Whole-protein alanine-scanning mutagenesis of allostery: A large percentage of a protein can contribute to mechanism

Rheostatic contributions to protein stability can obscure a position's functional role

Rheostat positions, which can be substituted with various amino acids to tune protein function across a range of outcomes, are a developing area for advancing personalized medicine and bioengineering. Current methods cannot accurately predict which proteins contain rheostat positions or their substitution outcomes. To compare the prevalence of rheostat positions in homologs, we previously investigated their occurrence in two pyruvate kinase (PYK) isozymes. Human liver PYK contained numerous rheostat positions that tuned the apparent affinity for the substrate phosphoenolpyruvate (Kapp-PEP) across a wide range. In contrast, no functional rheostat positions were identified in Zymomonas mobilis PYK (ZmPYK). Further, the set of ZmPYK substitutions included an unusually large number that lacked measurable activity. We hypothesized that the inactive substitution variants had reduced protein stability, precluding detection of Kapp-PEP tuning. Using modified buffers, robust enzymatic activity was obtained for 19 previously-inactive ZmPYK substitution variants at three positions. Surprisingly, both previously-inactive and previously-active substitution variants all had Kapp-PEP values close to wild-type. Thus, none of the three positions were functional rheostat positions, and, unlike human liver PYK, ZmPYK's Kapp-PEP remained poorly tunable by single substitutions. To directly assess effects on stability, we performed thermal denaturation experiments for all ZmPYK substitution variants. Many diminished stability, two enhanced stability, and the three positions showed different thermal sensitivity to substitution, with one position acting as a "stability rheostat." The differences between the two PYK homologs raises interesting questions about the underlying mechanism(s) that permit functional tuning by single substitutions in some proteins but not in others.

Rheostats, toggles, and neutrals, Oh my! A new framework for understanding how amino acid changes modulate protein function

Advances in personalized medicine and protein engineering require accurately predicting outcomes of amino acid substitutions. Many algorithms correctly predict that evolutionarily-conserved positions show "toggle" substitution phenotypes, which is defined when a few substitutions at that position retain function. In contrast, predictions often fail for substitutions at the less-studied "rheostat" positions, which are defined when different amino acid substitutions at a position sample at least half of the possible functional range. This review describes efforts to understand the impact and significance of rheostat positions: (1) They have been observed in globular soluble, integral membrane, and intrinsically disordered proteins; within single proteins, their prevalence can be up to 40%. (2) Substitutions at rheostat positions can have biological consequences and ∼10% of substitutions gain function. (3) Although both rheostat and "neutral" (defined when all substitutions exhibit wild-type function) positions are nonconserved, the two classes have different evolutionary signatures. (4) Some rheostat positions have pleiotropic effects on function, simultaneously modulating multiple parameters (e.g., altering both affinity and allosteric coupling). (5) In structural studies, substitutions at rheostat positions appear to cause only local perturbations; the overall conformations appear unchanged. (6) Measured functional changes show promising correlations with predicted changes in protein dynamics; the emergent properties of predicted, dynamically coupled amino acid networks might explain some of the complex functional outcomes observed when substituting rheostat positions. Overall, rheostat positions provide unique opportunities for using single substitutions to tune protein function. Future studies of these positions will yield important insights into the protein sequence/function relationship.

What is allosteric regulation? Exploring the exceptions that prove the rule!

"Allosteric" was first introduced to mean the other site (i.e., a site distinct from the active or orthosteric site), an adjective for "regulation" to imply a regulatory outcome resulting from ligand binding at another site. That original idea outlines a system with two ligand-binding events at two distinct locations on a macromolecule (originally a protein system), which defines a four-state energy cycle. An allosteric energy cycle provides a quantifiable allosteric coupling constant and focuses our attention on the unique properties of the four equilibrated protein complexes that constitute the energy cycle. Because many observed phenomena have been referenced as "allosteric regulation" in the literature, the goal of this work is to use literature examples to explore which systems are and are not consistent with the two-ligand thermodynamic energy cycle-based definition of allosteric regulation. We emphasize the need for consistent language so comparisons can be made among the ever-increasing number of allosteric systems. Building on the mutually exclusive natures of an energy cycle definition of allosteric regulation versus classic two-state models, we conclude our discussion by outlining how the often-proposed Rube-Goldberg-like mechanisms are likely inconsistent with an energy cycle definition of allosteric regulation.

CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods

BACKGROUND

The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.

RESULTS

Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic.

CONCLUSIONS

Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.

The intrinsically disordered transcriptional activation domain of CIITA is functionally tuneable by single substitutions: An exception or a new paradigm?

During protein evolution, some amino acid substitutions modulate protein function ("tuneability"). In most proteins, the tuneable range is wide and can be sampled by a set of protein variants that each contains multiple amino acid substitutions. In other proteins, the full tuneable range can be accessed by a set of variants that each contains a single substitution. Indeed, in some globular proteins, the full tuneable range can be accessed by the set of site-saturating substitutions at an individual "rheostat" position. However, in proteins with intrinsically disordered regions (IDRs), most functional studies-which would also detect tuneability-used multiple substitutions or small deletions. In disordered transcriptional activation domains (ADs), studies with multiple substitutions led to the "acidic exposure" model, which does not anticipate the existence of rheostat positions. In the few studies that did assess effects of single substitutions on AD function, results were mixed: the ADs of two full-length transcription factors did not show tuneability, whereas a fragment of a third AD was tuneable by single substitutions. In this study, we tested tuneability in the AD of full-length human class II transactivator (CIITA). Sequence analyses and experiments showed that CIITA's AD is an IDR. Functional assays of singly-substituted AD variants showed that CIITA's function was highly tuneable, with outcomes not predicted by the acidic exposure model. Four tested positions showed rheostat behavior for transcriptional activation. Thus, tuneability of different IDRs can vary widely. Future studies are needed to illuminate the biophysical features that govern whether an IDR is tuneable by single substitutions.

The 2.4 Å structure of Zymomonas mobilis pyruvate kinase: Implications for stability and regulation

Human liver pyruvate kinase (hlPYK) catalyzes the final step in glycolysis, the formation of pyruvate (PYR) and ATP from phosphoenolpyruvate (PEP) and ADP. Fructose 1,6-bisphosphate (FBP), a pathway intermediate of glycolysis, serves as an allosteric activator of hlPYK. Zymomonas mobilis pyruvate kinase (ZmPYK) performs the final step of the Entner-Doudoroff pathway, which is similar to glycolysis in that energy is harvested from glucose and pyruvate is generated. The Entner-Doudoroff pathway does not have FBP as a pathway intermediate, and ZmPYK is not allosterically activated. In this work, we solved the 2.4 Å X-ray crystallographic structure of ZmPYK. The protein is dimeric in solution as determined by gel filtration chromatography, but crystallizes as a tetramer. The buried surface area of the ZmPYK tetramerization interface is significantly smaller than that of hlPYK, and yet tetramerization using the standard interfaces from higher organisms provides an accessible low energy crystallization pathway. Interestingly, the ZmPYK structure showed a phosphate ion in the analogous location to the 6-phosphate binding site of FBP in hlPYK. Circular Dichroism (CD) was used to measure melting temperatures of hlPYK and ZmPYK in the absence and presence of substrates and effectors. The only significant difference was an additional phase of small amplitude for the ZmPYK melting curves. We conclude that the phosphate ion plays neither a structural or allosteric role in ZmPYK under the conditions tested. We hypothesize that ZmPYK does not have sufficient protein stability for activity to be tuned by allosteric effectors as described for rheostat positions in the allosteric homologues.

Divalent cations in human liver pyruvate kinase exemplify the combined effects of complex-equilibrium and allosteric regulation

There is growing recognition that the functional outcome of binding of an allosteric regulator to a protein/enzyme is influenced by the presence of other ligands. Here, this complexity is exemplified in the allosteric regulation of human liver pyruvate kinase (hLPYK) that is influenced by the presence of a range of divalent cation types and concentrations. For this system, fructose-1,6-bisphosphate (activator) and alanine (inhibitor) both influence the protein's affinity for the substrate, phosphoenolpyruvate (PEP). Mg2+, Mn2+, Ni2+, and Co2+ were the primary divalent cations evaluated, although Zn2+, Cd2+, V2+, Pb2+, Fe2+, and Cu2+also supported activity. Allosteric coupling between Fru-1,6-BP and PEP and between Ala and PEP varied depending on divalent cation type and concentration. Due to complicating interactions among small molecules, we did not attempt the fitting of response trends and instead we discuss a range of potential mechanisms that may explain those observed trends. Specifically, observed "substrate inhibition" may result from substrate A in one active site acting as an allosteric regulator for the affinity for substrate B in a second active site of a multimer. We also discuss apparent changes in allosteric coupling that can result from a sub-saturating concentration of a third allosteric ligand.

PYK-SubstitutionOME: an integrated database containing allosteric coupling, ligand affinity and mutational, structural, pathological, bioinformatic and computational information about pyruvate kinase isozymes

Interpreting changes in patient genomes, understanding how viruses evolve and engineering novel protein function all depend on accurately predicting the functional outcomes that arise from amino acid substitutions. To that end, the development of first-generation prediction algorithms was guided by historic experimental datasets. However, these datasets were heavily biased toward substitutions at positions that have not changed much throughout evolution (i.e. conserved). Although newer datasets include substitutions at positions that span a range of evolutionary conservation scores, these data are largely derived from assays that agglomerate multiple aspects of function. To facilitate predictions from the foundational chemical properties of proteins, large substitution databases with biochemical characterizations of function are needed. We report here a database derived from mutational, biochemical, bioinformatic, structural, pathological and computational studies of a highly studied protein family-pyruvate kinase (PYK). A centerpiece of this database is the biochemical characterization-including quantitative evaluation of allosteric regulation-of the changes that accompany substitutions at positions that sample the full conservation range observed in the PYK family. We have used these data to facilitate critical advances in the foundational studies of allosteric regulation and protein evolution and as rigorous benchmarks for testing protein predictions. We trust that the collected dataset will be useful for the broader scientific community in the further development of prediction algorithms. Database URL https://github.com/djparente/PYK-DB.

Prion Propagation is Dependent on Key Amino Acids in Charge Cluster 2 within the Prion Protein

To dissect the N-terminal residues within the cellular prion protein (PrP^C) that are critical for efficient prion propagation, we generated a library of point, double, or triple alanine replacements within residues 23-111 of PrP, stably expressed them in cells silenced for endogenous mouse PrP^C and challenged the reconstituted cells with four common but biologically diverse mouse prion strains. Amino acids (aa) 105-111 of Charge Cluster 2 (CC2), which is disordered in PrP^C, were found to be required for propagation of all four prion strains; other residues had no effect or exhibited strain-specific effects. Replacements in CC2, including aa105-111, dominantly inhibited prion propagation in the presence of endogenous wild type PrP^C whilst other changes were not inhibitory. Single alanine replacements within aa105-111 identified leucine 108 and valine 111 or the cluster of lysine 105, threonine 106 and asparagine 107 as critical for prion propagation. These residues mediate specific ordering of unstructured CC2 into β-sheets in the infectious prion fibrils from Rocky Mountain Laboratory (RML) and ME7 mouse prion strains.

Predicting binding affinity changes from long-distance mutations using molecular dynamics simulations and Rosetta

Computationally modeling how mutations affect protein-protein binding not only helps uncover the biophysics of protein interfaces, but also enables the redesign and optimization of protein interactions. Traditional high-throughput methods for estimating binding free energy changes are currently limited to mutations directly at the interface due to difficulties in accurately modeling how long-distance mutations propagate their effects through the protein structure. However, the modeling and design of such mutations is of substantial interest as it allows for greater control and flexibility in protein design applications. We have developed a method that combines high-throughput Rosetta-based side-chain optimization with conformational sampling using classical molecular dynamics simulations, finding significant improvements in our ability to accurately predict long-distance mutational perturbations to protein binding. Our approach uses an analytical framework grounded in alchemical free energy calculations while enabling exploration of a vastly larger sequence space. When comparing to experimental data, we find that our method can predict internal long-distance mutational perturbations with a level of accuracy similar to that of traditional methods in predicting the effects of mutations at the protein-protein interface. This work represents a new and generalizable approach to optimize protein free energy landscapes for desired biological functions.

Serendipitous Identification of a Covalent Activator of Liver Pyruvate Kinase

Enzymes are effective biological catalysts that accelerate almost all metabolic reactions in living organisms. Synthetic modulators of enzymes are useful tools for the study of enzymatic reactions and can provide starting points for the design of new drugs. Here, we report on the discovery of a class of biologically active compounds that covalently modifies lysine residues in human liver pyruvate kinase (PKL), leading to allosteric activation of the enzyme (EC₅₀ =0.29 μM). Surprisingly, the allosteric activation control point resides on the lysine residue K282 present in the catalytic site of PKL. These findings were confirmed by structural data, MS/MS experiments, and molecular modelling studies. Altogether, our study provides a molecular basis for the activation mechanism and establishes a framework for further development of human liver pyruvate kinase covalent activators.

Odd one out? Functional tuning of Zymomonas mobilis pyruvate kinase is narrower than its allosteric, human counterpart

Various protein properties are often illuminated using sequence comparisons of protein homologs. For example, in analyses of the pyruvate kinase multiple sequence alignment, the set of positions that changed during speciation ("phylogenetic" positions) were enriched for "rheostat" positions in human liver pyruvate kinase (hLPYK). (Rheostat positions are those which, when substituted with various amino acids, yield a range of functional outcomes). However, the correlation was moderate, which could result from multiple biophysical constraints acting on the same position during evolution and/or various sources of noise. To further examine this correlation, we here tested Zymomonas mobilis PYK (ZmPYK), which has <65% sequence identity to any other PYK sequence. Twenty-six ZmPYK positions were selected based on their phylogenetic scores, substituted with multiple amino acids, and assessed for changes in Kapp-PEP . Although we expected to identify multiple, strong rheostat positions, only one moderate rheostat position was detected. Instead, nearly half of the 271 ZmPYK variants were inactive and most others showed near wild-type function. Indeed, for the active ZmPYK variants, the total range of Kapp,PEP values ("tunability") was 40-fold less than that observed for hLPYK variants. The combined functional studies and sequence comparisons suggest that ZmPYK has evolved functional and/or structural attributes that differ from the rest of the family. We hypothesize that including such "orphan" sequences in MSA analyses obscures the correlations used to predict rheostat positions. Finally, results raise the intriguing biophysical question as to how the same protein fold can support rheostat positions in one homolog but not another.

High throughput and quantitative enzymology in the genomic era

Accurate predictions from models based on physical principles are the ultimate metric of our biophysical understanding. Although there has been stunning progress toward structure prediction, quantitative prediction of enzyme function has remained challenging. Realizing this goal will require large numbers of quantitative measurements of rate and binding constants and the use of these ground-truth data sets to guide the development and testing of these quantitative models. Ground truth data more closely linked to the underlying physical forces are also desired. Here, we describe technological advances that enable both types of ground truth measurements. These advances allow classic models to be tested, provide novel mechanistic insights, and place us on the path toward a predictive understanding of enzyme structure and function.

uPIC-M: Efficient and Scalable Preparation of Clonal Single Mutant Libraries for High-Throughput Protein Biochemistry

New high-throughput biochemistry techniques complement selection-based approaches and provide quantitative kinetic and thermodynamic data for thousands of protein variants in parallel. With these advances, library generation rather than data collection has become rate-limiting. Unlike pooled selection approaches, high-throughput biochemistry requires mutant libraries in which individual sequences are rationally designed, efficiently recovered, sequence-validated, and separated from one another, but current strategies are unable to produce these libraries at the needed scale and specificity at reasonable cost. Here, we present a scalable, rapid, and inexpensive approach for creating User-designed Physically Isolated Clonal-Mutant (uPIC-M) libraries that utilizes recent advances in oligo synthesis, high-throughput sample preparation, and next-generation sequencing. To demonstrate uPIC-M, we created a scanning mutant library of SpAP, a 541 amino acid alkaline phosphatase, and recovered 94% of desired mutants in a single iteration. uPIC-M uses commonly available equipment and freely downloadable custom software and can produce a 5000 mutant library at 1/3 the cost and 1/5 the time of traditional techniques.

A hierarchy of coupling free energies underlie the thermodynamic and functional architecture of protein structures

Protein sequences and structures evolve by satisfying varied physical and biochemical constraints. This multi-level selection is enabled not just by the patterning of amino acids on the sequence, but also via coupling between residues in the native structure. Here, we employ an energetically detailed statistical mechanical model with millions of microstates to extract such long-range structural correlations, i.e. thermodynamic coupling free energies, from a diverse family of protein structures. We find that despite the intricate and anisotropic distribution of coupling patterns, the majority of residues (>70%) are only marginally coupled contributing to functional motions and catalysis. Physical origins of ‘sectors’, determinants of native ensemble heterogeneity in extant, ancient and designed proteins, and the basis for allostery emerge naturally from coupling free energies. The statistical framework highlights how evolutionary selection and optimization occur at the level of global interaction network for a given protein fold impacting folding, function, and allosteric outputs.

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Evolution of protein structures occurs at the level of global interaction network.

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More than 70% of the protein residues are weakly or marginally coupled.

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Functional ‘sector’ regions are a manifestation of marginal coupling.

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Coupling indices vary across the entire proteins in extant-ancient and natural-designed pairs.

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The proposed methodology can be used to understand allostery and epistasis.

Structurally distributed surface sites tune allosteric regulation

Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mutations that tune allostery. Are these mutations few or abundant, structurally localized or distributed? To examine this, we conducted saturation mutagenesis of a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. Using a high-throughput assay wherein DHFR catalytic activity is coupled to E. coli growth, we assessed the impact of 1548 viable DHFR single mutations on allostery. Despite most mutations being deleterious to activity, fewer than 5% of mutations had a statistically significant influence on allostery. Most allostery disrupting mutations were proximal to the LOV2 insertion site. In contrast, allostery enhancing mutations were structurally distributed and enriched on the protein surface. Combining several allostery enhancing mutations yielded near-additive improvements to dynamic range. Our results indicate a path toward optimizing allosteric function through variation at surface sites.

Many proteins exhibit a property called ‘allostery’. In allostery, an input signal at a specific site of a protein – such as a molecule binding, or the protein absorbing a photon of light – leads to a change in output at another site far away. For example, the protein might catalyze a chemical reaction faster or bind to another molecule more tightly in the presence of the input signal. This protein ‘remote control’ allows cells to sense and respond to changes in their environment. An ability to rapidly engineer new allosteric mechanisms into proteins is much sought after because this would provide an approach for building biosensors and other useful tools. One common approach to engineering new allosteric regulation is to combine a ‘sensor’ or input region from one protein with an ‘output’ region or domain from another.

When researchers engineer allostery using this approach of combining input and output domains from different proteins, the difference in the output when the input is ‘on’ versus ‘off’ is often small, a situation called ‘modest allostery’. McCormick et al. wanted to know how to optimize this domain combination approach to increase the difference in output between the ‘on’ and ‘off’ states.

More specifically, McCormick et al. wanted to find out whether swapping out or mutating specific amino acids (each of the individual building blocks that make up a protein) enhances or disrupts allostery. They also wanted to know if there are many possible mutations that change the effectiveness of allostery, or if this property is controlled by just a few amino acids. Finally, McCormick et al. questioned where in a protein most of these allostery-tuning mutations were located.

To answer these questions, McCormick et al. engineered a new allosteric protein by inserting a light-sensing domain (input) into a protein involved in metabolism (a metabolic enzyme that produces a biomolecule called a tetrahydrofolate) to yield a light-controlled enzyme. Next, they introduced mutations into both the ‘input’ and ‘output’ domains to see where they had a greater effect on allostery.

After filtering out mutations that destroyed the function of the output domain, McCormick et al. found that only about 5% of mutations to the ‘output’ domain altered the allosteric response of their engineered enzyme. In fact, most mutations that disrupted allostery were found near the site where the ‘input’ domain was inserted, while mutations that enhanced allostery were sprinkled throughout the enzyme, often on its protein surface. This was surprising in light of the commonly-held assumption that mutations on protein surfaces have little impact on the activity of the ‘output’ domain. Overall, the effect of individual mutations on allostery was small, but McCormick et al. found that these mutations can sometimes be combined to yield larger effects.

McCormick et al.’s results suggest a new approach for optimizing engineered allosteric proteins: by introducing mutations on the protein surface. It also opens up new questions: mechanically, how do surface sites affect allostery? In the future, it will be important to characterize how combinations of mutations can optimize allosteric regulation, and to determine what evolutionary trajectories to high performance allosteric ‘switches’ look like.

Rheostat functional outcomes occur when substitutions are introduced at nonconserved positions that diverge with speciation

When amino acids vary during evolution, the outcome can be functionally neutral or biologically-important. We previously found that substituting a subset of nonconserved positions, "rheostat" positions, can have surprising effects on protein function. Since changes at rheostat positions can facilitate functional evolution or cause disease, more examples are needed to understand their unique biophysical characteristics. Here, we explored whether "phylogenetic" patterns of change in multiple sequence alignments (such as positions with subfamily specific conservation) predict the locations of functional rheostat positions. To that end, we experimentally tested eight phylogenetic positions in human liver pyruvate kinase (hLPYK), using 10-15 substitutions per position and biochemical assays that yielded five functional parameters. Five positions were strongly rheostatic and three were non-neutral. To test the corollary that positions with low phylogenetic scores were not rheostat positions, we combined these phylogenetic positions with previously-identified hLPYK rheostat, "toggle" (most substitution abolished function), and "neutral" (all substitutions were like wild-type) positions. Despite representing 428 variants, this set of 33 positions was poorly statistically powered. Thus, we turned to the in vivo phenotypic dataset for E. coli lactose repressor protein (LacI), which comprised 12-13 substitutions at 329 positions and could be used to identify rheostat, toggle, and neutral positions. Combined hLPYK and LacI results show that positions with strong phylogenetic patterns of change are more likely to exhibit rheostat substitution outcomes than neutral or toggle outcomes. Furthermore, phylogenetic patterns were more successful at identifying rheostat positions than were co-evolutionary or eigenvector centrality measures of evolutionary change.

AlloSigMA 2: paving the way to designing allosteric effectors and to exploring allosteric effects of mutations

The AlloSigMA 2 server provides an interactive platform for exploring the allosteric signaling caused by ligand binding and/or mutations, for analyzing the allosteric effects of mutations and for detecting potential cancer drivers and pathogenic nsSNPs. It can also be used for searching latent allosteric sites and for computationally designing allosteric effectors for these sites with required agonist/antagonist activity. The server is based on the implementation of the Structure-Based Statistical Mechanical Model of Allostery (SBSMMA), which allows one to evaluate the allosteric free energy as a result of the perturbation at per-residue resolution. The Allosteric Signaling Map (ASM) providing a comprehensive residue-by-residue allosteric control over the protein activity can be obtained for any structure of interest. The Allosteric Probing Map (APM), in turn, allows one to perform the fragment-based-like computational design experiment aimed at finding leads for potential allosteric effectors. The server can be instrumental in elucidating of allosteric mechanisms and actions of allosteric mutations, and in the efforts on design of new elements of allosteric control. The server is freely available at: http://allosigma.bii.a-star.edu.sg.

Rheostat positions: A new classification of protein positions relevant to pharmacogenomics

To achieve the full potential of pharmacogenomics, one must accurately predict the functional out comes that arise from amino acid substitutions in proteins. Classically, researchers have focused on understanding the consequences of individual substitutions. However, literature surveys have shown that most substitutions were created at evolutionarily conserved positions. Awareness of this bias leads to a shift in perspective, from considering the outcomes of individual substitutions to understanding the roles of individual protein positions. Conserved positions tend to act as "toggle" switches, with most substitutions abolishing function. However, nonconserved positions have been found equally capable of affecting protein function. Indeed, many nonconserved positions act like functional dimmer switches ("rheostat" positions): This is revealed when multiple substitutions are made at a single position. Each substitution has a different functional outcome; the set of substitutions spans arange of outcomes. Finally, some nonconserved positions appear neutral, capable of accommodating all amino acid types without modifying function. This manuscript reviews the currently-known properties of rheost at positions, with examples shown for pyruvate kinase, organic anion transporting polypeptide 1B1, the beta-lactamase inhibitory protein, and angiotensin-converting enzyme 2. Outcomes observed for rheostat positions have implications for the rational design of drug analogs and allosteric drugs. Furthermore, this new framework - comprising three types of protein positions - provides a new approach to interpreting disease and population-based databases of amino acid changes. In conclusion, although a full understanding of substitution out comes at rheostat positions poses a challenge, utilization of this new frame of reference will further advance the application of pharmacogenomics.

Identification of biochemically neutral positions in liver pyruvate kinase

Understanding how each residue position contributes to protein function has been a long-standing goal in protein science. Substitution studies have historically focused on conserved protein positions. However, substitutions of nonconserved positions can also modify function. Indeed, we recently identified nonconserved positions that have large substitution effects in human liver pyruvate kinase (hLPYK), including altered allosteric coupling. To facilitate a comparison of which characteristics determine when a nonconserved position does vs does not contribute to function, the goal of the current work was to identify neutral positions in hLPYK. However, existing hLPYK data showed that three features commonly associated with neutral positions-high sequence entropy, high surface exposure, and alanine scanning-lacked the sensitivity needed to guide experimental studies. We used multiple evolutionary patterns identified in a sequence alignment of the PYK family to identify which positions were least patterned, reasoning that these were most likely to be neutral. Nine positions were tested with a total of 117 amino acid substitutions. Although exploring all potential functions is not feasible for any protein, five parameters associated with substrate/effector affinities and allosteric coupling were measured for hLPYK variants. For each position, the aggregate functional outcomes of all variants were used to quantify a "neutrality" score. Three positions showed perfect neutral scores for all five parameters. Furthermore, the nine positions showed larger neutral scores than 17 positions located near allosteric binding sites. Thus, our strategy successfully enriched the dataset for positions with neutral and modest substitutions.

AlloMAPS: allosteric mutation analysis and polymorphism of signaling database

AlloMAPS database provides data on the causality and energetics of allosteric communication obtained with the structure-based statistical mechanical model of allostery (SBSMMA). The database contains data on allosteric signaling in three sets of proteins and protein chains: (i) 46 proteins with comprehensively annotated functional and allosteric sites; (ii) 1908 protein chains from PDBselect set of chains with low (<25%) sequence identity; (iii) 33 proteins with more than 50 known pathological SNPs in each molecule. In addition to energetics of allosteric signaling between known functional and regulatory sites, allosteric modulation caused by the binding to these sites, by SNPs, and by mutations designated by the user can be explored. Allosteric Signaling Maps (ASMs), which are produced via the exhaustive computational scanning for stabilizing and destabilizing mutations and for the modulation range caused by the sequence position are available for each protein/protein chain in the database. We propose to use this database for evaluating the effects of allosteric signaling in the search for latent regulatory sites and in the design of allosteric sites and effectors. The database is freely available at: http://allomaps.bii.a-star.edu.sg.

Direct coupling analysis of epistasis in allosteric materials

In allosteric proteins, the binding of a ligand modifies function at a distant active site. Such allosteric pathways can be used as target for drug design, generating considerable interest in inferring them from sequence alignment data. Currently, different methods lead to conflicting results, in particular on the existence of long-range evolutionary couplings between distant amino-acids mediating allostery. Here we propose a resolution of this conundrum, by studying epistasis and its inference in models where an allosteric material is evolved in silico to perform a mechanical task. We find in our model the four types of epistasis (Synergistic, Sign, Antagonistic, Saturation), which can be both short or long-range and have a simple mechanical interpretation. We perform a Direct Coupling Analysis (DCA) and find that DCA predicts well the cost of point mutations but is a rather poor generative model. Strikingly, it can predict short-range epistasis but fails to capture long-range epistasis, in consistence with empirical findings. We propose that such failure is generic when function requires subparts to work in concert. We illustrate this idea with a simple model, which suggests that other methods may be better suited to capture long-range effects.

Allostery in proteins is the property of highly specific responses to ligand binding at a distant site. To inform protocols of de novo drug design, it is fundamental to understand the impact of mutations on allosteric regulation and whether it can be predicted from evolutionary correlations. In this work we consider allosteric architectures artificially evolved to optimize the cooperativity of binding at allosteric and active site. We first characterize the emergent pattern of epistasis as well as the underlying mechanical phenomena, finding the four types of epistasis (Synergistic, Sign, Antagonistic, Saturation), which can be both short or long-range. The numerical evolution of these allosteric architectures allows us to benchmark Direct Coupling Analysis, a method which relies on co-evolution in sequence data to infer direct evolutionary couplings, in connection to allostery. We show that Direct Coupling Analysis predicts quantitatively point mutation costs but underestimates strong long-range epistasis. We provide an argument, based on a simplified model, illustrating the reasons for this discrepancy. Our analysis suggests neural networks as more promising tool to measure epistasis.

Gamabufotalin induces a negative feedback loop connecting ATP1A3 expression and the AQP4 pathway to promote temozolomide sensitivity in glioblastoma cells by targeting the amino acid Thr794

Objectives

Temozolomide (TMZ) is one of the most commonly used clinical drugs for glioblastoma (GBM) treatment, but its drug sensitivity needs to be improved. Gamabufotalin (CS‐6), the primary component of the traditional Chinese medicine “ChanSu,” was shown to have strong anti‐cancer activity. However, more efforts should be directed towards reducing its toxicity or effective treatment doses.

Methods

Target fishing experiment, Western blotting, PCR, confocal immunofluorescence and molecular cloning techniques were performed to search for possible downstream signalling pathways. In addition, GBM xenografts were used to further determine the potential molecular mechanisms of the synergistic effects of CS‐6 and TMZ in vivo.

Results

Mechanistic research revealed a negative feedback loop between ATP1A3 and AQP4 through which CS‐6 inhibited GBM growth and mediated the synergistic treatment effect of CS‐6 and TMZ. In addition, by mutating potential amino acid residues of ATP1A3, which were predicted by modelling and docking to interact with CS‐6, we demonstrated that abrogating hydrogen bonding of the amino acid Thr794 interferes with the activation of ATP1A3 by CS‐6 and that the Thr794Ala mutation directly affects the synergistic treatment efficacy of CS‐6 and TMZ.

Conclusions

As the main potential target of CS‐6, ATP1A3 activation critically depends on the hydrogen bonding of Thr794 with CS‐6. The combination of CS‐6 and TMZ could significantly reduce the therapeutic doses and promote the anti‐cancer efficacy of CS‐6/TMZ monotherapy.

Functional tunability from a distance: Rheostat positions influence allosteric coupling between two distant binding sites

For protein mutagenesis, a common expectation is that important positions will behave like on/off “toggle” switches (i.e., a few substitutions act like wildtype, most abolish function). However, there exists another class of important positions that manifests a wide range of functional outcomes upon substitution: “rheostat” positions. Previously, we evaluated rheostat positions located near the allosteric binding sites for inhibitor alanine (Ala) and activator fructose-1,6-bisphosphate (Fru-1,6-BP) in human liver pyruvate kinase. When substituted with multiple amino acids, many positions demonstrated moderate rheostatic effects on allosteric coupling between effector binding and phosphoenolpyruvate (PEP) binding in the active site. Nonetheless, the combined outcomes of all positions sampled the full range of possible allosteric coupling (full tunability). However, that study only evaluated allosteric tunability of “local” positions, i.e., positions were located near the binding sites of the allosteric ligand being assessed. Here, we evaluated tunability of allosteric coupling when mutated sites were distant from the allosterically-coupled binding sites. Positions near the Ala binding site had rheostatic outcomes on allosteric coupling between Fru-1,6-BP and PEP binding. In contrast, positions in the Fru-1,6-BP site exhibited modest effects on coupling between Ala and PEP binding. Analyzed in aggregate, both PEP/Ala and PEP/Fru-1,6-BP coupling were again fully tunable by amino acid substitutions at this limited set of distant positions. Furthermore, some positions exhibited rheostatic control over multiple parameters and others exhibited rheostatic effects on one parameter and toggle control over a second. These findings highlight challenges in efforts to both predict/interpret mutational outcomes and engineer functions into proteins.

Mutational mimics of allosteric effectors: a genome editing design to validate allosteric drug targets

Development of drugs that allosterically regulate enzyme functions to treat disease is a costly venture. Amino acid susbstitutions that mimic allosteric effectors in vitro will identify therapeutic regulatory targets enhancing the likelihood of developing a disease treatment at a reasonable cost. We demonstrate the potential of this approach utilizing human liver pyruvate kinase (hLPYK) as a model. Inhibition of hLPYK was the first desired outcome of this study. We identified individual point mutations that: 1) mimicked allosteric inhibition by alanine, 2) mimicked inhibition by protein phosphorylation, and 3) prevented binding of fructose-1,6-bisphosphate (Fru-1,6-BP). Our second desired outcome was activation of hLPYK. We identified individual point mutations that: 1) prevented hLPYK from binding alanine, the allosteric inhibitor, 2) prevented inhibitory protein phosphorylation, or 3) mimicked allosteric activation by Fru-1,6-BP. Combining the three activating point mutations produced a constitutively activated enzyme that was unresponsive to regulators. Expression of a mutant hLPYK transgene containing these three mutations in a mouse model was not lethal. Thus, mutational mimics of allosteric effectors will be useful to confirm whether allosteric activation of hLPYK will control glycolytic flux in the diabetic liver to reduce hepatic glucose production and, in turn, reduce or prevent hyperglycemia.

NQO1: A target for the treatment of cancer and neurological diseases, and a model to understand loss of function disease mechanisms

NAD(P)H quinone oxidoreductase 1 (NQO1) is a multi-functional protein that catalyses the reduction of quinones (and other molecules), thus playing roles in xenobiotic detoxification and redox balance, and also has roles in stabilising apoptosis regulators such as p53. The structure and enzymology of NQO1 is well-characterised, showing a substituted enzyme mechanism in which NAD(P)H binds first and reduces an FAD cofactor in the active site, assisted by a charge relay system involving Tyr-155 and His-161. Protein dynamics play important role in physio-pathological aspects of this protein. NQO1 is a good target to treat cancer due to its overexpression in cancer cells. A polymorphic form of NQO1 (p.P187S) is associated with increased cancer risk and certain neurological disorders (such as multiple sclerosis and Alzheimer´s disease), possibly due to its roles in the antioxidant defence. p.P187S has greatly reduced FAD affinity and stability, due to destabilization of the flavin binding site and the C-terminal domain, which leading to reduced activity and enhanced degradation. Suppressor mutations partially restore the activity of p.P187S by local stabilization of these regions, and showing long-range allosteric communication within the protein. Consequently, the correction of NQO1 misfolding by pharmacological chaperones is a viable strategy, which may be useful to treat cancer and some neurological conditions, targeting structural spots linked to specific disease-mechanisms. Thus, NQO1 emerges as a good model to investigate loss of function mechanisms in genetic diseases as well as to improve strategies to discriminate between neutral and pathogenic variants in genome-wide sequencing studies.

Chokepoints in Mechanical Coupling Associated with Allosteric Proteins: The Pyruvate Kinase Example

Although the critical role of allostery in controlling enzymatic processes is well appreciated, there is a current dearth in our understanding of its underlying mechanisms, including communication between binding sites. One potential key aspect of intersite communication is the mechanical coupling between residues in a protein. Here, we introduce a graph-based computational approach to investigate the mechanical coupling between distant parts of a protein, highlighting effective pathways via which protein motion can transfer energy between sites. In this method, each residue is treated as a node on a weighted, undirected graph, in which the edges are defined by locally correlated motions of those residues and weighted by the strength of the correlation. The method was validated against experimental data on allosteric regulation in the human liver pyruvate kinase as obtained from full-protein alanine-scanning mutagenesis (systematic mutation) studies, as well as computational data on two G-protein-coupled receptors. The method provides semiquantitative information on the regulatory importance of specific structural elements. It is shown that these elements are key for the mechanical coupling between distant parts of the protein by providing effective pathways for energy transfer. It is also shown that, although there are a multitude of energy transfer pathways between distant parts of a protein, these pathways share a few common nodes that represent effective "chokepoints" for the communication.

Toward Comprehensive Allosteric Control over Protein Activity

Universality of allosteric signaling in proteins, molecular machines, and receptors complemented by the great advantages of prospected allosteric drugs in the highly specific, non-competitive, and modulatory nature of their actions calls for deeper theoretical understanding of allosteric communication. We present a computational model that makes it possible to tackle the problem of modulating the energetics of protein allosteric communication. In the context of the energy landscape paradigm, allosteric signaling is always a result of perturbations, such as ligand binding, mutations, and intermolecular interactions. The calculation of local partition functions in the protein harmonic model with perturbations allows us to evaluate the energetics of allosteric communication at the single-residue level. In this framework, Allosteric Signaling Maps are proposed as a tool to exhaustively describe allosteric communication in the protein, to tune already existing signaling, and to design new elements of regulation for taking the protein activity under allosteric control.

Allosteric Methods and Their Applications: Facilitating the Discovery of Allosteric Drugs and the Investigation of Allosteric Mechanisms

Allostery, or allosteric regulation, is the phenomenon in which protein functional activity is altered by the binding of an effector at an allosteric site that is topographically distinct from the orthosteric, active site. As one of the most direct and efficient ways to regulate protein function, allostery has played a fundamental role in innumerable biological processes of all living organisms, including enzyme catalysis, signal transduction, cell metabolism, and gene transcription. It is thus considered as "the second secret of life". The abnormality of allosteric communication networks between allosteric and orthosteric sites is associated with the pathogenesis of human diseases. Allosteric modulators, by attaching to structurally diverse allosteric sites, offer the potential for differential selectivity and improved safety compared with orthosteric drugs that bind to conserved orthosteric sites. Harnessing allostery has thus been regarded as a novel strategy for drug discovery. Despite much progress having been made in the repertoire of allostery since the turn of the millennium, the identification of allosteric drugs for therapeutic targets and the elucidation of allosteric mechanisms still present substantial challenges. These challenges are derived from the difficulties in the identification of allosteric sites and mutations, the assessment of allosteric protein-modulator interactions, the screening of allosteric modulators, and the elucidation of allosteric mechanisms in biological systems. To address these issues, we have developed a panel of allosteric services for specific allosteric applications over the past decade, including (i) the creation of the Allosteric Database, with the aim of providing comprehensive allosteric information such as allosteric proteins, modulators, sites, pathways, etc., (ii) the construction of the ASBench benchmark of high-quality allosteric sites for the development of computational methods for predicting allosteric sites, (iii) the development of Allosite and AllositePro for the prediction of the location of allosteric sites in proteins, (iv) the development of the Alloscore scoring function for the evaluation of allosteric protein-modulator interactions, (v) the development of Allosterome for evolutionary analysis of query allosteric sites/modulators within the human proteome, (vi) the development of AlloDriver for the prediction of allosteric mutagenesis, and (vii) the development of AlloFinder for the virtual screening of allosteric modulators and the investigation of allosteric mechanisms. Importantly, we have validated computationally predicted allosteric sites, mutations, and modulators in the real cases of sirtuin 6, casein kinase 2α, phosphodiesterase 10A, and signal transduction and activation of transcription 3. Furthermore, our developed allosteric methods have been widely exploited by other users around the world for allosteric research. Therefore, these allosteric services are expected to expedite the discovery of allosteric drugs and the investigation of allosteric mechanisms.

Dissecting a novel allosteric mechanism of cruzain: A computer-aided approach

Trypanosoma cruzi is the causative agent of Chagas disease, a neglected infection affecting millions of people in tropical regions. There are several chemotherapeutic agents for the treatment of this disease, but most of them are highly toxic and generate resistance. Currently, the development of allosteric inhibitors constitutes a promising research field, since it can improve the accessibility to more selective and less toxic medicines. To date, the allosteric drugs prediction is a state-of-the-art topic in rational structure-based computational design. In this work, a simulation strategy was developed for computational discovery of allosteric inhibitors, and it was applied to cruzain, a promising target and the major cysteine protease of T. cruzi. Molecular dynamics simulations, binding free energy calculations and network-based modelling of residue interactions were combined to characterize and compare molecular distinctive features of the apo form and the cruzain-allosteric inhibitor complexes. By using geometry-based criteria on trajectory snapshots, we predicted two main allosteric sites suitable for drug targeting. The results suggest dissimilar mechanisms exerted by the same allosteric site when binding different potential allosteric inhibitors. Finally, we identified the residues involved in suboptimal paths linking the identified site and the orthosteric site. The present study constitutes the first approximation to the design of cruzain allosteric inhibitors and may serve for future pharmacological intervention. Here, no major effects on active site structure were observed due to compound binding (modification of distance and angles between catalytic residues), which indicates that allosteric regulation in cruzain might be mediated via alterations of its dynamical properties similarly to allosteric inhibition of human cathepsin K (HCatK). The current findings are particularly relevant for the design of allosteric modulators of papain-like cysteine proteases.

Modulation of allosteric coupling by mutations: from protein dynamics and packing to altered native ensembles and function

A large body of work has gone into understanding the effect of mutations on protein structure and function. Conventional treatments have involved quantifying the change in stability, activity and relaxation rates of the mutants with respect to the wild-type protein. However, it is now becoming increasingly apparent that mutational perturbations consistently modulate the packing and dynamics of a significant fraction of protein residues, even those that are located >10–15 Å from the mutated site. Such long-range modulation of protein features can distinctly tune protein stability and the native conformational ensemble contributing to allosteric modulation of function. In this review, I summarize a series of experimental and computational observations that highlight the incredibly pliable nature of proteins and their response to mutational perturbations manifested via the intra-protein interaction network. I highlight how an intimate understanding of mutational effects could pave the way for integrating stability, folding, cooperativity and even allostery within a single physical framework.

Insight into the specificity and severity of pathogenic mechanisms associated with missense mutations through experimental and structural perturbation analyses

Most pathogenic missense mutations cause specific molecular phenotypes through protein destabilization. However, how protein destabilization is manifested as a given molecular phenotype is not well understood. We develop here a structural and energetic approach to describe mutational effects on specific traits such as function, regulation, stability, subcellular targeting or aggregation propensity. This approach is tested using large-scale experimental and structural perturbation analyses in over thirty mutations in three different proteins (cancer-associated NQO1, transthyretin related with amyloidosis and AGT linked to primary hyperoxaluria type I) and comprising five very common pathogenic mechanisms (loss-of-function and gain-of-toxic function aggregation, enzyme inactivation, protein mistargeting and accelerated degradation). Our results revealed that the magnitude of destabilizing effects and, particularly, their propagation through the structure to promote disease-associated conformational states largely determine the severity and molecular mechanisms of disease-associated missense mutations. Modulation of the structural perturbation at a mutated site is also shown to cause switches between different molecular phenotypes. When very common disease-associated missense mutations were investigated, we also found that they were not among the most deleterious possible missense mutations at those sites, and required additional contributions from codon bias and effects of CpG sites to explain their high frequency in patients. Our work sheds light on the molecular basis of pathogenic mechanisms and genotype–phenotype relationships, with implications for discriminating between pathogenic and neutral changes within human genome variability from whole genome sequencing studies.

RheoScale: A tool to aggregate and quantify experimentally determined substitution outcomes for multiple variants at individual protein positions

Human mutations often cause amino acid changes (variants) that can alter protein function or stability. Some variants fall at protein positions that experimentally exhibit "rheostatic" mutation outcomes (different amino acid substitutions lead to a range of functional outcomes). In ongoing studies of rheostat positions, we encountered the need to aggregate experimental results from multiple variants, to describe the overall roles of individual positions. Here, we present "RheoScale" which generates quantitative scores to discriminate rheostat positions from those with "toggle" (most substitutions abolish function) or "neutral" (most substitutions have wild-type function) outcomes. RheoScale scores facilitate correlations of experimental data (such as binding affinity or stability) with structural and bioinformatic analyses. The RheoScale calculator is encoded into a Microsoft Excel workbook and an R script. Example analyses are shown for three model protein systems, including one assessed via deep mutational scanning. The RheoScale calculator quickly and efficiently provided quantitative descriptions that were in good agreement with prior qualitative observations. As an example application, scores were compared to the example proteins' structures; strong rheostat positions tended to occur in dynamic locations. In the future, RheoScale scores can be easily integrated into computational studies to facilitate improved algorithms for predicting outcomes of human variants.

Biophysical and functional perturbation analyses at cancer-associated P187 and K240 sites of the multifunctional NADP(H):quinone oxidoreductase 1

Once whole-genome sequencing has reached the clinical practice, a main challenge ahead is the high-throughput and accurate prediction of the pathogenicity of genetic variants. However, current prediction tools do not consider explicitly a well-known property of disease-causing mutations: their ability to affect multiple functional sites distant in the protein structure. Here we carried out an extensive biophysical characterization of fourteen mutant variants at two cancer-associated sites of the enzyme NQO1, a paradigm of multi-functional protein. We showed that the magnitude of destabilizing effects, their molecular origins (structural vs. dynamic) and their efficient propagation through the protein structure gradually led to functional perturbations at different sites. Modulation of these structural perturbations also led to switches between molecular phenotypes. Our work supports that experimental and computational perturbation analyses would improve our understanding of the molecular basis of many loss-of-function genetic diseases as well as our ability to accurately predict the pathogenicity of genetic variants in a high-throughput fashion.

Evolutionary Divergent Suppressor Mutations in Conformational Diseases

Neutral and adaptive mutations are key players in the evolutionary dynamics of proteins at molecular, cellular and organismal levels. Conversely, largely destabilizing mutations are rarely tolerated by evolution, although their occurrence in diverse human populations has important roles in the pathogenesis of conformational diseases. We have recently proposed that divergence at certain sites from the consensus (amino acid) state during mammalian evolution may have rendered some human proteins more vulnerable towards disease-associated mutations, primarily by decreasing their conformational stability. We herein extend and refine this hypothesis discussing results from phylogenetic and structural analyses, structure-based energy calculations and structure-function studies at molecular and cellular levels. As proof-of-principle, we focus on different mammalian orthologues of the NQO1 (NAD(P)H:quinone oxidoreductase 1) and AGT (alanine:glyoxylate aminotransferase) proteins. We discuss the different loss-of-function pathogenic mechanisms associated with diseases involving the two enzymes, including enzyme inactivation, accelerated degradation, intracellular mistargeting, and aggregation. Last, we take into account the potentially higher robustness of mammalian orthologues containing certain consensus amino acids as suppressors of human disease, and their relation with different intracellular post-translational modifications and protein quality control capacities, to be discussed as sources of phenotypic variability between human and mammalian models of disease and as tools for improving current therapeutic approaches.

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.

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.