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Progress in Biophysics and Molecular Biology 106 (2011) 463e473

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Progress in Biophysics and Molecular Biology

journal homepage: www.elsevier .com/locate/pbiomolbio

Review

Allostery in pharmacology: Thermodynamics, evolution and design

Gábor Maksay*

Department of Molecular Pharmacology, Institute of Biomolecular Chemistry, Chemical Research Center, Hungarian Academy of Sciences, P.O. Box 17, H-1525 Budapest, Hungary

a r t i c l e i n f o

Article history:Available online 9 January 2011

Keywords:Receptor activationLigand-gated ion channelsHomo/hetero/tropic cooperativityThermodynamic discrimination of efficacyConformational fluctuationsStatisticaleenergetic coupling

Abbreviations: GABAA, A-type g-aminobutyric acand Filmer; MWC, Monod, Wyman and Changeux; pLion channels; TM, transmembrane.* Tel.: þ361 325 7900/282; fax: þ361 325 7554.

E-mail address: maksay@chemres.hu.

0079-6107/$ e see front matter � 2011 Elsevier Ltd.doi:10.1016/j.pbiomolbio.2011.01.001

a b s t r a c t

This review focuses on basic models of allostery, the ambiguous application of the allosteric term inpharmacology illustrated by receptors, the role of thermodynamics in allosteric mechanisms, evolutionand design of allostery. The initial step of ligand activation is closure of the agonist-binding cavity. Largeentropy increases accompany the agonist-elicited conformational changes of pentameric ligand-gatedion channels due to cavity closure and rearrangement of transmembrane helices. The effects of pointmutations on thermodynamic parameters of binding and function can reveal energetic coupling ofneighbouring (and distant) amino acid residues in activation. High-order double-mutant cycle analysisand rate-equilibrium linear free-energy relationships can identify the trajectory and conformationalspread of activation.

Protein assembly and allostery can be deduced from colocalization and physicochemical principles.Molecular evolution has led from homooligomerization of protomers to heterotropic cooperativity and toallosteric regulation. Examples are discussed such as similar paths of protein (dis)assembly and evolu-tion, irreversible evolution, statistical analysis of sequence homology revealing coevolution, differentimpacts of adaptation and evolution on hemoglobin, and the flagellar motor switch of bacteria. Thedriving force of dynamic allostery is associated with funnel-like free energy landscapes of proteinbinding and shifts in conformational fluctuations upon binding. Allostery can be designed based on ourincreasing knowledge of natural allosteric mechanisms and evolution. The allosteric principle has beenapplied for various bio/macro/molecular and signal transduction systems as well as in cognitive sciences.

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Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4632. Allosteric models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4643. Pharmacological allostery and receptor activation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4644. Thermodynamic driving forces of allostery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4665. Thermodynamic methods with point mutations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4676. Molecular evolution of receptor proteins and allostery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4687. Design of allostery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4698. Miscellaneous (epistemological) aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .471

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471

id; KNF, Koshland, NémethyGIC, pentameric ligand-gated

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1. Introduction

Fifty years ago Max Perutz et al. (1960) revealed the structure ofhemoglobin via X-ray crystallography and opened theway to revealallostery and cooperativity within protein oligomers. The impor-tance of Perutz’ achievements was soon acknowledged by a NobelPrize in Chemistry (1962). The allosteric term was subsequentlyintroduced for enzyme regulation to distinguish regulatory and

Fig. 1. Unified scheme of conformational selection and induced fit based on the MWC(left side) and KNF models (right side) of allostery. Left side: both receptor and ligandexist in pre-equilibrium of conformations. Note the ratio of arrows indicating a pref-erential direction. Modified from Boehr et al. (2009).

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catalytic sites (Monod et al., 1963). The term of allostery has Greekorigin: allosmeans other, stereos is steric (object, effect). One of thedefinitions of allostery (Fenton, 2008) says that allostery is a chainof interactions when binding of a ligand changes the affinities ofdistant binding sites of a biopolymer, cooperativity of its subunits,or efficacy of its function (e.g. signal transduction and catalysis).The cooperative term has similar meaning but it has been mostlyused for interactions of whole subunits while allostery for those ofdistant (binding) sites.

Nowadays a search for “alloster*” in data bases yields tens ofthousands of publications. Half of the hits still fit in the field ofbiochemistry where the term has been introduced first. Conse-quently, protein allostery has been the topic of several excellentreviews (e.g. Fenton, 2008; Goodsell and Olson, 2000; Jardetzky,1996; Kern and Zuiderweg, 2003; Luque et al., 2002; Mandell andKortemme, 2009; Oh et al., 2009; Ostermeier, 2005). Another halfof the hits refers to further (life) sciences with pharmacology inleading position. This can be attributed to the increasing number ofknown oligomeric structures and to the importance of pharmaco-logical receptors. This is a review of the recent progress related topharmacological allostery, thermodynamics and evolution.

2. Allosteric models

Monod et al. (1965) introduced a concerted, symmetry or MWCmodel of allostery to interpret regulatory mechanisms of oligo-meric enzymes. According to the original MWC model, ligand-freehomooligomers exist in equilibrium of different states or confor-mations. It is assumed that 1) oligomeric structures are symmetric;2) the conformation of protomers changes in a concerted way(all-or-nothing); and 3) upon ligand binding, the symmetricarrangements of protomers are maintained while the equilibriumof pre-existing oligomeric conformations is shifted. In contrast tothe MWC model, Koshland et al. (1966) introduced a sequential orKNF model of allostery. According to the KNF model, conforma-tional changes of protomers are consecutive and asymmetric.Ligands bind sequentially with increasing affinity when the struc-ture of a ligand and its binding site are accommodated to each othervia induced fit.

Advanced methods such as nuclear magnetic resonance (NMR)relaxation can reveal very rapid (psems) dynamics of conforma-tional ensembles of proteins. The role of NMR in protein dynamicshas been reviewed thoroughly elsewhere (Boehr et al., 2006;Jardetzky, 1996; Kern and Zuiderweg, 2003). The correspondingdynamic model and the driving force of allostery will be discussedin detail in the thermodynamic chapter 4. Briefly, ligands selectfrom preexisting conformations of proteins, binding to the mostsuitable one shifts the equilibrium of conformations, according totheMWCmodel (Boehr et al., 2009; Smock and Gierasch, 2009; Tsaiet al., 1999). But the side chains of the oligomer are accommodatedto ligand binding, according to the KNF model. Although the effectsof induced fit are not necessarily propagated in transduction, bothconformational selection and induced fit play important roles inmolecular recognition. Thus, we progress from the antithesistoward the synthesis of MWC and KNF models of allostery (Boehret al., 2009; Csermely et al., 2010). Fig. 1 shows a cyclic combina-tion of conformational selection and induced fit. Here, the binding-competent conformations of the protein and ligand (lower forms)both pre-exist in minority, yet induced fit results in mutualconformational changes and a shift toward the accumulation of theligand-bound species (lower right corner).

The “morpheein”model of allostery has been introduced for thedual quaternary structures of porphobilinogen synthase (Jaffe,2005). This model requires equilibrium of protomer conforma-tions which dictate different quaternary structures of finite

multiplicity and different functionality. Magnesium binding to thisenzyme facilitates transition from hexamer to octamer by stabi-lizing a subunit interface that is present in the octamer but not inthe hexamer. The binding of the alloster requires oligomericdissociation, conformational change and reassembly into a func-tionally distinct oligomer with different stoichiometry (Jaffe, 2005).This model promises a functionally selective, new way of allostericregulation.

3. Pharmacological allostery and receptor activation

In biochemistry, the allosteric term was introduced for interac-tions between protein subunits. However, it has been raised thatallostery is an intrinsic property of all dynamic proteins based onthe redistribution of conformational ensembles upon binding (delSol et al., 2007; Gunasekaran et al., 2004). In pharmacology, theallosteric term has been frequently applied for interactions ofbinding sites within one subunit. Further, the term “orthosteric”has been subsequently introduced in order to distinguish a prom-inent (orthosteric) binding site of agonists (and antagonists) fromthe sites of allosteric agents. Pharmacology has imported the termallosteric in a developmental phase when receptors were facelesssubstances without structural information. Therefore the distinc-tion of orthosteric and allosteric sites has been obscure. Moreover,according to the original biochemical meaning of allostery, bothorthosteric and allosteric agents elicit remote conformational, thatis, allosteric effects during signal transduction.

Changeux extended the MWC model to chemical signal trans-duction while Karlin was the first to use the nicotinic acetylcholinereceptor as an experimental model of allostery (Changeux et al.,1984; Changeux and Edelstein, 2005; Karlin, 1967). However, allo-stery has key roles in several other processes such as enzyme-catalyzed metabolism, protein folding, receptor trafficking, generegulation and apoptosis as well. Nevertheless, signal transductionhas proved to be an ideal target because the investigation ofchemical neurotransmission has been extremely successful in thelast decades. First, it is not ideal that agonists and competitive

G. Maksay / Progress in Biophysics and Molecular Biology 106 (2011) 463e473 465

antagonists exert direct, crude pharmacological effects on neuro-transmission. Allosteric regulation is more suitable for the phar-macological fine-tuning of neurotransmission. Second, allosteric,but not (pseudo)orthosteric sites are structurally less conservative,andmore variable structures enable us to develop drugswith bettersubunit-selectivity. Consequently, several allosteric agents ofligand-gated ion channels (LGIC) and metabotropic neurotrans-mitter receptors have been developed into therapeutic agents.

LGIC receptors contain trimeric ATP-gated (P2X) receptor-channels (Browne et al., 2010), tetrameric glutamate receptors ofNMDA, AMPA and kainate type (Mayer, 2006), and pentamericligand-gated ion channels (pLGIC). The large pLGIC familycomprises glycine and A-type g-aminobutyric acid (GABAA)receptors, as well as nicotinic acetylcholine and 3-type serotonin(5-HT3) receptors which are selectively permeable for anions orcations, respectively (Keramidas et al., 2004; Sine and Engel, 2006).

Fig. 2. A model of the extracellular part of pentameric ligand-gated ion channels based on tequilibrium of ligand-free closed and agonist-bound (red symbol) open channel conformaConformational change can be modelled by concerted rotation of the subunits or loop C cligands bind in pseudo-identical interfaces of subunits. Lower figure: enlargement of the bbound muscle nicotinic acetylcholine receptor. Loop C conformations in blue: agonist-bou(2001) and Maksay et al. (2004).

They are also called Cys-loop receptors because of a characteristiccystine bridge in their subunits. The electron microscopic picture ofnicotinic acetylcholine receptors was the first to reveal the three-dimensional structure of pLGIC receptors with intermediateresolution (Unwin, 1995). By now we have learned several high-resolution structures of these LGIC receptor families via X-raycrystallography (Hilf and Dutzler, 2009; Mayer, 2006). All threefamilies have pseudo-symmetric oligomeric structures (Browneet al., 2010; Changeux and Edelstein, 2005; Sobolevsky et al.,2009). The upper part of Fig. 2 shows a structural model of pLGICreceptors. The subunit interfaces between the extracellulardomains comprise ligand-binding cavities. Several orthosteric andallosteric agents bind in these pseudo-identical interfaces. E.g.GABA agonists are bound between ß and a subunits of GABAAreceptors while benzodiazepine drugs between a and g subunits(Ernst et al., 2005). The allosteric agents alone do not affect pLGIC

he X-ray structure of an acetylcholine binding protein (Brejc et al., 2001). Upper figure:tions. Note the maintenance of symmetric structures according to the MWC model.losure. The heteropentamers are pseudo-symmetric, orthosteric and several allostericinding interface. It corresponds to the X-ray structures of the ligand-free and agonist-nd, closed cavity; red: ligand-free, accessible cavity. Based on Grutter and Changeux

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receptor function. But the binding of allosteric agents can exertpositive, negative or neutral (no) changes in the agonist-elicitedopening of ion channels. Binding of agonists and allosteric modu-lators leads to contraction of their binding cavities as shown inFig. 2 (Changeux and Edelstein, 2005; Ernst et al., 2005; Maksay,2009). This conformational change is propagated via rearrange-ments of coupled ß strands and transmembrane (TM) helices toopen an ion channel as indicated in Fig. 3 (Hilf and Dutzler, 2009).

Fig. 3. Conformational rearrangements in a subunit (upper) and in transmembranehelices of two subunits (lower) leading to pore opening of pLGICs. Upper figure:Ribbon representation of a pLGIC subunit. Positions of residues shown to participate inactivation are black. Important ß-strands and connecting loops are numbered in brownand blue. Red arrows indicate rearrangements associated with channel opening asdemonstrated by molecular dynamics simulation. Modified from Maksay (2009).Lower figure: Proposed rearrangement of TM helices 2 and 3 (TM2-TM3) in two pLGICsubunits opening the pore. The scheme is based on the comparison of the X-raystructures of two prokaryotic pLGICs with closed versus open proton channels.Modified from Hilf and Dutzler (2009).

Agonists pull down loop C that caps the binding cavity (see theupper part of Fig. 3) and elicits opposite (leftward) movements ofthe other end of the rigid ß strands. This drags the TM2-TM3 loopand tilts the TM helices according to the lower part of Fig. 3. Thebinding modes of orthosteric antagonists elicit different interac-tions and less contraction of the binding cavities which preventpore opening (Hansen et al., 2005; Maksay et al., 2009).

At AMPA-type glutamate receptors, agonists elicit rotation andclosure of a clamshell-like binding domain and lead to shrinking ofthe binding cavity around agonists (Armstrong and Gouaux, 2000).Closure of the glutamate-binding cavity has been correlated withthe efficacy of agonists (Jin et al., 2003). At NMDA-type glutamatereceptors, binding of the co-agonist glycine, but not of antagonists,also leads to the contraction of the glycine-binding cavity andinitiates the signal transduction cascade (Furukawa and Gouaux,2003). Similar closure of the binding cavities of modulators (Zn2þ,Mg2þ, Hþ, polyamines and neurosteroids) leads to allostericmodulation of NMDA receptors (Gielen et al., 2008).

G protein-coupled receptors exist as homo- or heterodimerswith bidirectional and multiple allosteric modulations (Villardagaet al., 2005). Accumulating evidence suggests the existenceof higher-order (trimeric) heteromers in this receptor familysuch as adenosine(A2A)-cannabinoid(CB1)-dopamine(D2) receptorcomplexes (Fuxe et al., 2010). Such triple promiscuity can furtherconfound allostery (Schwartz and Holst, 2007) because orthostericligands of one receptor component might also act as allostericmodulators of other components and vice versa. On the other hand,“dualsteric” ligands can be deliberately designed which bindsimultaneously to nearby located orthosteric and allosteric sites ofmuscarinic acetylcholine receptors (Mohr et al., 2010). In metabo-tropic muscarinic receptors, activation is also associated withrotation of transmembrane helices and closure of the binding cavityaround acetylcholine (Lu et al., 2001). Moreover, the closure of bothagonist-binding cavities of homodimeric metabotropic glutamatereceptors is required for full activation (Kniazeff et al., 2004).Consequently, agonist binding to both ionotropic and metabotropicreceptors leads to closure of the binding cavity for activation.

4. Thermodynamic driving forces of allostery

What are the thermodynamic driving forces of spontaneousbinding of agonists and antagonists to ionotropic receptors?Temperature-dependent displacement of radioligand binding hasrevealed that the major driving force of antagonist binding isenthalpy decrease, while agonist binding is driven by entropyincreases for pLGIC-type GABAA, glycine and 5-HT3 receptors(Maksay, 2001). Such “thermodynamic discrimination” of the effi-cacy of ligands has been demonstrated also for an acetylcholine-binding protein homologous with pLGICs (Celie et al., 2005) as wellas for other receptor types as a manifestation of enthalpy-entropycompensation (Gilli et al., 1994). Ligand binding should be distin-guished from subsequent conformational changes. Characteristicinteractions of ionic agonists are polar, while those of larger, ring-enclosed antagonists have dominant hydrophobic components forpLGIC receptors (Maksay, 2001). We can conclude that binding perse to pLGIC receptors is exothermic (Celie et al., 2005; Maksay,2005). Activation by agonists leads to shrinking of the bindingcavity and several solvent-accessible crevices which accompany therearrangement of TM helices (Ernst et al., 2005; Maksay, 2005;Unwin, 2003). This elicits the release of several water moleculesand large entropy increases. Rigidification of the binding cavity byagonists is associated by remote entropy overcompensation.Generally, not only solvent but also conformational entropy cancontribute significantly to the free energy of proteineligand asso-ciation as NMR relaxation confirmed the change in internal

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dynamics of calmodulin upon binding of various peptides(Frederick et al., 2007).

Protein binding of some ligands can elicit conformationalchanges driven by enthalpy decreases while other proteineligandinteractions are not associated with conformational changes in thepeptide backbone (Tsai et al., 2008). Protein dynamics can beconsidered as ergotic systems in which averaging space (ensembleof states) and time-averaging are equivalent. Consequently,proteins exist in a dynamic equilibrium of preexisting conforma-tions (space) or statistical ensembles created by local unfoldingreactions (Luque et al., 2002; Smock and Gierasch, 2009). If ligandsonly shift the distribution of conformers, binding and allostery aredriven by entropy gains via side-chain dynamics (Frederick et al.,2007; Tsai et al., 2008). This is frequently called dynamic allostery(Petit et al., 2009). The free energy profiles of protein binding andfolding are funnel-like as shown in Fig. 4 (Csermely et al., 2010;Frauenfelder et al., 1991; Smock and Gierasch, 2009). The localminima on the bottom of the funnel correspond to native proteinconformations. Ligand binding (signal) increases the stability ofa native conformation according to the old ‘lock-and-key’ theory.Alternatively, the ligand might shift the equilibrium of conforma-tions to its most suitable direction and reshape the local minima(see the lower part of Fig. 4). E.g. agonists shift the equilibrium ofclosed, open and desensitized states of pLGIC receptors accordingto the MWC model (Changeux and Edelstein, 2005). Ligand-induced redistribution in the probabilities of conformational statesand allosteric transmission require that the unliganded site isbinding-competent in only a subset of native states while in othersubsets the site is less stable or not binding-competent (Luqueet al., 2002). Accordingly, agonists have lower affinity to theclosed state of pLGICs. It is obvious although hardly emphasizedthat ligands also exist in a dynamic ensemble of preexistingconformations such as included into Fig. 1. Even intrinsicallyunstructured proteins have preformed secondary structuralelements which facilitate their binding to target proteins (Fuxreiteret al., 2004). This decreases the entropic penalty of binding. As to

Fig. 4. Free energy profile of protein folding. Ligand binding (þ signal) to a binding-competent conformation can shift the equilibrium of probability ratios of conforma-tions. Simplified from Smock and Gierasch (2009).

small ligands and drug development, conformationally constrainedand ring-closed structures in receptor-binding conformations havebeen frequently successful in medicinal chemistry.

Allosteric coupling efficiency can be defined as sensitivity ofligand-binding conformations for perturbation by ligands bound atdistant sites (Hilser and Thompson, 2007). Conformational fluctu-ations reflect the disorder of proteins and facilitate allostericcoupling. Flexible regions can bind in distinct conformations andelicit allosteric modulation in opposite directions. Accordingly, therandom-coil C fragment of loops II-III of the dihydropyridinereceptor, a voltage-gated Ca2þ channel (Cav1.1) can activate orinhibit native ryanodine receptors (Haarmann et al., 2003). Thesereceptors mediate the excitation-contraction coupling in skeletalmuscle fibres.

Allostery is not restricted to proteins. Nucleic acids also formdynamic ensembles (Sethi et al., 2009). Conformational selection isvalid for interactions of ligands, proteins and nucleic acids (Boehret al., 2009). Selective interactions of transcription factors withdegenerate response elements of DNAs are also regulated alloste-rically (Pan et al., 2009). In summary, allosteric regulation, coop-erativity and stability are correlated through thermodynamic rules(Luque et al., 2002). Both interacting partners select from anensemble of their preexisting conformations of each other in orderto reach optimal free energy decreases.

5. Thermodynamic methods with point mutations

Functional and thermodynamic effects of point mutations havebeen frequently analyzed and interpreted in the framework ofreceptor models. A straightforward model is a single mutationR271L of a1 human glycine receptors causing hereditary hyper-ekplexia or “startle” disease. This inherited mutation at the channelmouth is a “gating mutation”which uncouples binding from gatingand reduces agonist efficacy (Langosch et al., 1994). The R271Lmutation is far from the orthosteric binding site, thus it did notaffect the thermodynamic parameters of binding for [3H]strych-nine, an orthosteric antagonist (Maksay et al., 2002). In contrast,R271L not only decreased the efficacy and displacing potency ofglycine, a full agonist, but also resulted in a biphasic temperaturedependence for [3H]strychnine binding. This is similar to that oftaurine, a partial agonist of wild type a1 glycine receptors.Furthermore, for R271L the temperature dependence of taurinebinding became similar to that of strychnine, in accordance withtaurine becoming an antagonist. Consequently, the thermodynamicparameters of binding to a1 glycine receptors and to the hyper-ekplexia mutation fit in the thermodynamic discrimination fornative glycine receptors in spinal cord. The R271L mutant is a suit-able model to demonstrate correlations among pathophysiology,gating efficacy and receptor binding thermodynamics. Further, itconfirms that thermodynamic discrimination of efficacy is theconsequence of channel activation of pLGIC receptors predomi-nantly driven by increases in entropy (Maksay, 2005).

A statistical thermodynamic method and structure-basedcombinatorial algorithm (COREX) can generate an ensemble of low-energy conformational states; predict folding pathways and NMR-detected hydrogen exchange protection factors (Hilser and Freire,1996). Pair-wise couplings of distal mutations and functionalconnectivity along the allosteric pathway to signal transduction canbe detected with COREX (Pan et al., 2000). It can reveal theheterogeneous susceptibility to small (point mutations) and large(ligand binding) perturbations.

Double-mutant cycle analysis of proteins is a powerful tool todemonstrate energetic coupling of amino acid residues (Horovitz,1996). If the free energy change of a double mutant differs fromthe sum of those for single mutants then the residues are coupled.

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The roles of conserved residues in salt bridges and closure of theorthosteric binding cavity have been confirmed for several pLGICreceptors (e.g. Mukhtasimova et al., 2005; Venkatachalan andCzajkowski, 2008). Mutant cycle analysis could even demonstratelong-range allosteric couplings in pLGIC receptors (Gleitsman et al.,2009). High-order double-mutant cycle-couplings could also revealenergetic coupling of residues along the allosteric trajectory(Zandany et al., 2008). This was applied for a voltage-gated potas-sium channel, a symmetric homotetramer in which state transi-tions of the protomers occur in a concerted, all-or-none manner, incooperative opening of the channel according to the MWC model(Zandany et al., 2008). Higher-order couplings are propagated vialower-order couplings and overlapping spheres of perturbation(Boyer et al., 2010).

Auerbach and coworkers (Grosman et al., 2000) have analyzedthe transition states leading to channel gating of nicotinic acetyl-choline receptors. Rate-equilibrium linear free-energy relation-ships were determined for the closed-to-open conformationalchange of several point-mutated single channels. The slope value(F) of the correlations is related to the position of the transitionstate along the reaction coordinate. F values vary between0 (closed-like) and 1 (open-like). The resulting map has revealeda spatial gradient of positional values suggesting a conformationalwave from the agonist site spreading to complete opening of thepore (Grosman et al., 2000). In summary of the signal transductionof ion channels, activating interactions are spreading consecutivelyfrom sensory or ligand-binding domains of the protomers to theactivation gate while they are simultaneous in each protomer. Eventhough the allosteric transduction from binding to gating cannot bestudied directly, point mutations and their thermodynamiccoupling can pave the connecting pathway.

6. Molecular evolution of receptor proteins and allostery

Protein evolution usually leads to increases in size, symmetry,cooperative function and stability against denaturation (Goodselland Olson, 2000). Colocalization seems to be one of the mostbasic sources of molecular evolution. Self-aggregation (homo-complementarity) of peptides has been supposed to lead toprimordial peptide receptors (Root-Bernstein, 2005). Glucagonreceptors have insulin-like regions associated with glucagonbinding (hetero-complementarity). On the other hand, insulin- andglucagon-like modules of insulin receptors have recently displayedinsulin and glucose binding (Root-Bernstein and Vonck, 2010).Another theory was based on the strong binding of corticotropin(ACTH) to RNA sequences complementary to the mRNA of ACTH(Bost et al., 1985). Accordingly, coevolution of peptides and theirreceptors might have originated from translocation of the peptide’scomplementary DNA sequence.

Kuriyan and Eisenberg (2007) have also deduced evolutionarydevelopment of allostery and proteineprotein interactions fromcolocalization. Two basic principles can be invoked. First, colocali-zation of proteins increases their local concentrations by severalorders of magnitude. Second, binding increases with increasingconcentrations according to the law of mass action. They haveconsidered four significant forms of colocalization: 1) micro-compartments such as ribosomes (Fischer et al., 2010); 2) protein-DNA interaction such as for transcription factors; 3) insertion intoplasma membranes which is characteristic for ionotropic andmetabotropic receptors; and 4) gene fusion, followed by linkershortening (Kuriyan and Eisenberg, 2007). An eightfold ß/a barrelof histidine biosynthetic enzymes has evolved from an ancestralhalf-barrel by tandem duplication and fusion (Höcker et al., 2001).N-terminal extension of the primary sequence leads to the devel-opment of a cavity where the product of the synthase enzyme binds

and allosterically inhibits the synthesis (feedback regulation).A single amino acid difference at this cavity can account forthe evolutionary divergence of eukaryotic tyrosine-regulatedversus prokaryotic phenylalanine-regulated synthase isoenzymes(Hartmann et al., 2003). Colocalization facilitates the molecularevolution via spontaneous mutations which form specific interac-tions from weak ones in homooligomers (Dey et al., 2010) andresult in heteromeric oligomerization and allostery with functionalbenefits. In conclusion, the network of macromolecular interactionsis the necessary consequence of natural selection on the basis ofphysicochemical principles (Kuriyan and Eisenberg, 2007). Theevolutionary origin of differential colocalization can be mimickedby the supramolecular self-assembly of small molecules intodifferent domains depending on the type of interaction such as thephase separation of homologous amphiphiles (Pal et al., 2010). Thishelps to unravel the design rules of self-assembly leading toprimordial bio-systems.

Xu et al. (1998) have considered three possible ways for theevolution of dimers, the most prevalent oligomers. 1) Stable pro-tomer development followed by surface mutations into comple-mentary pairs. Allostery of the homodimeric tetracycline repressormight have evolved via destabilizing mutations in the hydrophobiccore of protomers which might have created ligand-bindingcavities (Reichheld et al., 2009). 2) Three-dimensional domainswapping between identical protomeric proteins with multi-domain structure (Bennett et al., 1995). 3) A dimeric speciesemerges fully formed, not preceded bymonomers. The prototypicalallosteric system, hemoglobin might have emerged as a “frozenaccident” of evolution via gene duplication into a2ß2 tetramers(Wolynes, 1996). It is interesting to know how evolutionary diver-sification and physiological adaptation affect protein structure andfunction. This question has been addressed via analysis of hemo-globin by Milo et al. (2007). The binding parameters of oxygensaturation curves have been determined for different species andpH values (physiological adaptation) according to the MWC model.Only the partial tension of half-saturation, that is, the affinity ofoxygen changed as a function of pH, while species differences werefound predominantly in the cooperativity of four protomers.Consequently, environment, pH at least, affects only the ligand-binding site while evolution seems to modify subunit interfacesand cooperativity rather than the O2-binding site (Milo et al., 2007).

The assembly path of nicotinic acetylcholine receptors has beenmodelled by computer analysis of the contact surfaces of thesubunits of a pentameric acetylcholine-binding protein homolo-gous with the extracellular domains of nicotinic receptors (Ortellsand Barrantes, 2008). Mass spectrometric and X-ray crystallo-graphic analyses of several thousands of oligomeric structures andtheir disassembly have led Levy et al. (2008) to remarkableconclusions. Membrane-imbedded oligomers, not only ion chan-nels, have central symmetry. Subunits form head-to-tail interac-tions the strength of which increases parallel with the size ofcontact surfaces. Disassembly and reassembly of the oligomers usethe same path. Bold as it is, the path of (dis)assembly seems tomimic the path of evolution. According to the authors, oligomericstructure and molecular evolution can be predicted from crystalstructures of proteins (Levy et al., 2008).

The reversibility of evolution does not follow from the abovereversibility of assembly-disassembly. At least, evolution of a DNA-binding transcription factor, the receptor of the stress hormoneglucocorticoid, seems to be irreversible (Bridgham et al., 2009). Thecontemporary receptor is activated by cortisol while a primordialreceptor by other mineralocorticoids. The evolution of ligandspecificity was reproduced by two point mutations of the ancientamino acid sequence (Bridgham et al., 2009). However, introduc-tion of these ’ancient’ residues into the contemporary protein

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resulted in inactive receptors. Five spontaneous mutations werefound which block the function of restored ancient receptor. Thisinhibition was called an “epistatic ratchet” but we can call it allo-steric as well. Reintroduction of the amino acids of either the ligandpocket or the functional ratchet resulted in receptors withoutfunction. That is, reversal of natural selection would lead to a deadend (Bridgham et al., 2009).

Electrophysiological analysis of pLGIC homopentamers led Rayeset al. (2009) to conclusions on the evolution of pLGIC receptors.Mutational diversification of a primordial homopentamer andfunctional optimization might have led to heteropentamers whoseactivation requires agonist binding inonly threeoutoffive interfacesto elicit maximal ion responses. Thus, additional response for thethird agonist is similar to the enhancement by an allosteric agent ina thirdbinding cavity, beyond theeffects of twoagonists (Rayes et al.,2009). This iswhat happens for benzodiazepines at GABAA receptors(Ernst et al., 2005) and for tropeines at glycine receptors (Maksayet al., 2009). Evolution might thus lead to homotropic, then heter-otropic cooperativity and allostery (Rayes et al., 2009). Geneticanalysis of pLGIC receptor subunits has suggested similar conclu-sions (Ortells and Lunt, 1995). A receptor archetype of about 3�109

years old has been specialized for different agonists, with homo-pentameric structure and ion selectivity. This might be the case forthe a7 and a8 subunits of nicotinic acetylcholine receptors aswell asfor 5-HT3Areceptor subunits, all ofwhich formhomopentamersandthey are functional cation channels.

Two distinct sets determining differences in D2 dopamine and5-HT2A serotonin receptors, nearly identical G protein-coupledreceptors, were revealed by difference evolutionary trace andresidue-swapping methods (Rodriguez et al., 2010). One set at theligand-binding pocket determines different affinities for theneurotransmitters, the other one elsewhere is a filter for efficacy ofG protein activation.

Statistical analysis of the sequence homology of receptor andprotein families can lead to conclusions on the evolution of allo-stery. If the mutational appearance of an amino acid in a position isless than its abundance in proteins, this might hint at restrictions ofmolecular evolution in order to preserve function (Lockless andRanganathan, 1999). Moreover, functional coupling of two, evendistant positions mutually restrict evolution which can be man-ifested in statistical coupling of the corresponding amino acids. Thismethod can reveal evolutionally conserved energetic coupling ofparticular sequence positions in membrane transporters as well ascoevolution, concerted changes of different sequence ranges andprotein sectors (Halabi et al., 2009; Jeon et al., 2009; Lockless andRanganathan, 1999; Yeang and Haussler, 2007). Combinatorialmethods can demonstrate coevolutional coupling of amino acidnetworks (Baussand and Carbone, 2009). Cluster analysis ofmetabotropic receptors revealed coevolutional coupling of aminoacids which connect the agonist-binding cavity, the G protein-binding region and the seven transmembrane regions with eachother. These amino acids form a network of van der Waals inter-actions in the interior of protein, an “allosteric core cluster” (Sayaret al., 2008; Süel et al., 2003).

Network analysis of allosteric proteins can demonstrate inde-pendent dynamic segments, modules within protein domains.Intra-modular regions including ligand binding sites are flexible. Incontrast, inter-modular boundaries are rigid. Computationalremoval of crucial nodes can reveal “fold centrally conserved resi-dues” which constitute the shortest pathway connecting themodules and have key roles in signal transmission (del Sol et al.,2007). In conclusion, allosteric pathways can be elucidated notonly by the thermodynamic coupling of experimental mutationsbut also by statistical coupling of natural mutations duringevolution.

The following structural restraints are important during diver-gent evolution: solvent accessibility, secondary structure, positivemain-chain torsion angle, and buried polar side chains hydrogenbonded to main chains (Gong et al., 2009). Functional restraints ofinterface residues and allosteric couplings help to conserveconcerted functions while a major part of the sequence may varyduring mutagenesis (Gong et al., 2009; Süel et al., 2003). Con-formationally fluctuating, intrinsically unstructured proteins seemto have the greatest evolvability (Gsponer and Babu, 2009; Tokurikiand Tawfik, 2009; Tompa, 2005). Dey et al. (2010) invoked Shannonentropy from information theory to express evolutionary diver-gence of aligned amino acid sequences. These authors concludedthat surfaces of weak homomers evolve more quickly than thechain average while interfaces are conserved better than surfaces.

Drug resistance due to rapid evolution of various microorgan-isms has been a permanent challenge for drug development. Viralmutations in HIV-1 can lead to drug resistance of reverse tran-scriptase or protease enzymes. Many mutations are far from eitherthe active site or the drug-binding pocket of HIV-1 protease butthey are in hot spots which perturb signal propagation or energynetworks stabilizing the drug-enzyme complex (Genoni et al.,2010). Evolution of the influenza A virus has led to amantadineresistance. This drug binds and occludes the pore inside thehomotetrameric M2 proton channel of the virus (Stouffer et al.,2008). Most drug-resistant mutations surround and reshape theamantadine site and decrease its binding affinity. All mutants formmore stable tetramers and increase the evolutionary fitness of thevirus.

The immune response is a microcosm of molecular evolution inorder to quickly arrest foreign compounds (James and Tawfik,2003). Conformational selection from germline antibodies is fol-lowed by somatic mutations which increase the binding affinity ofa hapten from long distance (Wedemayer et al., 1997). It has beensupposed that gene duplication result in a copy to maintainconformational flexibility while mutations in the other one lead tofunctional optimization (James and Tawfik, 2003). In conclusion,the study of rapidly evolving biosystems might elucidate better thedistinctive features of allosteric mechanisms. Generally, oligomer-ization and allostery of receptors and proteins is the result ofmolecular evolution based on physicochemical principles.

7. Design of allostery

Based on the accumulating basic knowledge of protein structureand function as well as molecular evolution, is it possible to engi-neer and exploit allostery (Freire, 2000)? In other words, how canwe mimic nature via creating artificial macromolecules, e.g.sensors, and restore functional deficiencies via allosteric ligands astherapeutic agents, drugs?

It has been successful to design orthosteric and allosteric ligandsfor receptors of known structures and to develop drugs. Severalreviews of drug design have summarized the specific interactionsof ligands and drugs with a particular receptor structure (e.g.Goodey and Benkovic, 2008; Jaakola and IJzerman, 2010; McDevittand Callaghan, 2007). This review is restricted to summarize theprinciples of allosteric mechanisms via pharmacological receptorsand biomacromolecules. X-ray crystallography, NMR spectroscopyand isothermal titration calorimetry have contributed to the recentemergence of fragment-based drug design (Murray and Blundell,2010). Scoring functions in rational design are usually based onadditivity models although group contributions to the thermody-namic parameters are cooperative often rather than additive (Baumet al., 2010).

A major prerequisite for allosteric modulation is the existence ofa binding site. Compact structures are most amenable to initiate

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signal transduction inbinding crevices likedental cavities. Such sitesmight be localized, reshaped or created in receptor proteins bycomputational design (Looger et al., 2003). Similarly, some inter-faces can be reshaped or created for desirable oligomerization(Mandell andKortemme, 2009). A straightforward interface strategyis to introduce hydrophobic groups instead of polar ones havingpoorly satisfied hydrogen bonding and to increase the interfacehydrophobic surface area, both of which might increase affinity(positive design). In contrast, negative design can destabilizecompeting states and turn homodimers into heterodimers. Speci-ficity-oriented dual (positive and negative) design often results inless stability according to the biophysical tradeoff between speci-ficity and stability (Bolon et al., 2005). However, some computeralgorithms in order to design a protein that binds a particular ligandstrongly have recently raised some doubts (Hayden, 2009).

Let us see some criteria how to design allosteric interactions.Based on structural conservation, some algorithms can find cavitieson the surface of proteins inwhich potential orthosteric or allostericligands can bind (Demerdash et al., 2009; Panjkovich and Daura,2010). In order to endow binding with functional consequences,the binding cavity should be possibly situated between subunits. Itshould be close to the end of the transduction cascade of receptors,in critical crossings of flexible structural elements. Apart from thesequalitative criteria, there are predictive algorithms which canlocalize hot spots of functional epitopes and binding allostery(Demerdash et al., 2009; Lockless and Ranganathan, 1999). Inho-mogeneous stability can be demonstrated by thermodynamic andhigh-throughput analysis of protein structure and fragmentreconstitution (Dutta et al., 2008; Pan et al., 2000). Flexible regionsfacilitate the opening of active sites for ligands while more stableones are responsible for affinity and selectivity of binding (Smockand Gierasch, 2009). By comparing active and inactive conforma-tions, the following structural parameters have been found to besignificant in allostery: hinge regions, deformation energy, solvent-accessible surface, local structural entropy and hydrogen bondingnetworks (Demerdash et al., 2009).

Binding cavities can be formed by deficiency-creating substi-tutions (Baldwin et al., 1998). Introduction of residues with smaller,less hydrophobic side chains in T4 lysozyme facilitate the binding ofhydrophobic ligands of complementary shape and size, withbinding driven by entropy increases due to solvent release.Replacement of a polar arginine by alanine residue in T4 lysozymeforms a cavity for a guanidinium ion. However, polar ligands haveto recreate intramolecular polar networks. This method is furtherlimited if multiple substitutions result in extensive destabilizationor perturbation of the local secondary structure around the cavity(Baldwin et al., 1998).

Allosteric regulation can be established and modified bycomplex genetic methods. This can be applied for biocatalysts andbiosensors. Structural module insertions can create molecularswitches by combining the genes of modules with input and outputfunctions (Ostermeier, 2005). In the actin regulatory proteinN-WASP the output domain of N-WASP was recombined withheterologous autoinhibitory input domains (Dueber et al., 2003).These switch proteins with diverse gating properties constitutea modular framework and facilitate the evolution and engineeringof signalling proteins. Another example is T4 lysozyme, a dupli-cated helix flanked with N- and C-terminal loops. Destabilizing theC-terminal loop via replacement of an arginine to alanine residueswitches the enzyme to off state. Guanidinium binding restabilizesthis loop and restores the on state (Youssef et al., 2004). Colocali-zation can elicit heterotropic cooperativity. The genes of twoproteins were coupled via a directed evolution algorithm for theallosteric regulation of ß-lactam hydrolysis (Guntas et al., 2005).The hydrolytic activity of the hybrid of a bacterial maltose-binding

protein and ß-lactamase was increased by maltose with severalorders of magnitude. The maltose-binding protein was also con-verted into a zinc biosensor by computational design (Marvin andHellinga, 2001).

A new engineering strategy, “directed domain-interferenceevolution” attaches a protein scaffold (“enhancer” domain) toa peptide-binding (capture) domain (Huang and Koide, 2010). The“affinity clamp” in the interface between these domains mightpossess high affinity and specificity. Directed evolution inducedallostery in a monooxygenase enzyme whose binding pocketwas reshaped by distal mutations (Wu et al., 2010). This methodcan change the substrate specificity and enantioselectivity ofenzymes.

Ligand binding does not elicit great conformational changes inmost proteins. However, greater changes accompany proteinfolding which can be exploited in biotechnology. Cytokines,calmodulin, disordered proteins and mRNA-based riboswitchesdisplay significant ligand-induced conformational changes; there-fore they have proved to be the most suitable biosensors (Vallée-Bélisle et al., 2009). The relationship of two opposing effects hasto be optimized via rational structural modifications and muta-tions. Even if a ligand binds to a poor-binding conformation withless affinity, its binding elicits greater signal. For example, struc-ture-switching diagnostic sensors, “molecular beacons”, syntheticDNAs prefer nonbinding stem-loop conformations. They mustchange into an extended, binding-competent conformation inorder to hybridize with the target DNA leading to fluorescenceincrease. The most stable beacon had the lowest affinity to thetarget but it gave the greatest fluorescence signal. Thermodynamicanalysis of mutants can also elucidate how evolution has optimizedbiomolecular switches (Vallée-Bélisle et al., 2009).

Point mutations might elicit significant conformational changesin small proteins. Elimination of four C-terminal amino acids ina small protein FynSH3 can prevent its folding into ß sheets (Kohnand Plaxco, 2005). In contrast, engineered proteins unfolded bymutation will refold upon ligand binding if the free energy ofbinding is sufficient to overcome unfavourable free energies offolding (Oh et al., 2009). A general method of “alternate framefolding” can engineer allosteric control into any ligand-bindingprotein (Stratton et al., 2008). One portion of the protein’s sequenceis duplicated and creates another fold that does not bind the ligand.However, ligand binding drives a great conformational change backto the native fold.

Glycine mutations on the surface of cold-adapted proteins resultin local unfolding and conformational fluctuation which createmore excited states from a native one (Schrank et al., 2009). Thesemutations did not change the overall structure of a bacterial ade-nylate kinase but even a single distant glycine mutation resulted instrong shifts of adaptive temperature (DT¼�10 �C) and thermo-dynamic parameters of binding for an adenosine monophosphatederivative (Schrank et al., 2009). In these examples, either a uniqueprotein with large, ligand-induced conformational change wasidentified first and then its ligand specificity was reengineered, oran appropriate binding protein was modified to achieve significantbinding-elicited conformational changes.

Molecular beacons have been invented for the label-free opticaldetection of nucleic acids (Tyagi and Kramer, 1996). This principlehas been recently applied for peptide beacons as engineered opticalbiosensors based on binding-induced protein folding (Oh et al.,2009). A new method of evolving protein stability does not evenrequire any knowledge of protein structure and function because ituses a genetic selection that links thermodynamic stability toantibiotic resistance (Foit et al., 2009). Stabilizing mutations of theprotein Im7 were concentrated on the surface involved in bindingto its cognate toxin colicin E7. This shows how the evolutionary

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pressure has compromised stability. This method might be used forthe optimization of subunit interfaces.

In summary, the increasing knowledge of high-resolutionstructure, folding and dynamics (e.g. via X-ray and NMR) ofoligomeric proteins, receptors and nucleic acids, as well as molec-ular evolution and adaptation, antibiotic resistance, geneticengineering, high-throughput screening and various computermethods all have contributed to the increasing versatility andefficiency of the design of allostery. It is possible 1) to find bindingsites of functional (receptor) proteins for allosteric regulation anddrug design; 2) to optimize a potential binding site for regulationvia genetic engineering; and 3) to attach a known binding proteinto the protein to be regulated via gene fusion.

8. Miscellaneous (epistemological) aspects

The bacterial flagellum has become a weapon in the hands ofintelligent design creationism (Miller, 2004). Modern flagellantslash evolution by saying that this nano-motor driving the bacterialflagellum back and forth could not be perfected by evolutionbecause its interim forms would have led the signal transduction ofchemotaxis into dead ends. This anomaly has been a worthy chal-lenge for research in evolution and allostery. The classical models ofallostery are deterministic (all-or-none); coupling of subunits isabsolute in the concerted (MWC) model while in the induced fit(KNF) model it is the effect of ligand on the conformational changeof the binding subunit which is absolute. However, allostericinteractions have been recently considered as probabilistic,stochastic rather than deterministic. The probability of statesdepends on their free energy differences; transitions proceedthrough continuous conformational spreads (Duke et al., 2001).This stochastic model of allostery has been recently supported byan optical study of the flagellar switch of Escherichia coli (Bai et al.,2010). A multistate system of the subunits of the cyclic motor dis-played strong cooperativity and the oligomer existed mostfrequently in only two states according to the MWC model.

Even farther fields of science have been affected by the terms ofallostery and evolution. Changeux, a father and tutor of the MWCmodel, and his coworkers have developed the epigenesis theory ofneuronal networks and reached far-fetched conclusions: activeinteractions between the nervous system and environment resultin selection and consolidation of preexisting internal representa-tions (mental objects) (Changeux et al., 1973), a bit like dynamicallostery in cognition (nomen est omen). Edelman (1987) has elab-orated this theory into neural Darwinism that has been developedinto a psychological trend.

In his book entitled “This Is Biology”, Ernst Mayr (1997), theevolution-biologist considered cognition in biology asking threebasic questions: what, how andwhy. “Why” is the deepest questionasking the driving force of a particular process or phenomenon.Following Darwin’s double jubilee, one can hardly challenge Mayr’view that Darwinian evolution theory has elevated biology to thelevel of “why-sciences”. This review attempts to define allostery(what?), illustrates some of its mechanisms (how?) and claims thatthe driving force (why?) of the development of allostery is naturalselection and molecular evolution based on simple physicochem-ical, thermodynamic rules. No matter how simplifying and gener-alizing this claim is, it might be valid in several fields ofbiochemistry. As to allostery, metaphorically speaking, it is a bridgeconnecting different regions of the nano-world.

Acknowledgments

This study was supported by a grant OTKA K 62203. Criticalreading of the manuscript and comments are acknowledged to

Dr. Mikko Uusi-Oukari (Turku, Finland), Dr. László Fodor (Budapest,Hungary) and the anonymous referees.

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