Binding sites in Escherichia coli dihydrofolate reductase communicate by modulating the conformational ensemble

Interpretation of Hydrogen/Deuterium Exchange Mass Spectrometry

This paper sheds light on the meaning of hydrogen/deuterium exchange-mass spectrometry (HDX-MS) data. HDX-MS data provide not structural information but dynamic information on an analyte protein. First, the reaction mechanism of backbone amide HDX reaction is considered and the correlation between the parameters from an X-ray crystal structure and the protection factors of HDX reactions of cytochrome c is evaluated. The presence of H-bonds in a protein structure has a strong influence on HDX rates which represent protein dynamics, while the solvent accessibility only weakly affects the HDX rates. Second, the energy diagrams of the HDX reaction at each residue in the presence and absence of perturbation are described. Whereas the free energy change upon mutation can be directly measured by the HDX rates, the free energy change upon ligand binding may be complicated due to the presence of unbound analyte protein in the protein-ligand mixture. Third, the meanings of HDX and other biophysical techniques are explained using a hypothetical protein folding well. The shape of the protein folding well describes the protein dynamics and provides Boltzmann distribution of open and closed states which yield HDX protection factors, while a protein's crystal structure represents a snapshot near the bottom of the well. All biophysical data should be consistent yet provide different information because they monitor different parts of the same protein folding well.

A cell-free antigen processing system informs HIV-1 epitope selection and vaccine design

Distinct CD4+ T cell epitopes have been associated with spontaneous control of HIV-1 replication, but analysis of antigen-dependent factors that influence epitope selection is lacking. To examine these factors, we used a cell-free antigen processing system that incorporates soluble HLA-DR (DR1), HLA-DM (DM), cathepsins, and full-length protein antigens for epitope identification by LC-MS/MS. HIV-1 Gag, Pol, Env, Vif, Tat, Rev, and Nef were examined using this system. We identified 35 novel epitopes, including glycopeptides. Epitopes from smaller HIV-1 proteins mapped to regions of low protein stability and higher solvent accessibility. HIV-1 antigens associated with limited CD4+ T cell responses were processed efficiently, while some protective epitopes were inefficiently processed. 55% of epitopes obtained from cell-free processing induced memory CD4+ T cell responses in HIV-1+ donors, including eight of 19 novel epitopes tested. Thus, an in vitro processing system utilizing the components of Class II processing reveals factors influencing epitope selection of HIV-1 and represents an approach to understanding epitope selection from non-HIV-1 antigens.

Ligand-specific changes in conformational flexibility mediate long-range allostery in the lac repressor

Biological regulation ubiquitously depends on protein allostery, but the regulatory mechanisms are incompletely understood, especially in proteins that undergo ligand-induced allostery with few structural changes. Here we used hydrogen-deuterium exchange with mass spectrometry (HDX/MS) to map allosteric effects in a paradigm ligand-responsive transcription factor, the lac repressor (LacI), in different functional states (apo, or bound to inducer, anti-inducer, and/or DNA). Although X-ray crystal structures of the LacI core domain in these states are nearly indistinguishable, HDX/MS experiments reveal widespread differences in flexibility. We integrate these results with modeling of protein-ligand-solvent interactions to propose a revised model for allostery in LacI, where ligand binding allosterically shifts the conformational ensemble as a result of distinct changes in the rigidity of secondary structures in the different states. Our model provides a mechanistic basis for the altered function of distal mutations. More generally, our approach provides a platform for characterizing and engineering protein allostery.

Molecular Dynamics Simulations Establish the Molecular Basis for the Broad Allostery Hotspot Distributions in the Tetracycline Repressor

It is imperative to identify the network of residues essential to the allosteric coupling for the purpose of rationally engineering allostery in proteins. Deep mutational scanning analysis has emerged as a function-centric approach for identifying such allostery hotspots in a comprehensive and unbiased fashion, leading to observations that challenge our understanding of allostery at the molecular level. Specifically, a recent deep mutational scanning study of the tetracycline repressor (TetR) revealed an unexpectedly broad distribution of allostery hotspots throughout the protein structure. Using extensive molecular dynamics simulations (up to 50 μs) and free energy computations, we establish the molecular and energetic basis for the strong anticooperativity between the ligand and DNA binding sites. The computed free energy landscapes in different ligation states illustrate that allostery in TetR is well described by a conformational selection model, in which the apo state samples a broad set of conformations, and specific ones are selectively stabilized by either ligand or DNA binding. By examining a range of structural and dynamic properties of residues at both local and global scales, we observe that various analyses capture different subsets of experimentally identified hotspots, suggesting that these residues modulate allostery in distinct ways. These results motivate the development of a thermodynamic model that qualitatively explains the broad distribution of hotspot residues and their distinct features in molecular dynamics simulations. The multifaceted strategy that we establish here for hotspot evaluations and our insights into their mechanistic contributions are useful for modulating protein allostery in mechanistic and engineering studies.

Computational Modeling of Molecular Structures Guided by Hydrogen-Exchange Data

Data produced by hydrogen-exchange monitoring experiments have been used in structural studies of molecules for several decades. Despite uncertainties about the structural determinants of hydrogen exchange itself, such data have successfully helped guide the structural modeling of challenging molecular systems, such as membrane proteins or large macromolecular complexes. As hydrogen-exchange monitoring provides information on the dynamics of molecules in solution, it can complement other experimental techniques in so-called integrative modeling approaches. However, hydrogen-exchange data have often only been used to qualitatively assess molecular structures produced by computational modeling tools. In this paper, we look beyond qualitative approaches and survey the various paradigms under which hydrogen-exchange data have been used to quantitatively guide the computational modeling of molecular structures. Although numerous prediction models have been proposed to link molecular structure and hydrogen exchange, none of them has been widely accepted by the structural biology community. Here, we present as many hydrogen-exchange prediction models as we could find in the literature, with the aim of providing the first exhaustive list of its kind. From purely structure-based models to so-called fractional-population models or knowledge-based models, the field is quite vast. We aspire for this paper to become a resource for practitioners to gain a broader perspective on the field and guide research toward the definition of better prediction models. This will eventually improve synergies between hydrogen-exchange monitoring and molecular modeling.

A thermodynamic atlas of proteomes reveals energetic innovation across the tree of life

Protein stability is a fundamental molecular property enabling organisms to adapt to their biological niches. How this is facilitated and whether there are kingdom specific or more general universal strategies is not known. A principal obstacle to addressing this issue is that the vast majority of proteins lack annotation, specifically thermodynamic annotation, beyond the amino acid and chromosome information derived from genome sequencing. To address this gap and facilitate future investigation into large-scale patterns of protein stability and dynamics within and between organisms, we applied a unique ensemble-based thermodynamic characterization of protein folds to a substantial portion of extant sequenced genomes. Using this approach, we compiled a database resource focused on the position-specific variation in protein stability. Interrogation of the database reveals; 1) domains of life exhibit distinguishing thermodynamic features, with eukaryotes particularly different from both archaea and bacteria, 2) the optimal growth temperature of an organism is proportional to the average apolar enthalpy of its proteome, 3) intrinsic disorder content is also proportional to the apolar enthalpy (but unexpectedly not the predicted stability at 25 °C), and 4) secondary structure and global stability information of individual proteins is extractable. We hypothesize that wider access to residue-specific thermodynamic information of proteomes will result in deeper understanding of mechanisms driving functional adaptation and protein evolution. Our database is free for download at https://afc-science.github.io/thermo-env-atlas/.

Signal Transmission in Escherichia coli Cyclic AMP Receptor Protein for Survival in Extreme Acidic Conditions

During the life cycle of enteric bacterium Escherichia coli, it encounters a wide spectrum of pH changes. The asymmetric dimer of the cAMP receptor protein, CRP, plays a key role in regulating the expressions of genes and the survival of E. coli. To elucidate the pH effects on the mechanism of signal transmission, we present a combination of results derived from ITC, crystallography, and computation. CRP responds to a pH change by inducing a differential effect on the affinity for the binding events to the two cAMP molecules, ensuing in a reversible conversion between positive and negative cooperativity at high and low pH, respectively. The structures of four crystals at pH ranging from 7.8 to 6.5 show that CRP responds by inducing a differential effect on the structures of the two subunits, particularly in the DNA binding domain. Employing the COREX/BEST algorithm, computational analysis shows the change in the stability of residues at each pH. The change in residue stability alters the connectivity between residues including those in cAMP and DNA binding sites. Consequently, the differential impact on the topology of the connectivity surface among residues in adjacent subunits is the main reason for differential change in affinity; that is, the pH-induced differential change in residue stability is the biothermodynamic basis for the change in allosteric behavior. Furthermore, the structural asymmetry of this homodimer amplifies the differential impact of any perturbations. Hence, these results demonstrate that the combination of these approaches can provide insights into the underlying mechanism of an apparent complex allostery signal and transmission in CRP.

Ligand Binding Introduces Significant Allosteric Shifts in the Locations of Protein Fluctuations

Allostery is usually considered to be a mechanism for transmission of signals associated with physical or dynamic changes in some part of a protein. Here, we investigate the changes in fluctuations across the protein upon ligand binding based on the fluctuations computed with elastic network models. These results suggest that binding reduces the fluctuations at the binding site but increases fluctuations at remote sites, but not to fully compensating extents. If there were complete conservation of entropy, then only the enthalpies of binding would matter and not the entropies; however this does not appear to be the case. Experimental evidence also suggests that energies and entropies of binding can compensate but that the extent of compensation varies widely from case to case. Our results do however always show transmission of an allosteric signal to distant locations where the fluctuations are increased. These fluctuations could be used to compute entropies to improve evaluations of the thermodynamics of binding. We also show the allosteric relationship between peptide binding in the GroEL trans-ring that leads directly to the release of GroES from the GroEL-GroES cis-ring. This finding provides an example of how calculating these changes to protein dynamics induced by the binding of an allosteric ligand can regulate protein function and mechanism.

Structural and Energetic Characterization of the Denatured State from the Perspectives of Peptides, the Coil Library, and Intrinsically Disordered Proteins

The α and polyproline II (PPII) basins are the two most populated regions of the Ramachandran map when constructed from the protein coil library, a widely used denatured state model built from the segments of irregular structure found in the Protein Data Bank. This indicates the α and PPII conformations are dominant components of the ensembles of denatured structures that exist in solution for biological proteins, an observation supported in part by structural studies of short, and thus unfolded, peptides. Although intrinsic conformational propensities have been determined experimentally for the common amino acids in short peptides, and estimated from surveys of the protein coil library, the ability of these intrinsic conformational propensities to quantitatively reproduce structural behavior in intrinsically disordered proteins (IDPs), an increasingly important class of proteins in cell function, has thus far proven elusive to establish. Recently, we demonstrated that the sequence dependence of the mean hydrodynamic size of IDPs in water and the impact of heat on the coil dimensions, provide access to both the sequence dependence and thermodynamic energies that are associated with biases for the α and PPII backbone conformations. Here, we compare results from peptide-based studies of intrinsic conformational propensities and surveys of the protein coil library to those of the sequence-based analysis of heat effects on IDP hydrodynamic size, showing that a common structural and thermodynamic description of the protein denatured state is obtained.

Allosteric Modulation of Neurotransmitter Transporters as a Therapeutic Strategy

Neurotransmitter transporters (NTTs) are involved in the fine-tuning of brain neurotransmitter homeostasis. As such, they are implicated in a plethora of complex behaviors, including reward, movement, and cognition. During recent decades, compounds that modulate NTT functions have been developed. Some of them are in clinical use for the management of different neuropsychiatric conditions. The majority of these compounds have been found to selectively interact with the orthosteric site of NTTs. Recently, diverse allosteric sites have been described in a number of NTTs, modulating their function. A more complex NTT pharmacology may be useful in the development of novel therapeutics. Here, we summarize current knowledge on such modulatory allosteric sites, with specific focus on their pharmacological and therapeutic potential.

Identification of Alternative Allosteric Sites in Glycolytic Enzymes for Potential Use as Species-Specific Drug Targets

Three allosteric glycolytic enzymes, phosphofructokinase, glyceraldehyde-3 phosphate dehydrogenase and pyruvate kinase, associated with bacterial, parasitic and human species, were explored to identify potential allosteric sites that would be used as prime targets for species-specific drug design purposes using a newly developed approach which incorporates solvent mapping, elastic network modeling, sequence and structural alignments. The majority of binding sites detected by solvent mapping overlapped with the interface regions connecting the subunits, thus appeared as promising target sites for allosteric regulation. Each binding site was then evaluated by its ability to alter the global dynamics of the receptor defined by the percentage change in the frequencies of the lowest-frequency modes most significantly and as anticipated, the most effective ones were detected in the vicinity of the well-reported catalytic and allosteric sites. Furthermore, some of our proposed regions intersected with experimentally resolved sites which are known to be critical for activity regulation, which further validated our approach. Despite the high degree of structural conservation encountered between bacterial/parasitic and human glycolytic enzymes, the majority of the newly presented allosteric sites exhibited a low degree of sequence conservation which further increased their likelihood to be used as species-specific target regions for drug design studies.

Structural Energy Landscapes and Plasticity of the Microstates of Apo Escherichia coli cAMP Receptor Protein

The theory for allostery has evolved to a modern energy landscape ensemble theory, the major feature of which is the existence of multiple microstates in equilibrium. The properties of microstates are not well defined due to their transient nature. Characterization of apo protein microstates is important because the specific complex of the ligand-bound microstate defines the biological function. The information needed to link biological function and structure is a quantitative correlation of the energy landscapes between the apo and holo protein states. We employed the Escherichia coli cAMP receptor protein (CRP) system to test the features embedded in the ensemble theory because multiple crystalline apo and holo structures are available. Small angle X-ray scattering data eliminated one of the three apo states but not the other two. We defined the underlying energy landscape differences among the apo microstates by employing the computation algorithm COREX/BEST. The same connectivity patterns among residues in apo CRP are retained upon binding of cAMP. The microstates of apo CRP differ from one another by minor structural perturbations, resulting in changes in the energy landscapes of the various domains of CRP. Using the differences in energy landscapes among these apo states, we computed the cAMP binding energetics that were compared with solution biophysical results. Only one of the three apo microstates yielded data consistent with the solution data. The relative magnitude of changes in energy landscapes embedded in various apo microstates apparently defines the ultimate outcome of the cooperativity of binding.

Differential modulation of energy landscapes of cyclic AMP receptor protein (CRP) as a regulatory mechanism for class II CRP-dependent promoters

The Escherichia coli cAMP receptor protein, CRP, is a homodimeric global transcription activator that employs multiple mechanisms to modulate the expression of hundreds of genes. These mechanisms require different interfacial interactions among CRP, RNA, and DNA of varying sequences. The involvement of such a multiplicity of interfaces requires a tight control to ensure the desired phenotype. CRP-dependent promoters can be grouped into three classes. For decades scientists in the field have been puzzled over the differences in mechanisms between class I and II promoters. Using a new crystal structure, IR spectroscopy, and computational analysis, we defined the energy landscapes of WT and 14 mutated CRPs to determine how a homodimeric protein can distinguish nonpalindromic DNA sequences and facilitate communication between residues located in three different activation regions (AR) in CRP that are ∼30 Å apart. We showed that each mutation imparts differential effects on stability among the subunits and domains in CRP. Consequently, the energetic landscapes of subunits and domains are different, and CRP is asymmetric. Hence, the same mutation can exert different effects on ARs in class I or II promoters. The effect of a mutation is transmitted through a network by long-distance communication not necessarily relying on physical contacts between adjacent residues. The mechanism is simply the sum of the consequences of modulating the synchrony of dynamic motions of residues at a distance, leading to differential effects on ARs in different subunits. The computational analysis is applicable to any system and potentially with predictive capability.

Networked Communication between Polymerase and Exonuclease Active Sites in Human Mitochondrial DNA Polymerase

High fidelity human mitochondrial DNA polymerase (Pol γ) contains two active sites, a DNA polymerization site (pol) and a 3'-5' exonuclease site (exo) for proofreading. Although separated by 35 Å, coordination between the pol and exo sites is crucial to high fidelity replication. The biophysical mechanisms for this coordination are not completely understood. To understand the communication between the two active sites, we used a statistical-mechanical model of the protein ensemble to calculate the energetic landscape and local stability. We compared a series of structures of Pol γ, complexed with primer/template DNA, and either a nucleotide substrate or a series of nucleotide analogues, which are differentially incorporated and excised by pol and exo activity. Despite the nucleotide or its analogues being bound in the pol, Pol γ residue stability varied across the protein, particularly in the exo domain. This suggests that substrate presence in the pol can be "sensed" in the exo domain. Consistent with this hypothesis, in silico mutations made in one active site mutually perturbed the energetics of the other. To identify specific regions of the polymerase that contributed to this communication, we constructed an allosteric network connectivity map that further demonstrates specific pol-exo cooperativity. Thus, a cooperative network underlies energetic connectivity. We propose that Pol γ and other dual-function polymerases exploit an energetic coupling network that facilitates domain-domain communication to enhance discrimination between correct and incorrect nucleotides.

Molecular Dynamics Simulations of the Allosteric Modulation of the Adenosine A2A Receptor by a Mini-G Protein

Through their coupling to G proteins, G Protein-Coupled Receptors (GPCRs) trigger cellular responses to various signals. Some recent experiments have interestingly demonstrated that the G protein can also act on the receptor by favoring a closed conformation of its orthosteric site, even in the absence of a bound agonist. In this work, we explored such an allosteric modulation by performing extensive molecular dynamics simulations on the adenosine A2 receptor (A2aR) coupled to the Mini-Gs protein. In the presence of the Mini-Gs, we confirmed a restriction of the receptor’s agonist binding site that can be explained by a modulation of the intrinsic network of contacts of the receptor. Of interest, we observed similar effects with the C-terminal helix of the Mini-Gs, showing that the observed effect on the binding pocket results from direct local contacts with the bound protein partner that cause a rewiring of the whole receptor’s interaction network.

Identifying coupled clusters of allostery participants through chemical shift perturbations

Allosteric couplings underlie many cellular signaling processes and provide an exciting avenue for development of new diagnostics and therapeutics. A general method for identifying important residues in allosteric mechanisms would be very useful, but remains elusive due to the complexity of long-range phenomena. Here, we introduce an NMR method to identify residues involved in allosteric coupling between two ligand-binding sites in a protein, which we call chemical shift detection of allostery participants (CAP). Networks of functional groups responding to each ligand are defined through correlated NMR perturbations. In this process, we also identify allostery participants, groups that respond to both binding events and likely play a role in the coupling between the binding sites. Such residues exhibit multiple functional states with distinct NMR chemical shifts, depending on binding status at both binding sites. Such a strategy was applied to the prototypical ion channel KcsA. We had previously shown that the potassium affinity at the extracellular selectivity filter is strongly dependent on proton binding at the intracellular pH sensor. Here, we analyzed proton and potassium binding networks and identified groups that depend on both proton and potassium binding (allostery participants). These groups are viewed as candidates for transmitting information between functional units. The vital role of one such identified amino acid was validated through site-specific mutagenesis, electrophysiology functional studies, and NMR-detected thermodynamic analysis of allosteric coupling. This strategy for identifying allostery participants is likely to have applications for many other systems.

Effect of Asp122 Mutation on the Hydride Transfer in E. coli DHFR Demonstrates the Goldilocks of Enzyme Flexibility

Dihydrofolate reductase (DHFR) catalyzes the reduction of dihydrofolate (DHF) to tetrahydrofolate (THF) in the presence of NADPH. The key hydride transfer step in the reaction is facilitated by a combination of enzyme active site preorganization and correlated protein motions in the Michaelis-Menten (E:NADPH:DHF) complex. The present theoretical study employs mutagenesis to examine the relation between structural and functional properties of the enzyme. We mutate Asp122 in Escherichia coli DHFR, which is a conserved amino acid in the DHFR family. The consequent effect of the mutation on enzyme catalysis is examined from an energetic, structural and short-time dynamic perspective. Our investigations suggest that the structural and short-time dynamic perturbations caused by Asp122X mutations (X = Asn, Ser, Ala) are along the reaction coordinate and lower the rate of hydride transfer. Importantly, analysis of the correlated and principle component motions in the enzyme suggest that the mutation alters the coupled motions that are present in the wild-type enzyme. In the case of D122N and D122S, the mutations inhibit coupled motion, whereas in the case of D122A, the mutation enhances coupled motion, although all mutations result in similar rate reduction. These results emphasize a Goldilocks principle of enzyme flexibility, that is, enzymes should neither be too rigid nor too flexible.

Evolutionarily Related Dihydrofolate Reductases Perform Coequal Functions Yet Show Divergence in Their Trajectories

The enzyme dihydrofolate reductase (DHFR) catalyzes NADPH dependent reduction of dihydrofolate to tetrahydrofolate. It plays a crucial role in the DNA synthesis. The investigation of evolution of DHFR generates immense curiosity. It aids in predicting how the enzyme has adapted to the surroundings of various cell types. In spite of great similarity in the structure of E. coli DHFR and human DHFR, their primary sequences are divergent to a great extent, which is evident in variations in the kinetics mechanism of their catalysis. In presence of physiological levels of ligands, they possess distinct kinetics and different rate limiting steps. We have reviewed the process of their unfolding and refolding, their behaviour in denaturing conditions and in presence of various chaperones. Although there is structural similarity between these two homologous enzymes yet they have established distinct mechanisms to accomplish the coequal functions.

Dissecting conformational changes in APP's transmembrane domain linked to ε-efficiency in familial Alzheimer's disease

The mechanism by which familial Alzheimer's disease (FAD) mutations within the transmembrane domain (TMD) of the Amyloid Precursor Protein (APP) affect ε-endoproteolysis is only poorly understood. Thereby, mutations in the cleavage domain reduce ε-efficiency of γ-secretase cleavage and some even shift entry into production lines. Since cleavage occurs within the TMD, a relationship between processing and TMD structure and dynamics seems obvious. Using molecular dynamic simulations, we dissect the dynamic features of wild-type and seven FAD-mutants into local and global components. Mutations consistently enhance hydrogen-bond fluctuations upstream of the ε-cleavage sites but maintain strong helicity there. Dynamic perturbation-response scanning reveals that FAD-mutants target backbone motions utilized in the bound state. Those motions, obscured by large-scale motions in the pre-bound state, provide (i) a dynamic mechanism underlying the proposed coupling between binding and ε-cleavage, (ii) key sites consistent with experimentally determined docking sites, and (iii) the distinction between mutants and wild-type.

Structural Stability of the Coiled-Coil Domain of Tumor Susceptibility Gene (TSG)-101

The tumor susceptibility gene-101 coiled coil domain (TSG101cc) is an integral component of the endosomal maturation machinery and cytokinesis, and also interacts with several transcription factors. The TSG101cc has been crystallized as a homotetramer but is known to interact with two of its binding partners as a heterotrimer. To investigate this apparent discrepancy, we examined the solution thermodynamics of the TSG101cc. Here, we use circular dichroism, differential scanning calorimetry, analytical ultracentrifugation, fluorescence, and structural thermodynamic analysis to investigate the structural stability and the unfolding of the TSG101cc. We demonstrate that TSG101cc exists in solution primarily as a tetramer, which unfolds in a two-state manner. Surprisingly, no homodimeric or homotrimeric species were detected. Structural thermodynamic analysis of the homotetrameric structure and comparison with known oligomeric coiled-coils suggests that the TSG101cc homotetramer is comparatively unstable on a per residue basis. Furthermore, the homotrimeric coiled-coil is predicted to be much less stable than the functional heterotrimeric coiled-coil in the endosomal sorting complex required for transport 1 (ESCRT1). These results support a model whereby the tetramer–monomer equilibrium of TSG101 serves as the cellular reservoir of TSG101, which is effectively outcompeted when its binding partners are present and the heteroternary complex can form.

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.

Entropy redistribution controls allostery in a metalloregulatory protein

Allosteric communication between two ligand-binding sites in a protein is a central aspect of biological regulation that remains mechanistically unclear. Here we show that perturbations in equilibrium picosecond-nanosecond motions impact zinc (Zn)-induced allosteric inhibition of DNA binding by the Zn efflux repressor CzrA (chromosomal zinc-regulated repressor). DNA binding leads to an unanticipated increase in methyl side-chain flexibility and thus stabilizes the complex entropically; Zn binding redistributes these motions, inhibiting formation of the DNA complex by restricting coupled fast motions and concerted slower motions. Allosterically impaired CzrA mutants are characterized by distinct nonnative fast internal dynamics "fingerprints" upon Zn binding, and DNA binding is weakly regulated. We demonstrate the predictive power of the wild-type dynamics fingerprint to identify key residues in dynamics-driven allostery. We propose that driving forces arising from dynamics can be harnessed by nature to evolve new allosteric ligand specificities in a compact molecular scaffold.

Allosteric sites can be identified based on the residue-residue interaction energy difference

Allosteric drugs act at a distance to regulate protein functions. They have several advantages over conventional orthosteric drugs, including diverse regulation types and fewer side effects. However, the rational design of allosteric ligands remains a challenge, especially when it comes to the identification allosteric binding sites. As the binding of allosteric ligands may induce changes in the pattern of residue-residue interactions, we calculated the residue-residue interaction energies within the allosteric site based on the molecular mechanics generalized Born surface area energy decomposition scheme. Using a dataset of 17 allosteric proteins with structural data for both the apo and the ligand-bound state available, we used conformational ensembles generated by molecular dynamics simulations to compute the differences in the residue-residue interaction energies in known allosteric sites from both states. For all the known sites, distinct interaction energy differences (>25%) were observed. We then used CAVITY, a binding site detection program to identify novel putative allosteric sites in the same proteins. This yielded a total of 31 "druggable binding sites," of which 21 exhibited >25% difference in residue interaction energies, and were hence predicted as novel allosteric sites. Three of the predicted allosteric sites were supported by recent experimental studies. All the predicted sites may serve as novel allosteric sites for allosteric ligand design. Our study provides a computational method for identifying novel allosteric sites for allosteric drug design.

Rigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein Allostery

Intra-protein information is transmitted over distances via allosteric processes. This ubiquitous protein process allows for protein function changes due to ligand binding events. Understanding protein allostery is essential to understanding protein functions. In this study, allostery in the second PDZ domain (PDZ2) in the human PTP1E protein is examined as model system to advance a recently developed rigid residue scan method combining with configurational entropy calculation and principal component analysis. The contributions from individual residues to whole-protein dynamics and allostery were systematically assessed via rigid body simulations of both unbound and ligand-bound states of the protein. The entropic contributions of individual residues to whole-protein dynamics were evaluated based on covariance-based correlation analysis of all simulations. The changes of overall protein entropy when individual residues being held rigid support that the rigidity/flexibility equilibrium in protein structure is governed by the La Châtelier's principle of chemical equilibrium. Key residues of PDZ2 allostery were identified with good agreement with NMR studies of the same protein bound to the same peptide. On the other hand, the change of entropic contribution from each residue upon perturbation revealed intrinsic differences among all the residues. The quasi-harmonic and principal component analyses of simulations without rigid residue perturbation showed a coherent allosteric mode from unbound and bound states, respectively. The projection of simulations with rigid residue perturbation onto coherent allosteric modes demonstrated the intrinsic shifting of ensemble distributions supporting the population-shift theory of protein allostery. Overall, the study presented here provides a robust and systematic approach to estimate the contribution of individual residue internal motion to overall protein dynamics and allostery.

The Promiscuity of Allosteric Regulation of Nuclear Receptors by Retinoid X Receptor

The promiscuous protein retinoid X receptor (RXR) displays essential allosteric regulation of several members in the nuclear hormone receptor superfamily via heterodimerization and (anti)cooperative binding of cognate ligands. Here, the structural basis of the positive allostery of RXR and constitutive androstane receptor (CAR) is revealed. In contrast, a similar computational approach had previously revealed the mechanism for negative allostery in the complex of RXR and thyroid receptor (TR). By comparing the positive and negative allostery of RXR complexed with CAR and TR respectively, we reported the promiscuous allosteric control involving RXR. We characterize the allosteric mechanism by expressing the correlated dynamics of selected residue-residue contacts which was extracted from atomistic molecular dynamics simulation and statistical analysis. While the same set of residues in the binding pocket of RXR may initiate the residue-residue interaction network, RXR uses largely different sets of contacts (only about one-third identical) and allosteric modes to regulate TR and CAR. The promiscuity of RXR control may originate from multiple factors, including (1) the frustrated fit of cognate ligand 9c to the RXR binding pocket and (2) the different ligand-binding features of TR (loose) versus CAR (tight) to their corresponding cognate ligands.

Correlated rigid modes in protein families

A great deal of evolutionarily conserved information is contained in genomes and proteins. Enormous effort has been put into understanding protein structure and developing computational tools for protein folding, and many sophisticated approaches take structure and sequence homology into account. Several groups have applied statistical physics approaches to extracting information about proteins from sequences alone. Here, we develop a new method for sequence analysis based on first principles, in information theory, in statistical physics and in Bayesian analysis. We provide a complete derivation of our approach and we apply it to a variety of systems, to demonstrate its utility and its limitations. We show in some examples that phylogenetic alignments of amino-acid sequences of families of proteins imply the existence of a small number of modes that appear to be associated with correlated global variation. These modes are uncovered efficiently in our approach by computing a non-perturbative effective potential directly from the alignment. We show that this effective potential approaches a limiting form inversely with the logarithm of the number of sequences. Mapping symbol entropy flows along modes to underlying physical structures shows that these modes arise due to correlated compensatory adjustments. In the protein examples, these occur around functional binding pockets.

The role of negative selection in protein evolution revealed through the energetics of the native state ensemble

Knowing the determinants of conformational specificity is essential for understanding protein structure, stability, and fold evolution. To address this issue, a novel statistical measure of energetic compatibility between sequence and structure was developed using an experimentally validated model of the energetics of the native state ensemble. This approach successfully matched sequences from a diverse subset of the human proteome to their respective folds. Unexpectedly, significant energetic compatibility between ostensibly unrelated sequences and structures was also observed. Interrogation of these matches revealed a general framework for understanding the origins of conformational specificity within a proteome: specificity is a complex function of both the ability of a sequence to adopt folds other than the native, and ability of a fold to accommodate sequences other than the native. The regional variation in energetic compatibility indicates that the compatibility is dominated by incompatibility of sequence for alternative fold segments, suggesting that evolution of protein sequences has involved substantial negative selection, with certain segments serving as "gatekeepers" that presumably prevent alternative structures. Beyond these global trends, a size dependence exists in the degree to which the energetic compatibility is determined from negative selection, with smaller proteins displaying more negative selection. This partially explains how short sequences can adopt unique folds, despite the higher probability in shorter proteins for small numbers of mutations to increase compatibility with other folds. In providing evolutionary ground rules for the thermodynamic relationship between sequence and fold, this framework imparts valuable insight for rational design of unique folds or fold switches.

Identifying and Reducing Systematic Errors in Chromosome Conformation Capture Data

Chromosome conformation capture (3C)-based techniques have recently been used to uncover the mystic genomic architecture in the nucleus. These techniques yield indirect data on the distances between genomic loci in the form of contact frequencies that must be normalized to remove various errors. This normalization process determines the quality of data analysis. In this study, we describe two systematic errors that result from the heterogeneous local density of restriction sites and different local chromatin states, methods to identify and remove those artifacts, and three previously described sources of systematic errors in 3C-based data: fragment length, mappability, and local DNA composition. To explain the effect of systematic errors on the results, we used three different published data sets to show the dependence of the results on restriction enzymes and experimental methods. Comparison of the results from different restriction enzymes shows a higher correlation after removing systematic errors. In contrast, using different methods with the same restriction enzymes shows a lower correlation after removing systematic errors. Notably, the improved correlation of the latter case caused by systematic errors indicates that a higher correlation between results does not ensure the validity of the normalization methods. Finally, we suggest a method to analyze random error and provide guidance for the maximum reproducibility of contact frequency maps.

Dancing through Life: Molecular Dynamics Simulations and Network-Centric Modeling of Allosteric Mechanisms in Hsp70 and Hsp110 Chaperone Proteins

Hsp70 and Hsp110 chaperones play an important role in regulating cellular processes that involve protein folding and stabilization, which are essential for the integrity of signaling networks. Although many aspects of allosteric regulatory mechanisms in Hsp70 and Hsp110 chaperones have been extensively studied and significantly advanced in recent experimental studies, the atomistic picture of signal propagation and energetics of dynamics-based communication still remain unresolved. In this work, we have combined molecular dynamics simulations and protein stability analysis of the chaperone structures with the network modeling of residue interaction networks to characterize molecular determinants of allosteric mechanisms. We have shown that allosteric mechanisms of Hsp70 and Hsp110 chaperones may be primarily determined by nucleotide-induced redistribution of local conformational ensembles in the inter-domain regions and the substrate binding domain. Conformational dynamics and energetics of the peptide substrate binding with the Hsp70 structures has been analyzed using free energy calculations, revealing allosteric hotspots that control negative cooperativity between regulatory sites. The results have indicated that cooperative interactions may promote a population-shift mechanism in Hsp70, in which functional residues are organized in a broad and robust allosteric network that can link the nucleotide-binding site and the substrate-binding regions. A smaller allosteric network in Hsp110 structures may elicit an entropy-driven allostery that occurs in the absence of global structural changes. We have found that global mediating residues with high network centrality may be organized in stable local communities that are indispensable for structural stability and efficient allosteric communications. The network-centric analysis of allosteric interactions has also established that centrality of functional residues could correlate with their sensitivity to mutations across diverse chaperone functions. This study reconciles a wide spectrum of structural and functional experiments by demonstrating how integration of molecular simulations and network-centric modeling may explain thermodynamic and mechanistic aspects of allosteric regulation in chaperones.

Long-Range Communication Network in the Type 1B Bone Morphogenetic Protein Receptor

Protein-protein interactions are recognized as a fundamental phenomenon that is intimately associated with biological functions and thus are ideal targets for developing modulators for regulating biological functions. A challenge is to identify a site that is situated away from but functionally connected to the protein-protein interface. We employed bone morphogenetic proteins (BMPs) and their receptors as a model system to develop a strategy for identifying such a network of communication. Accordingly, using computational analyses with the COREX/BEST algorithm, we uncovered an overall pattern connecting various regions of BMPR-1B ectodomain, including the four conserved residues in the protein-protein interface. In preparation for testing the long-range effects of mutations of distal residues for future studies, we examined the extent of measurable perturbation of the four conserved residues by determination of the conformation and relative affinities of these BMPR-1B mutants for ligands BMP-2, -6, and -7 and GDF-5. Results suggest no significant structural changes in the receptor but do suggest that the four residues play different roles in defining ligand affinity and both intra- and intermolecular interactions play a role in defining ligand affinity. Thus, these results established two primary but necessary goals: (1) the baseline knowledge of perturbation of conserved interfacial residues for future reference and (2) the ability of the computational approach to identify the distal residues connecting to the interfacial residues. The data presented here provide the foundation for future experiments to identify the effects of distal residues that affect the specificity and affinity of BMP recognition. Protein-protein interactions are integral reactions in essentially all biological activities such as gene regulation and age-related development. Often, diseases are consequences of the alteration of these intermacromolecular interactions, which are thus recognized as a legitimate target for developing modulators for regulating biological functions. One approach is to design ligands that bind to the protein-protein interface. Another is to identify an allosteric site, an advantage of which is bypassing the potential challenge in competing for high-affinity interfacial interactions or a specific interface in a superassembly of multiple macromolecules. However, a challenge of this approach is identifying a site that is situated away from but functionally connected to the protein-protein interface.

Allosteric Dynamic Control of Binding

Proteins have a highly dynamic nature and there is a complex interrelation between their structural dynamics and binding behavior. By assuming various conformational ensembles, they perform both local and global fluctuations to interact with other proteins in a dynamic infrastructure adapted to functional motion. Here, we show that there is a significant association between allosteric mutations, which lead to high-binding-affinity changes, and the hinge positions of global modes, as revealed by a large-scale statistical analysis of data in the Structural Kinetic and Energetic Database of Mutant Protein Interactions (SKEMPI). We further examined the mechanism of allosteric dynamics by conducting studies on human growth hormone (hGH) and pyrin domain (PYD), and the results show how mutations at the hinge regions could allosterically affect the binding-site dynamics or induce alternative binding modes by modifying the ensemble of accessible conformations. The long-range dissemination of perturbations in local chemistry or physical interactions through an impact on global dynamics can restore the allosteric dynamics. Our findings suggest a mechanism for the coupling of structural dynamics to the modulation of protein interactions, which remains a critical phenomenon in understanding the effect of mutations that lead to functional changes in proteins.

Global ITC fitting methods in studies of protein allostery

Allostery is a nearly ubiquitous feature of biological systems in which ligand binding or covalent modification at one site alters the activities of distant sites in a macromolecule or macromolecular complex. The molecular mechanisms underlying this phenomenon have been studied for decades. Nevertheless there are many aspects that remain poorly understood. ITC yields detailed information on the thermodynamics of biomacromolecular interactions and their coupling to additional equilibria, therefore in principle it is a powerful tool for better understanding how allostery is achieved. A particularly powerful approach involves simultaneously fitting multiple ITC data sets together with those of complementary techniques, especially nuclear magnetic resonance and circular dichroism spectroscopies. In this review, we describe several group-fitting methods for discriminating between different binding models and for improving the accuracy of thermodynamic parameters extracted from variable-temperature ITC data. The techniques were applied to the antibiotic resistance-causing enzyme aminoglycoside-6'-acetyltransferase Ii, uncovering the existence of competition between opposing mechanisms and ligand-dependent switching of the underlying mechanism. These novel observations underline the potential of combining ITC and spectroscopic techniques to study allostery.

Mapping allostery through computational glycine scanning and correlation analysis of residue-residue contacts

Understanding allosteric mechanisms is essential for the physical control of molecular switches and downstream cellular responses. However, it is difficult to decode essential allosteric motions in a high-throughput scheme. A general two-pronged approach to performing automatic data reduction of simulation trajectories is presented here. The first step involves coarse-graining and identifying the most dynamic residue-residue contacts. The second step is performing principal component analysis of these contacts and extracting the large-scale collective motions expressed via these residue-residue contacts. We demonstrated the method using a protein complex of nuclear receptors. Using atomistic modeling and simulation, we examined the protein complex and a set of 18 glycine point mutations of residues that constitute the binding pocket of the ligand effector. The important motions that are responsible for the allostery are reported. In contrast to conventional induced-fit and lock-and-key binding mechanisms, a novel "frustrated-fit" binding mechanism of RXR for allosteric control was revealed.

A statistical thermodynamic model for investigating the stability of DNA sequences from oligonucleotides to genomes

We describe the development and testing of a simple statistical mechanics methodology for duplex DNA applicable to sequences of any composition and extensible to genomes. The microstates of a DNA sequence are modeled in terms of blocks of basepairs that are assumed to be fully closed (paired) or open. This approach generates an ensemble of bubblelike microstates that are used to calculate the corresponding partition function. The energies of the microstates are calculated as additive contributions from hydrogen bonding, basepair stacking, and solvation terms parameterized from a comprehensive series of molecular dynamics simulations including solvent and ions. Thermodynamic properties and nucleotide stability constants for DNA sequences follow directly from the partition function. The methodology was tested by comparing computed free energies per basepair with the experimental melting temperatures of 60 oligonucleotides, yielding a correlation coefficient of -0.96. The thermodynamic stability of genic/nongenic regions was tested in terms of nucleotide stability constants versus sequence for the Escherichia coli K-12 genome. It showed clear differentiation of the genes from promoters and captures genic regions with a sensitivity of 0.94. The statistical thermodynamic model presented here provides a seemingly new handle on the challenging problem of interpreting genomic sequences.

Ligand binding to a high-energy partially unfolded protein

The conformational energy landscape of a protein determines populations of all possible conformations of the protein and also determines the kinetics of the conversion between the conformations. Interaction with ligands influences the conformational energy landscapes of proteins and shifts populations of proteins in different conformational states. To investigate the effect of ligand binding on partial unfolding of a protein, we use Escherichia coli dihydrofolate reductase (DHFR) and its functional ligand NADP(+) as a model system. We previously identified a partially unfolded form of DHFR that is populated under native conditions. In this report, we determined the free energy for partial unfolding of DHFR at varying concentrations of NADP(+) and found that NADP(+) binds to the partially unfolded form as well as the native form. DHFR unfolds partially without releasing the ligand, though the binding affinity for NADP(+) is diminished upon partial unfolding. Based on known crystallographic structures of NADP(+) -bound DHFR and the model of the partially unfolded protein we previously determined, we propose that the adenosine-binding domain of DHFR remains folded in the partially unfolded form and interacts with the adenosine moiety of NADP(+) . Our result demonstrates that ligand binding may affect the conformational free energy of not only native forms but also high-energy non-native forms.

Structure of a partially unfolded form of Escherichia coli dihydrofolate reductase provides insight into its folding pathway

Proteins frequently fold via folding intermediates that correspond to local minima on the conformational energy landscape. Probing the structure of the partially unfolded forms in equilibrium under native conditions can provide insight into the properties of folding intermediates. To elucidate the structures of folding intermediates of Escherichia coli dihydrofolate reductase (DHFR), we investigated transient partial unfolding of DHFR under native conditions. We probed the structure of a high-energy conformation susceptible to proteolysis (cleavable form) using native-state proteolysis. The free energy for unfolding to the cleavable form is clearly less than that for global unfolding. The dependence of the free energy on urea concentration (m-value) also confirmed that the cleavable form is a partially unfolded form. By assessing the effect of mutations on the stability of the partially unfolded form, we found that native contacts in a hydrophobic cluster formed by the F-G and Met-20 loops on one face of the central β-sheet are mostly lost in the partially unfolded form. Also, the folded region of the partially unfolded form is likely to have some degree of structural heterogeneity. The structure of the partially unfolded form is fully consistent with spectroscopic properties of the near-native kinetic intermediate observed in previous folding studies of DHFR. The findings suggest that the last step of the folding of DHFR involves organization in the structure of two large loops, the F-G and Met-20 loops, which is coupled with compaction of the rest of the protein.

Substrate-dependent switching of the allosteric binding mechanism of a dimeric enzyme

Enzyme activity is commonly controlled by allostery, where ligand binding at one site alters the activities of distant sites. Classical explanations for multisubunit proteins involve conformational transitions that are fundamentally deterministic. For example, in the Monod-Wyman-Changeaux (MWC) paradigm, conformational transitions occur simultaneously in all subunits. In the Koshland-Nemethy-Filmer (KNF) paradigm, conformational transitions only occur in ligand-bound subunits. In contrast, recent models predict conformational changes that are governed by probabilities rather than absolute rules. To better understand allostery at the molecular level, we applied a recently developed spectroscopic and calorimetric method to the interactions of a dimeric enzyme with two different ligands. We found that conformational transitions appear MWC-like for a ligand that binds at the dimer interface and KNF-like for a distal ligand. These results provide strong experimental support for probabilistic allosteric theory predictions that an enzyme can exhibit a mixture of MWC and KNF character, with the balance partly governed by subunit interface energies.

Thermodynamic mechanism for the evasion of antibody neutralization in flaviviruses

Mutations in the epitopes of antigenic proteins can confer viral resistance to antibody-mediated neutralization. However, the fundamental properties that characterize epitope residues and how mutations affect antibody binding to alter virus susceptibility to neutralization remain largely unknown. To address these questions, we used an ensemble-based algorithm to characterize the effects of mutations on the thermodynamics of protein conformational fluctuations. We applied this method to the envelope protein domain III (ED3) of two medically important flaviviruses: West Nile and dengue 2. We determined an intimate relationship between the susceptibility of a residue to thermodynamic perturbations and epitope location. This relationship allows the successful identification of the primary epitopes in each ED3, despite their high sequence and structural similarity. Mutations that allow the ED3 to evade detection by the antibody either increase or decrease conformational fluctuations of the epitopes through local effects or long-range interactions. Spatially distant interactions originate in the redistribution of conformations of the ED3 ensembles, not through a mechanically connected array of contiguous amino acids. These results reconcile previous observations of evasion of neutralization by mutations at a distance from the epitopes. Finally, we established a quantitative correlation between subtle changes in the conformational fluctuations of the epitope and large defects in antibody binding affinity. This correlation suggests that mutations that allow viral growth, while reducing neutralization, do not generate significant structural changes and underscores the importance of protein fluctuations and long-range interactions in the mechanism of antibody-mediated neutralization resistance.

Population shift of binding pocket size and dynamic correlation analysis shed new light on the anticooperative mechanism of PII protein

PII protein is one of the largest families of signal transduction proteins in archaea, bacteria, and plants, controlling key processes of nitrogen assimilation. An intriguing characteristic for many PII proteins is that the three ligand binding sites exhibit anticooperative allosteric regulation. In this work, PII protein from Synechococcus elongatus, a model for cyanobacteria and plant PII proteins, is utilized to reveal the anticooperative mechanism upon binding of 2-oxoglutarate (2-OG). To this end, a method is proposed to define the binding pocket size by identifying residues that contribute greatly to the binding of 2-OG. It is found that the anticooperativity is realized through population shift of the binding pocket size in an asymmetric manner. Furthermore, a new algorithm based on the dynamic correlation analysis is developed and utilized to discover residues that mediate the anticooperative process with high probability. It is surprising to find that the T-loop, which is believed to be responsible for mediating the binding of PII with its target proteins, also takes part in the intersubunit signal transduction process. Experimental results of PII variants further confirmed the influence of T-loop on the anticooperative regulation, especially on binding of the third 2-OG. These discoveries extend our understanding of the PII T-loop from being essential in versatile binding of target protein to signal-mediating in the anticooperative allosteric regulation.

The ensemble nature of allostery

Allostery is the process by which biological macromolecules (mostly proteins) transmit the effect of binding at one site to another, often distal, functional site, allowing for regulation of activity. Recent experimental observations demonstrating that allostery can be facilitated by dynamic and intrinsically disordered proteins have resulted in a new paradigm for understanding allosteric mechanisms, which focuses on the conformational ensemble and the statistical nature of the interactions responsible for the transmission of information. Analysis of allosteric ensembles reveals a rich spectrum of regulatory strategies, as well as a framework to unify the description of allosteric mechanisms from different systems.

Towards structural systems pharmacology to study complex diseases and personalized medicine

Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.

Uncovering allosteric pathways in caspase-1 using Markov transient analysis and multiscale community detection

Atomistic graph–theoretical analysis of caspase-1 reveals details of intra-protein communication pathways.

Using the COREX/BEST server to model the native-state ensemble

Protein structures under normal conditions exist as ensembles of interconverting, transient microstates. A computer algorithm known as COREX/BEST (Biology using Ensemble-based Structural Thermodynamics) was developed to model microstate structures and describe the native ensembles of proteins in statistical thermodynamic terms. This algorithm has been tested extensively and validated through experimental comparisons examining a range of biophysical and functional phenomena, such as structural cooperativity, pH-dependent stability, and cold denaturation. Here, we describe a Web-based implementation of the COREX/BEST algorithm, called the COREX/BEST Server, and demonstrate how to use this online resource to characterize the structural and thermodynamic properties of the native protein ensemble.

The designability of protein switches by chemical rescue of structure: mechanisms of inactivation and reactivation

The ability to selectively activate function of particular proteins via pharmacological agents is a longstanding goal in chemical biology. Recently, we reported an approach for designing a de novo allosteric effector site directly into the catalytic domain of an enzyme. This approach is distinct from traditional chemical rescue of enzymes in that it relies on disruption and restoration of structure, rather than active site chemistry, as a means to achieve modulate function. However, rationally identifying analogous de novo binding sites in other enzymes represents a key challenge for extending this approach to introduce allosteric control into other enzymes. Here we show that mutation sites leading to protein inactivation via tryptophan-to-glycine substitution and allowing (partial) reactivation by the subsequent addition of indole are remarkably frequent. Through a suite of methods including a cell-based reporter assay, computational structure prediction and energetic analysis, fluorescence studies, enzymology, pulse proteolysis, X-ray crystallography, and hydrogen-deuterium mass spectrometry, we find that these switchable proteins are most commonly modulated indirectly, through control of protein stability. Addition of indole in these cases rescues activity not by reverting a discrete conformational change, as we had observed in the sole previously reported example, but rather rescues activity by restoring protein stability. This important finding will dramatically impact the design of future switches and sensors built by this approach, since evaluating stability differences associated with cavity-forming mutations is a far more tractable task than predicting allosteric conformational changes. By analogy to natural signaling systems, the insights from this study further raise the exciting prospect of modulating stability to design optimal recognition properties into future de novo switches and sensors built through chemical rescue of structure.