Allosteric Modalities for Membrane-Bound Receptors: Insights from

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Allosteric Modalities for Membrane-Bound Receptors: Insights from Drug Hunting for Brain Diseases Quinn Coughlin, Allen T. Hopper, Maria-Jesus Blanco, Vijaya Tirunagaru, Albert J Robichaud, and Dario Doller J. Med. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jmedchem.8b01651 • Publication Date (Web): 05 Feb 2019 Downloaded from http://pubs.acs.org on February 6, 2019

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Journal of Medicinal Chemistry

Allosteric Modalities for Membrane-Bound Receptors: Insights from Drug Hunting for Brain Diseases

Quinn Coughlin,a Allen T. Hopper,a Maria-Jesus Blanco,b Vijaya Tirunagaru,a Albert J. Robichaud,c and Dario Doller a,* a. Exploratory Research; b. Medicinal Chemistry; c. Discovery & Nonclinical Development. Sage Therapeutics, Inc. 215 First St. Cambridge, MA 02142, USA.

Abstract Medicinal chemists are accountable for embedding the appropriate drug target profile into the molecular architecture of a clinical candidate. An accurate characterization of the functional effects following binding of a drug to its biological target is a fundamental step in the discovery of new medicines, informing the translation of preclinical efficacy and safety observations into human trials. Membrane-bound proteins, particularly ion channels and G protein-coupled receptors (GPCRs), are biological targets prone to allosteric modulation. Investigations using allosteric drug candidates and chemical tools suggest that their functional effects may be tailored with a high degree of translational alignment, making them molecular tools to correct pathophysiological functional tone and enable personalized medicine, when a causative target-to-disease link is known. We present select examples of functional molecular fine-tuning of allosterism and discuss consequences relevant to drug design.

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1. Introduction and scope Despite the incessant progress in scientific understanding within the life sciences, there remains a large body of unknowns, and the task of finding new drug treatments to deal with human disease remains a major undertaking. The promise from the late 20th century that genomics would deliver a significant number of novel drug targets causally linked to a disease is yet to be fulfilled in many therapeutic areas – in particular for central nervous system (CNS) diseases, where the complexity of brain physiology presents daunting challenges. Fundamental mechanisms linked to higher order processes (e.g., mood, sleep/wake, chronic pain, feeding, cognition) remain insufficiently understood. Designing potential treatments based on biological hypotheses grounded on brain circuitry often show preclinical-to-clinical translational gaps. These last two factors, added to the multifactorial nature of CNS misfunction (same apparent disease phenotypes caused by different dysregulation mechanisms) portend major challenges for neurobiology.

Arguably, discovery of novel disease treatments would benefit from breakthroughs in our current scientific understanding, excursions into new experimental systems and computational models developed to enable the analysis of polygenic causal influences among brain cells.1 Less than 2% of the human genome encodes protein, often considered as a biological target of new drug action.2 Indeed, it has been suggested that viable new drug targets may be a finite resource rapidly running out and near exhaustion.3 These challenges are negatively impacting the identification of new and novel treatments for patients in need, and an infusion of productivity is immediately required to realize the potential promises of the genomics revolution. How can medicinal chemists help?

Major progress at the interface between medicinal chemistry and molecular biology achieved during the last few years is disrupting the current drug discovery paradigm and offering feasible solutions. A decade ago, one of the first questions asked when proposing a novel biological target for a drug discovery project 2


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was “is the target druggable?”. The question aimed to estimate the likelihood of identifying a small molecule that could be a good ligand to the target under examination, and incorporating the right pharmaceutical properties to achieve the desired target drug profile.4 Efforts to answer that question led to the development of a number of new chemistry modalities aimed at biologically relevant targets which are not only proteins, but increasingly, also DNA and RNA.5 While not fully validated by regulatory approvals, these novel modalities rely on using stabilized cyclopeptides,6 non-peptidic macrocycles, protein degradation by proteolysis-targeting chimeras or PROTACs,7 allosteric enzyme inhibitors and enhancers,8 antibody-based modalities (including brain target enabled bifunctional monoclonal antibodies9 and antibody-drug conjugates10), nucleic acids, protein-protein interaction inhibitors, small molecules binding to nucleic acids, and the scope of this review: allosteric small molecule modulators of membrane bound targets – mainly GPCRs and ion channels.11 Today, that early question (is the target druggable?) has mostly been replaced by “what is the right chemistry modality to achieve the desired functional target modulation?”

This understanding of allosteric drug modalities has the potential to provide medicinal chemists with a unique dexterity to create compounds acting at their biological targets with finely-tuned precision compared with classical modalities based on competitive mode of action.12,13 Furthermore, the functional consequences derived by a number of endogenous biomolecules are dependent on interactions between molecules in their physically accessible surroundings. For example, disruption of chaperone proteins14 or protein-protein interactions by small molecules, which shift the equilibria between conformations of disordered proteins15 can also be considered a particular type of allosteric interaction. Receptor activitymodifying proteins (RAMPs) are widely expressed in human tissues and, in some cases, have been shown to affect surface expression, ligand specificity, trafficking, and posttranslational modification of some GPCRs by acting as allosteric modulators via protein-protein interactions.16 However, allosteric modulation of these proteins is beyond the scope of this discussion. Given the importance, volume and 3



depth of work done with some biological targets prone to allosteric modulation and relevant to CNS diseases (e.g., GABAA, NMDAR, mGluRs, mAChRs), it should not be surprising that most of the key examples arise from research in these areas and are the focus of this work. Some examples from additional receptors are provided (e.g., D1R, P2X7, -OR ). Of note, a number of excellent reviews were recently published covering diverse aspects of allosteric drug discovery,17,18,19,20,21,22,23,24 including a themed issue of the Journal of Medicinal Chemistry.25

Allostery in drug action – Sixty Years Young The allostery concept introduced in 1961 by Monod and Jacob was based on conformational change in a two-state model for select oligomeric proteins. Allosterism was initially conceived as a concept closely linked to enzyme function, and most work focused on these types of biomolecules (Figure 1). Notably, while benzodiazepines were recognized as allosteric modulators of GABAA ion channels some forty years ago, work using allosteric modulators of GPCRs only reached meaningful levels after the year 2000.

Figure 1. PubMed hits from searches related to allosterism in drug discovery. Accessed on March 8, 2018. 4


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Since then, allostery has evolved significantly and it is now explained by advanced models based on a dynamic process linked to multiple conformational states defined by an ensemble of relevant ligands interacting with a monomeric or oligomeric biological target, and which is relevant to most, if not all proteins.26,27

2. What? Allosteric drug modalities Progress in understanding drug action at the molecular level achieved during the last decade constitutes a remarkable example of the interdependence and synergism potentially attainable by combining concepts from diverse scientific disciplines within the “Life Science” ecosystem, arguably leading to “a second molecular biology revolution”.28 On one end of the spectrum, some of these disciplines are highly virtual (e.g., computational biology, molecular dynamics, mathematical modeling). On the other end, some are heavily empirical, such as developing new biochemical systems and chemical probes to explore the nature of the functional response of a receptor, or most relevant to the medicinal chemist, the development of structure-functional activity relationships. Naturally, given their broad scope, a number of these areas may not always be familiar to industrial teams working in drug discovery or to academic scientists lacking the perspective obtained from testing large numbers of closely related analogs. By necessity, both of these groups take a pragmatic approach, focus on well-known strategies and may be reluctant to invest resources in new findings, with uncertain short-term impact.

Our experience is that allosteric drug discovery efforts benefit from a combination of mathematical, empirical and mechanistic approaches to enable deeper understanding of receptor function. In turn, these provide a common language for sharper communication between pharmacologists, pharmacokineticists

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and medicinal chemists, a necessity in the quest to deliver drug candidates. A working knowledge of the basic nomenclature of allosteric modulators is assumed.29,30 A number of complex mathematical models have been built for GPCRs and ion channels.31,32,33 A relatively simple model, although at first glance may not appear to be so, used to facilitate the mechanistic interpretation of GPCR functional effects resulting from the interaction of agonists and allosteric modulators on receptors is represented by Equation 1, sometimes referred to as the Leach equation (Table 1).34,35

E m (τ A A(K B + αβB) + τ B BK A )

n

E=

(AK B + K A K B + K A B + αAB)n + (τ A A(K B + αβB) + τ B BK A )n

Equation 1

Table 1. Definition of parameters used in Equation 1 (Leach equation). Parameter

Definition

E

functional effect caused by the allosteric modulator

Em

maximum functional effect in the system

[A] and [B]

concentrations of agonist and allosteric ligand, respectively

KA and KB

equilibrium dissociation constants for the agonist- and modulator-receptor complexes (each alone), respectively

τA and τB

efficacies of the agonist and modulator (each alone), respectively

Α

binding affinity cooperativity (the same for both the agonist and the modulator)

Β

efficacy cooperativity produced by the modulator on the agonist

N

Hill slope parameter in the system under study

6


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According to this model, allosteric drugs impact the functional response of the target protein through four parameters: KB, ,  or τB. As these parameters are independent of each other, their combination almost certainly provides diverse modalities of allosterism for non-covalent small molecule allosteric drugs.36 Clearly, this affords a major opportunity to medicinal chemists who understand how to create drug candidates with the appropriate allosteric attributes (Figure 2) as required to chemically modulate disease pathophysiology.

Figure 2. Examples of simulated concentration response curves for an agonist in the presence of saturating concentration of functionally distinct allosteric modulators.37

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While combinations of these allosteric parameters are generally seen in a given compound, chemical probes have been described occasionally where one of these effects is preponderant over the others in defining the allosteric nature of the compound. For example, PAMs characterized by τB=0 are often called “pure” PAMs, to differentiate them from “Ago-PAMs” (τB>0), which enhance the receptor functional response even in the absence of orthosteric agonist. These compounds may become important tools to define optimal allosteric target drug profiles (ATDP) and align them according to the appropriate disease pathophysiology. For example, in a disease state characterized by an excess of endogenous agonist acting at an autoreceptor (e.g., hyperglutamatergic states for presynaptic mGluR2 or mGluR4), the ATDP would theoretically be that producing enhancement of functional efficacy above the Emax of the orthosteric agonist (c, d or e on Figure 2), whose binding site is already saturated by excess agonist.38 On the other hand, a disease state characterized by insufficient agonist tone, functional enhancement at low agonist concentrations by an  PAM (such as b in Figure 2) would be more relevant (vide infra, section on muscarinic PAMs).

Figure 3 shows the concentration-response curves obtained by titrating the allosteric ligand, either in PAM mode (agonist concentration [A] = EC20) or NAM mode (agonist concentration [A] = EC80). Examples of some of these modalities are presented below.

8


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A

B

Figure 3. Modeling of concentration-response curves (CRCs) for different combinations of  and  parameters tested under conditions to detect enhancers (A, [Agonist]=EC20) or inhibitors (B, [Agonist]=EC80) of functional response. Additional parameters used are: pKA=7; pKB=7; τA=1; τB=0, n=1.5.

Equation 1 or similar may be used in a number of ways to support decision making in allosteric drug discovery projects, besides conducting simulations of different allosteric modalities as shown in Figures 2 and 3. Popular software packages use it for the global fitting of experimental functional datasets obtained varying both the concentrations of orthosteric agonist and allosteric modulator.39 A number of reports in the literature support an agreement between this model and experimental data, although this is not always the case (vide infra). Early work of medicinal chemists establishing allosteric SAR relied on classical parameters based on different agonist concentrations. For example, using EC20 of agonist to determine EC50 and Emax, of a PAM, (Figure 3A) or several agonist concentrations to measure Fold-Shift (FS, the maximal change in agonist activity in the presence of a PAM). Following a recent trend, compounds are qualified using pKB, ,  and τB values (obtained using the Leach equation), or combinations thereof (e.g., log; Figure 4). The 9



increased complexity due to more parameters required for SAR optimization, from three (EC50, Emax and FS) to four (pKB, ,  and τB), is more than offset by the ability to identify compounds with unique functional properties and avoid non-tractable SAR by deconstructing the individual contributions of these parameters to the global functional activity.22,33,40

Figure 4. Example of an SAR table for developing SAR for a putative set of PAMs using classical parameters versus those in Equation 1.

A number of recent disclosures have followed this methodology in their investigations of allosteric ligands. Selective enhancers of dopamine D1 receptors (D1R) have attracted interest as potential therapies in cognition, schizophrenia, Huntington’s disease and Alzheimer’s disease, and the D1R PAMs ASP4345 (Astellas, structure not disclosed) and LY3154207 (1) have reached clinical studies.41 A practical liability discovered with some early D1R PAM tool compounds is their species selectivity, as they are active at human and nonhuman primate D1R, but lack efficacy at the rat and mouse D1R presumably due to a single amino acid difference (R130Q point mutation).42 One successful strategy followed to circumvent this issue was the development of mice with a humanized knock-in hD1R, so as to enable in vivo readouts of behavioral efficacy.43,44 Another productive strategy included hit identification using a primary highthroughput screen (Ca2+ mobilization in D1R-G15 expressed in HEK293 cells) of the Molecular Libraries Screening Center Network,45 followed by hits characterization through a combination of functional, bias (-arrestin recruitment and cAMP accumulation) and binding affinity (vs. [3H]-SCH-23390) assays using 10


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Equation 1. This led to the discovery of two structurally distinct D1R PAM tool compounds, MLS6585 (2) and MLS 1082 (3). Table 2 shows the allosteric attributes obtained for these two compounds. Of note, the binding affinities of 2 and 3 to the D1R obtained using either a binding or a -arrestin recruitment assay show good agreement. Overall, these compounds seem to bind at two distinct allosteric sites and may operate different potentiation mechanisms.46

1

2

3

h, NHP D1R PAM

h D1R PAM

h, rat D1R PAM

species selective vs rodent

species selective vs rodent

no species selectivity

Table 2. Characterization of D1R PAMs using a combination of binding and functional assays and the Leach equation. Dopamine-induced -arrestin recruitment assayb

Binding assaya

Dopamine-induced cAMP accumulation assay

Compound

KB (μM)



Fold shiftc

Efficacy ratioc



AgoPAM

KB (μM)

Fold shiftc

Efficacy ratioc

AgoPAM

2

0.54

3.1

3

1.2

0.41

No

0.46

3

1.0

No

3

5.4

6.6

6

1.3

0.32

No

5.4

6

1.0

No

a. [3H]-SCH-23390 binding assays. b. DiscoverX -arrestin-D1R complementation assay. c. Versus dopamine alone. Data obtained from reference 46.

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The allosteric properties of compound 4 as a prototype δ-opioid receptor-selective PAM tool compound were studied using a combination of receptor binding, G protein activation, β-arrestin recruitment, adenylyl cyclase inhibition, and extracellular signal-regulated kinases (ERK) activation and applying the Leach equation (Figure 5). Probe dependency was also studied using both peptidic and nonpeptidic orthosteric agonists SNC-80 (5) and leu-enkephalin (6).47 Analysis of the data on Figure 5 indicates some consistent trends as well as significant variability in the parameters obtained (e.g., KB values across assay types). A possible explanation for this discrepancy may likely be related to the use of different cell lines for each functional readout; thus it is recommended that this type of analysis be made using cells with similar backgrounds as much as it is feasible.

4

5

 Opioid receptor PAM

 Opioid receptor selective orthosteric agonist

6  Opioid receptor selective orthosteric agonist

12


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Figure 5. Comparison of allosteric parameters obtained from the Leach equation on functional readouts from screens using PAM 4 and either orthosteric agonist 5 or 6. KA and KB values are in nM. Graphics obtained using data from reference 47.

In a clinical application of this model, Equation 1 was used to conduct the pharmacokinetic and pharmacodynamic profiling of an orally bioavailable P2X7 receptor NAM GSK1482160 (7) in healthy human subjects. In this case, with ATP as the agonist and GSK1482160 as the allosteric modulator, the model provided support for the hypothesis that 7 reduces the efficacy of ATP at the P2X7 receptor without affecting its affinity.48

7 P2X7R NAM

13



However, sometimes disparities are observed between experimental data and this model. There are multiple possible explanations that can account for such findings, including intricacies due to multiple, non-equivalent orthosteric or allosteric binding sites, receptor desensitization, state dependency, or the formation of homo- or hetero-oligomeric receptors. Nonetheless, this information is useful because it enlightens medicinal chemists of the complexities impacting the interpretation of functional and binding structure-activity relationships (SAR).

Positive binding cooperativity (-PAMs) This may be the simplest mode of allosteric modulation: when the allosteric drug enhances only the affinity of the orthosteric ligand (Figure 2, trace b). There are no major observed changes to the maximum efficacy of the system compared with that of the agonist (generally considered as Emax=100%). An important example of major efforts by many organizations seeking a drug with such an ATDP is in the area of muscarinic M1 PAMs (vide infra). BQCA (8) is an early tool compound characterized by a large =400, KB=19 μM (based on a radioligand binding assay) and τB=28 (Ca2+ mobilization assay).49 PF-06827443 (9), a related advanced preclinical compound, also showed a large left-shift of agonist potency with values of α=200, KB=3 μM, and τB=0.35.50 M1 PAM clinical development compounds include MK-7622 (10), with agoPAM properties characterized by approximate values of α=338, KB=0.95 μM, and τB=1.07,51 and PF-06764427 (11), also showing triple-digit acetylcholine FS values when tested in Ca2+ mobilization assays.52 Thus, these advanced compounds (8-11) share large binding cooperativity as a common feature.

14


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8 High FS M1 mAChR PAM

9

10

High FS

High FS

M1 mAChR agoPAM

M1 mAChR agoPAM

11

12

High FS

Low FS

M1 mAChR PAM

M1 mAChR PAM

Compounds that enhance binding cooperativity (measured by  or FS) to a very small extent may have a desirable ATDP under some circumstances where excessive activation must be avoided. One such examples is a low FS M1 PAM, which may produce use-dependent attenuation of transmitter-signaling and avoid agonist-like behavior, a limitation of previously reported high FS PAMs. It was hypothesized that compounds with very small, yet detectable functional effects could derive from a new allosteric site.53 To identify such putative binding site, the team at Roche utilized a high throughput screening of the compound collection using a cell line expressing the wild type hM1 receptor (WT hM1), followed by the use of a double Y179A-W400A mutant, corresponding to the known “gallamine/brucine site”. Thus, PAMs retaining activity at this double mutant would bind to a different allosteric site, with potential to lead to lower FS than those already known and explored (Figure 6). These efforts in conjunction with optimization of drug-like properties, led to 12 with an EC50=71 nM, Emax=72%; its FS=8.6 at human receptors was 20-40fold lower than the above referenced tools and earlier clinical compounds.

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•Stable WT human M1 receptor FLIPR HTS

Remove WT M1 agonists •Compounds tested without acetylcholine

•Addition of EC20 of acetylcholine

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mutant M1 Y179A-W400A •Exclude binders to other sites

Identify WT PAMs

•Identify low FS hM1 PAMs

FS in WT hM1 receptor

Figure 6. Strategy used to uncover low FS M1 mAChR PAMs binding to a novel binding site.

It remains to be seen whether low FS M1 PAMs, obtained via a more informed screening and design process, will identify ligands with better profiles in an area where earlier M1 PAM clinical compounds with high FS values failed to provide improved profiles compared with agonists.

Supra-physiological efficacy cooperativity (-PAMs) Have membrane receptors evolved to deliver the highest possible functional efficacy for their endogenous agonists? It appears that is not always the case, as for some notable cases (e.g., GABAA and mGluRs) allosteric modulators have been reported that enhance the system’s maximal efficacy above the nominal value of 100%, typically attributed to the endogenous agonists. In GABAA ion channels containing the  subunit, the synthetic agonist gaboxadol, also known as 4,5,6,7tetrahydroisoxazolo(5,4-c)pyridin-3-ol or THIP (13) acts as a super-agonist (not a PAM as it functions in absence of native ligand). In addition, various neuroactive steroid (NAS) PAMs also potentiate GABA responses above its Emax in vitro. In a recent study, the functional effects at 42 and 422 receptor subtypes were evaluated using recombinant receptors expressed in Xenopus oocytes for a chemically

16


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diverse group of agonists, including THIP (13) and muscimol (14), and PAMs, such as (R)-etomidate (15), pentobarbital (16), DS2 (17) and the neuroactive steroids alfaxalone (18), allopregnanolone (19) and tetrahydrodeoxycorticosterone

(3α,21-dihydroxy-5α-pregnan-20-one

or

THDOC,

20).

Maximal

modulatory efficacies, relative to saturating concentrations of GABA (100 μM), evoked currents at the two subtypes investigated are shown in Figure 7. While etomidate and pentobarbital both have efficacies moderately larger than GABA Emax, at 422, all PAMs tested have significantly larger efficacies than GABA Imax at the 42 subtype. In addition, this systematic work showed that the two subtypes studied present divergent intrinsic activation properties under the conditions of this study, showcasing the challenges associated with establishing physiologically relevant measures of subtype selectivity for some allosteric modulators.54

13

14

15

16

17

GABAA agonist

GABAA agonist

GABAA PAM

GABAA PAM

GABAA PAM

18

19

20

GABAA PAM

GABAA PAM

GABAA PAM

17



Figure 7. Modulation of efficacy for GABA-evoked 42 and 422 currents in Xenopus laevis oocytes. Values are relative to efficacies at saturating GABA concentrations. Graphic made with data reported in reference 54.

For GPCRs, support for the concept of supra-physiological efficacy has become better understood recently.55 For example, the potent and selective mGluR4 PAM ADX88178 (21) was shown to enhance the system’s maximal functional response well above that for the endogenous agonist glutamate or the selective synthetic agonist LSP-2111 (22), in a number of in vitro systems, including Ca2+ mobilization, [35S]GTPS, phenotypic “label free” and electrophysiology field excitatory postsynaptic potentials (fEPSP) measurements. Furthermore, this molecular feature (indicated by values of >1 using the Operational model) was proposed as necessary to obtain efficacy in in vivo preclinical models of pharmacological response in a system exposed to saturating concentrations of the endogenous orthosteric ligand 18


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glutamate.56 Supra-physiological efficacy was also reported for the clinical mGluR2 PAMs JNJ40411813/ADX71149 (23; Emax ca. 200%), AZD8529 (24; Emax=110%), and the tool compound JNJ-46281222 (25; Emax ca. 200%), all based on functional in vitro assays57,58,59 and, to a lower extent, for the mGluR5 PAM clinical candidate VU0409551/JNJ-46778212 (26; Emax=120%).60

21

22

23

mGluR4 -PAM

mGluR4 orthosteric agonist

mGluR2 -PAM

24

25

26

mGluR2 -PAM

mGluR2 -PAM

mGluR5 -PAM

These observations underscore that unique perspectives on drug action may be obtained by characterizing compounds made in drug discovery projects by parameters derived from operational measures of agonist functional efficacy, such as , , τB and KB using Equation 1.

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Neutral allosteric ligands (NALs) Neutral allosteric ligands (NALs), also known as silent modulators, are compounds that bind at an allosteric site but do not perceptibly impact the functional activity of the orthosteric ligand. Identification of compounds with such properties are generally rare, as they are significantly more difficult to identify, particularly if one is not looking for them. First, it takes a number of functional and binding assays to sufficiently characterize a NAL. Second, functionally inactive compounds are often not followed up with binding assays to explore their potential NAL properties. NALs may be encountered during in vitro screening in SAR studies where a potent binder is subsequently found to have no functional activity. The pharmacological properties for a handful of GPCR and ion channel NALs have been thoroughly studied. As the examples discussed below show, the lack of a functional effect upon binding of a NAL to an allosteric site does not imply lack of pharmacological effects. NALs may act competitively at the allosteric site and block PAM or NAM activity of endogenous or exogenous ligands.

SAR studies on a group of oxazolidinones demonstrated tractable features as allosteric modulators of mGluR5 with a range of functional activities (compounds 27-31; Figure 8), and led to the discovery of the potent NAL BMS-984923 (30), that enabled studies to clarify the mechanism-based neurotoxicity liabilities associated with mGluR5 activation.61 Furthermore, recent studies with 30 suggest it has potential for the treatment of Alzheimer’s disease.62 It was shown that this compound does not change agonist glutamate signaling as determined by measuring Ca2+ responses, but blocks the effects of the well characterized mGluR5 NAM MTEP, and prevents mGluR5 PAM induced seizures in vivo. mGluR5 PAMs have previously been associated with toxicities and side effects such as induction of seizures, leading many to conclude the target may not be viable. However, this work demonstrated that the ATDP of the close analogs tested (in this case, the magnitude of the FS PAM effect) was key in driving convulsions in mice: compounds with FS  3.4 did not produce convulsions in mice at saturating concentrations of compound. BMS-984923’s

20


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interaction with mGluR5, while silent in terms of agonist signaling, imparts inhibitory effects on other mGluR5 functions. It inhibits the interaction between mGluR5 and cellular prion protein (PrPc) bound to amyloid-beta oligomer (Aβo) and thereby antagonizes Aβo signal transduction and associated detrimental effects of synaptic depletion in transgenic AD mice. Mechanistic support for this hypothesis was obtained through sub-chronic dosing of 30 for 5 weeks in APP/PS1 mice, which resulted in restoration of synapses and improved memory performance but did not affect gliosis or Aβ plaques.62 Thus, while mGluR5 PAMs may lead to neurotoxicity and some mGluR5 NAMs have shown detrimental psychotomimetic effects in the clinic, an mGluR5 NAL may provide unique functional modulations and optimal therapeutic index (TI).

Compound

27

28

29

30

31

R

2-F

3-F

4-F

2-Cl

2,6-F2

ATDP

Low FS PAM

High FS PAM

Ago-PAM

NAL

NAM

PAM EC50 (nM)

1.5

0.8

0.4

>3000

>3000

Agonist EC50 (nM)

>3000

>3000

503

>3000

>3000

Fold shift

1.5

8.7

8.4

---

---

NAM IC50 (nM)

>3000

>3000

>3000

>3000

27

Binding affinity Ki (nM)

1.9

1.5

1.7

0.6

2.4

Figure 8. Structure activity relationship of a set of oxazolidinones as allosteric modulators of mGluR5 with a range of functional activities. Data from reference 61.

Allopregnanolone (19), an endogenous neuroactive steroid, acts as a PAM at the GABAA receptor, enhancing GABA-mediated Cl- currents by acting at an allosteric site distinct from the binding sites for

21



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GABA, benzodiazepines, barbiturates and picrotoxin.63 Structure–activity relationships for this neuroactive steroid binding site are defined by a 3-hydroxy group and a 20-ketone functionality in the pregnane molecule. Interestingly, the 3-OH diastereoisomer of 19, called isoallopreganolone (32), can inhibit

non-competitively

allopregnanolone-enhanced

GABA-mediated

Cl-

flux,

even

as

isoallopregnanolone alone does not affect baseline Cl- uptake nor inhibits the functional effects of up to 10 μM GABA in the Cl- uptake assay. Isoallopregnanolone does not affect flunitrazepam and pentobarbitalinduced increase in Cl- uptake, either. Thus, isoallopregnanolone appears to be acting as a NAL at the GABAA receptor. These in vitro antagonistic effects on GABAA PAMs driven by the inversion of configuration at C-3 seem to be tractable across several analogs made, and translate to the in vivo setting, as isoallopregnanolone antagonizes allopregnanolone-induced anesthesia in rats, and in humans it antagonizes allopregnanolone-induced sedation and reductions in saccadic eye velocity.64 The therapeutic potential of both diastereomeric series is being further tested in clinical studies. Among the 3-OH GABAA PAMs,65 allopregnanolone (19, brexanolone) has completed Phase 3 clinical development for postpartum depression and a New Drug Application is currently under review with the U.S. Food and Drug Administration, ganaxolone (33) is in Phase 2 stage for Postpartum Depression (PPD) and orphan epilepsies,66 and SAGE-217 (34) is in Phase 3 clinical development for PPD and Major Depressive Disorders.67 In addition, alfaxolone (18) is already approved as an animal intravenous anesthetic in some countries. Among the 3-OH GABAA NALs, isoallopregnanolone (32, sepranolone or UC1010) is under clinical studies for premenstrual dysphoric disorder,68 and GR3027 (35) is in Phase 2 for the treatment of idiopathic hypersomnia and hepatic encephalopathy.69

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32

33

GABAA NAL

GABAA PAM

34

35

GABAA PAM

GABAA NAL

Another interesting example of NAL activity by an endogenous metabolite is the case of the neuroactive oxysterol 25-hydroxycholesterol (25-HC, 36). On its own, 25-HC shows a mild potentiation of the NMDA receptor (maximum 1.2-fold potentiation of recombinant GluN1a/GluN2A NMDA receptors expressed in Xenopus oocytes).70 On the other hand, its regioisomer 24(S)-hydroxycholesterol (24(S)-HC, 37), is one of the major brain metabolites of cholesterol, and has potent NMDAR PAM activity (2-fold potentiation).71 When 25-HC is co-applied with either 24(S)-HC or its congener, SGE-201 (38), it noncompetitively antagonizes the NMDAR effect of both PAMs, 37 or 38.70 It is interesting that these two brain-derived endogenous cholesterol metabolites have opposing actions at the NMDAR, where they seem to act through distinct binding sites, suggesting a role in neuropsychiatric and neurological disorders for oxysterols.

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36

37

38

NMDAR NAL

NMDAR PAM

NMDAR PAM

From this growing body of work, it is evident that NALs may have biological effects distinct from PAMs, NAMs or compounds not binding at the respective receptor. Thus, it is important to differentiate drugs that are functionally selective (comparable binding affinities at different targets, but different efficacies) from those that provide selectivity through large differences in their binding affinities. For example, the clinical drug PF-06372865 (39) is considered a functionally-selective 2/3 GABAA PAM, even though the compound has 10-fold higher affinity for 1-subtype receptor.72 Thus, since 39 is an 1 GABAA NAL, it confers functional PAM selectivity for the 2/3 GABAA receptor. While functionally selective, 39 may have different pharmacological properties than a compound that has functional activity at the 2/3 GABAA subtype and no significant affinity for its 1-counterpart, again highlighting the importance of the defining properties of allosteric modulators.

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39 1-NAL, 2/3-PAM of GABAA

While largely unexplored, compounds with NAL functionality may have additional unique therapeutic potential, as well as major mechanistic utility as chemical probes in allosteric drug research.

Partial negative allosteric modulators (partial NAMs) Occasionally, excessive functional response by a biological receptor may lead to a pathophysiology, yet complete functional inhibition can be associated with undesired side effects and toxicity. The goal would be to have a drug that affords partial inhibition of the target to impart the desired efficacy without the undesired effects observed with high levels of target inhibition. While difficult in practice, competitive compounds may theoretically present a solution to this problem by avoiding doses leading to high levels of receptor occupancy (RO). This approach is typically dependent upon having optimal pharmacokinetic properties and usually associated with a narrow TI. An alternative improved approach to avoid such effects is to use partial NAM compounds, where full occupancy at the allosteric site provides only partial inhibition of functional response regardless of the concentration of the ligand.

25



For example, mGluR5 functional inhibition by negative allosteric modulation is a promising approach for the treatment of a variety of neuropsychiatric indications including addictions, depression and anxiety, and has been the subject of significant effort with a number of mGluR5 NAMs having reached advanced clinical testing.73 However, it has been shown that high levels of functional inhibition with NAMs such as MTEP (3-[(2-methyl-1,3-thiazol-4-yl)ethynyl]pyridine, 40) or basimglurant (41) are associated with psychotomimetic effects both preclinically and clinically, leading to the discontinuation of several clinical development programs based on this approach.74 MTEP and analogs also act as an inverse agonist at the mGluR5 receptor, which may contribute to both the efficacy and side effects, therefore complicating the data interpretation for these analogs.

VU0477573 (42), M-5MPEP (2-(2-(3-methoxyphenyl)ethynyl)-5-methylpyridine, 43) and Br-5MPEPγ (2-(2(5-bromopyridin-3-yl)ethynyl)-5-methylpyridine, 44) are examples of compounds reportedly having mGluR5 partial NAM activity. The tool compound 42 was qualified through extensive in vitro and in vivo studies, demonstrating a partial mGluR5 NAM profile. When compared with a full mGluR5 NAM across a number of biological systems, it was shown that partial functional inhibition may be sufficient for efficacy. In vitro, at full RO, VU0477573 (42) produces a maximum 80% inhibition of Ca2+ release in mGluR5expressing HEK293A cells stimulated with a concentration of glutamate that yields maximal receptor activation. In contrast, full NAMs MPEP (2-methyl-6-(phenylethynyl)-pyridine , 45) and MTEP (40) show 100% inhibition of Ca2+ release when tested under the same conditions. All three compounds show complete binding to the MPEP site, measured in membranes from the same mGluR5 expressing HEK293A cells.75

While it has been demonstrated that partial NAM activity with 42 is sufficient for efficacy preclinically, the question of whether partial NAM activity would be devoid of the undesired side effects was not initially evaluated. In a follow up paper, NAM activity at 80% RO was not associated with psychotomimetic-like

26


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effects. At full RO, where strong efficacy is observed, partial mGluR5 NAMs 43 and 44 did not potentiate PCP-induced increases in locomotor activity in preclinical models, nor did they impact PCP discrimination, suggestive of a broader TI relative to fully functional NAMs.76 However, inverse agonist activity of MTEP and MPEP on [3H]-inositol phosphate accumulation is not observed with these partial NAMs, making it unclear if the reduced potential for side effects with these compounds is due to their partial NAM activity or lack of inverse agonist activity. Nonetheless, the concept of partial NAMs remains a viable avenue for potentially safer therapeutics.

40

41

42

mGluR5 NAM

mGluR5 NAM

mGluR5 partial NAM

43

44

45

mGluR5 partial NAM

mGluR5 partial NAM

mGluR5 NAM

27



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-PAM/-NAMs (or PAM-NAMs) Historically, the functional profile of a given compound (antagonist, agonist, PAM, NAM, etc.) has been linked to a core chemical structure. However, that clearly is not the case for all allosteric modulators. For example, probe dependence shows that the actual functional response is a property of the specific combination of ligands bound to a target subject to allosteric regulation – in other words, the combination of orthosteric/allosteric ligands determine the system functional response.77 Furthermore, the same agonist/allosteric ligand pair may display seemingly opposite functionalities at closely related receptor subtypes. For example, PNU-107484A (46) was shown to act as a PAM enhancing GABA-induced Clcurrents in the 122 subtype of GABAA ion channels, but a NAM causing inhibition of the currents in the 322 and 622 subtypes.78

46

47

GABAA 122 PAM, 322/622 NAM

NMDAR PAM/NAM

Furthermore, the phenomenon known as “use dependency” indicates that a compound may have mixed effects depending on its concentration: such as enhancing the affinity for the orthosteric ligand as well as inhibiting its efficacy (Figure 2, curve f). Such compounds have been called -PAMs/-NAMs (or sometimes PAM-antagonists).79 Compared with “classical” orthosteric antagonists or NAMs, these PAMNAMs have the unique characteristic of binding more tightly to the receptor at higher agonist concentrations, thus providing a favorable target coverage in vivo versus competitive inhibitors.

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While there is a paucity of such compounds that have been characterized in the literature to-date, these are particularly important tool compounds often used in mechanistic studies. This select group includes ifenprodil (47), an antagonist of NMDA responses that in whole-cell voltage-clamp recordings from cultured cortical rat neurons antagonized functional effects of high NMDA concentrations (10 μM and 100 μM). On the other hand, at lower NMDA concentrations (0.3 μM and 1 μM), ifenprodil potentiated approximately 200% of control. Thus, with increasing concentrations of NMDA the effect of ifenprodil NMDA-evoked changed from potentiation to inhibition.80

Therefore, the inherently uncorrelated structural links for allosteric parameters for binding cooperativity () and efficacy () cooperativity may lead to therapeutically useful drugs with truly unique pharmacological properties and impossible to emulate using ligands working through competitive mechanisms with orthosteric agonists. In addition, during the characterization of new compounds, measuring allosteric drug properties at a single concentration of the orthosteric ligand may be an oversimplification and fail to provide enough information to accurately conclude on a drug’s ADTP. Indeed, the challenging tasks required to characterize allosteric ligands are also associated with delivering uniquely differentiated and potentially more valuable drugs.

Mutant protein or autoantibody-linked functional rescue The versatility of allosteric ligands to fine-tune biological function is not limited to naturally occurring protein sequences. It has been used to restore functional output away from pathophysiological limits in diseases where amino acid mutations lead to loss or gain of function receptor systems.

The gene GRIN2B encodes the GluN2B subunit of the NMDA receptor, and missense mutations have been linked to autism, intellectual disability, Lennox-Gastaut and West Syndromes and a number of epileptic 29



encephalopathies. Functionally, these mutations lead to changes in glutamate potency, increased receptor desensitization and ablation of Mg2+ block, resulting in NMDA receptor dysfunction and concomitant neurological disorders.81

NMDARs containing GluN2B gain of function single-nucleotide polymorphisms (SNPs) in GRIN2 were reported to be sensitive to the NAM radiprodil (48).82

Specifically, three gain of function mutations

(R540H, N615I and V618G) of the GluN2B subunit were studied. The R540H mutation, located in the ligand binding domain, resulted in a 2.5-fold decrease in the glutamate EC50 (with co-application of 1 µM glycine) relative to wild type receptor at pH 7.6, while the N615I and V618G forms had no impact on glutamate EC50. In the WT and R540H forms of the receptor, addition of Mg2+ gave near complete blockade of glutamate-induced current. Remarkably, the transmembrane N615I and V618G mutants had a dramatic impact on the effect of Mg2+, which rather than block, potentiated glutamate-induced current. The non-selective NMDAR channel blockers MK-801 and memantine were equally potent against the WT and R540H mutant forms of the receptors. However, relative to the WT NMDAR, MK-801 was about 30fold less potent against both the N615I and V618G mutants. Memantine on the other hand had similar activity against the WT and N615I mutant but was 30-fold less potent against the V618G form. These observations may be due to the proximity of the amino acid changes relative to the channel where MK801 and memantine bind. Radiprodil (48), a selective GluN2B NAM which binds in the extracellular amino terminal region, far from the three sites of mutation, blocks glutamate-induced currents similarly across the WT and three mutant forms of the enzyme and importantly with similar potency both in the presence and absence of Mg2+.

Yet another example is the calcium-sensing receptor (CaSR), which has many functionally disease relevant loss and gain of function SNPs leading to impaired cell surface expression and or altered functional Ca2+ and ERK signaling.83 It is therefore important to understand the impact of these SNPs on drug efficacy, as

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it has meaningful consequences in how patients are treated. The CaSR PAM cinacalcet (49) and NAM NPS-2143 (50) were able to reverse SNP-induced impairments in cell-surface CaSR expression, purportedly through protein stabilization, enabling more of the protein to reach the cell surface. It is interesting to note that this effect was independent of the functional activity of the ligand, occurring with both a PAM and NAM. In addition, cinacalcet was shown to enhance Ca2+ mobilization in some of the loss of function CaSR mutants, whereas NPS-2143 was able to reduce Ca2+ mobilization in the gain of function CaSR mutants. Several of the SNPs modified the binding affinity of these ligands, whereas others modified the level of cooperativity with Ca2+. This data demonstrates feasibility for PAMs and NAMs to maintain effectiveness in altering functional effects of CaSR mutations, and points to the highly dependent nature of both the specific SNP and allosteric modulator in question.

48

49

GluN2B-selective NMDAR NAM

CaSR PAM

50 CaSR NAM

Allosteric strategies may lead to effective treatments for diseases mechanistically linked to functional changes caused by the generation of autoantibodies under pathophysiological conditions. For example, Anti-N-methyl-D-aspartate receptor encephalitis (NMDARE) is an autoimmune disease associated with GluN1 antibody-mediated NMDAR internalization and loss of function.84 It is increasingly recognized as an 31



important cause of sudden-onset psychosis and other neuropsychiatric symptoms and comorbidities. Evidence recently obtained from in vitro studies on rat hippocampal neurons of both sexes using cerebrospinal fluid samples obtained from female human NMDARE patients or healthy controls is consistent with a loss of NMDA surface receptors caused by these antibodies. Following CSF exposure, the remaining functional NMDAR population was indistinguishable from baseline in terms of parameters such as channel open probability and synaptic or extrasynaptic NMDAR localization. Treatment with the NMDAR PAM tool compound SGE-301 (51) restored NMDAR function in samples incubated with patient CSF. This suggests that NMDAR PAMs may be a potential therapeutic strategy for NMDARE, and allosteric modulators in general, for autoimmune diseases modifying functional effects at other receptors.85

51 NMDAR PAM

Covalent allosteric modulators Drugs that bind covalently to their targets represent a drug design opportunity,86 which is beginning to gain interest within the field of allosteric modulation.87 The principal advantage of this approach is longlasting target engagement and duration of action, beyond that expected by their plasma half-life. The first example of covalent allosteric modulators was discovered by serendipity for the glucagon-like peptide-1 (GLP-1) receptor (GLP-1R) PAM scaffold. 88 GLP-1R is a class B GPCR involved in the potentiation of glucose-dependent insulin secretion for the treatment of type 2 diabetes, where only a few low molecular weight agonists have been disclosed.89 The discovery of PAMs of GLP-1R avoids the difficulty 32


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in mimicking with an agonist the complex two-step process by which the endogenous polypeptide ligands of GLP-1R activate the receptor.

Some key examples of GLP-1R PAMs are 4-(3-benzyloxyphenyl)-2-ethylsulfinyl-6-(trifluoromethyl) pyrimidine90 (BETP, 52), 6,7-dichloro-2-methylsulfonyl-3-tert-butylaminoquinoxaline91 (53), quercetin92 (54), VU045337993 (55), and HIT-465 (undisclosed structure). Several of these PAMs have been shown to increase insulin secretion in islet preparations and glucose-dependent insulin secretion in animal models of diabetes. During the process to identify the GLP-1R binding sites of 52 and 53, an unexpected mechanism of action was unveiled. These compounds potentiated the activities of several agonist peptides at GLP-1R by a covalent, irreversible mechanism, as opposed to the reversible fashion by which all other GPCR PAMs evoked their pharmacological effects. As mentioned, there are several unique potential advantages for covalent PAMs versus reversible PAMs of GPCRs, in particular more complete and prolonged target engagement.

The unexpected reactivity of 52 and 53 in the presence of glutathione or 1,4-dithiothreitol led to studies to evaluate a covalent mechanism of action. Results from washout studies in which GLP-1R-expressing cells pre-treated with 52 or 53 maintained their PAM activity after washout when activating the receptor with endogenous orthosteric agonist GLP-1(9–36)NH2. The irreversibility of the PAM activity of both compounds and the agonist activity of 53 is consistent with a covalent mechanism of action. A clickable analog of BETP (52) called PETP (56) was synthesized to confirm a covalent mechanism of action. Moreover, 56 indicated the potential for BETP (52) to alkylate a broad range of other proteins. While the covalent mechanism of action offers certain advantages as discussed above, in this case non-selective alkylation of a broad set of proteins might lead to safety and heightened immunogenicity risks.94

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52

53

54

Covalent GLP-1R PAM

Covalent GLP-1R PAM

GLP-1R PAM

55

56

GLP-1R PAM

clickable GLP-1R PAM

GLP-1R covalent PAMs contain electrophilic groups which can react with free thiol groups of cysteine residues, generating covalent adducts. BETP (52), reacts with several different cysteine residues present in the receptor, although the interaction with a specific cysteine residue (i.e., Cys347) is responsible to grant PAM responsiveness. An important part of future work will be to acquire a deeper understanding on how to modulate the electrophilic character of 52 and 53 to attain GLP-1R specificity.

Another interesting example of the use of covalent allosteric modulation in drug discovery comes from studies with the cannabinoid 1 receptor (CB1R). This target is a class-A GPCR, expressed predominantly in the brain and implicated in several physiological processes, comprising learning, memory, mood and cardiovascular regulation. Dysregulation of CB1R activity has been associated with neurodegenerative diseases and multiple sclerosis.95,96 To that end, multiple organizations have developed approaches

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towards the design of CB1R modulators.97 Org27569 (57) enhances the binding affinity of the orthosteric ligand CP55940 (58), while inhibiting its functional efficacy, being best described as a CB1R PAM/NAM (vide supra).98 Recently an analog of 57 containing an isothiocyanate reactive group at C5 was synthesized (59)99, which interacts with CB1R in a covalent fashion has higher potency and efficacy than the parent, Org27569 (57), in CB1R-dependent -arrestin recruitment and cAMP accumulation. In addition, compound 59 demonstrated the highest functional selectivity (83-fold) for recruiting -arrestin relative to stimulating cAMP production. Importantly, it was also devoid of inverse agonism, a function previously associated with psychotropic side-effect caused by CB1R orthosteric antagonists or inverse agonists.

57: X = -Cl, CB1R PAM

58

59: X = -N=C=S, covalent CB1R PAM

CB1R agonist

The design, synthesis, and pharmacological characterization of the first covalent PAM for a class C GPCR, the mGluR2 receptor, was recently reported.100 Positive allosteric modulation of the mGluR2 receptor has been pursued as a therapeutic approach for neurological disorders such as schizophrenia and anxiety.101 Although the structure of the extracellular domain of the mGluR2 receptor is known, the current structural understanding of the 7TM domain is based on the crystal structures of the mGluR1 and mGluR5 7TM domains. These were crystallized in an inactive state with a NAM bound in the allosteric binding pocket.102,103,104 Aiming to further understand mGluR2 PAM binding and receptor pharmacology, three putatively covalent mGluR2 PAMs, compounds 60, 61, and 62, were designed to take advantage of the privileged nature of sulfonyl fluorides, which display the right balance of stability and reactivity towards 35



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nucleophilic protein residues.105 In vitro pharmacological characterization led to the identification of 60 as a chemical biology tool compound binding covalently to mGluR2. Kinetic parameters for JNJ-46281222 (25) were determined using classical binding experiments with [3H]JNJ-46281222 (63), having a residence time (RT) of 12 min, association rate constant kon of 1.2 × 106 M−1s−1 and dissociation rate constant koff of 0.0013 s−1. In comparison to 63, compound 60 displayed a much slower on-rate (kon of 3.2 × 103 M−1s−1) and an insignificant off-rate (koff of 3.2 × 10−13 s−1), leading to an infinite RT. As a result, it was concluded that compound 60 was acting through an irreversible binding mode.

60

61

Covalent mGluR2 PAM

Covalent mGluR2 PAM

62

63

Covalent mGluR2 PAM

mGluR2 PAM

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In addition, computational docking identified several amino acid residues that could potentially form a covalent interaction with 60. Subsequent mutagenesis studies identified T7917.29×30 as the position of the covalent interaction. Due to its favorable allosteric properties, compound 60 was presented as a tool compound and a starting point to further evaluate the use of covalent ligands for mGluR2 structure elucidation and pharmacological characterization.

Covalent allosteric modulators have potential pharmacological merits, including increased biochemical efficiency and higher specificity, extended duration of action and lower toxicity. The design of covalent allosteric modulators has, not surprisingly, proven arduous. An initial major hurdle is simply the identification of allosteric binding pockets, much less the good fortune to have a nucleophilic residue in proximity to covalently interact with an allosteric ligand in such a way that PAM or NAM activity is maintained. For these reasons, most covalent allosteric modulators have been found serendipitously.

Biased allosteric modulators An agonist binding to a receptor can activate numerous signaling pathways. Recent evidence demonstrates that different ligands may lead to differential activation of the downstream pathways by stabilizing a limited range of receptor conformations. This concept, termed “biased signaling” (also called “stimulus trafficking,” “functional selectivity” and more recently, “agonist bias”) represents an exciting therapeutic opportunity to target specific pathways that elicit only desired effects, while avoiding undesired effects mediated by different signaling cascades via preferential stabilization of selected conformational states. Different ligands acting on the same GPCR, in the same tissue, can give rise to markedly different cellular responses due to each ligand stabilizing different receptor conformations.106

37



While biased agonists activate selective downstream pathways, selective modulation of a specific receptor within a highly homologous family of receptors is challenging due to high sequence homology of the agonist binding site. In such cases, allosteric modulators that allow binding to a site other than the orthosteric site potentially enable selective modulation of the receptor. Due to the nature of binding at a non-orthosteric site, allosteric modulators allow refinement of signaling efficacy to desired levels. Recently, biased allosteric modulators have been reported, that selectively modulate the ability of agonists to stabilize specific active conformations of the receptor and differentially alter the effects of the endogenous agonist on specific signaling pathways, such as compound 60, as discussed above.105 Several examples follow wherein such biased modulation offers potential for an improved therapeutic window by limiting undesirable effects.

NMDAR hypofunction plays an important role in the pathophysiology of schizophrenia and administration of agents that enhance NMDAR function provides symptomatic improvement in schizophrenic patients.107,108 Metabotropic glutamate receptor subtype 5 (mGluR5) is a closely associated signaling partner with the NMDAR and activation of mGluR5 potentiates NMDAR responses and NMDAR-mediated synaptic plasticity in forebrain regions implicated in the pathology of schizophrenia.109 However, excessive activation of NMDARs, including their potentiation by mGluR5 activation, can induce seizures and excitotoxicity in preclinical models. These adverse effects were reduced but not eliminated after chronic treatment with mGluR5 PAM 5PAM-523 (64).110 This led to a hypothesis that a biased mGluR5 PAM could selectively dissociate the toxic NMDA modulating effects from the desired downstream effects of mGluR5 and therefore improve tolerability and broaden the therapeutic window. Indeed, efforts to dissociate NMDAR activation led to the identification of a biased mGluR5 PAM, VU0409551 (26) that potentiates mGluR5 coupling to Gq, Ca2+ mobilization and ERK phosphorylation but does not enhance mGluR5 modulation of NMDAR currents. Compound 26 produced robust antipsychotic-like and cognitionenhancing effects in rodent models,60,111,112 suggesting NMDAR-independent actions. This NMDAR sparing 38


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activity was associated with a better tolerability profile where chronic administration of VU0409551 had no adverse effects at doses over 100-fold those required to achieve in vivo efficacy.60 This data demonstrates that biased PAMs-mediated signaling of GPCRs can dissociate the signaling pathway(s) that produce undesirable effects.12

64 mGluR5 PAM

The CaSR is a family C GPCR with a variety of coupling partners including Gg/11, Gi/o, G12/13 and. Its function is also linked to β-arrestin and filamin A. CaSR activation by its endogenous ligand Ca2+ leads to a decrease in parathyroid hormone (PTH) release (desired activity for treating hyperparathyroidism) and an increase in calcitonin release (undesirable activity, leading to hypocalcemia). The calcimimetic drug cinacalcet (49) acts as a PAM of the CaSR and is used clinically to treat secondary hyperparathyroidism (elevated PTH). Clinical use of cinacalcet in hyperparathyroidism, however, is limited to treatment of only end-stage renal disease due to its enhancement of calcitonin release resulting in hypocalcemia. CaSR regulates extracellular Ca2+ levels in the body. When Ca2+ levels rise in the parathyroid gland, CaSR activation suppresses the secretion of parathyroid hormone (PTH) resulting in reduced renal Ca2+ reabsorption and reduced bone resorption113. In addition, CaSR also mediates numerous non-calciostatic roles.114,115,116 While drugs targeting CaSR have therapeutic applications, they are limited by adverse effects arising from actions in multiple tissues expressing the CaSR. Indeed, cinacalcet causes hypocalcemia117 likely due to reduced calcium reabsorption induced by CaSR in the kidney and calcitonin-mediated inhibition of bone resorption via CaSR activation in the thyroid C-cells.118 39



Biased modulation of CaSR to maximize suppression of PTH levels while minimizing the release of calcitonin is hypothesized to provide a more desirable profile for treating hyperparathyroidism and avoiding calcitonin-induced hypocalcemia. (S)-AC-265347 (65), a third generation CaSR PAM, appears to have enhanced tissue-selective effects due to biased signaling. It inhibits PTH secretion at concentrations that do not induce calcitonin release in rats hypothetically due to ligand-biased allosteric modulation towards pERK1/2 and IP1 accumulation.119,120 (S)-AC-265347 exhibited high cooperativity in pERK1/2 assays, maximally enhancing the potency of extracellular Ca2+ nearly 10-fold, compared to 3-fold enhancement with cinacalcet. Thus, it is possible to selectively modulate CaSR for beneficial effects while avoiding undesirable effects using biased allosteric modulators. Further understanding of the effects of the signaling pathways will facilitate translation of preclinical observations to clinic.

65 Biased CaSR PAM

Ion channels may potentially display functional bias as they are modulated by allosteric ligands, which manifest itself as changes to the selectivity for permeant ions and/or the dynamic properties characterizing the opening/closing properties of the channel. These effects have been reported for voltage-gated,121,122,123 mechanosensitive,124,125 and ligand-gated ion channels.126,127 Mechanistically, ligands are thought to alter the quaternary structure of some channels or the tertiary structure of a given subunit. Likewise, the discovery that some ion channels regulate other receptors or signaling enzymes (e.g., ERK, PI3K, Rho), provides another mechanism by which ligands may impact the functional outcome of their interactions with ion channels in a biased way.128 40


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These changes to ion channel protein dynamics by allosteric ligands are described through two parameters captured by the terms of type I and type II modulators. This behavior has been observed for a number of ion channels. For example, the 7 nicotinic acetylcholine receptor (nAChR) PAM chemical probes 5-HI (66) and genistein (67) predominantly affected the apparent peak current (type I) whereas PNU-120596 (68) and TQS (69) increased the apparent peak current and evoked a distinct weakly decaying current (type II).129 This functional nomenclature has also been extended to NMDAR allosteric modulators, where type I PAMs such as PYD-106 (70) or oxysterols such as 37 or 38 modulate mainly peak current, and type II PAMs such as spermine (71) modulate current decay times, while pregnenolone sulfate (PS, 72) seems to function as a mixed PAM with both type I and type II PAM effects.130 The same principles apply to NAMs of GABAA like PS, which acts mainly via a type II mechanism by both mostly increasing desensitization kinetics and, to a smaller degree, depressing peak chloride currents.131,132 Linking these in vitro effects to unique and distinct potentiation profiles in vivo could potentially offer unique opportunities for the development of tailored CNS therapeutics.

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(S)-2-amino-3-(3-hydroxy-5-methylisoxazol-4-yl)propanoic acid receptors (AMPARs) are among the most extensively studied ion channels. Numerous crystal structures of wildtype and mutant proteins obtained using different ligands led to models for receptor activation (channel opening by agonist binding) and desensitization (channel remains closed while agonist is still bound), inhibition by antagonists and block of desensitization by PAMs.133 Mechanisms of ion channel functional modulation by allosteric ligands have been described in terms of alterations to molecular dynamics selectively triggering pre-existing cooperative motion modes, which are already encoded by the receptor structure. The effects may be felt by the receptor as a whole or by isolated protein domains and impact an extensive spectrum of dynamic rearrangements leading to changes to receptor function.134 While collectively these processes govern the magnitude and time course of synaptic transmission, individually they are thought to be independent of each other, leading to distinct patterns of modulation by allosteric ligands.135 For example, using twoelectrode voltage clamped X. laevis oocytes expressing GluA4i receptors, the AMPAR allosteric modulator NS1376 (73) showed functionally opposite effects, reducing 30-fold and 42-fold glutamate potency but enhancing glutamate efficacy by 3-fold and 5-fold at GluA4flip and GluA4flop, respectively.136 42


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Most AMPAR PAMs studied to-date appear to bind to a common, solvent-accessible allosteric binding region localized close to the plasma membrane at the interface between two subunits, near the extracellular domain of AMPA receptors. Studies using a number of distinct AMPAR PAM chemotypes suggest the existence of as many as five “subsites” with distinct modulator affinities and apparent efficacies.137 Upon binding to the allosteric site, these compounds enhance agonist response either by attenuating desensitization and/or by slowing receptors deactivation, and facilitate induction and maintenance of long-term potentiation, a form of synaptic plasticity that is believed to underlie memory formation. The AMPAR PAM S 47445 (74) was characterized using receptors expressed either in Xenopus laevis oocytes or in HEK293 cells and rat cortical cell cultures. S 47445 robustly increased the amplitude of the glutamate-evoked current and prolonged the response time. Furthermore, low concentrations of S 47445 (below the EC50) added upon repetitive glutamate pulses induced a progressive potentiation of the glutamate-evoked currents. Of note, this effect was not accompanied by desensitization after several glutamate pulses.138 Among AMPAR NAMs, the most recognized example is perampanel (Fycompa, 75), which obtained FDA approval in 2012 as an antiepileptic drug to treat partial seizures and generalized tonic-clonic seizures for people older than 12 years. The blocking mechanism of perampanel has recently been characterized as high-affinity (Kd=60 nM in rat forebrain membranes), with similar affinities for the open and closed states of AMPA receptors and with no effect on AMPA receptor desensitization.139 Using whole-cell voltageclamp recording in cultured rat hippocampal neurons, perampanel showed a slow, concentrationdependent inhibition of AMPA-evoked AMPAR currents. The rates of block and unblock of AMPA receptor currents indicated relatively slow but reversible block onset and recovery.140 Not much is known about the location and structure of binding sites for perampanel or other prototypical AMPAR NAMs such as GYKI-53,655 (76) and CP-465,022 (77). Work towards identifying NAM binding sites and binding modes is crucial to understand the molecular mechanism and can lead to future development of other NAMs.141 43



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Allosteric modulation of kainate receptors (KRs) is not as well understood as for their AMPAR or NMDAR counterparts. Excellent progress in the area of structural biology has yielded important insights at the molecular level, including knowledge of binding modes of KRs agonists and antagonists.142 The same principles as for other ion channels seem to apply to KRs in terms of allosteric ligands exerting functional effects via impact on properties such as agonist-evoked peak current amplitude, deactivation or desensitization kinetics.143 The difficulties in rationalizing, let alone predicting the functional consequences derived from allosteric ligands acting on ion channels point to the challenging aspects of proactively designing and accurately translating in vivo pharmacological effects of allosteric modulators acting at membrane bound proteins.

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Therefore, numerous examples exist of more traditional drug candidates that failed in the clinic for any number of reasons, many due to mechanism-based dose-limiting adverse effects and limited efficacy due to inadequate target coverage. In some of the examples above, biased signaling drug candidates demonstrated the ability to overcome these shortcomings to provide potentially safer and more efficacious therapeutics.

3. How? Allosteric ecosystem and protein dynamics A view of the molecular mechanisms by which allosteric drugs exert their effects is developing on the basis of new perspectives gained from three major areas: structural biology, protein conformational dynamics and the contribution of system chemistry to cellular homeostasis (the allosterome).144 The number of publications and entries in the Protein Data Bank pertaining to structural information of allosteric modulators interacting with their protein targets is rapidly growing, including both GPCRs145 and ion channels.146 This is partly due to improvements in protein purification and crystallization techniques for membrane bound proteins,147,148,149 as well as to the increasing resolution and availability of electron microscopy (Cryo-EM) for structural elucidation.150 Examples include identification of distinct binding sites for inhibitory or potentiating oxysterols at a chimeric GABAA homopentamer formed by 3 extracellular domains and 5-transmembrane domains,151 or high-resolution Cryo-EM structures of the human α1β2γ2 GABAA receptor bound to flumazenil, used as first-line clinical treatment for benzodiazepine overdose.152 Likewise, crystallographic structures published recently for the NMDA receptor reveal new aspects of this complex receptor. For example, the discoveries of GNE-0723 (78) and GNE-9278 (79), GluN2A-selective NMDAR PAMs, were enabled by structure-based studies, showing distinct binding sites for these two structurally-related compounds. The former binds the GluN1/GluN2A ligand binding domain interface at an analogous site to where AMPAR PAMs bind,153 while the latter binding to a unique site on the 45



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extracellular surface of the transmembrane domain.154 These X-ray crystallography studies suggest chemically related allosteric modulators may bind at different receptor areas and impact receptor pharmacology in distinct ways.155

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Glu2A selective NMDAR PAM

A recent retrospective analysis comparing and contrasting X-ray crystallography structures of a set of known (45, 80-82) and novel (83, 84) mGluR5 NAMs showed that small molecule allosteric ligands bind in the transmembrane domain of the mGluR5 receptor, with access to a narrow subpocket not accessible in other mGluR subtypes. In addition, this allosteric site of mGluR5 is located in a functional water channel, where the binding pocket is occupied by water molecules thought to affect signal transduction. The impact of a small ligand on these water molecules may provide favorable or unfavorable contributions to binding, depending on whether they displace high free-energy (“unhappy”) water molecules or low freeenergy (“happy”) water molecules.156

While these observations are important, gathering such insights in a prospective manner such as to guide SAR efforts would require routine access to multiple X-ray structures, unlikely for most groups working on transmembrane proteins. Substituting structural biology determinations with computational docking studies may be risky. For example, fenobam (81) showed a novel binding mode where the ligand is rotated 180° when compared with previous docking models.157 This new orientation shown in the crystallographic 46


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work could be related to the different linker structural motif, an urea in 80 vs. an acetylenic linker in MMPEP (81) and mavoglurant (82), leading to different growing vectors identified for the head groups as well as unexpected water-mediated receptor interactions. Despite the differences between the crystallographic and the computationally docked poses, nanomolar potency compounds were obtained.156 Therefore, while some of these structural biology observations may explain differences among analogs, assessment of functional activity ultimately resides on an empirical evaluation through in vitro assays. The fate of GPCR allosteric modulator drug discovery projects is probably brighter when multiple, orthogonal approaches are pursued in parallel.156

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Structural biology studies provide valuable insights on the allosteric binding location and relative orientation of ligands and residues in the receptor binding pocket, as well as protein conformational changes required for the binding event as reported in crystallographic studies. However, the ensuing functional effects (e.g., PAM or NAM) are not predicted from these solid state studies, suggesting protein 47



dynamics aspects are at play. Thus, learnings from structural biology of allosteric modulators of membrane bound receptors are not always as useful guiding SAR development by medicinal chemists as they might be in kinase inhibitor projects, for example, due to the inability to predict functional effect.

The study of protein folding and molecular dynamics are gaining much appreciation. One classical view of protein biochemistry is that its amino acid sequence defines a single three-dimensional native conformation serving a single biological function. This view has strong support from X-ray crystallography studies, the most commonly used technique for structure determination. This view of the sequencestructure-function relationship has recently evolved as new experimental evidence suggests a far more complex nature of protein structure. Proteins often perform multiple functional tasks, in part due to their considerable structural flexibility. Thus, elements of structural dynamics and conformational plasticity are increasingly recognized as important attributes that contribute to protein function. This view is consistent with modern technologies like nuclear magnetic resonance spectroscopy and molecular dynamics computational calculations. Indeed, this new perspective led to proteins being described by qualifiers such as intrinsically disordered proteins, morpheeins, chameleonic sequences, and metamorphic proteins.15

Allostery provides a mechanism by which functional biomolecules such as proteins or nucleic acids are able to sense the changing concentrations of molecules in the neighboring cellular matrix and respond with the appropriate functional effects to maintain cellular homeostasis. This adjusting takes place very rapidly, essentially at diffusion-controlled rates and in a reversible manner unlike covalent posttranslational modifications (e.g., phosphorylation, dephosphorylation), and with a minimal energy cost. Thus, allosteric regulation of functional response provides a complementary mechanism of cellular regulation, with unique attributes from transcriptional or translational regulation, alternative splicing, post-translational covalent modifications, degradation, localization, or protein–protein interactions.144

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How are protein dynamics and system chemistry relevant to allosteric drug function? In the simplest case, a protein bound to an orthosteric ligand exists in one of two states: active or inactive (Figure 9.A). The minima are separated by a surmountable energy barrier, and the respective conformations interconvert between these states. Upon binding, the allosteric modulator modifies the free energy balance of the system, stabilizing (or de-stabilizing) a specific conformation, linked to a signal transduction pathway. This model is very much in line with lessons learned designing competitive ligands. However, it was not able to sufficiently explain observations from early days in allosteric dug research, where non-additive or nonlinear structure-activity relationships or switches in functional activity (e.g., PAM to NAM) caused concern among medicinal chemists about the chemical tractability of such targets. Furthermore, such switches appear to be a feature of GPCRs and ion channels, where small structural modifications to GPCR ligands often convert agonists to antagonists and vice versa, frequently accompanied by negligible changes in binding affinity. Examples of functional enhancer/inhibitor switches within the same chemical core have been reviewed for GPCRs and won’t be discussed here.158

Proteins are dynamic macromolecules and display many degrees of conformational freedom, reflected by ensembles of conformations with a certain distribution (Figure 9B). Molecular dynamics simulations predict a protein’s access to different shapes with unique signaling properties and functional states within such ensemble of conformers. “Functional selectivity” may be obtained if an allosteric ligand can induce a subset of the ensemble of responses.159 The biology associated with the protein is also modulated according to the residence time in each energy minimum. Allosteric modulator association and dissociation kinetics, which determine the residence time on the receptor, may differ for different conformations. The duration of a ligand–receptor complex may then lead to changes in the conformational landscape over time, giving rise to the phenomenon called ‘kinetic bias’.160

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Figure 9. Free energy versus conformation diagrams A. Classical system with one active and one inactive protein confirmation and the changes produced by an allosteric ligand (PAM in this case). B. Model considering a number of conformations, each one providing its own distinct contribution to the global functional response. Addition of an allosteric ligand creates a comparable number of local changes, and the resulting impact on global function.161

In summary, the recognition of a receptor as the platform where the relevant chemical “allosterome” defines the global functional effects implies that these are determined by a number of conformationally distinct entities, linked among themselves by their dynamics.

4. Why? Is a thorough characterization of allosteric drug effects worth the effort? The inherent difficulties and potential rewards of allosteric drug design are clear in many protein families, but GPCRs are likely the most contemporary (Figure 1). The early years of GPCR allosteric drug discovery faced many unexpected disconnections, as assumptions carried over from earlier medicinal chemistry 50


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learnings using competitive ligands were routinely challenged. One such example is seen in efforts targeting muscarinic acetylcholine receptors (mAChRs).162 As discussed previously, these receptors are attractive drug targets due to their promising, yet unfulfilled, clinical therapeutic potential. Medicinal chemists have traditionally focused on developing selective mAChR agonists binding at the orthosteric acetylcholine binding site, particularly for the M1 mAChR subtype. However, mounting research demonstrated that orthosteric M1 ligands are non-subtype selective due to high orthosteric site homology across members of the mAChR family (M1-M5). Moreover, acute agonism of muscarinic receptors yields side effects such as seizures and generalized convulsions. Considering these limitations, efforts have gradually shifted from M1-selective orthosteric agonists to M1-selective PAMs with minimal agonist activity, assuming functional enhancement based on allosteric ligands would circumvent side effects observed with orthosteric agonists.162,163

One of the earliest putative M1 PAMs, benzyl quinolone carboxylic acid BQCA (8), was first reported in 2008. Claims of BQCA allosteric activation of the M1 receptor were supported by mouse EEG, Laser Doppler blood flow, and sleep telemetry.164 A follow-up study bolstered these reports, demonstrating that 8 is >100-fold more selective for the M1 receptor than its counterparts M2-M5 (no changes to functional concentration-response curve of acetylcholine in a Ca2+ mobilization assay) and potentiates the effects of the agonist acetylcholine at M1 up to 100-fold.165 While these studies were initially promising, further experiments revealed that 8 alone (no added agonist) also activates M1 in cell types expressing high levels of the receptor.166 These data indicate that 8 itself weakly stabilizes an active conformation of the M1 receptor, but functional effects are only observable when signal-response coupling is relatively robust (i.e., high receptor and second messenger expression) or 8 alone is at high-micromolar concentrations.165,166 As a result, 8 has been labeled as an “ago-PAM” because it acts both as an allosteric agonist (τβ>0) and as an allosteric potentiator of orthosteric ligand-mediated activity. This also

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underscores a need for careful interpretation of functional readouts obtained in Ca2+ functional tests on allosteric ligands.

Other attempts to create M1 PAMs have encountered similar pitfalls and contradictions despite initially encouraging functional data. For example, two putative M1 PAMs, VU0090157 (85) and VU0029767 (86) have different functional effects. Compound 85 selectively potentiated PLC activation while 86 selectively potentiated PLD activation.167 These findings suggest that different M1 allosteric ligands regulate receptor coupling to downstream signaling pathways by distinct mechanisms – known as signal bias. Therefore, distinct pharmacological profiles may be encountered with these two M1 PAMs, suggesting the benefits of deeper functional allosteric drug characterization.

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In a different case, MK-7622 (10), a reportedly highly selective M1 PAM, was progressed to Phase 2 clinical trials for a pro-cognitive endpoint in Alzheimer’s patients. Ultimately, the trial was terminated due to lack of efficacy shown by 10 as an adjunctive therapy to acetylcholinesterase inhibitors vs. placebo in improving cognition in AD patients.168 Besides these findings, 10 independently was shown to induce seizures at high doses in mice, as well as directly agonize Ca2+ flux in M1-expressing CHO cells with a B>0, indicating that 10 acts as an ago-PAM.169

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Another clinical M1 mAChR PAM, PF-06764427 (11), potentiates acetylcholine agonism at low concentrations,

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concentrations.169,170,171 Additional in vitro and in vivo studies have roundly characterized 11 as strong agoPAM with adverse effects such as pronounced behavioral convulsions in mice.170,171,172

Over the last decade, research on these difficult-to-characterize biased PAMs and ago-PAMs has made it clear that M1 mAChR PAMs (and generally other GPCR allosteric modulators) exhibit different modulating properties depending on the orthosteric ligand used in in vitro assays, the relative expression and/or coupling strength of the downstream G-protein signaling cascade, the modulator’s bias toward one or more active conformation over others, receptor subtype selectivity, and so on.169 This suggests that different PAMs will modulate multifaceted receptor functional states in different ways, such that one or several functional conformations might be stabilized over others. In other words, medicinal chemistry research on allosteric modulators is revealing that the model where functional states of proteins are thought of as two-state systems (active/inactive) may be an oversimplification (Figure 9).

The unexpected pitfalls described above suggest that allosteric modulators may mitigate preventable risks and benefit from more nuanced approaches than customarily conducted with drugs designed to compete directly with orthosteric ligands. As discussed, this complexity demands an increased diversity of functional assays for compound characterization. In general, using a single in vitro assay (e.g., only an intracellular Ca2+ mobilization assay) before moving to inherently more complex in vivo behavioral models may incompletely address the different molecular mechanisms of action and transduction pathways by which an allosteric ligand might modulate functional response. Informative functional assays that might be used as a supplement for GPCR projects include cAMP accumulation, [35S]-GTPS binding, whole-cell electrophysiology, β-arrestin screens, label free assays, and so on. These assays would be performed over a range of native ligand concentrations, PAM concentrations and if possible, receptor expression levels,

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as demonstrated in the BQCA example. In a minimal case, exploration of biased modulation and physiologically relevant functional assays (e.g., in native tissues) are preferable before advancing to behavioral assays. In addition, due to probe dependency, the native ligand of a protein target (and potential endogenous allosteric ligands) is considered as ideal when conducting binding assays with allosteric compounds.

An example of combining multiple functional assays to characterize potential PAM/ago-PAM activity comes from Vanderbilt University. Recently, robust PAM activity was demonstrated for VU0453595 (87) and VU0550164 (88) by contrasting these compounds with the ago-PAMs, MK-7622 (10) and PF-06764427 (11).171 These compounds were characterized in a workflow situated within a physiologically relevant context that is properly suited to an allosteric model: wherever possible, native ligand was used to avoid probe-dependent artifacts and functional characterization was rigorously pursued both in vitro (i.e., Ca2+ accumulation and whole cell electrophysiology) and in vivo (i.e., cortical extracellular field electrophysiology) before attempting behavioral assays.

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Through these comparisons of known ago-PAM, a compelling argument was made that 87 and 88 may indeed positively modulate acetylcholine without intrinsic agonist activity. However, a potential weakness in their presentation is that no assay addressed the possibility of biased modulation of G protein signaling pathways. This may problematically overlook these compound’s unique modulation profiles.

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In summary, research aiming to discover allosteric drugs would maximize its probability of success by conducting a nuanced, mechanistic approach to compound characterization and informing medicinal chemistry decision-making. Given the factors impacting allosteric drug effects that remain to be understood—such as in silico predictions of conformational free energy landscapes and folding kinetics— the empirical characterization of allosteric ligands must be as thorough as practically feasible. The benefit of such an approach is clear, as amply demonstrated by the example of M1 mAChRs. Similar factors are most likely at play for the design of allosteric modulators of ion channel functional response. Classes of proteins that appear undruggable in the tradition of orthosteric pharmacology may very well be amenable to allosteric modulation. In such cases, the increased effort needed to characterize these ligands is well worth the reward. Time will tell, as Vanderbilt University is currently conducting clinical Phase 1 studies with VU319 (structure undisclosed).173

5. Conclusions: Towards translational chemistry For decades, medicinal chemists have extracted useful information from binding affinity data using radioligand binding assays. Eventually, key caveats to SAR studies were recognized, such as binding sites not fully-overlapping, physiological relevance of assay conditions,174 and effects of water networks, suggesting that ligand-protein interactions are not the only factors, or even decisive for the binding of ligands to their targets.159 The toolbox of compound characterization then added powerful functional assays, which while still not perfect, complement binding information and are vital to deriving a mechanistic understanding for drug candidates – a key tenet in maximizing the probability of clinical success of drug discovery programs.175 Driven by these technological advances in measuring functional output of a drug-target interaction, allosteric modalities are now recognized as a major force to address some previously failed drug discovery 55



efforts. Allostery is a universal phenomenon taking place among molecules interacting in the context of a chemical ecosystem, regardless of their relative sizes. Mechanistically, allosteric drug action is being linked to dynamic conformational changes that dictate the functional consequences of interactions within biologically-relevant networks of molecules, both large and small. Concepts derived from studying allosteric drugs are key to understanding biological systems and diseases and has established a new paradigm in drug discovery representing an enormous opportunity. More recently, models where the effects on binding affinity () and functional cooperativity () caused by an allosteric ligand are considered to be independent of each other has led to a number of distinct allosteric modalities. When combined with the potential to bias signal transduction pathways, these modalities enable the exquisite fine tuning of allosteric drug properties (the ADTP) consistent with molecular-level disease etiology knowledge, thus allowing a translational alignment with a mechanistic disease hypothesis. Of note, in light of new information derived from mechanistic studies, many drugs and tool compounds discovered in the past considered orthosteric agonists or antagonists have been reclassified as acting within a certain allosteric modality, yet in the literature they may be treated as agonists or antagonists, creating confusion and sometimes misleading conclusions. Among these are several benzodiazepines (PAMs referred to as agonists), and ifenprodil (47), a PAM/NAM called antagonist. These are not simply semantic differences, as oversimplification during drug characterization may lead to challenges in translation to clinical effects, thus making the investment in resources and intellect required to characterize allosteric drug candidates well worth the effort. As expected, the increased complexity of the biochemical processes underlying allosteric drug actions is reflected in the mathematics of the models aiming at representing them. However, the insights into compound differentiation and the mechanistic understanding obtained from experimentation based on such models justifies the effort and resources needed to execute this strategy.

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Finally, allosterism points to the existence of a molecular hierarchy among different ligands that interact and influence the functional effects of their protein hub – both qualitative and quantitatively. On one end, ligands that trigger receptor function on their own, and on the other end are those that cannot, but are able to modify the magnitude and the signaling consequences of the functional effects of the former. This suggests that an understanding of the “allosteric ecosystem”, including receptor oligomerization and components of the “molecular system” are necessary, albeit not sufficient,) to predicting receptor function and maximizing translational veracity of a drug candidate. The large number of such potential endogenous compounds, and possibly changing during disease states or ageing, provides yet another reason to emphasize the importance of characterizing drug candidates using the most physiologically and therapeutically relevant systems whenever feasible. This is not a new idea. Indeed, the late Dr. James Black wrote,176 “If a number of chemical messengers each bring information from a different source and each deliver only a subthreshold stimulus but together mutually potentiate each other, then the desired information-rich switching can be achieved with minimum risk of miscuing… Bioassays can be designed to mimic and analyze such convergent control systems.” In summary, just as the genetic code has long been recognized as “the first secret of life”, our growing understanding of the concept of allostery and its relevance to biological systems argue for its consideration as “the second secret of life.”177 The use of allosteric modalities in small molecule drug discovery programs is in its infancy, and we believe it holds a key to realizing the potential of programs where competitive or insufficiently characterized allosteric ligands have failed. The challenge for medicinal chemists is set.

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CORRESPONDING AUTHOR INFORMATION Email: [email protected] ORCID ID: https://orcid.org/0000-0002-5944-383X Sage Therapeutics, Inc. 215 First Street, Cambridge MA 02142, USA

ABBREVIATIONS USED ATDP: allosteric target drug profile CaSR: Calcium sensing receptor D1R: Dopamine receptor type 1 GABAA: Gamma-aminobutyric acid receptor type A NMDAR: N-Methyl-D-aspartate receptor mAChR: muscarinic acetylcholine receptor nAChR: nicotinic acetylcholine receptor mGluR: metabotropic glutamate receptor -OR: Delta opioid receptor PPD: Postpartum Depression P2X7: P2 purinergic receptor type 7 RO: receptor occupancy SNP: single-nucleotide polymorphism TI: therapeutic index WT: wild type

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BIOGRAPHIES Quinn P. Coughlin Quinn received his B.Sc. in Biochemistry from Boston College in 2018. After completion of a medicinal chemistry internship at Sage Therapeutics, he joined the company’s Exploratory Research group in June 2018 working in allosteric modelling and project support. Prior to his entry into industry, Mr. Coughlin contributed to undergraduate research in developmental biology.

Allen T. Hopper Allen Hopper received his Ph.D. in Medicinal Chemistry from the Ohio State University in 1993 under the mentorship of Professor D. T. Witiak, followed by a post-doc position at the University of Wisconsin. Dr. Hopper is currently Director of Exploratory Research at Sage Therapeutics. Prior to joining Sage, he worked for a variety of Biotech companies including NPS Pharmaceuticals, Memory Pharmaceuticals and Lundbeck. The majority of his 23-year career has been in the area of small molecule CNS drug discovery focused on compound design and building mechanistic links from target engagement to disease relevant biological consequences. As project leader, contributed to discovery of clinical compounds targeting GlyT1, PDE4 and T. gondii DHFR. Allen is co-author on over 50 patent applications and publications.

Maria-Jesus Blanco Maria-Jesus Blanco has >18 years of experience working in drug discovery and molecular drug design in the pharmaceutical industry, in both big pharma and biotech. She is Director of Medicinal Chemistry at Sage Therapeutics, contributing from early drug discovery to IND and clinical studies. Previously, Maria was Director of Discovery Chemistry Research & Technologies at Eli Lilly and member of the Discovery 59



Chemistry management team. She has lead teams and actively contributed to the delivery of >10 compounds to clinical studies in CNS drug discovery. Maria has co-authored >65 scientific publications, presentations, patent and patent applications. She obtained her B.S. and Ph.D. degree in Chemistry from the University of Santiago de Compostela, Spain, followed by postdoctoral positions at MIT and University of Strasbourg, France.

Vijaya Tirunagaru Vijaya received Ph.D. in biochemistry from the Center for Cellular and Molecular Biology, Hyderabad, India. She is currently VP and Head of Biology and Non-clinical Development at Rain Therapeutics. Prior to joining Rain, she was Associate Vice President and Head of Discovery Biology at GVK Biosciences, where she was responsible for overseeing a portfolio of 10 discovery programs across oncology, metabolic disorders and pain therapeutic areas. She began her pharmaceutical career at AstraZeneca, where she was biology leader for project teams from concept to clinical phase 2, led discovery programs and was a member of psychiatry disease area strategy team.

Albert J. Robichaud Al joined Sage Therapeutics as CSO in 2011, where he provides leadership and drug discovery expertise to teams delivering drug candidates into clinical development. Most recently, as Vice President of Chemistry and Pharmacokinetic Sciences at Lundbeck Research USA, Al was responsible for the medicinal, analytical and computational chemistry and pharmacokinetics departments within the synaptic transmission and neuroinflammation disease biology units. Earlier, as Head of the Neuroscience Discovery Chemistry Department of Wyeth Research, Al led a group that delivered 15 drug candidates into clinical development

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in neuroscience. He has co-authored more than 110 manuscripts and is a co-inventor on 73 patents and patent applications. Al holds a B.S. in chemistry from Rensselaer Polytechnic Institute, and a Ph.D. in organic chemistry from the University of California, Irvine.

Dario Doller Dario leads the Exploratory Research group at Sage Therapeutics, building a pipeline of early projects to treat brain disorders. Mentored by Prof. Eduardo Gros, he earned a Ph.D. in Organic Chemistry from the Facultad de Ciencias Exactas y Naturales, UBA, Argentina. He conducted post-doctoral studies with Sir Derek Barton at Texas A&M University. His industrial career includes Rohm & Haas, Schering-Plough Research Institute, 3-Dimensional Pharmaceuticals, Gliatech, Neurogen, Lundbeck, and CoNCERT. He contributed to the discovery of the marketed PAR-1 antagonist vorapaxar, the clinical compounds NGD4715, Lu AF09535 and CTP-692. Dario co-authored over 100 articles, patents or patent applications and book chapters, and edited the book Allosterism in Drug Discovery. Current interests include molecular concepts at the chemistry/biology interface to enhance the translatability of preclinical research.

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"Table of Contents graphic"

Receptor

Binding assays

Combinatorial Chemistry

1890’s

1960’s

1990’s

Physicochemical properties optimization

Functional assays 2000’s

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Allostery 2010’s

Translational Chemistry

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