results pave the way to a molecular understanding of polyubiquitin recognition.

Enzyme dynamics: Looking beyond a single structure

Conventional understanding of how enzymes function strongly emphasizes the role of structure. However, increasing evidence clearly indicates that enzymes do not remain fixed or operate exclusively in or close to their native structure. Different parts of the enzyme (from individual residues to full domains) undergo concerted motions on a wide range of time-scales, including that of the catalyzed reaction. Information obtained on these internal motions and conformational fluctuations has so far uncovered and explained many aspects of enzyme mechanisms, which could not have been understood from a single structure alone. Although there is wide interest in understanding enzyme dynamics and its role in catalysis, several challenges remain. In addition to technical difficulties, the vast majority of investigations are performed in dilute aqueous solutions, where conditions are significantly different than the cellular milieu where a large number of enzymes operate. In this review, we discuss recent developments, several challenges as well as opportunities related to this topic. The benefits of considering dynamics as an integral part of the enzyme function can also enable new means of biocatalysis, engineering enzymes for industrial and medicinal applications.

Real-time observation of ligand-induced allosteric transitions in a PDZ domain

While allostery is of paramount importance for protein regulation, the underlying dynamical process of ligand (un)binding at one site, resulting time evolution of the protein structure, and change of the binding affinity at a remote site are not well understood. Here the ligand-induced conformational transition in a widely studied model system of allostery, the PDZ2 domain, is investigated by transient infrared spectroscopy accompanied by molecular dynamics simulations. To this end, an azobenzene-derived photoswitch is linked to a peptide ligand in a way that its binding affinity to the PDZ2 domain changes upon switching, thus initiating an allosteric transition in the PDZ2 domain protein. The subsequent response of the protein, covering four decades of time, ranging from ∼1 ns to ∼μs, can be rationalized by a remodeling of its rugged free-energy landscape, with very subtle shifts in the populations of a small number of structurally well-defined states. It is proposed that structurally and dynamically driven allostery, often discussed as limiting scenarios of allosteric communication, actually go hand-in-hand, allowing the protein to adapt its free-energy landscape to incoming signals.

Transglutaminase-Mediated Cross-Linking of Tropoelastin to Fibrillin Stabilises the Elastin Precursor Prior to Elastic Fibre Assembly

Elastic fibres are essential components of all mammalian elastic tissues such as blood vessels, lung and skin, and are critically important for the mechanical properties they endow. The main components of elastic fibres are elastin and fibrillin, where correct formation of elastic fibres requires a fibrillin microfibril scaffold for the deposition of elastin. It has been demonstrated previously that the interaction between fibrillin and tropoelastin, the elastin precursor, increases the rate of assembly of tropoelastin. Furthermore, tropoelastin and fibrillin can be cross-linked by transglutaminase-2, but the function of cross-linking on their elastic properties is yet to be elucidated. Here we show that transglutaminase cross-linking supports formation of a 1:1 stoichiometric fibrillin-tropoelastin complex. SAXS data show that the complex retains features of the individual proteins but is elongated supporting end-to-end assembly. Elastic network models were constructed to compare the dynamics of tropoelastin and fibrillin individually as well as in the cross-linked complex. Normal mode analysis was performed to determine the structures' most energetically favourable, biologically accessible motions which show that within the complex, tropoelastin is less mobile and this molecular stabilisation extends along the length of the tropoelastin molecule to regions remote from the cross-linking site. Together, these data suggest a long-range stabilising effect of cross-linking that occurs due to the covalent linkage of fibrillin to tropoelastin. This work provides insight into the interactions of tropoelastin and fibrillin and how cross-link formation stabilises the elastin precursor so it is primed for elastic fibre assembly.

Probing the Structural Dynamics of the Plasmodium falciparum Tunneling-Fold Enzyme 6-Pyruvoyl Tetrahydropterin Synthase to Reveal Allosteric Drug Targeting Sites

The de novo folate synthesis pathway is a well-established drug target in the treatment of many infectious diseases. Antimalarial antifolate drugs have proven to be effective against malaria, however, rapid drug resistance has emerged on the two primary targeted enzymes: dihydrofolate reductase and dihydroptoreate synthase. The need to identify alternative antifolate drugs and novel metabolic targets is of imminent importance. The 6-pyruvol tetrahydropterin synthase (PTPS) enzyme belongs to the tunneling fold protein superfamily which is characterized by a distinct central tunnel/cavity. The enzyme catalyzes the second reaction step of the parasite’s de novo folate synthesis pathway and is responsible for the conversion of 7,8-dihydroneopterin to 6-pyruvoyl-tetrahydropterin. In this study, we examine the structural dynamics of Plasmodium falciparum PTPS using the anisotropic network model, to elucidate the collective motions that drive the function of the enzyme and identify potential sites for allosteric modulation of its binding properties. Based on our modal analysis, we identified key sites in the N-terminal domains and central helices which control the accessibility to the active site. Notably, the N-terminal domains were shown to regulate the open-to-closed transition of the tunnel, via a distinctive wringing motion that deformed the core of the protein. We, further, combined the dynamic analysis with motif discovery which revealed highly conserved motifs that are unique to the Plasmodium species and are located in the N-terminal domains and central helices. This provides essential structural information for the efficient design of drugs such as allosteric modulators that would have high specificity and low toxicity as they do not target the PTPS active site that is highly conserved in humans.

A single amino acid substitution uncouples catalysis and allostery in an essential biosynthetic enzyme in Mycobacterium tuberculosis

Allostery exploits the conformational dynamics of enzymes by triggering a shift in population ensembles toward functionally distinct conformational or dynamic states. Allostery extensively regulates the activities of key enzymes within biosynthetic pathways to meet metabolic demand for their end products. Here, we have examined a critical enzyme, 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase (DAH7PS), at the gateway to aromatic amino acid biosynthesis in Mycobacterium tuberculosis, which shows extremely complex dynamic allostery: three distinct aromatic amino acids jointly communicate occupancy to the active site via subtle changes in dynamics, enabling exquisite fine-tuning of delivery of these essential metabolites. Furthermore, this allosteric mechanism is co-opted by pathway branchpoint enzyme chorismate mutase upon complex formation. In this study, using statistical coupling analysis, site-directed mutagenesis, isothermal calorimetry, small-angle X-ray scattering, and X-ray crystallography analyses, we have pinpointed a critical node within the complex dynamic communication network responsible for this sophisticated allosteric machinery. Through a facile Gly to Pro substitution, we have altered backbone dynamics, completely severing the allosteric signal yet remarkably, generating a nonallosteric enzyme that retains full catalytic activity. We also identified a second residue of prime importance to the inter-enzyme communication with chorismate mutase. Our results reveal that highly complex dynamic allostery is surprisingly vulnerable and provide further insights into the intimate link between catalysis and allostery.

Allosteric communication in molecular machines via information exchange: what can be learned from dynamical modeling

Allosteric regulation is crucial for the operation of protein machines and molecular motors. A major challenge is to characterize and quantify the information exchange underlying allosteric communication between remote functional sites in a protein, and to identify the involved relevant pathways. We review applications of two topical approaches of dynamical protein modeling, a kinetic-based single-molecule stochastic model, which employs information thermodynamics to quantify allosteric interactions, and structure-based coarse-grained modeling to characterize intra-molecular couplings in terms of conformational motions and propagating mechanical strain. Both descriptions resolve the directionality of allosteric responses within a protein, emphasizing the concept of causality as the principal hallmark of protein allostery. We discuss the application of techniques from information thermodynamics to dynamic protein elastic networks and evolutionary designed model structures, and the ramifications for protein allostery.

Integrated Computational Approaches and Tools forAllosteric Drug Discovery

Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.

Exploring the different states of wild-type T-cell receptor and mutant conformational changes towards understanding the antigen recognition

Recognition of proteolytic peptide fragments presented by major histocompatibility complex (MHC) on target cells by T-cell receptor (TCR) is among the most important interactions in the adaptive immune system. Several computational studies have been performed to investigate conformational and dynamical properties of TCRs for enhanced immunogenicity. Here, we present the large-scale molecular dynamics (MD) simulation studies of the two comprehensive systems consisting of the wild-type and mutant IG4 TCR in complex with the tumor epitope NY-ESO peptide (SLLMWITQC) and analyzed for mapping conformational changes of TCR in the states prior to antigen binding, upon antigen binding and after the antigen was released. All of the simulations were performed with different states of TCRs for each 1000 ns of simulation time, providing six simulations for time duration of 6000 ns (6µs). We show that rather than undergoing most critical conformational changes upon antigen binding, the high proportion of complementarity-determining region (CDR) loops change by comparatively small amount. The hypervariable CDRα3 and CDRβ3 loops showed significant structural changes. Interestingly, the TCR β chain loops showed the least changes, which is reliable with recent implications that β domain of TCR may propel antigen interaction. The mutant shows higher rigidity than wild-type even in released state; expose an induced fit mechanism occurring from the re-structuring of CDRα3 loop and can allow enhanced binding affinity of the peptide antigen. Additionally, we show that CDRα3 loop and peptide contacts are an adaptive feature of affinity enhanced mutant TCR.Communicated by Ramaswamy H. Sarma.

Effect of conjugated (EK)10 peptide on structural and dynamic properties of ubiquitin protein: a molecular dynamics simulation study

Peptide conjugation modulates the stability and biological acitivty of proteins via the allosteric effect.

Effector responsive hydroformylation catalysis

Herein, we report a supramolecular rhodium complex that can form dimeric or monomeric Rh-species catalytically active in hydroformylation, depending on the binding of effectors within the integrated DIM-receptor. X-ray crystal structures, in situ (high-pressure (HP)) spectroscopy studies, and molecular modelling studies show that in the absence of effectors, the preferred Rh-species formed is the dimer, of which two ligands coordinate to two rhodium metals. Importantly, upon binding guest molecules, -effectors-, to the DIM-receptor under hydroformylation conditions, the monomeric Rh-active species is formed, as evidenced by a combination of in situ HP NMR and IR spectroscopy studies and molecular modelling. As the monomeric complex has different catalytic properties from the dimeric complex, we effectively generate a catalytic system of which the properties respond to the presence of effectors, reminiscent of how the properties of proteins are regulated in nature. Indeed, catalytic and kinetic experiments show that both the selectivity and activity of this supramolecular catalytic system can be influenced in the hydroformylation of 1-octene using acetate as an effector that shift the equilibrium from the dimeric to monomeric species.

Data-driven computational analysis of allosteric proteins by exploring protein dynamics, residue coevolution and residue interaction networks

BACKGROUND

Computational studies of allosteric interactions have witnessed a recent renaissance fueled by the growing interest in modeling of the complex molecular assemblies and biological networks. Allosteric interactions in protein structures allow for molecular communication in signal transduction networks.

METHODS

In this work, we performed a large scale comprehensive and multi-faceted analysis of >300 diverse allosteric proteins and complexes with allosteric modulators. By modeling and exploring coarse-grained dynamics, residue coevolution, and residue interaction networks for allosteric proteins, we have determined unifying molecular signatures shared by allosteric systems.

RESULTS

The results of this study have suggested that allosteric inhibitors and allosteric activators may differentially affect global dynamics and network organization of protein systems, leading to diverse allosteric mechanisms. By using structural and functional data on protein kinases, we present a detailed case study that that included atomic-level analysis of coevolutionary networks in kinases bound with allosteric inhibitors and activators.

CONCLUSIONS

We have found that coevolutionary networks can form direct communication pathways connecting functional regions and can recapitulate key regulatory sites and interactions responsible for allosteric signaling in the studied protein systems. The results of this computational investigation are compared with the experimental studies and reveal molecular signatures of known regulatory hotspots in protein kinases.

GENERAL SIGNIFICANCE

This study has shown that allosteric inhibitors and allosteric activators can have a different effect on residue interaction networks and can exploit distinct regulatory mechanisms, which could open up opportunities for probing allostery and new drug combinations with broad range of activities.

A non-beta-lactam antibiotic inhibitor for enterohemorrhagic Escherichia coli O104:H4

The overuse of antibiotics has caused an increased prevalence of drug-resistant bacteria. Bacterial resistance in E. coli is regulated via production of β-lactam-hydrolyzing β-lactamases enzymes. Escherichia coli O104: H4 is a multi-drug resistant strain known to resist β-lactam as well as several other antibiotics. Here, we report a molecular dynamic simulation-combined docking approach to identify, screen, and verify active pharmacophores against enterohemorrhagic Escherichia coli (EHEC). Experimental studies revealed a boronic acid cyclic monomer (BACM), a non-β-lactam compound, to inhibit the growth of E. coli O104: H4. In vitro Kirby Bauer disk diffusion susceptibility testing coupled interaction analysis suggests BACM inhibits E. coli O104:H4 growth by not only inhibiting the β-lactamase pathway but also via direct inhibition of the penicillin-binding protein. These results suggest that BACM could be used as a lead compound to develop potent drugs targeting beta-lactam resistant Gram-negative bacterial strains. KEY MESSAGES: • An in silico approach was reported to identify pharmacophores against E. coli O104: H4. • In vitro studies revealed a non-β-lactam compound to inhibit the growth of E. coli O104: H4. • This non-β-lactam compound could be used as a lead compound for targeting beta-lactam strains.

Simple mechanics of protein machines

While belonging to the nanoscale, protein machines are so complex that tracing even a small fraction of their cycle requires weeks of calculations on supercomputers. Surprisingly, many aspects of their operation can be however already reproduced by using very simple mechanical models of elastic networks. The analysis suggests that, similar to other self-organized complex systems, functional collective dynamics in such proteins is effectively reduced to a low-dimensional attractive manifold.

Signalling networks and dynamics of allosteric transitions in bacterial chaperonin GroEL: implications for iterative annealing of misfolded proteins

Signal transmission at the molecular level in many biological complexes occurs through allosteric transitions. Allostery describes the responses of a complex to binding of ligands at sites that are spatially well separated from the binding region. We describe the structural perturbation method, based on phonon propagation in solids, which can be used to determine the signal-transmitting allostery wiring diagram (AWD) in large but finite-sized biological complexes. Application to the bacterial chaperonin GroEL-GroES complex shows that the AWD determined from structures also drives the allosteric transitions dynamically. From both a structural and dynamical perspective these transitions are largely determined by formation and rupture of salt-bridges. The molecular description of allostery in GroEL provides insights into its function, which is quantitatively described by the iterative annealing mechanism. Remarkably, in this complex molecular machine, a deep connection is established between the structures, reaction cycle during which GroEL undergoes a sequence of allosteric transitions, and function, in a self-consistent manner.This article is part of a discussion meeting issue 'Allostery and molecular machines'.

Allostery in Its Many Disguises: From Theory to Applications

Allosteric regulation plays an important role in many biological processes, such as signal transduction, transcriptional regulation, and metabolism. Allostery is rooted in the fundamental physical properties of macromolecular systems, but its underlying mechanisms are still poorly understood. A collection of contributions to a recent interdisciplinary CECAM (Center Européen de Calcul Atomique et Moléculaire) workshop is used here to provide an overview of the progress and remaining limitations in the understanding of the mechanistic foundations of allostery gained from computational and experimental analyses of real protein systems and model systems. The main conceptual frameworks instrumental in driving the field are discussed. We illustrate the role of these frameworks in illuminating molecular mechanisms and explaining cellular processes, and describe some of their promising practical applications in engineering molecular sensors and informing drug design efforts.

Conformational Dynamics in Asymmetric Catalysis: Is Catalyst Flexibility a Design Element?

Traditionally, highly selective low molecular weight catalysts have been designed to contain rigidifying structural elements. As a result, many proposed stereochemical models rely on steric repulsion for explaining the observed selectivity. Recently, as is the case for enzymatic systems, it has become apparent that some flexibility can be beneficial for imparting selectivity. Dynamic catalysts can reorganize to maximize attractive non-covalent interactions that stabilize the favored diastereomeric transition state, while minimizing repulsive non-covalent interactions for enhanced selectivity. This Short Review discusses catalyst conformational dynamics and how these effects have proven beneficial for a variety of catalyst classes, including tropos ligands, cinchona alkaloids, hydrogen-bond donating catalysts, and peptides.

Coarse-Grained Simulation of Full-Length Integrin Activation

Integrin conformational dynamics are critical to their receptor and signaling functions in many cellular processes, including spreading, adhesion, and migration. However, assessing integrin conformations is both experimentally and computationally challenging because of limitations in resolution and dynamic sampling. Thus, structural changes that underlie transitions between conformations are largely unknown. Here, focusing on integrin αvβ₃, we developed a modified form of the coarse-grained heterogeneous elastic network model (hENM), which allows sampling conformations at the onset of activation by formally separating local fluctuations from global motions. Both local fluctuations and global motions are extracted from all-atom molecular dynamics simulations of the full-length αvβ₃ bent integrin conformer, but whereas the former are incorporated in the hENM as effective harmonic interactions between groups of residues, the latter emerge by systematically identifying and treating weak interactions between long-distance domains with flexible and anharmonic connections. The new hENM model allows integrins and single-point mutant integrins to explore various conformational states, including the initiation of separation between α- and β-subunit cytoplasmic regions, headpiece extension, and legs opening.

Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy

Single-particle analysis by electron microscopy is a well established technique for analyzing the three-dimensional structures of biological macromolecules. Besides its ability to produce high-resolution structures, it also provides insights into the dynamic behavior of the structures by elucidating their conformational variability. Here, the different image-processing methods currently available to study continuous conformational changes are reviewed.

Designed Elastic Networks: Models of Complex Protein Machinery

Recently, the design of mechanical networks with protein-inspired responses has become increasingly popular. Here, we review contributions which were motivated by studies of protein dynamics employing coarse-grained elastic network models. First, the concept of evolutionary optimization that we developed to design network structures which execute prescribed tasks is explained. We then review what presumably marks the origin of the idea to design complex functional networks which encode protein-inspired behavior, namely the design of an elastic network structure which emulates the cycles of ATP-powered conformational motion in protein machines. Two recent applications are reviewed. First, the construction of a model molecular motor, whose operation incorporates both the tight coupling power stroke as well as the loose coupling Brownian ratchet mechanism, is discussed. Second, the evolutionary design of network structures which encode optimal long-range communication between remote sites and represent mechanical models of allosteric proteins is presented. We discuss the prospects of designed protein-mimicking elastic networks as model systems to elucidate the design principles and functional signatures underlying the operation of complex protein machinery.

Theoretical analysis of inducer and operator binding for cyclic-AMP receptor protein mutants

Allosteric transcription factors undergo binding events at inducer binding sites as well as at distinct DNA binding domains, and it is difficult to disentangle the structural and functional consequences of these two classes of interactions. We compare the ability of two statistical mechanical models—the Monod-Wyman-Changeux (MWC) and the Koshland-Némethy-Filmer (KNF) models of protein conformational change—to characterize the multi-step activation mechanism of the broadly acting cyclic-AMP receptor protein (CRP). We first consider the allosteric transition resulting from cyclic-AMP binding to CRP, then analyze how CRP binds to its operator, and finally investigate the ability of CRP to activate gene expression. We use these models to examine a beautiful recent experiment that created a single-chain version of the CRP homodimer, creating six mutants using all possible combinations of the wild type, D53H, and S62F subunits. We demonstrate that the MWC model can explain the behavior of all six mutants using a small, self-consistent set of parameters whose complexity scales with the number of subunits, providing a significant benefit over previous models. In comparison, the KNF model not only leads to a poorer characterization of the available data but also fails to generate parameter values in line with the available structural knowledge of CRP. In addition, we discuss how the conceptual framework developed here for CRP enables us to not merely analyze data retrospectively, but has the predictive power to determine how combinations of mutations will interact, how double mutants will behave, and how each construct would regulate gene expression.

Interface Residues That Drive Allosteric Transitions Also Control the Assembly of l-Lactate Dehydrogenase

The allosteric enzyme, l-lactate dehydrogenase (LDH), is activated by fructose 1,6-metaphosphate (FBP) to reduce pyruvate to lactate. The molecular details of the FBP-driven transition from the low affinity T state to the high affinity R state in LDH, a tetramer composed of identical subunits, are not known. The dynamics of the T → R allosteric transition, investigated using Brownian dynamics (BD) simulations of the self-organized polymer (SOP) model, revealed that coordinated rotations of the subunits drive the T → R transition. We used the structural perturbation method (SPM), which requires only the static structure, to identify the allostery wiring diagram (AWD), a network of residues that transmits signals across the tetramer, as LDH undergoes the T → R transition. Interestingly, the residues that play a major role in the dynamics, which are predominantly localized at the interfaces, coincide with the AWD identified using the SPM. Although the allosteric pathways are highly heterogeneous, on the basis of our simulations, we surmise that predominantly the conformational changes in the T → R transition start from the region near the active site, comprised of helix αC, helix α1/2G, helix α3G, and helix α2F, and proceed to other structural units, thus completing the global motion. Brownian dynamics simulations of the tetramer assembly, triggered by a temperature quench from the fully disrupted conformations, show that the bottleneck for assembly is the formation of the correct orientational registry between the subunits, requiring contacts between the interface residues. Surprisingly, these residues are part of the AWD, which was identified using the SPM. Taken together, our results show that LDH, and perhaps other multidomain proteins, may have evolved to stabilize distinct states of allosteric enzymes using precisely the same AWD that also controls the functionally relevant allosteric transitions.

A non-equilibrium approach to allosteric communication

While the theory of protein folding is well developed, including concepts such as rugged energy landscape, folding funnel, etc., the same degree of understanding has not been reached for the description of the dynamics of allosteric transitions in proteins. This is not only due to the small size of the structural change upon ligand binding to an allosteric site, but also due to challenges in designing experiments that directly observe such an allosteric transition. On the basis of recent pump-probe-type experiments (Buchli et al. 2013 Proc. Natl Acad. Sci. USA110, 11 725-11 730. (doi:10.1073/pnas.1306323110)) and non-equilibrium molecular dynamics simulations (Buchenberg et al. 2017 Proc. Natl Acad. Sci. USA114, E6804-E6811. (doi:10.1073/pnas.1707694114)) studying an photoswitchable PDZ2 domain as model for an allosteric transition, we outline in this perspective how such a description of allosteric communication might look. That is, calculating the dynamical content of both experiment and simulation (which agree remarkably well with each other), we find that allosteric communication shares some properties with downhill folding, except that it is an 'order-order' transition. Discussing the multiscale and hierarchical features of the dynamics, the validity of linear response theory as well as the meaning of 'allosteric pathways', we conclude that non-equilibrium experiments and simulations are a promising way to study dynamical aspects of allostery.This article is part of a discussion meeting issue 'Allostery and molecular machines'.