drug target lifetime

8/12/2019 Drug Target Lifetime

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1491ISSN 1756-8919Future Med. Chem.(2011) 3(12), 1491150110.4155/FMC.11.112 2011 Future Science Ltd

PERSPECTIVE

The pharmacologic basis of drug action almostalways involves modulation of the physiologi-cal activity of macromolecules (e.g., enzymes,receptors and ribosomes) by binding of drugmolecules (e.g., small organic molecules andbiologics) to these targets. Thus, pharmacologyis based on the formation of a drugtarget com-plex and, in turn, the duration of pharmacologiceffect is often dictated by the temporal persis-tence of target occupancy by the drug. Althoughdrugtarget interactions are commonly illus-

trated in terms of structurally static binding anddissociation events, in which the conformationof the drug molecule and that of its target mac-romolecule are fixed, such a description is inad-equate to explain the impact of conformationaldynamics on drugtarget interactions. Both theassociation phase of drug binding to a target,and the subsequent dissociation of the binarydrugtarget complex, are often controlled byconformational changes, especially involvingstructural changes in the immediate vicinity ofthe drug-binding pocket [13].

Historically, the effectiveness of a drugsinteraction with a target has been quantified bymeasuring the concentration of drug requiredto achieve a specific level of target occupancyunder equilibrium conditions (e.g., the K

dor

IC50

value). In recent years, however, there hasbeen increased recognition that drugtargetinteractions in vivoare not defined by equilib-rium conditions. In particular, the importanceof stabilizing the binary drugtarget complexin vivo for sustained pharmacologic effecthas been highlighted, and the term residence

time has been coined to describe the temporal

duration of the drugtarget complex under dif-ferent conditions [4,5]. In addition, a differentiallylong target residence time provides a mechanismfor temporal target selectivity, hence a cogentapproach to the mitigation of off-target basedtoxicity in vivo; this topic has been covered inconsiderable detail in previous reports [46].

Residence time (t) is commonly quanti-fied through experimental measurements ofthe reciprocal of the dissociation rate con-stant (t = 1/k

off) or the dissociative half-life

(t1/2

= 0.693/koff

), and it has been argued thatthe residence time provides an important metricfor compound optimization through medicinalchemistry. The residence time of the drugtargetcomplex is very clearly dependent on the confor-mational stabilization of the drugtarget com-plex; hence, conformational adaptation plays akey role in drug binding and stabilization of thefinal structure of the drugtarget complex, aswill be described later.

While the concept of conformational adapt-ation in drugtarget interactions has been pre-

sented previously [17], it is not widely appreciatedthroughout the drug-discovery and medicinalchemistry communities. In this brief perspec-tive, we review some aspects of conformationaladaptation in drugtarget interactions as theyrelate to drug-discovery efforts.

The static view of

drugtarget interactions

The conventional view of drugtarget inter-actions was first formulated by H Emil Fischer,to describe enzymesubstrate interactions and

has been dubbed the lock-and-key model [8].

Conformational adaptation in drugtarget

interactions and residence time

Although drugtarget interactions are commonly illustrated in terms of structurally static binding and dissociation

events, such descriptions are inadequate to explain the impact of conformational dynamics on these processes. For

high-afnity interactions, both the association and dissociation of drug molecules to and from their targets are

often controlled by conformational changes of the target. Conformational adaptation can greatly inuence the

residence time of a drug on its target (i.e., the lifetime of the binary drugtarget complex); long residence time can

lead to sustained pharmacology and may also mitigate off-target toxicity. In this perspective, the kinetics of

drugtarget association and dissociation reactions are explored, with particular emphasis on the impact of

conformational adaptation on drugtarget residence time.

Robert A Copeland

Epizyme, Inc., 325 Vassar Street,Cambridge, MA 02139, USATel.: +1 617 500 0707Fax: +1 617 349 0707

E-mail: [email protected]


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PERSPECTIVE|Copeland

Future Med. Chem.(2011) 3(12)1492 future science group

In this model, the target macromolecule con-tains a binding pocket that is complementaryto the drug molecule (or other ligand), in bothsteric and electronic ways, such that a networkof favorable interactions between the drug and

recognition elements within the binding pocketis established upon binding; thus the binarydrugtarget complex is stabilized relative tothe free reactants (i.e., receptor and ligand) [2,3].This conventional view further considers therecognition elements of the binding pocketto be held static in the most complementaryarrangement with respect to ligand interactions.Hence, drug association and dissociation eachoccur in a single kinetic step, and the efficiencyof interaction may be quantified by familiar,mathematically related parameters such as IC

50

values, Kd values and DGbinding(F IGURE 1)

[3]

.Although Kdand DG

bindingare thermodynamic

constants, they can be readily related to thekinetic rate constants for drug association anddissociation as follows [2].

Kk

kd

on

off=

EQUATION1

G RTln K RTlnkk

binding don

off= =D 6 ;@ E

EQUATION2

For weak binding interactions (i.e., Kdval-

ues in the M to mM range), association anddissociation are usually rapid, with half-liveson the s timescale. This rapidity of bindingand dissociation can be important for physio-logical reactions, such as enzymes binding tosubstrates and cofactors. As binding affinityincreases, however, it is often the case that therate of association and, especially, of dissociationslow down to timescales of seconds, minutes andsometimes longer; hence, these reactions maybe conveniently measured in vitroby a number

of biochemical and biophysical methods [14,9].

Using convenient experimental methods,one can mix a macromolecular target (let usrefer to these universally as receptors and usethe symbol R to represent them) with a drugor other ligand (we will use the symbol L to

universally represent these molecules) andmeasure the amount of binary complex (RL)formed as a function of time after mixing. Inmost experimental approaches to measuringreceptorligand binding, the receptor concen-tration is held constant at a very low, limitingconcentration relative to that of the ligand.Under these conditions, binding of ligand tothe receptor follows pseudo-first order kinet-ics [3] and the approach to equilibrium cantherefore be described by a pseudo-first orderrate constant k

obs.

The value of kobsdepends on the concentra-tion of ligand in characteristic ways that can bemechanistically informative [1,5]. For the simple,static binding mechanism illustrated in FIGURE1,the value of k

obs is a linear function of ligand

concentration for which the slope is equal tothe value of k

onand the intercept is equal to the

value of koff

[5].There are indeed examples of drugtarget

complexes for which this type of binding mea-surement yields a linear plot of k

obsas a func-

tion of ligand concentration. Hence, in thesecases the experimental data are consistent with

single-step binding and dissociation, and there-fore a static drug binding pocket. These casesare not common, however, and often it turns outthat there are conformational adjustments tothe binding pocket that attend ligand binding.In these cases the thermodynamic stability ofthe protein conformers are similar and there-fore interconversion among conformers occurstoo rapidly to be observed in standard bindingexperiments. This was the case, for example, instudies of piperidine inhibitors of the aspartylprotease pepsin [10].

Conformational adaptation in

drugtarget interactions

Despite being commonly found in textbooks,the static model of drugtarget interactions(see earlier) is seldom adequate to describe fullythe association and dissociation of high-affin-ity drugs with their targets. For the majorityof drugs that bind with nanomolar or lowerK

dvalues, it is common to find conformation

adjustments of the drug binding pocket thatattend complex formation [26,11]. This type of

conformational adaptation can result from two

+

L

RR RL

kon

koff

Figure 1. Static lock-and-key model of receptorligand binding in whichk

onand k

offeach occur in a single kinetic step.

kon

: Complex association rate constant; koff

: Complex dissociation rate constant.

Key Term

Temporal targetselectivity:Refers to thedegree of target occupancy,relative to occupancy ofcollateral off-target proteins, by

a drug as a function of time overthe course of in vivodosing. Thetemporal target selectivity canbe quantied as the ratio of

residence times for theoff-target protein and that forthe target protein.


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Conformational adaptation in drugtarget interactions & residence time | PERSPECTIVE

www.future-science.com 1493future science group

kinetic pathways for drug association that havebeen referred to as the conformational selectionand induced-fit models of binding (FIGURE2)[1].

In the conformational selection model thereceptor exists in an ensemble of conformers

in the absences of ligand; only some of theseconformers are capable of binding ligand. Forsimplicity let us say that the ensemble of con-formers is composed of only two states that arein equilibrium with one another: a state thatis unable to bind ligand (R) and an alterna-tive conformer that does bind ligand (R*). Inthe absence of ligand, the equilibrium stronglyfavors the R state over the R* state, and inter-conversion between these states is relativelyslow. Upon addition of ligand, those receptormolecules in the R* conformer will bind ligand

(R*L) and therefore be removed from the equi-librium between the free forms R and R*. Thisleads to a shift in the equilibrium position tofavor formation of more R*, which can then bindmore ligand until, at infinite ligand concentra-tion, the entire system has shifted to the R*Lstate (FIGURE2) . In this model the rate limiting

step in binding is assumed to be interconver-sion between the two free forms R and R*; onceformed, R* binds ligand rapidly.

The induced-fit model (FIGURE2) results inthe same final form of the drugtarget complex,

R*L, but arrives at this state through a differ-ent kinetic pathway. Here the unbound receptorexists in a single conformational state, R, that iscapable of binding ligand to form an encountercomplex, RL. The recognition elements withinthe binding pocket are not optimally comple-mentary to ligand in the RL state. The act ofligand binding causes a conformational read-justment of the target to form a new conforma-tion (R*L) in which optimal complementaritybetween ligand and binding pocket is achieved.In this model, ligand binding to the initial

encounter state, R, is considered rapid and therate-limiting step is a slow conformational tran-sition (i.e., isomerization) from the RL state tothe final R*L state.

An important point to bear in mind is that,for both models, each target conformer (R,R*, RL and R*L) represents an ensemble of

Conformationalselection

Induced

fit

kiso

krev

+ +

R R*

R*LRL

L L

B

R

Interatomic distance

PE


R*

PE



PE

R*L

PE

RL

Kd

Kd

kiso

krev

A

Figure 2. (A)Thermodynamic cycle for two-step L binding to R. The reaction scheme for the conformational selection mechanismstarts with the unliganded receptor state R (top left corner) and proceeds along the clockwise direction indicated by the arrow.The induced-fit mechanism also starts with unliganded receptor state R, but proceeds along the trajectory indicated by thecounterclockwise arrow. In both models R and R* refer to distinct conformational states of the same receptor molecule. In theconformational selection model, the interconversion between states R and R* is slow and occurs prior to rapid ligand binding to stateR*. In the induced-fit model, ligand binds rapidly to state R after which there is a slow conversion (i.e., receptor isomerization) to thebound state R*L. (B) Thermodynamic cycle for two-step ligand binding to a receptor, as in (A), illustrating the changes inconformational microstate ensembles associated with each overall state of the receptor. Note that the stability of the system is definedby the depth of the potential energy well(s) associated with each state.K

d: Concentration of drug required to achieve a specific level of target occupancy under equilibrium conditions; k

iso: Rate constant for

forward isomerization from state R to R*; krev

: Rate constant for the reverse isomerization from R* to R; PE: Potential energy.


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conformational microstates that may interconvertthrough vibrational, rotational and translationalexcursions, depending on the energy barrier tointerconversion. Hence, stabilization of a particu-lar state, such as a ligand-bound state, depends

on populating a deep, narrow potential energywell that creates a substantial energy barrier toescape and thus to interconversion. This con-cept is pictorially illustrated in FIGURE2B. It isalso important to realize that the conformationalselection and induced-fit models merely representopposite poles of a continuum of conformationaladaptation mechanisms that nature may use topromote molecular recognition between bindingpartners [12,13]. A final point that is worth mentionis that the conformational selection and induced-fit models are thermodynamically indistinguish-

able. That is, the overall binding affinity in bothmodels will depend on the free energy differencebetween the starting and ending states of the sys-tem. By what kinetic process the system arrives atthe final state is irrelevant from a thermodynamicperspective (i.e., the free energy of binding is apath-independent parameter).

The conformational selection and induced-fit models may be experimentally distinguishedby measurements of the pseudo-first order rateconstant for approach to equilibrium as a func-tion of ligand concentration [15,12]. Equationsdescribing the dependence of k

obson ligand con-

centration for the two mechanisms have beenindependently derived by multiple investigatorsand are well established in the biochemical lit-erature. One finds that the quantitative value ofk

obsvaries with ligand concentration in opposing

fashions for the two mechanisms [3,5,14,15]. Forthe conformational selection, mechanism k

obs

depends on ligand concentration as described bythe following equation:

k k kK L

Kobs iso rev

d

d= ++ 6 @

EQUATION3

where kiso

is the rate constant for forward isomer-ization from state R to R* and k

rev is the rate

constant for the reverse isomerization from R*to R (FIGURE2A) . We can define the limits ofk

obsat zero and infinite ligand concentrations by

inspection of EQUATION3. When [L] is zero, kobs

reduces to (k

iso+ k

rev), and when [L] is infinite,

kobs

reduces to kiso

. Thus the value of kobs

decreasescurvilinearly with increasing ligand concentra-tion from an intercept value of (k

iso+ k

rev) to a

final value of kiso

at infinite ligand concentration

(FIGURE3).

For the induced-fit model, kobs

depends onligand concentration as follows:

k kK L

Lkobs iso

d

rev=+

+6

6

@

@

EQUATION4The limits at zero and infinite concentration

from EQUATION4are krev

and (kiso

+ krev

), respec-tively. Thus, for the induced-fit model, k

obsis a

saturable, hyperbolic function of ligand concen-tration, increasing from an intercept value of k

rev

to a final value of (kiso

+ krev

) at infinite ligandconcentration (FIGURE3).

This type of experiment provides a clear andunambiguous basis for defining the mechanism ofinteraction that is germane to a specific drugtargetpair. In this manner, the two mechanisms of con-

formational adaptation in drug binding are readilydistinguished from one another.Most high-affinity drugs bind to their targets

through a conformational adaptation mecha-nism [11]. Hence, one may ask which of the twoconformational adaptation models presentedabove is most germane for drugs binding to theirmacromolecular targets. In fact, examples of bothmechanisms can be found in the literature, basedon the type of kinetic analysis just described.TABLE1provides examples of drugs or drug-relatedcompounds for which either a conformationalselection or induced-fit model may be invoked

on the basis of kinetic data. Note that the entriesin TABLE1for conformational selection representall examples of this mechanism that are known tothe author from survey of the literature. In con-trast, the entries for induced fit represent a sam-pling of a much larger pool of known examplesof this mechanism.

Reviewing the information summarized inTABLE1, all of the examples of conformationalselection are for enzymes, mainly binding tonatural substrates or cofactors. In the over-whelming majority of cases of a drug molecule

binding to a macromolecular target, the bind-ing appears to conform to an induced-fit mecha-nism. Thus, while both mechanisms appear to beapplicable to receptor-ligand binding in general,pharmacologic modulation of targets appearsto often involve an induced-fit mechanism ofconformational adaptation.

Structural changes associated with

conformational adaptation

The difference in affinity between the states RLand R*L can be quite significant for some drug

target pairs; it is not uncommon to see the Kd


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value change from micromolar to nanomolar orpicomolar during this transition [16]. A commonquestion raised in such cases is what are the struc-tural alterations to the target that result in suchdramatic changes in compound affinity? Recently,

Garvey reviewed this topic and concluded thatthree broad mechanisms account for the affinitychanges observed during conformational adapta-tion [16]: protein conformational changes, cova-lent adduct formation and compound ionization.Of the three, protein conformational changes areperhaps of the most interest to medicinal chemistsand others focused on lead optimization. In hissurvey of the literature, Garvey found many casesin which the conformational changes that attendtwo-step binding of compounds to targets werequite subtle in nature [16]. Garvey concluded that

most of the recognition elements that resulted inhigh-affinity interactions between compoundand target are formed within the context of theinitial encounter complex (RL) and these are rein-forced through small conformational adjustmentsthat lead to the final binary complex state (R*L).

The conclusions of Garvey are based largely oncomparison of crystallographic structures of theligand-free target with that of compound-boundforms of the target. In fact, there is a dearth ofstructural information in the literature compar-ing different ligand-bound conformers of targets(e.g., RL and R*L) as a basis for formulating a

structural hypothesis for explaining affinity dif-ferences. Certainly, there are many exceptionsto the generalization that structural differencesbetween RL and R*L states are small. Among theproteins kinases, for example, there are severalexamples of significant loop movement and otherstructural rearrangements that attend inhibitorbinding [17,18]. Likewise, in the case of the aspartylproteases, closure of a flap region to occlude theenzyme active site from bulk solvent is a commonfeature of substrate and inhibitor binding [19].

Structural changes that stabilize the R*L state

also lead to extended residence times for the over-all drugtarget complex. Indeed, while thermo-dynamic affinity (i.e., K*

dfor the R*L state) and

residence time can be independent parameters,it is often the case that the same structural ele-ments of recognition are involved in optimizationof both. In many cases, the optimization of K*

dis

actually achieved by inadvertent optimization ofresidence time [46]. Hence, understanding struc-tureactivity relationships (SARs) with a viewtowards maximizing the stability of the R*L stateshould be an important goal of lead optimization

activities [11].

Although, as discussed, the literature is scant onthis topic, some generalization can nevertheless bemade with respect to SARs. First, conformationalchanges that attend the RL to R*L transition tendto lead to greater occlusion of the binding pocketfrom bulk solvent; hence, hydrophobichydro-phobic interactions favor stabilization of the R*Lstate. Often, this occlusion involves ordering ofloops and other structural elements of proteinsto form a lid over the drug binding site [19].Second, while similar recognition elements tend

to be engaged in the RL and R*L states (e.g.,hydrogen bonds and salt bridges), these tend tobe strengthened in the R*L state. Finally, the R*Lstate can provide additional recognition elementsfor compound engagement that are not availablein the RL state. Examples of this include engage-ment of hydrogen bond networks between boundinhibitors and flap elements in aspartyl proteaseinhibitors [2,19], back pocket engagement byATP-competitive inhibitors of protein kinases [18],and side-pocket engagement by selective inhibi-tors of cyclooxygenase-2 [2].A particularly com-

mon mechanism of binding pocket occlusion for

1

2

3

4

5

6

7

8

0 20 40 60 80 100

Ligand concentration

kobs

(s-11

03)

Figure 3. Plot of kobs

as a function of ligand concentration (arbitrary units)for a receptorligand complex conforming to the conformationalselection mechanism (closed circles) or one conforming to the induced-fitmechanism (open circles).

Key Term

Drugtarget residencetime:Lifetime of the binarycomplex between a drugmolecule and a macromoleculartarget. Experimentally, theresidence time is measured asthe reciprocal of the rateconstant for drugtargetcomplex dissociation (1/koff).


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targets that display induce-fit inhibitor binding isthe folding (or ordering) of unstructured, flexibleloops within the polypeptide sequence, over thesolvent-exposed surface of the binding site[19]. Inthis manner, proteins form lids over the inhibi-

tor-bound pocket to block the escape trajectory ofligands from the protein (FIGURE4B ; vide infra).This mechanism is seen, for example, upon potentinhibitor binding to a variety of kinases, HIVprotease, HIV integrase [20], methionine adeno-methionine adeno-syltransferase [21], ribulose-bisphosphate carbox-ylase [22], Hepatitis NS3 protease [23], enoyl-ACPreductase [24] and many other protein targets.Given the commonality of this mechanism, itseems reasonable to suggest medicinal chemistryefforts focused on engaging specific intermolecu-lar interactions between drug molecules and rec-

ognition elements within such flexible loop lidsas a concrete approach to systematic optimizationof both overall target affinity and drugtargetresidence time.

A retrograde induce-t model of

drugtarget complex dissociation

Regarding drug interactions with pharmaco-logic targets, it seems clear that the induced-fitmechanism is relevant to a large number of medi-cally important systems. As described previously,formation of the drugtarget binary complex isa bimolecular process that can be mediated by

the induced-fit mechanism, the conformationalselection mechanism or other mechanisms thatincorporate features of both extreme models.Regardless of the sequence of events that leadto drugtarget binary complex formation, dura-ble pharmacologic action is determined by theresidence time of drug occupancy on the receptor.

We [46]and others [2527]have made the casethat in vivo, the duration of drugtarget occu-pancy is determined mainly by the rate of drugdissociation (i.e., dissociative half-life and resi-dence time [4]). Drug dissociation from the binary

drugtarget complex is kinetically a unimolecularprocess (i.e., the observed rate constant for theprocess is dependent only on the concentrationof binary complex and not on the concentrationsof total [or free] receptor and ligand). Thus, anyconformational changes that must accompanydrug dissociation most likely occur through theequivalent of a retrograde induced-fit mecha-nism (i.e., operating in the reverse sequence ofconformational events leading to association).

As described above, formation of the final R*Lstate likely includes conformational changes that

occlude the drug binding site (hence the drug)

Table 1. Some examples of receptorligand binding interactions for

which a conformational selection or induced-fit mechanism has

been demonstrated.

Target Ligand(s) Ref.

Conformational selection

Human glucokinase Glucose [32]

Rat liver glucokinase Glucose [33]

a-chymotrypsin Proflavin [34]

Escherichia coli

alkaline phosphatase

2,4-dinitrophenyl phosphate [35]

Ribonuclease T1

Guanosine 3-GMP [36]

Protein kinase A PLN120

[37]

Induced-fit

Cyclooxygenase-2 DuP697

NS-398

[38]

Cyclooxygenase-1 Indomethacin [39]

Purine nucleoside

phosphorylase

DADMe-ImmH

DADMe-IMMG

[40]

Xanthine oxidase Allopurinol [41]

Mycobacterium tuberculosis

enoyl reductase

Isoniazid [42]

Dihydrofolate reductase Methotrexate [43]

Hepatitis C virus NS3 protease ITMN-191

VX-950

[44,45]

HIV-1 protease Darunivir [46]

Prostate-specific antigen Phosphoramidate peptidomimetics [47]

Hsp90 Geldenamycin [29]

Bacterial -ketoacyl-acyl carrier

protein synthases

Thiolactomycin [48]

HIV-1 Integrase Elitegravir

Raltegravir

GSK364735

[20]

Aurora B GSK1070916 [30]

AKT GSK690693 [49]

Steroid 5a-reductase Finasteride

Dutasteride

[50]

Bacterial ribosome Erythromycin

Retapamulin

[51]

HIV reverse transcriptase Efavirenz [52]

Glu-tRNAGlnamidotransferase Boronate peptidomimetics [53]

Polypeptide deformylase Actinonin [54]

Kinesin motor protein Ispinesib [55]

Bacterial deacetylase LpxC Ciprofloxacin [56]

HMG CoA reductase Rosuvastin [57]

Lipoxygenase-1 Amidrazine [58]

Calcineurin L-732531 [59]

Xylanose ABTI [60]

Nitric oxide synthase 1400W [61]

BACE Statine peptidomimetic [62]

p38 MAP kinase BIRB796 [63]

Dialkylglycine decarboxylase Aminophosphonates [64]


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from exposure to bulk solvent [19]. A well-knownexample of such a conformational change is theflap closing that occurs after ligand binding to theactive site of aspartyl proteases, such as the HIVprotease. It is difficult to imagine how a drug mol-

ecule could escape from such an occluded bindingpocket without first opening up an escape trajec-tory by displacement of the occluding flap region.Hence, a retrograde induced-fit mechanism seemslikely to be a necessary component of drug disso-ciation in cases such as this. Thermodynamically,an energetically equal path to ligand dissociationis afforded by the reverse trajectory associated withthe conformational selection model, as illustratedin FIGURE2A. From a physical structure perspec-tive, however, this latter dissociation path wouldrequire the ligand to diffuse out of the binding

pocket through the occlusion barrier imposed bythe protein lid, flap, or other conformation transi-tions resulting in the R*L state. Ligand tunnelingthrough proteins has been invoked to describe thediffusion of protons and diatomic gaseous ligands(e.g., O

2, CO and NO) out of metalloproteins

(e.g., heme proteins) [28], but this seems a veryunlikely possibility for a large, organic compound,such as a drug molecule.

The retrograde induced-fit mechanism requiresthe conversion of the R*L complex back to theRL complex before dissociation of the drug andrecovery of the free R state of the receptor. As

illustrated in FIGURE4, both of these conversionsrequire the system to surmount a significantenergy barrier to transiently attain two sequentialtransition states: R*Land RL. Once the systemhas reached the RL state, it can again surmountthe R*Ltransition state to return to the R*L stateor surmount the RL transition state to completethe ligand escape process. Thus, the residencetime of a drugtarget complex relates directly tothe relative stabilities of the R*L and RL states,which in turn relate directly to the depth of thepotential energy wells associated with each state of

the system and the energetic height of the accom-panying transition states [27]. The value of the freeenergy differences between the states R, RL andR*L are experimentally measurable through avariety of biochemical and biophysical methods,as described previously [2]. For example, amongthe drugtarget pairs summarized in TABLE1, theratio of K

i/K

i* vary from 3.5-fold to more than

2300-fold, representing differences in binding freeenergy (DDG

binding) between R*L and RL of 0.7 to

more than 4.6 kcal/mol [15]. Consideration of thistype of retrograde induced-fit mechanism pro-

vides a useful framework for drug optimization

A

Escape trajectory

Gbinding

B

RL

R

RL

R*L

R*L

Escape trajectory

G

binding

R*L

RL

R

Figure 4. Reaction coordinate diagram of the escape trajectory for liganddissociation following a retrograde induced-fit mechanism.(A)Free-energyreaction coordinate diagram. The system starts off in the R*L state and mustovercome the energy barrier to attain the first transition state R*L. From there, thesystem decays to the intermediate state RL. The system next must overcome anotherenergy barrier to attain a second transition state, RL, before decaying to the final,unliganded form of the receptor. (B) Representation of the reaction coordinatediagram of the escape trajectory for ligand dissociation following a retrogradeinduced-fit mechanism, illustrating the conformational changes required to open upan escape trajectory to bulk solvent for the bound ligand.


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activities. Thus, improvements in overall com-pound affinity and residence time may, in somecases, be achieved by optimization of compoundinteractions with both states RL and R*L. Inother cases, destabilization of the RL state that is

accompanied by stabilization of the R*L state maybe most optimal for prolonged residence time.Ultimately, it is the overall stabilization of theR*L state that has the greatest impact on affinityand residence time.

Future perspective

There is growing appreciation for the importanceof understanding the kinetics of drug interactionswith their macromolecular targets. In particular,the drug-discovery community has begun toconsider drugtarget residence time as an impor-

tant factor for sustained pharmacologic impactin patients. Hence, there is growing interest inmeasuring dissociation rates of compoundtargetcomplexes during lead optimization activities, toidentify clinical candidates that may demonstratelong residence time in vivo. This is a significantchange from the exclusive reliance on thermo-dynamic parameters (e.g., IC

50) that has domi-

nated drug-discovery efforts for much of the 19thand 20th Centuries. Yet, treating residence time asa phenomenological measurement is unsatisfyingin the context of hypothesis-driven SAR. Hence,medicinal chemists rightly ask questions about the

elements of molecular recognition that bear onprolonged residence time and how these recogni-tion elements may be most optimally engaged bysmall-molecule drugs.

The key theme of this article has been thatrecognition elements are not static, and that con-formational adaptation is an important aspect ofdrugtarget interactions that must be consideredcarefully during lead optimization. We have seenhow conformational adjustments can lead tochanges in drugtarget affinity that contributedirectly to prolongation of residence time. We have

introduced the concept of a retrograde induced-fitmechanism for drug dissociation in the commonsituation of two-step, conformationally gatedinteractions between drugs and their targets. Thisconcept highlights the importance of conforma-tional adaptation for enhanced residence time andthe need to take this into consideration in drugdiscovery. While not stated explicitly above, it isclear that failure to properly consider the role ofbinding kinetics and conformational adaptationin the evaluation of drugtarget interactions canlead to significant errors in SAR that can mislead

medicinal chemistry efforts. For example, failure

to account for slow compound association and/or dissociation during binding assays can grosslyunderestimate the affinity and residence timeof a compound [2]. An excellent example of thisis provided by the evaluation of Hsp90 inhibi-

tors, such as geldenamycin [29]. For some timeresearchers were puzzled by the low affinity ofsuch compounds, determined by in vitroHsp90binding assays (IC

50~1 M), when contrasted

to the nanomolar effects of such compounds incellular assays. This apparent discordance wasresolved by Gooljarsinghet al.by carefully mea-suring the time required to reach full equilibriumin the binding assays [29]. Geldenamycin andsimilar compounds turn out to be slow bindingand very slow dissociating compounds with nano-molar affinity for Hsp90. The true affinity was

not previously realized because the binding assaysfailed to account fully for the kinetics of com-pound association and dissociation. Surely, thereare many other unknown examples of such mis-informed SAR due to a failure to properly accountfor the kinetics of drugtarget interactions.

The residence time concept is now fairly wellestablished within the medicinal chemistry andpharmacology communities. In many, but cer-tainly not all cases, prolonged residence time isseen as a cogent mechanistic underpinning fordurable pharmacology and mitigation of off-targetmediated toxicity for drugs in vivo(see [46]how-

ever, for examples where long residence time iscontraindicated). What remains to be developedover the next 5 to 10 years, is a detailed under-next 5 to 10 years, is a detailed under-standing of the structural determinants that medi-ate prolonged drugtarget residence time. In thisarticle we have made the general statement thatlonger residence time is facilitated by stabiliza-tion of the more closed, solvent occluded R*L state(see earlier), within the context of the retrogradeinduced-fit mechanism of drugtarget dissocia-tion. We have further suggested that stabilizationof the R*L state might be optimized by engage-

ment of recognition elements within flexible loopsof the target macromolecule, that form lid-likegates to compound exodus. Yet, these generaliza-tions provide little direction to medicinal chemistsin their efforts to optimize residence time.

Overall, this article should be viewed as a call-to-action for the medicinal chemistry, biochemis-try and structural biology communities. As thesetopics have not yet received the experimentalefforts that they deserve, we have not been ableto address the questions of residence time SAR inany systemic fashion. This remains a challenge

for the drug-discovery community to address in


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Executive summary

Conformational dynamics of target macromolecules significantly affect the binding and dissociation of drug molecules. Drugtarget residence time relates to the lifetime of a drugtarget complex. It is the lifetime of the drugtarget complex, rather than the affinity, that determines the duration of pharmacologic effect of drugs

in vivo. Long target residence time can also provide a mechanism for mitigating off-target mediated toxicity by limiting systemic

exposure of drugs.

Many potent drugs bind their targets through a two-step, induced-fit mechanism. Drugtarget dissociation is often mediated by a retrograde induced-fit mechanism, requiring surmounting of multiple energy barriers

along the drug escape trajectory.

Stabilization of the final drugtarget complex state provides a mechanism for prolonging drugtarget residence time.

a prospective way. Recently, a number of moredetailed reports of residence time SAR, coupledwith crystallographic data, have been submitted tovarious journals for publication. This is an encour-aging development, and it is hoped that more such

reports will begin to appear in the scientific litera-ture. Basic questions also remain to be answeredregarding the relative contributions of enthalpicand entropic forces in drug binding and release,and in surmounting the multiple transition statesassociated with retrograde induced-fit drug disso-ciation. Similarly, the question of how heat capac-ity differences among conformational states of thetarget might influence drug dissociation remainsto be addressed systematically. Again, some pre-liminary reports, based largely on calorimetricstudies, are beginning to appear in the literature

to address these questions. A final area for futureexploration is the influence of auxiliary proteinsand other intracellular binding partners of targets,on drugtarget residence time. It is reasonable toconsider that binding partners could influence theconformational dynamics of targets and in thisway indirectly influence drug residence time. Forexample, in a recent set of studies, Andersonet al.demonstrated that substrate and inhibitor bind-ing to Aurora kinases could be significantly influ-enced by the presents of auxiliary proteins, suchas TPX2 and INCEPE [30,31].

As additional work in all of these areas con-tinues and begins to populate the literature, itis hoped that more definitive answers to theseimportant questions may soon emerge. As moreclear descriptions of the structural determinants

of drugtarget residence time arise, the pharma-ceutical community will be in a much better posi-tion to fully exploit the residence time conceptfor improved development of safe, long-lastingtherapies against currently unmet medical needs.

Acknowledgements

I wish to thank Roderick Hubbard, of the University of

York, and Roman Hillig, of Bayer Schering Pharma AG,

for encouraging me to writ e this arti cle. I also wish to

thank my colleagues at Epizyme, especially Mikel Moyer,

Richard Chesworth, Robert Gould and Jason Rhodes for

helpful suggestions and Caroline Hill for help in preparingthe manuscript.

Financial & competing interests disclosure

The author is an employee and stockholder of Epizyme, Inc.

The author has no other relevant affiliations or financial

involvement with any organization or entity with a finan-

cial interest in or financial conflict with the subject matter

or materials discussed in the manuscript apart from

those disclosed.

No writing assistance was utilized in the production of

this manuscript.

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drug target lifetime

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