Allosteric approaches to the targeting of G-protein-coupled receptors for novel drug discovery: A critical assessment

An Allosteric Potentiator of the Dopamine D1 Receptor Increases Locomotor Activity in Human D1 Knock-In Mice without Causing Stereotypy or Tachyphylaxis

Allosteric potentiators amplify the sensitivity of physiologic control circuits, a mode of action that could provide therapeutic advantages. This hypothesis was tested with the dopamine D1 receptor potentiator DETQ [2-(2,6-dichlorophenyl)-1-((1S,3R)-3-(hydroxymethyl)-5-(2-hydroxypropan-2-yl)-1-methyl-3,4-dihydroisoquinolin-2(1H)-yl)ethan-1-one]. In human embryonic kidney 293 (HEK293) cells expressing the human D1 receptor, DETQ induced a 21-fold leftward shift in the cAMP response to dopamine, with a K_b of 26 nM. The maximum response to DETQ alone was ∼12% of the maximum response to dopamine, suggesting weak allosteric agonist activity. DETQ was ∼30-fold less potent at rat and mouse D1 receptors and was inactive at the human D5 receptor. To enable studies in rodents, an hD1 knock-in mouse was generated. DETQ (3–20 mg/kg orally) caused a robust (∼10-fold) increase in locomotor activity (LMA) in habituated hD1 mice but was inactive in wild-type mice. The LMA response to DETQ was blocked by the D1 antagonist SCH39166 and was dependent on endogenous dopamine. LMA reached a plateau at higher doses (30–240 mg/kg) even though free brain levels of DETQ continued to increase over the entire dose range. In contrast, the D1 agonists SKF 82958, A-77636, and dihydrexidine showed bell-shaped dose-response curves with a profound reduction in LMA at higher doses; video-tracking confirmed that the reduction in LMA caused by SKF 82958 was due to competing stereotyped behaviors. When dosed daily for 4 days, DETQ continued to elicit an increase in LMA, whereas the D1 agonist A-77636 showed complete tachyphylaxis by day 2. These results confirm that allosteric potentiators may have advantages compared with direct-acting agonists.

Exploiting protein flexibility to predict the location of allosteric sites

BACKGROUND

Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure.

RESULTS

By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity), by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing that this simple coarse-grained methodology is able to capture the effects triggered by allosteric ligands already described in the literature.

CONCLUSIONS

We introduce a simple computational approach to predict the presence and position of allosteric sites in a protein based on the analysis of changes in protein normal modes upon the binding of a coarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newly curated non-redundant set of 91 proteins with reported allosteric properties. The software developed in this work is available upon request from the authors.

The significance of G protein-coupled receptor crystallography for drug discovery

Crucial as molecular sensors for many vital physiological processes, seven-transmembrane domain G protein-coupled receptors (GPCRs) comprise the largest family of proteins targeted by drug discovery. Together with structures of the prototypical GPCR rhodopsin, solved structures of other liganded GPCRs promise to provide insights into the structural basis of the superfamily's biochemical functions and assist in the development of new therapeutic modalities and drugs. One of the greatest technical and theoretical challenges to elucidating and exploiting structure-function relationships in these systems is the emerging concept of GPCR conformational flexibility and its cause-effect relationship for receptor-receptor and receptor-effector interactions. Such conformational changes can be subtle and triggered by relatively small binding energy effects, leading to full or partial efficacy in the activation or inactivation of the receptor system at large. Pharmacological dogma generally dictates that these changes manifest themselves through kinetic modulation of the receptor's G protein partners. Atomic resolution information derived from increasingly available receptor structures provides an entrée to the understanding of these events and practically applying it to drug design. Supported by structure-activity relationship information arising from empirical screening, a unified structural model of GPCR activation/inactivation promises to both accelerate drug discovery in this field and improve our fundamental understanding of structure-based drug design in general. This review discusses fundamental problems that persist in drug design and GPCR structural determination.

Selective targeting of G-protein-coupled receptor subtypes with venom peptides

The G-protein-coupled receptor (GPCR) family is one of the largest gene superfamilies with approx. 370 members responding to endogenous ligands in humans and a roughly equal amount of receptors sensitive to external stimuli from the surrounding. A number of receptors from this superfamily are well recognized targets for medical treatment of various disease conditions, whereas for many others the potential medical benefit of interference is still obscure. A general problem associated with GPCR research and therapeutics is the insufficient specificity of available ligands to differentiate between closely homologous receptor subtypes. In this context, venom peptides could make a significant contribution to the development of more specific drugs. Venoms from certain animals specialized in biochemical hunting contain a mixture of molecules that are directed towards a variety of membrane proteins. Peptide toxins isolated from these mixtures usually exhibit high specificity for their targets. Muscarinic toxins found from mamba snakes attracted much attention during the 1990s. These are 65-66 amino acid long peptides with a structural three-finger folding similar to the α-neurotoxins and they target the muscarinic acetylcholine receptors in a subtype-selective manner. Recently, several members of the three-finger toxins from mamba snakes as well as conotoxins from marine cone snails have been shown to selectively interact with subtypes of adrenergic receptors. In this review, we will discuss the GPCR-directed peptide toxins found from different venoms and how some of these can be useful in exploring specific roles of receptor subtypes.

Drug discovery in the next decade: innovation needed ASAP

Pharmaceutical companies must find a better way to increase their output of truly new drugs for the benefit of patients and for their business survival. Here, I highlight a general perspective from within pharmaceutical research as it pertains to research advances in chemistry, biology, pharmacology, pharmacokinetics and toxicology that, if well integrated, stands to put the industry on a productive path. In addition, I provide a complementary perspective on the corporate culture aspect of innovation. I also introduce a new concept, termed 'innovation ASAP' (iASAP; asking powerful questions, seeking the outliers, accepting defeat and populating astutely) and provide support for it using examples of several successful drugs.

Drug discovery in the next decade: innovation needed ASAP

Pharmaceutical companies must find a better way to increase their output of truly new drugs for the benefit of patients and for their business survival. Here, I highlight a general perspective from within pharmaceutical research as it pertains to research advances in chemistry, biology, pharmacology, pharmacokinetics and toxicology that, if well integrated, stands to put the industry on a productive path. In addition, I provide a complementary perspective on the corporate culture aspect of innovation. I also introduce a new concept, termed 'innovation ASAP' (iASAP; asking powerful questions, seeking the outliers, accepting defeat and populating astutely) and provide support for it using examples of several successful drugs.

Nanometer propagation of millisecond motions in V-type allostery

Imidazole glycerol phosphate synthase (IGPS) is a V-type allosteric enzyme, which is catalytically inactive for glutamine hydrolysis until the allosteric effector, N'-[(5'-phosphoribulosyl)formimino]-5-aminoimidazole-4-carboxamide-ribonucleotide (PRFAR) binds 30 Å away. In the apo state, NMR relaxation dispersion experiments indicate the absence of millisecond (ms) timescale motions. Binding of the PRFAR to form the active ternary complex is endothermic with a large positive entropy change. In addition, there is a protein wide enhancement of conformational motions in the ternary complex, which connect the two active sites. NMR chemical shift changes and acrylamide quenching experiments suggest that little in the way of structural changes accompany these motions. The data indicate that enzyme activation in the ternary complex is primarily due to an enhancement of ms motions that allows formation of a population of enzymatically active conformers.

Preclinical profile of a novel metabotropic glutamate receptor 5 positive allosteric modulator

Recent reports have indicated that patients with schizophrenia have a profound hypo-functionality of glutamatergic signaling pathways. Positive allosteric modulation of mGlu(5) receptor has been postulated to augment NMDA function and thereby alleviate the glutamatergic hypo-function observed in schizophrenic patients. Here we report the in vitro and in vivo characterization of CPPZ (1-(4-(2-chloro-4-fluorophenyl)piperazin-1-yl)-2-(pyridin-4-ylmethoxy)ethanone), a structurally novel positive allosteric modulator selective for mGlu(5) receptor. In HEK293 cells stably over-expressing human mGlu(5) receptor, CPPZ potentiates the intracellular calcium response elicited by a suboptimal concentration of the endogenous agonist glutamate. CPPZ does not have any intrinsic agonist activity and behaves functionally as a positive allosteric modulator. This is further supported by binding data, which demonstrate that CPPZ is able to displace the negative allosteric modulator MPEP but does not compete with the orthosteric ligand quisqualic acid. Instead, CPPZ enhances the binding of the orthosteric ligand. In native preparations, CPPZ potentiates calcium flux in rat cortical neurons stimulated with the group I agonist dihydroxyphenylglycine (DHPG). In addition, CPPZ modulates long-term potentiation in rat hippocampal slices, a process known to be NMDA dependent. In vivo, CPPZ reverses hyper locomotion triggered by the NMDA open channel blocker MK801 in CD1 mice. CPPZ was also able to reduce rat conditioned avoidance responding to electric shock. Both in vitro and in vivo data demonstrate that this novel compound acts as an mGlu(5) receptor positive allosteric modulator, which modulates NMDA dependent responses and suggests that the enhancement of mGlu(5) receptor activity may prove useful in the treatment of schizophrenia.

Allosteric modulation of family C G-protein-coupled receptors: from molecular insights to therapeutic perspectives

Allosteric receptor modulation is an attractive concept in drug targeting because it offers important potential advantages over conventional orthosteric agonism or antagonism. Allosteric ligands modulate receptor function by binding to a site distinct from the recognition site for the endogenous agonist. They often have no effect on their own and therefore act only in conjunction with physiological receptor activation. This article reviews the current status of allosteric modulation at family C G-protein coupled receptors in the light of their specific structural features on the one hand and current concepts in receptor theory on the other hand. Family C G-protein-coupled receptors are characterized by a large extracellular domain containing the orthosteric agonist binding site known as the "venus flytrap module" because of its bilobal structure and the dynamics of its activation mechanism. Mutational analysis and chimeric constructs have revealed that allosteric modulators of the calcium-sensing, metabotropic glutamate and GABA(B) receptors bind to the seven transmembrane domain, through which they modify signal transduction after receptor activation. This is in contrast to taste-enhancing molecules, which bind to different parts of sweet and umami receptors. The complexity of interactions between orthosteric and allosteric ligands is revealed by a number of adequate biochemical and electrophysiological assay systems. Many allosteric family C GPCR modulators show in vivo efficacy in behavioral models for a variety of clinical indications. The positive allosteric calcium sensing receptor modulator cinacalcet is the first drug of this type to enter the market and therefore provides proof of principle in humans.

Exploring the intermediate states of ADP-ATP exchange: a simulation study on Eg5

While mitotic kinesins have attracted significant attention in recent years as new anticancer drug targets, the underlying mechanism of kinesin-catalyzed ATP hydrolysis is still under investigation. Crystal structures of Eg5, one of the best-studied kinesins, have been solved in both ADP-bound and ATP-bound states. However, it is still extremely challenging to experimentally obtain structural information on the functionally important intermediate states, such as the nucleotide free (apo) and the initial ATP-kinesin collision state. Systematic molecular dynamics simulations were performed in this study to mimic different nucleotide binding states and explore the critical structural and dynamic variations during ADP-ATP exchange. Clear conformational changes from "ADP-like" toward "ATP-like" were observed from the simulation results. A highly conserved residue Arg(234) was found to play a key role during the nucleotide exchange. This positively charged residue acted as the "hub" of a hydrogen-bond network that extended the effect of γ-phosphoryl group to both SW-I and SW-II regions. Comparison among the results of different nucleotide binding states indicated that the existence of γ-phosphoryl was immediately sensed at the initial ATP collision state by residue Ser(233), and this initial interaction induced the "back-door" opening and the "front-door" closing of the nucleotide binding pocket. In addition, several potential allosteric binding sites were identified through combination of correlation analysis and binding site mapping approaches based on the simulated apo ensemble, which provided additional targeting sites for novel allosteric Eg5 inhibition. These molecular simulation results provided not only a better understanding of Eg5-catalyzed ATP hydrolysis but also the structural basis for design of novel specific Eg5 inhibitors as anticancer therapeutic agents.

Allosteric Modulation of G Protein Coupled Receptors by Cytoplasmic, Transmembrane and Extracellular Ligands

G protein coupled receptors (GPCRs) bind diverse classes of ligands, and depending on the receptor, these may bind in their transmembrane or the extracellular domains, demonstrating the principal ability of GPCRs to bind ligand in either domains. Most recently, it was also observed that small molecule ligands can bind in the cytoplasmic domain, and modulate binding and response to extracellular or transmembrane ligands. Thus, all three domains in GPCRs are potential sites for allosteric ligands, and whether a ligand is allosteric or orthosteric depends on the receptor. Here, we will review the evidence supporting the presence of putative binding pockets in all three domains of GPCRs and discuss possible pathways of communication between these pockets.

Molecular determinants of non-competitive antagonist binding to the mouse GPRC6A receptor

GPRC6A displays high sequence homology to the Ca2+-sensing receptor (CaSR). Here we report that the calcimimetic Calindol and the calcilytic NPS2143 antagonize increases in inositol phosphate elicited by L-ornithine-induced activation of mouse GPRC6A after transient coexpression with Galpha(qG66D) in HEK293 cells. The calcilytic Calhex 231 did not modulate this response. A three-dimensional model of the GPRC6A seven transmembrane domains (TMs) was constructed. It was used to identify seven residues strictly conserved within the CaSR and GPRC6A allosteric binding pockets, and previously demonstrated to interact with calcilytics or calcimimetics. The mutations F666A(3.32), F670A(3.36), W797A(6.48) caused a loss of L-ornithine ability to activate GPRC6A mutants. The F800A(6.51) mutant was not implicated in either Calindol or NPS 2143 recognition. The E816Q(7.39) mutation led to a loss of Calindol antagonist activity but was without effect on NPS2143 inhibitory response. In summary, these data suggest that Calindol is primarily anchored through an H-bond to E816(7.39) in TM7 and highlight important local differences at the level of the CaSR and GPRC6A allosteric binding pockets. We have identified the first antagonists of GPRC6A that could represent new tools to analyze GPRC6A functions and serve as chemical leads for the development of more specific modulators.

Unraveling the allosteric mechanism of serine protease inhibition by an antibody

Recent structural studies have outlined the mechanism of protease inhibition by active site-directed antibodies. However, the molecular basis of allosteric inhibition by antibodies has been elusive. Here we report the 2.35 A resolution structure of the trypsin-like serine protease hepatocyte growth factor activator (HGFA) in complex with the allosteric antibody Ab40, a potent inhibitor of HGFA catalytic activity. The antibody binds at the periphery of the substrate binding cleft and imposes a conformational change on the entire 99-loop (chymotrypsinogen numbering). The altered conformation of the 99-loop is incompatible with substrate binding due to the partial collapse of subsite S2 and the reorganization of subsite S4. Remarkably, a single residue deletion of Ab40 abolished inhibition of HGFA activity, commensurate with the reversal of the 99-loop conformation to its "competent" state. The results define an "allosteric switch" mechanism as the basis of protease inhibition by an allosteric antibody.

Structure-based predictive models for allosteric hot spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues.

Allostery is the process whereby a molecule binds to one site in a protein and alters the function of a distant site. This phenomenon is ubiquitous, as proteins frequently must adapt their behavior to changes in the cellular milieu. The mechanism(s) underlying allostery remains incompletely understood. In particular, predictive models are needed that distinguish amino-acid residues that are critical to allostery, or “hotspots”, from non-hotspots. Here we have used data-mining approaches to infer rules that distinguish hotspots from non-hotspots. Starting with a data set of known hotspot and non-hotspot residues from a diverse set of allosteric proteins, the training data set, we applied machine learning to this data to “learn” models, or sets of rules, for distinguishing hotspots and non-hotspots by inferring associations between the classification (hotspot or non-hotspot) and an associated set of calculated attributes. Many models that showed the highest predictive power on the training data also exhibited high accuracy and sensitivity when applied to an independent data set. Moreover, the pattern of predicted hotspots in the proteins we studied was consistent with known structure/function relationships and previous work suggesting that a network of essential residues mediates the allosteric transition.

GPCR homomers and heteromers: a better choice as targets for drug development than GPCR monomers?

G protein-coupled receptors (GPCR) are targeted by many therapeutic drugs marketed to fight against a variety of diseases. Selection of novel lead compounds are based on pharmacological parameters obtained assuming that GPCR are monomers. However, many GPCR are expressed as dimers/oligomers. Therefore, drug development may consider GPCR as homo- and hetero-oligomers. A two-state dimer receptor model is now available to understand GPCR operation and to interpret data obtained from drugs interacting with dimers, and even from mixtures of monomers and dimers. Heteromers are distinct entities and therefore a given drug is expected to have different affinities and different efficacies depending on the heteromer. All these concepts would lead to broaden the therapeutic potential of drugs targeting GPCRs, including receptor heteromer-selective drugs with a lower incidence of side effects, or to identify novel pharmacological profiles using cell models expressing receptor heteromers.

Large-scale evaluation of dynamically important residues in proteins predicted by the perturbation analysis of a coarse-grained elastic model

Backgrounds

It is increasingly recognized that protein functions often require intricate conformational dynamics, which involves a network of key amino acid residues that couple spatially separated functional sites. Tremendous efforts have been made to identify these key residues by experimental and computational means.

Results

We have performed a large-scale evaluation of the predictions of dynamically important residues by a variety of computational protocols including three based on the perturbation and correlation analysis of a coarse-grained elastic model. This study is performed for two lists of test cases with >500 pairs of protein structures. The dynamically important residues predicted by the perturbation and correlation analysis are found to be strongly or moderately conserved in >67% of test cases. They form a sparse network of residues which are clustered both in 3D space and along protein sequence. Their overall conservation is attributed to their dynamic role rather than ligand binding or high network connectivity.

Conclusion

By modeling how the protein structural fluctuations respond to residue-position-specific perturbations, our highly efficient perturbation and correlation analysis can be used to dissect the functional conformational changes in various proteins with a residue level of detail. The predictions of dynamically important residues serve as promising targets for mutational and functional studies.

Allosteric regulation and catalysis emerge via a common route

Allosteric regulation of protein function is a mechanism by which an event in one place of a protein structure causes an effect at another site, much like the behavior of a telecommunications network in which a collection of transmitters, receivers and transceivers communicate with each other across long distances. For example, ligand binding or an amino acid mutation at an allosteric site can alter enzymatic activity or binding affinity in a distal region such as the active site or a second binding site. The mechanism of this site-to-site communication is of great interest, especially since allosteric effects must be considered in drug design and protein engineering. In this review, conformational mobility as the common route between allosteric regulation and catalysis is discussed. We summarize recent experimental data and the resulting insights into allostery within proteins, and we discuss the nature of future studies and the new applications that may result from increased understanding of this regulatory mechanism.

Transposition of three amino acids transforms the human metabotropic glutamate receptor (mGluR)-3-positive allosteric modulation site to mGluR2, and additional characterization of the mGluR2-positive allosteric modulation site

Glutamate is a major neurotransmitter in the central nervous system, and abnormal glutamate neurotransmission has been implicated in many neurological disorders, including schizophrenia, Alzheimer's disease, Parkinson's disease, addiction, anxiety, depression, epilepsy, and pain. Metabotropic glutamate receptors (mGluRs) activate intracellular signaling cascades in a G protein-dependent manner, which offer the opportunity for developing drugs that regulate glutamate neurotransmission in a functionally selective manner. In the present study, we further characterize the human mGluR2 (hmGluR2) potentiator binding site by showing that the substitution of the three amino acids found to be required for hmGluR2 potentiation, specifically Ser(688), Gly(689), and Asn(735), with the homologous hmGluR3 amino acids, inactivates the positive allosteric modulator activity of several structurally unique mGluR2 potentiators. Based on the characterization of the hmGluR2 potentiator binding site, we developed a novel scintillation proximity assay that was able to discriminate between compounds that were hmGluR2-specific potentiators, and those that were active on both hmGluR2 and hmGluR3. In addition, we substituted Ser(688), Gly(689), and Asn(735) into hmGluR3 and created an active hmGluR2 allosteric modulation site on the hmGluR3 receptor.