Protein Allostery and Conformational Dynamics

Advances in the Computational Identification of Allosteric Sites and Pathways in Proteins

With the increasing difficulty to develop new drugs and the emergence of resistance to traditional orthosteric-site inhibitors, the search for alternatives is finally approaching the focus on allosteric sites. Allosteric sites offer opportunities to regulate many pharmacologically targeted pathways by inhibition or activation. In addition, allosteric sites tend to be less conserved than the functional site, which may facilitate the design of specific effectors in the protein families for which specific orthosteric inhibitors have proved difficult to design. Furthermore, recent evidence suggests that all proteins might be susceptible of allosteric regulation, increasing the space of druggable targets. Computational identification of allosteric sites has therefore become an active field of research. The problem can be approached from two sides: (1) the identification of allosteric-communication pathways between the functional site and potential allosteric sites and (2) the functional-site-independent identification of allosteric sites. While the first approach tends to be more laborious and thus restricted to a single protein, the second tends to be more amenable to larger-scale analysis, thus providing tools for the two drug discovery scenarios: the analysis of known targets and the screening for new potential targets. Here, I show some basic concepts and methods useful to the identification of allosteric sites and pathways, in line with these two approaches. I describe them in some detail to build a clear framework, at the risk of losing the interest of experts. Examples of recent studies involving these methods are also illustrated, focusing on the techniques rather than on their findings on allosterism.

Eigenvector centrality for characterization of protein allosteric pathways

Determining the principal energy-transfer pathways responsible for allosteric communication in biomolecules remains challenging, partially due to the intrinsic complexity of the systems and the lack of effective characterization methods. In this work, we introduce the eigenvector centrality metric based on mutual information to elucidate allosteric mechanisms that regulate enzymatic activity. Moreover, we propose a strategy to characterize the range of correlations that underlie the allosteric processes. We use the V-type allosteric enzyme imidazole glycerol phosphate synthase (IGPS) to test the proposed methodology. The eigenvector centrality method identifies key amino acid residues of IGPS with high susceptibility to effector binding. The findings are validated by solution NMR measurements yielding important biological insights, including direct experimental evidence for interdomain motion, the central role played by helix h[Formula: see text], and the short-range nature of correlations responsible for the allosteric mechanism. Beyond insights on IGPS allosteric pathways and the nature of residues that could be targeted by therapeutic drugs or site-directed mutagenesis, the reported findings demonstrate the eigenvector centrality analysis as a general cost-effective methodology to gain fundamental understanding of allosteric mechanisms at the molecular level.

Are the Apo Proteins Suitable for the Rational Discovery of Allosteric Drugs?

Allosteric modulators, by targeting the less-conserved allosteric sites, represent an innovative strategy in drug discovery. These modulators have a distinctive advantage over orthosteric ligands that attach to the conserved, functional orthosteric sites. However, in structure-based drug design, it remains unclear whether allosteric protein structures determined without orthosteric ligand binding are suitable for allosteric drug screening. In this study, we performed large-scale conformational samplings of six representative allosteric proteins uncomplexed ( apo) and complexed ( holo) with orthosteric ligands to explore the effect of orthosteric site binding on the conformational dynamics of allosteric sites. The results, coupled with the redocking evaluation of allosteric modulators to their apo and holo proteins using their MD trajectories, indicated that orthosteric site binding had an effect on the dynamics of the allosteric sites and allosteric modulators preferentially bound to their holo proteins. According to the analysis data, we constructed a new correlation model for quantifying the allosteric site change driven by substrate binding to the orthosteric site. These results highlight the strong demand to select holo allosteric proteins as initial inputs in structure-based allosteric drug screening when the distance between orthosteric and allosteric sites in the protein is below 5 Å, which is expected to contribute to allosteric drug discovery.

Fatty Acids Compete with Aβ in Binding to Serum Albumin by Quenching Its Conformational Flexibility

Human serum albumin (HSA) has been identified as an important regulator of amyloid-β (Aβ) fibrillization both in blood plasma and in cerebrospinal fluid. Fatty acids bind to HSA, and high serum levels of fatty acids increase the risk of Alzheimer's disease. In vitro, fatty-acid-loaded HSA (FA·HSA) loses the protective effect against Aβ fibrillization, but the mechanism underlying the interference of fatty acids on Aβ-HSA interactions has been unclear. Here, we used molecular dynamics simulations to gain atomic-level insight on the weak binding of monomeric Aβ40 and Aβ42 peptides with apo and FA·HSA. Consistent with recent NMR data, C-terminal residues of the Aβ peptides have the highest propensities for interacting with apo HSA. Interestingly, the Aβ binding residues of apo and FA·HSA exhibit distinct patterns, which qualitatively correlate with backbone flexibility. In FA·HSA, both flexibilities and Aβ binding propensities are relatively even among the three domains. In contrast, in apo HSA, domain III shows the highest flexibility and is the primary target for Aβ binding. Specifically, deformation of apo HSA creates strong binding sites within subdomain IIIb, around the interface between subdomains IIIa and IIIb, and at the cleft between domains III and I. Therefore, much like disordered proteins, HSA can take advantage of flexibility in forming promiscuous interactions with partners, until the flexibility is quenched by fatty-acid binding. Our work explains the effect of fatty acids on Aβ-HSA binding and contributes to the understanding of HSA regulation of Aβ aggregation.

Perspective: Identification of collective variables and metastable states of protein dynamics

The statistical analysis of molecular dynamics simulations requires dimensionality reduction techniques, which yield a low-dimensional set of collective variables (CVs) {x _i } = x that in some sense describe the essential dynamics of the system. Considering the distribution P( x ) of the CVs, the primal goal of a statistical analysis is to detect the characteristic features of P( x ), in particular, its maxima and their connection paths. This is because these features characterize the low-energy regions and the energy barriers of the corresponding free energy landscape ΔG( x ) = -k _B T ln P( x ), and therefore amount to the metastable states and transition regions of the system. In this perspective, we outline a systematic strategy to identify CVs and metastable states, which subsequently can be employed to construct a Langevin or a Markov state model of the dynamics. In particular, we account for the still limited sampling typically achieved by molecular dynamics simulations, which in practice seriously limits the applicability of theories (e.g., assuming ergodicity) and black-box software tools (e.g., using redundant input coordinates). We show that it is essential to use internal (rather than Cartesian) input coordinates, employ dimensionality reduction methods that avoid rescaling errors (such as principal component analysis), and perform density based (rather than k-means-type) clustering. Finally, we briefly discuss a machine learning approach to dimensionality reduction, which highlights the essential internal coordinates of a system and may reveal hidden reaction mechanisms.

Millisecond Timescale Motions Connect Amino Acid Interaction Networks in Alpha Tryptophan Synthase

Tryptophan synthase is a model system for understanding allosteric regulation within enzyme complexes. Amino acid interaction networks were previously delineated in the isolated alpha subunit (αTS) in the absence of the beta subunit (βTS). The amino acid interaction networks were different between the ligand-free enzyme and the enzyme actively catalyzing turnover. Previous X-ray crystallography studies indicated only minor localized changes when ligands bind αTS, and so, structural changes alone could not explain the changes to the amino acid interaction networks. We hypothesized that the network changes could instead be related to changes in conformational dynamics. As such, we conducted nuclear magnetic resonance relaxation studies on different substrate- and products-bound complexes of αTS. Specifically, we collected ¹⁵N R₂ relaxation dispersion data that reports on microsecond-to-millisecond timescale motion of backbone amide groups. These experiments indicated that there are conformational exchange events throughout αTS. Substrate and product binding change specific motional pathways throughout the enzyme, and these pathways connect the previously identified network residues. These pathways reach the αTS/βTS binding interface, suggesting that the identified dynamic networks may also be important for communication with the βTS subunit.

Modeling of Protein Structural Flexibility and Large-Scale Dynamics: Coarse-Grained Simulations and Elastic Network Models

Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this minireview, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions, and highly simplified structure-based elastic network models of protein flexibility. In contrast to classical all-atom molecular dynamics, the modeling strategies discussed here allow the quite accurate modeling of much larger systems and longer-time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.

Induced-fit expansion and contraction of a self-assembled nanocube finely responding to neutral and anionic guests

Induced-fit or conformational selection is of profound significance in biological regulation. Biological receptors alter their conformation to respond to the shape and electrostatic surfaces of guest molecules. Here we report a water-soluble artificial molecular host that can sensitively respond to the size, shape, and charged state of guest molecules. The molecular host, i.e. nanocube, is an assembled structure consisting of six gear-shaped amphiphiles (GSAs). This nanocube can expand or contract its size upon the encapsulation of neutral and anionic guest molecules with a volume ranging from 74 to 535 Å3 by induced-fit. The responding property of this nanocube, reminiscent of a feature of biological molecules, arises from the fact that the GSAs in the nanocubes are connected to each other only through the hydrophobic effect and very weak intermolecular interactions such as van der Waals and cation-π interactions.

Quantifying Intramolecular Protein Conformational Dynamics Under Lipid Interaction Using smFRET and FCCS

Fӧrster-type resonance energy transfer (FRET) with fluorescence cross-correlation spectroscopy (FCCS) is a powerful combination for observing intramolecular conformational dynamics on the micro- to millisecond timescale. Owing to its sensitivity to various physical parameters, FRET-FCCS has also been used to detect the reagent effects on proteins dynamics. However, FRET-FCCS alone cannot acquire the exact measurements of rate constants. Moreover, this technique is highly model dependent and can be unreliable when determining too many parameters at once. On the contrary, single-molecular FRET (smFRET) can measure the conformational states and their populations directly, although it is extremely challenging for probing fast dynamics under 1 ms. In this chapter, we describe how to realize sub-millisecond conformational dynamics measurements of a SNARE protein Ykt6 under lipid environments by smFRET and FRET-FCCS. This protocol includes sample preparation, microscope designs, data acquisition, and analysis methodology.

Thermodynamic Scaling of Interfering Hemoglobin Strain Field Waves

Hemoglobin (Hgb) forms tetramers (dimerized α-β dimers), which enhance its globular stability and may also facilitate small gas molecule transport, as shown by recent all-atom Newtonian solvated simulations. Hydropathic bioinformatic thermodynamic scaling enables close comparisons of hemoglobin dimers with myoglobin and neuroglobin, and reveals many nonlocal wave-like features of strained Hgb structures at the coarse-grained amino acid level. The thermodynamic analysis employs two hydropathic scales, one describing abrupt first-order unfolding transitions, the other continuous second-order transitions. Small molecule exchange at hemes is a first-order process. Wave-like collective tetrameric features appropriate to ligand absorption and release, seen in optical experiments (short times), are identified thermodynamically at long times. Strain fields localized near hemes interfere with extended strain fields associated with dimer interfacial misfit, resulting in novel wavelength dependent dimer correlation function Fano antiresonances.

Allosterism and signal transfer in DNA

We analysed the basic mechanisms of signal transmission in DNA and the origins of the allostery exhibited by systems such as the ternary complex BAMHI-DNA-GRDBD. We found that perturbation information generated by a primary protein binding event travels as a wave to distant regions of DNA following a hopping mechanism. However, such a structural perturbation is transient and does not lead to permanent changes in the DNA geometry and interaction properties at the secondary binding site. The BAMHI-DNA-GRDBD allosteric mechanism does not occur through any traditional models: direct (protein-protein), indirect (reorganization of the secondary site) readout or solvent-release. On the contrary, it is generated by a subtle and less common entropy-mediated mechanism, which might have an important role to explain other DNA-mediated cooperative effects.

Propagated Perturbations from a Peripheral Mutation Show Interactions Supporting WW Domain Thermostability

Inter-residue interactions stabilize protein folds and facilitate allosteric communication. Predicting which interactions are crucial and understanding why remain challenging. We highlight this through studies of a single peripheral mutation (Q33E) on the surface of the Pin1 WW domain that causes an unexpected loss of thermostability. Nuclear magnetic resonance studies attribute the loss to reorganizations of electrostatic and hydrophobic interactions, resulting in propagated conformational perturbations. The propagation demonstrates the cooperative response of Pin1 WW to external perturbations, consistent with its allosteric behavior within Pin1. Microsecond molecular dynamics simulations suggest the wild-type fold relies on couplings between a surface electrostatic network and a highly conserved hydrophobic core; Q33E directly perturbs the former, thereby disrupting the latter. These couplings suggest that predictions of mutation consequences that assume dominance of a single interaction type can be limiting, and highlight challenges in predicting protein mutational landscapes.

A computational model for controlling conformational cooperativity and function in proteins

We present a computational model that allows for rapid prediction of correlations among a set of residue pairs when the fluctuations of another set of residues are perturbed. The simple theory presented here is based on the knowledge of the fluctuation covariance matrix only. In this sense, the theory is model independent and therefore universal. Perturbation of any set of fluctuations and the resulting response of the remaining set are calculated using conditional probabilities of a multivariate normal distribution. The model is expected to rapidly and accurately map the consequences of mutations in proteins, as well as allosteric activity and ligand binding. Knowledge of triple correlations of fluctuations of residues i, j, and k, 〈 Δ R i Δ R j Δ R k 〉 emerges as the necessary source of information for controlling residue pairs by perturbing a distant residue. Triple correlations have not received wide attention in literature. Perturbation-response-function relations for ubiquitin (UBQ) are discussed as an example. Covariance matrix for UBQ obtained from the Gaussian Network Model combined with the present computational algorithm is able to reflect the millisecond molecular dynamics correlations and observed NMR results. © 2018 Wiley Periodicals, Inc.

Engineering enzyme microenvironments for enhanced biocatalysis

Protein engineering provides a means to alter protein structure leading to new functions. Much work has focused on the engineering of enzyme active sites to enhance catalytic activity, however there is an increasing trend towards engineering other aspects of biocatalysts as these efforts can also lead to useful improvements. This tutorial discusses recent advances in engineering an enzyme's local chemical and physical environment, with the goal of enhancing enzyme reaction kinetics, substrate selectivity, and activity in harsh conditions (e.g., low or high pH). By introducing stimuli-responsiveness to these enzyme modifications, dynamic control of activity also becomes possible. These new biomolecular and protein engineering techniques are separate and independent from traditional active site engineering and can therefore be applied synergistically to create new biocatalyst technologies with novel functions.

Allostery and cooperativity in multimeric proteins: bond-to-bond propensities in ATCase

Aspartate carbamoyltransferase (ATCase) is a large dodecameric enzyme with six active sites that exhibits allostery: its catalytic rate is modulated by the binding of various substrates at distal points from the active sites. A recently developed method, bond-to-bond propensity analysis, has proven capable of predicting allosteric sites in a wide range of proteins using an energy-weighted atomistic graph obtained from the protein structure and given knowledge only of the location of the active site. Bond-to-bond propensity establishes if energy fluctuations at given bonds have significant effects on any other bond in the protein, by considering their propagation through the protein graph. In this work, we use bond-to-bond propensity analysis to study different aspects of ATCase activity using three different protein structures and sources of fluctuations. First, we predict key residues and bonds involved in the transition between inactive (T) and active (R) states of ATCase by analysing allosteric substrate binding as a source of energy perturbations in the protein graph. Our computational results also indicate that the effect of multiple allosteric binding is non linear: a switching effect is observed after a particular number and arrangement of substrates is bound suggesting a form of long range communication between the distantly arranged allosteric sites. Second, cooperativity is explored by considering a bisubstrate analogue as the source of energy fluctuations at the active site, also leading to the identification of highly significant residues to the T ↔ R transition that enhance cooperativity across active sites. Finally, the inactive (T) structure is shown to exhibit a strong, non linear communication between the allosteric sites and the interface between catalytic subunits, rather than the active site. Bond-to-bond propensity thus offers an alternative route to explain allosteric and cooperative effects in terms of detailed atomistic changes to individual bonds within the protein, rather than through phenomenological, global thermodynamic arguments.

Energy transport pathway in proteins: Insights from non-equilibrium molecular dynamics with elastic network model

Intra-molecular energy transport between distant functional sites plays important roles in allosterically regulating the biochemical activity of proteins. How to identify the specific intra-molecular signaling pathway from protein tertiary structure remains a challenging problem. In the present work, a non-equilibrium dynamics method based on the elastic network model (ENM) was proposed to simulate the energy propagation process and identify the specific signaling pathways within proteins. In this method, a given residue was perturbed and the propagation of energy was simulated by non-equilibrium dynamics in the normal modes space of ENM. After that, the simulation results were transformed from the normal modes space to the Cartesian coordinate space to identify the intra-protein energy transduction pathways. The proposed method was applied to myosin and the third PDZ domain (PDZ3) of PSD-95 as case studies. For myosin, two signaling pathways were identified, which mediate the energy transductions form the nucleotide binding site to the 50 kDa cleft and the converter subdomain, respectively. For PDZ3, one specific signaling pathway was identified, through which the intra-protein energy was transduced from ligand binding site to the distant opposite side of the protein. It is also found that comparing with the commonly used cross-correlation analysis method, the proposed method can identify the anisotropic energy transduction pathways more effectively.

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'.

Allosteric Self-Assembly of Coordinating Terthiophene Amphiphile for Triggered Light Harvesting

Allosteric regulation is extensively employed by nature to achieve functional control of protein or deoxyribonucleic acid through triggered conformational change at a remote site. We report that a similar strategy can be utilized in artificial self-assembly to control the self-assembled structure and its function. We show that on binding of metal ions to the headgroup of an amphiphile TTC4L, the conformational change may lead to change of the dipole orientation of the energy donor at the chain end. This on the one hand leads to a drastically different self-assembled structure; on the other hand, it enables light harvesting between the donor-acceptor. Because the Forster resonance fluorescence transfer efficiency is gated by metal ions, controlling the feeding of metal ions allows switching on and off of light harvesting. We expect that using allosteric self-assembly, we will be able to create abundant structures with distinct function from limited molecules, which show prominent potential for the postorganic modification of the structure and function of self-assembled materials.

Signal transduction in oligoamide foldamers by selective non-covalent binding of chiral phosphates at a urea binding site

The transduction of biological signals depends on the spatial communication of conformational change. We report a synthetic mimic of this signal transduction process in which non-covalent binding induces a change in the position of equilibrium between two rapidly interconverting screw-sense conformers of a synthetic helical polyamide. Selectivity was achieved by incorporating at the N-terminus of the polyamide a urea-based anion recognition site capable of binding chiral phosphate anions. As a result of solvent-dependent binding, an induced conformational change propagates from the binding site through the amide chain, leading to a screw-sense preference detectable in the form of a chemical shift separation between two NMR active ¹³C labels. The remote induction of screw sense preference indicates successful communication of a signal originating solely from non-covalent binding.

Biotechnological and protein-engineering implications of ancestral protein resurrection

Approximations to the sequences of ancestral proteins can be derived from the sequences of their modern descendants. Proteins encoded by such reconstructed sequences can be prepared in the laboratory and subjected to experimental scrutiny. These 'resurrected' ancestral proteins often display remarkable properties, reflecting ancestral adaptations to intra-cellular and extra-cellular environments that differed from the environments hosting modern/extant proteins. Recent experimental and computational work has specifically discussed high stability, substrate and catalytic promiscuity, conformational flexibility/diversity and altered patterns of interaction with other sub-cellular components. In this review, we discuss these remarkable properties as well as recent attempts to explore their biotechnological and protein-engineering potential.

Recognition of protein allosteric states and residues: Machine learning approaches

Allostery is a process by which proteins transmit the effect of perturbation at one site to a distal functional site upon certain perturbation. As an intrinsically global effect of protein dynamics, it is difficult to associate protein allostery with individual residues, hindering effective selection of key residues for mutagenesis studies. The machine learning models including decision tree (DT) and artificial neural network (ANN) models were applied to develop classification model for a cell signaling allosteric protein with two states showing extremely similar tertiary structures in both crystallographic structures and molecular dynamics simulations. Both DT and ANN models were developed with 75% and 80% of predicting accuracy, respectively. Good agreement between machine learning models and previous experimental as well as computational studies of the same protein validates this approach as an alternative way to analyze protein dynamics simulations and allostery. In addition, the difference of distributions of key features in two allosteric states also underlies the population shift hypothesis of dynamics-driven allostery model. © 2018 Wiley Periodicals, Inc.

Direct observation of ultrafast large-scale dynamics of an enzyme under turnover conditions

The potential effect of conformational dynamics of enzymes on their chemical steps has been intensely debated recently. We use single-molecule FRET experiments on adenylate kinase (AK) to shed new light on this question. AK closes its domains to bring its two substrate close together for reaction. We show that domain closure takes only microseconds to complete, which is two orders of magnitude faster than the chemical reaction. Nevertheless, active-site mutants that reduce the rate of domain closure also reduce the reaction rate, suggesting a connection between the two phenomena. We propose that ultrafast domain closure is used by enzymes as a mechanism to optimize mutual orientation of substrates, a novel mode of coupling between conformational dynamics and catalysis.

The functional cycle of many proteins involves large-scale motions of domains and subunits. The relation between conformational dynamics and the chemical steps of enzymes remains under debate. Here we show that in the presence of substrates, domain motions of an enzyme can take place on the microsecond time scale, yet exert influence on the much-slower chemical step. We study the domain closure reaction of the enzyme adenylate kinase from Escherichia coli while in action (i.e., under turnover conditions), using single-molecule FRET spectroscopy. We find that substrate binding increases dramatically domain closing and opening times, making them as short as ∼15 and ∼45 µs, respectively. These large-scale conformational dynamics are likely the fastest measured to date, and are ∼100–200 times faster than the enzymatic turnover rate. Some active-site mutants are shown to fully or partially prevent the substrate-induced increase in domain closure times, while at the same time they also reduce enzymatic activity, establishing a clear connection between the two phenomena, despite their disparate time scales. Based on these surprising observations, we propose a paradigm for the mode of action of enzymes, in which numerous cycles of conformational rearrangement are required to find a mutual orientation of substrates that is optimal for the chemical reaction.

Programmable DNA switches and their applications

DNA switches are ideally suited for numerous nanotechnological applications, and increasing efforts are being directed toward their engineering. In this review, we discuss how to engineer these switches starting from the selection of a specific DNA-based recognition element, to its adaptation and optimisation into a switch, with applications ranging from sensing to drug delivery, smart materials, molecular transporters, logic gates and others. We provide many examples showcasing their high programmability and recent advances towards their real life applications. We conclude with a short perspective on this exciting emerging field.

Effect of ligand binding on a protein with a complex folding landscape

Ligand binding to a protein can stabilize it significantly against unfolding. The variation of the folding free energy, ΔΔG⁰, due to ligand binding can be derived from a simple reaction scheme involving exclusive binding to the native state. One obtains the following expression: , where K_d is the ligand dissociation constant and L is its concentration, R is the universal gas constant and T is the temperature. This expression has been shown to correctly describe experimental results on multiple proteins. In the current work we studied the effect of ligand binding on the stability of the multi-domain protein adenylate kinase from E. coli (AKE). Unfolding experiments were conducted using single-molecule FRET spectroscopy, which allowed us to directly obtain the fraction of unfolded protein in a model-free way from FRET efficiency histograms. Surprisingly, it was found that the effect of two inhibitors (Ap₅A and AMPPNP) and a substrate (AMP) on the stability of AKE was much smaller than expected based on K_d values obtained independently using microscale thermophoresis. To shed light on this issue, we measured the K_d for Ap₅A over a range of chemical denaturant concentrations where the protein is still folded. It was found that K_d increases dramatically over this range, likely due to the population of folding intermediates, whose binding to the ligand is much weaker than that of the native state. We propose that binding to folding intermediates may dominate the effect of ligands on the stability of multi-domain proteins, and could therefore have a strong impact on protein homeostasis in vivo.

Hinge-Shift Mechanism Modulates Allosteric Regulations in Human Pin1

Allostery, which is regulation from distant sites, plays a major role in biology. While traditional allostery is described in terms of conformational change upon ligand binding as an underlying principle, it is possible to have allosteric regulations without significant conformational change through modulating the conformational dynamics by altering the local effective elastic modulus of the protein upon ligand binding. Pin1 utilizes this dynamic allostery to regulate its function. It is a modular protein containing a WW domain and a larger peptidyl prolyl isomerase domain (PPIase) that isomerizes phosphoserine/threonine-proline (pS/TP) motifs. The WW domain serves as a docking module, whereas catalysis solely takes place within the PPIase domain. Here, we analyze the change in the dynamic flexibility profile of the PPIase domain upon ligand binding to the WW domain. Substrate binding to the WW domain induces the formation of a new rigid hinge site around the interface of the two domains and loosens the flexibility of a rigid site existing in the Apo form around the catalytic site. This hinge-shift mechanism enhances the dynamic coupling of the catalytic positions with the PPIase domain, where the rest of the domain can cooperatively respond to the local conformational changes around the catalytic site, leading to an increase in catalytic efficiency.

Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation

Charged and polar groups, through forming ion pairs, hydrogen bonds, and other less specific electrostatic interactions, impart important properties to proteins. Modulation of the charges on the amino acids, e.g., by pH and by phosphorylation and dephosphorylation, have significant effects such as protein denaturation and switch-like response of signal transduction networks. This review aims to present a unifying theme among the various effects of protein charges and polar groups. Simple models will be used to illustrate basic ideas about electrostatic interactions in proteins, and these ideas in turn will be used to elucidate the roles of electrostatic interactions in protein structure, folding, binding, condensation, and related biological functions. In particular, we will examine how charged side chains are spatially distributed in various types of proteins and how electrostatic interactions affect thermodynamic and kinetic properties of proteins. Our hope is to capture both important historical developments and recent experimental and theoretical advances in quantifying electrostatic contributions of proteins.

Dynamics changes of CRISPR-Cas9 systems induced by high fidelity mutations

CRISPR-Cas9, a powerful genome editing tool, has widely been applied in biological fields.

Proline hydroxylation at different sites in hypoxia-inducible factor 1α modulates its interactions with the von Hippel–Lindau tumor suppressor protein

Proline hydroxylation of HIF-1α affects the interaction affinity between pVHL and HIF-1α and allosterically induces the conformational change of pVHL.

Atomistic simulations and network-based modeling of the Hsp90-Cdc37 chaperone binding with Cdk4 client protein: A mechanism of chaperoning kinase clients by exploiting weak spots of intrinsically dynamic kinase domains

A fundamental role of the Hsp90 and Cdc37 chaperones in mediating conformational development and activation of diverse protein kinase clients is essential in signal transduction. There has been increasing evidence that the Hsp90-Cdc37 system executes its chaperoning duties by recognizing conformational instability of kinase clients and modulating their folding landscapes. The recent cryo-electron microscopy structure of the Hsp90-Cdc37-Cdk4 kinase complex has provided a framework for dissecting regulatory principles underlying differentiation and recruitment of protein kinase clients to the chaperone machinery. In this work, we have combined atomistic simulations with protein stability and network-based rigidity decomposition analyses to characterize dynamic factors underlying allosteric mechanism of the chaperone-kinase cycle and identify regulatory hotspots that control client recognition. Through comprehensive characterization of conformational dynamics and systematic identification of stabilization centers in the unbound and client- bound Hsp90 forms, we have simulated key stages of the allosteric mechanism, in which Hsp90 binding can induce instability and partial unfolding of Cdk4 client. Conformational landscapes of the Hsp90 and Cdk4 structures suggested that client binding can trigger coordinated dynamic changes and induce global rigidification of the Hsp90 inter-domain regions that is coupled with a concomitant increase in conformational flexibility of the kinase client. This process is allosteric in nature and can involve reciprocal dynamic exchanges that exert global effect on stability of the Hsp90 dimer, while promoting client instability. The network-based rigidity analysis and emulation of thermal unfolding of the Cdk4-cyclin D complex and Hsp90-Cdc37-Cdk4 complex revealed weak spots of kinase instability that are present in the native Cdk4 structure and are targeted by the chaperone during client recruitment. Our findings suggested that this mechanism may be exploited by the Hsp90-Cdc37 chaperone to recruit and protect intrinsically dynamic kinase clients from degradation. The results of this investigation are discussed and interpreted in the context of diverse experimental data, offering new insights into mechanisms of chaperone regulation and binding.

Insights on the conformational dynamics of human frataxin through modifications of loop-1

Human frataxin (FXN) is a highly conserved mitochondrial protein involved in iron homeostasis and activation of the iron-sulfur cluster assembly. FXN deficiency causes the neurodegenerative disease Friedreich's Ataxia. Here, we investigated the effect of alterations in loop-1, a stretch presumably essential for FXN function, on the conformational stability and dynamics of the native state. We generated four loop-1 variants, carrying substitutions, insertions and deletions. All of them were stable and well-folded proteins. Fast local motions (ps-ns) and slower long-range conformational dynamics (μs-ms) were altered in some mutants as judged by NMR. Particularly, loop-1 modifications impact on the dynamics of a distant region that includes residues from the β-sheet, helix α1 and the C-terminal. Remarkably, all the mutants retain the ability to activate cysteine desulfurase, even when two of them exhibit a strong decrease in iron binding, revealing a differential sensitivity of these functional features to loop-1 perturbation. Consequently, we found that even for a small and relatively rigid protein, engineering a loop segment enables to alter conformational dynamics through a long-range effect, preserving the native-state structure and important aspects of function.

Role of Conformational Dynamics in the Evolution of Retro-Aldolase Activity

Enzymes exist as ensembles of conformations that are important for function. Tuning these populations of conformational states through mutation enables evolution toward additional activities. Here we computationally evaluate the population shifts induced by distal and active site mutations in a family of computationally designed and experimentally optimized retro-aldolases. The conformational landscape of these enzymes was significantly altered during evolution, as pre-existing catalytically active conformational substates became major states in the most evolved variants. We further demonstrate that key residues responsible for these substate conversions can be predicted computationally. Significantly, the identified residues coincide with those positions mutated in the laboratory evolution experiments. This study establishes that distal mutations that affect enzyme catalytic activity can be predicted computationally and thus provides the enzyme (re)design field with a rational strategy to determine promising sites for enhancing activity through mutation.

Ensemble- and Rigidity Theory-Based Perturbation Approach To Analyze Dynamic Allostery

Allostery describes the functional coupling between sites in biomolecules. Recently, the role of changes in protein dynamics for allosteric communication has been highlighted. A quantitative and predictive description of allostery is fundamental for understanding biological processes. Here, we integrate an ensemble-based perturbation approach with the analysis of biomolecular rigidity and flexibility to construct a model of dynamic allostery. Our model, by definition, excludes the possibility of conformational changes, evaluates static, not dynamic, properties of molecular systems, and describes allosteric effects due to ligand binding in terms of a novel free-energy measure. We validated our model on three distinct biomolecular systems: eglin c, protein tyrosine phosphatase 1B, and the lymphocyte function-associated antigen 1 domain. In all cases, it successfully identified key residues for signal transmission in very good agreement with the experiment. It correctly and quantitatively discriminated between positively or negatively cooperative effects for one of the systems. Our model should be a promising tool for the rational discovery of novel allosteric drugs.

Decomposing Dynamical Couplings in Mutated scFv Antibody Fragments into Stabilizing and Destabilizing Effects

Conformational fluctuations within scFv antibodies are characterized by a novel perturbation-response decomposition of molecular dynamics trajectories. Both perturbation and response profiles are stratified into stabilizing and destabilizing conditions. The linker between the VH and VL domains exhibits the dominant dynamical response by being coupled to nearly the entire protein, responding to both stabilizing and destabilizing perturbations. Perturbations within complementarity-determining regions (CDR) induce rich behavior in dynamic response. Among many effects, stabilizing any CDR loop in the VH domain triggers a destabilizing response in all CDR loops in the VL domain and vice versa. Destabilizing residues within the VL domain are likely to stabilize all CDR loops in the VH domain, and, when these residues are not buried, the CDR loops in the VL domain are also likely to be stabilized. These effects, described by shifts in normal mode characteristics, initiate a propensity for dynamic allostery with possible functional implications in bispecific antibodies.

Allosteric fine-tuning of the conformational equilibrium poises the chaperone BiP for post-translational regulation

BiP is the only Hsp70 chaperone in the endoplasmic reticulum (ER) and similar to other Hsp70s, its activity relies on nucleotide- and substrate-controllable docking and undocking of its nucleotide-binding domain (NBD) and substrate-binding domain (SBD). However, little is known of specific features of the BiP conformational landscape that tune BiP to its unique tasks and the ER environment. We present methyl NMR analysis of the BiP chaperone cycle that reveals surprising conformational heterogeneity of ATP-bound BiP that distinguishes BiP from its bacterial homologue DnaK. This unusual poise enables gradual post-translational regulation of the BiP chaperone cycle and its chaperone activity by subtle local perturbations at SBD allosteric 'hotspots'. In particular, BiP inactivation by AMPylation of its SBD does not disturb Hsp70 inter-domain allostery and preserves BiP structure. Instead it relies on a redistribution of the BiP conformational ensemble and stabilization the domain-docked conformation in presence of ADP and ATP.

An engineered photoswitchable mammalian pyruvate kinase

Changes in allosteric regulation of glycolytic enzymes have been linked to metabolic reprogramming involved in cancer. Remarkably, allosteric mechanisms control enzyme function at significantly shorter time-scales compared to the long-term effects of metabolic reprogramming on cell proliferation. It remains unclear if and how the speed and reversibility afforded by rapid allosteric control of metabolic enzymes is important for cell proliferation. Tools that allow specific, dynamic modulation of enzymatic activities in mammalian cells would help address this question. Towards this goal, we have used molecular dynamics simulations to guide the design of mPKM2 internal light/oxygen/voltage-sensitive domain 2 (LOV2) fusion at position D24 (PiL[D24]), an engineered pyruvate kinase M2 (PKM2) variant that harbours an insertion of the light-sensing LOV2 domain from Avena Sativa within a region implicated in allosteric regulation by fructose 1,6-bisphosphate (FBP). The LOV2 photoreaction is preserved in the PiL[D24] chimera and causes secondary structure changes that are associated with a 30% decrease in the Km of the enzyme for phosphoenolpyruvate resulting in increased pyruvate kinase activity after light exposure. Importantly, this change in activity is reversible upon light withdrawal. Expression of PiL[D24] in cells leads to light-induced increase in labelling of pyruvate from glucose. PiL[D24] therefore could provide a means to modulate cellular glucose metabolism in a remote manner and paves the way for studying the importance of rapid allosteric phenomena in the regulation of metabolism and enzyme control.

Protein Assembly and Building Blocks: Beyond the Limits of the LEGO Brick Metaphor

Proteins, like other biomolecules, have a modular and hierarchical structure. Various building blocks are used to construct proteins of high structural complexity and diverse functionality. In multidomain proteins, for example, domains are fused to each other in different combinations to achieve different functions. Although the LEGO brick metaphor is justified as a means of simplifying the complexity of three-dimensional protein structures, several fundamental properties (such as allostery or the induced-fit mechanism) make deviation from it necessary to respect the plasticity, softness, and cross-talk that are essential to protein function. In this work, we illustrate recently reported protein behavior in multidomain proteins that deviates from the LEGO brick analogy. While earlier studies showed that a protein domain is often unaffected by being fused to another domain or becomes more stable following the formation of a new interface between the tethered domains, destabilization due to tethering has been reported for several systems. We illustrate that tethering may sometimes result in a multidomain protein behaving as "less than the sum of its parts". We survey these cases for which structure additivity does not guarantee thermodynamic additivity. Protein destabilization due to fusion to other domains may be linked in some cases to biological function and should be taken into account when designing large assemblies.

Characterization of Chemical Exchange Using Relaxation Dispersion of Hyperpolarized Nuclear Spins

Chemical exchange phenomena are ubiquitous in macromolecules, which undergo conformational change or ligand complexation. NMR relaxation dispersion (RD) spectroscopy based on a Carr-Purcell-Meiboom-Gill pulse sequence is widely applied to identify the exchange and measure the lifetime of intermediate states on the millisecond time scale. Advances in hyperpolarization methods improve the applicability of NMR spectroscopy when rapid acquisitions or low concentrations are required, through an increase in signal strength by several orders of magnitude. Here, we demonstrate the measurement of chemical exchange from a single aliquot of a ligand hyperpolarized by dissolution dynamic nuclear polarization (D-DNP). Transverse relaxation rates are measured simultaneously at different pulsing delays by dual-channel ¹⁹F NMR spectroscopy. This two-point measurement is shown to allow the determination of the exchange term in the relaxation rate expression. For the ligand 4-(trifluoromethyl)benzene-1-carboximidamide binding to the protein trypsin, the exchange term is found to be equal within error limits in neutral and acidic environments from D-DNP NMR spectroscopy, corresponding to a pre-equilibrium of trypsin deprotonation. This finding illustrates the capability for determination of binding mechanisms using D-DNP RD. Taking advantage of hyperpolarization, the ligand concentration in the exchange measurements can reach on the order of tens of μM and protein concentration can be below 1 μM, i.e., conditions typically accessible in drug discovery.

Protospacer Adjacent Motif-Induced Allostery Activates CRISPR-Cas9

CRISPR-Cas9 is a genome editing technology with major impact in life sciences. In this system, the endonuclease Cas9 generates double strand breaks in DNA upon RNA-guided recognition of a complementary DNA sequence, which strictly requires the presence of a protospacer adjacent motif (PAM) next to the target site. Although PAM recognition is essential for cleavage, it is unknown whether and how PAM binding activates Cas9 for DNA cleavage at spatially distant sites. Here, we find evidence of a PAM-induced allosteric mechanism revealed by microsecond molecular dynamics simulations. PAM acts as an allosteric effector and triggers the interdependent conformational dynamics of the Cas9 catalytic domains (HNH and RuvC), responsible for concerted cleavage of the two DNA strands. Targeting such an allosteric mechanism should enable control of CRISPR-Cas9 functionality.

Molecular Dynamics Information Improves cis-Peptide-Based Function Annotation of Proteins

cis-Peptide bonds, whose occurrence in proteins is rare but evolutionarily conserved, are implicated to play an important role in protein function. This has led to their previous use in a homology-independent, fragment-match-based protein function annotation method. However, proteins are not static molecules; dynamics is integral to their activity. This is nicely epitomized by the geometric isomerization of cis-peptide to trans form for molecular activity. Hence we have incorporated both static (cis-peptide) and dynamics information to improve the prediction of protein molecular function. Our results show that cis-peptide information alone cannot detect functional matches in cases where cis-trans isomerization exists but 3D coordinates have been obtained for only the trans isomer or when the cis-peptide bond is incorrectly assigned as trans. On the contrary, use of dynamics information alone includes false-positive matches for cases where fragments with similar secondary structure show similar dynamics, but the proteins do not share a common function. Combining the two methods reduces errors while detecting the true matches, thereby enhancing the utility of our method in function annotation. A combined approach, therefore, opens up new avenues of improving existing automated function annotation methodologies.

Time-resolved observation of protein allosteric communication

Allostery represents a fundamental mechanism of biological regulation that is mediated via long-range communication between distant protein sites. Although little is known about the underlying dynamical process, recent time-resolved infrared spectroscopy experiments on a photoswitchable PDZ domain (PDZ2S) have indicated that the allosteric transition occurs on multiple timescales. Here, using extensive nonequilibrium molecular dynamics simulations, a time-dependent picture of the allosteric communication in PDZ2S is developed. The simulations reveal that allostery amounts to the propagation of structural and dynamical changes that are genuinely nonlinear and can occur in a nonlocal fashion. A dynamic network model is constructed that illustrates the hierarchy and exceeding structural heterogeneity of the process. In compelling agreement with experiment, three physically distinct phases of the time evolution are identified, describing elastic response ([Formula: see text] ns), inelastic reorganization ([Formula: see text] ns), and structural relaxation ([Formula: see text]s). Issues such as the similarity to downhill folding as well as the interpretation of allosteric pathways are discussed.

In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function

Small molecules, such as solvent, substrate, and cofactor molecules, are key players in enzyme catalysis. Computational methods are powerful tools for exploring the dynamics and thermodynamics of these small molecules as they participate in or contribute to enzymatic processes. In-depth knowledge of how small molecule interactions and dynamics influence protein conformational dynamics and function is critical for progress in the field of enzyme catalysis. Although numerous computational studies have focused on enzyme-substrate complexes to gain insight into catalytic mechanisms, transition states and reaction rates, the dynamics of solvents, substrates, and cofactors are generally less well studied. Also, solvent dynamics within the biomolecular solvation layer play an important part in enzyme catalysis, but a full understanding of its role is hampered by its complexity. Moreover, passive substrate transport has been identified in certain enzymes, and the underlying principles of molecular recognition are an area of active investigation. Enzymes are highly dynamic entities that undergo different conformational changes, which range from side chain rearrangement of a residue to larger-scale conformational dynamics involving domains. These events may happen nearby or far away from the catalytic site, and may occur on different time scales, yet many are related to biological and catalytic function. Computational studies, primarily molecular dynamics (MD) simulations, provide atomistic-level insight and site-specific information on small molecule interactions, and their role in conformational pre-reorganization and dynamics in enzyme catalysis. The review is focused on MD simulation studies of small molecule interactions and dynamics to characterize and comprehend protein dynamics and function in catalyzed reactions. Experimental and theoretical methods available to complement and expand insight from MD simulations are discussed briefly.