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Chapter • Optimization of Lead Structures
8
specic drugs would simply not exist if it were not for the
much-disparaged “me-too” research.
8.3 Systematic Variation of Aromatic
Substituents: The Topliss Trees
The goal of lead structure optimization has an impact
on the planning of the relevant experimental series. If
the biological consequences of structural changes are
to be evaluated with minimal effort, careful design must
precede the synthesis of the substances. Here, an almost
unsolvable problem emerges in that, as ageneral rule,
the exchange of a substituent or group leads to complex changes in multiple properties. The exchange of an
ethyl group for amethyl group changes only the lipophilicity and size of the substituent. If a methyl group
is exchanged for achlorine atom, the polarizability, electronic properties, and moreover the metabolism are altered. Other substituents could then change the H-bond
donor and acceptor properties as well as the ionization
and dissociation.
In 1971, Paul Craig proposed the use of asimple diagram for the structural variation of aromatic substituents, with which the important characteristics of these
substituents, for instance, lipophilicity and electronic
properties, are plotted against each other. The selection
of substituents from different quadrants of this diagram
allows an evaluation of different combinations of properties. The concept can be extended to multiple dimensions, possibly with the aid of mathematical and statistical methods.
In 1972, John Topliss made asuggestion that went
further, which would be called today an evolutionary
strategy. One substituent at atime (e.g., hydrogen for
chlorine) is exchanged in the optimization of the substitution pattern of an aromatic compound. The next
compound is planned based on which of the rst two
compounds demonstrated better effects. If the new substituent improves the effect, anew substituent will be
chosen that has the same physicochemical properties, in
larger measure, or more of these substituents are added.
If the new substituents impair the biological activity,
then asubstituent will be chosen that has the opposite
physicochemical properties. If two different substituents
produce the same effect, it should be evaluated whether
changes in the physicochemical properties will inuence
the activity in the opposite direction. Despite its elegance,
this strategy often fails for the mundane reason that it is
too time consuming to take such astepwise approach.
As aconsequence of the work of Craig and Topliss,
further design methods were developed. None of these
methods should be interpreted too closely. Synthesis
planning must be oriented on both the accessibility of
the compounds as well as achieving the largest possible
structural variation, that is, adiversity of physicochemi-
cal properties and 3D structure. Since the introduction of
combinatorial chemistry (Chap.11), the rational design
of diverse substance libraries has taken on entirely new
possibilities and perspectives.
8.4 Optimizing the Activity
and Selectivity Profile
The structural variation of a lead structure inuences
not only the potency but also the activity spectrum. That
can be thoroughly advantageous, but it also brings with
it the risk that the selectivity can deteriorate. Asimple
rule of thumb is that enlarging the molecule, introducing
optically active centers, and rigidication improves the
selectivity, assuming that the activity is not entirely lost.
On the other hand, removing achiral center, establishing
more exibility, or reducing the size of the molecule usually results in unspecic and weaker activity.
Because of the sequencing of the human genome, the
gene family to which atarget protein belongs is known,
as is the number of members of the gene family. By using
gene technology, it is possible to construct single isoform
test systems (assays). As aresult, today pharmaceutical
research is in aposition to make apredictive selectivity
prole. This has stimulated efforts to develop selective
drugs. An interesting corollary to these efforts is the fact
that the molecular weight of drugs has increased in the
last few years as statistics have shown, thus, conrming
the above-mentioned rule of thumb.
For drugs that are meant to act on neuroreceptors
in the brain, polarity governs whether they can cross the
blood–brain barrier. Polar compounds are unable to do
this and act only in the periphery, for instance, on the
circulatory system. Examples of this are adrenaline8.5
. Fig. 8.3 The polar compounds adrenaline 8.5 and dopamine 8.6
are cardiovascularly active in the periphery after intravenous administration. Ephedrine8.7 is more lipophilic and, therefore, shows both
peripheral and central effects. The more nonpolar compound amphetamine8.8 (“speed”) has an overwhelmingly stimulatory effect in the
CNS. 3,4-Methylenedioxymethamphetamine8.9 (MDMA; “ecstasy”)
is hallucinogenic. Polar groups are red and neutral or lipophilic groups
are blue
. • From Agonists to Antagonists
. Fig. 8.4 Noradrenaline 8.11, adrenaline8.5, and isoprenaline 8.12
act to different extents on the α- and β-receptors. Selective β1- and
β2-agonists, for instance, 8.13, 8.14, and 8.15, act specically as cardiac
stimulants or bronchodilators
and dopamine8.6 (. Fig.8.3). The stepwise removal or
masking of polar groups brings the central effects into
the foreground. Ephedrine8.7 acts in the brain and in the
periphery; it is centrally stimulating and raises the blood
pressure. Amphetamine8.8 (“speed”) and the intoxicant
MDMA8.9 (the designer drug “ecstasy”) are weak bases.
Their relatively nonpolar neutral forms easily overcome
the blood–brain barrier and their CNS effects dominate
(. Fig.8.3).
There are exceptions even here. l-DOPA 8.10
(. Fig.8.3) is an extremely polar amino acid. It could
never cross the blood–brain barrier by passive diffusion
alone. Instead it is recognized by an amino acid transporter and actively transported over the membrane and
into the brain. This simultaneously solves the problem of
bringing dopamine8.6, which is used to treat Parkinson’s
disease, into the brain because l-DOPA is decarboxylated to dopamine there (Sects.9.4 and27.8).
The activity prole of the hormones and neurotransmitters noradrenaline and adrenaline and their synthetic
analogues shows the decisive inuence that even small
changes in structure can have. Whereas noradrenaline
8.11 (. Fig.8.4) affects the α-adrenergic receptors, its
N-methyl derivative adrenaline8.5 (. Fig.8.3) acts on
α
- and β-receptors as amixed α/β-agonist. This difference was used to enlarge the N-alkyl group to arrive
at the specic β-agonist isoprenaline8.2 (. Fig. 8.4).
Further differentiation of the effects could be achieved
within the class of β-adrenergic substances. Dobutamine 8.13 is missing the alcoholic hydroxyl group of
adrenaline. Despite its structural relationship to dopamine8.6 (. Fig.8.3), it is a
tive effects. Specic
β
β
-agonist with cardioselec-
-agonists, for instance salbutamol
2
1
8.14 and clenbuterol 8.15 (. Fig.8.4) are used to treat
asthma because they are bronchodilators without the
. Fig. 8.5 The sulfonamides hydrochlorothiazide 8.16, furosemide
8.17, and related diuretics are different from most antibacterial ana-
logues because of the unsubstituted sulfonamide group. Carbutamide
8.18 and tolbutamide 8.19 were the rst unspecic sulfonamides with
hypoglycemic effects that were later replaced with specic hypoglycemics of the glibenclamide-type8.20
cardiostimulatory effects of the unspecic β-agonists
(Sect.29.3).
The sulfonamides are aprime example for the targeted
optimization of lead structures in different therapeutic
indications. From the rst antibacterial examples, diuretics as well as hypoglycemics (antidiabetics) resulted.
It had already been noticed in 1940 that sulfanilamide
(Sect.2.3) inhibits the enzyme carbonic anhydrase and,
therefore, should lead to increased urine production
(Sect.25.7). Among other substances, hydrochlorothiazide 8.16, furosemide 8.17 (. Fig.8.5), and structurally
related compounds gained therapeutic importance. In the
early 1940s, hypoglycemic effects of afew sulfonamides
were clinically observed. The antibacterial and simultaneously hypoglycemic carbutamide 8.18 was introduced
into therapy in 1955; the lipophilic and therefore more
bioavailable tolbutamide 8.19 was introduced later. Systematic structural variation nally led to glibenclamide
8.20 (. Fig.8.5 andSect.30.2), which is much more po-
tent and specic.
8.5 From Agonists to Antagonists
There is no general recipe for the transformation of an
agonist into an antagonist. An example of this is found
in the tedious route from the agonist histamine to the
H2 antagonist, as described in Sect.3.5. There are, however, recognized principles that have proven to be of
value. For example, the exchange of polar for nonpolar
substituents or the introduction of large groups such
as additional aromatic rings changes some receptor ag-
8
Chapter • Optimization of Lead Structures
. Fig. 8.6 3,4-Dichloroisoprenaline 8.21 (DCI) and pronethalol
8.22, the rst unspecic β-blockers, were derived from isoprenaline
8.12. Practolol 8.23 and metoprolol 8.24 are specic β1-agonists. Xamoterol 8.25 is apartial β1-agonist, acombined agonist and antagonist
. Fig. 8.7 By starting with histamine 8.26 and introducing large
hydrophobic groups, H1-antagonists, for instance, diphenhydramine
8.27, were obtained. The nonsedating terfenadine 8.28 (R = CH3)
crosses the blood–brain barrier but is immediately expelled by atransporter. In the meantime, the active metabolite, fexofenadine with
R = COOH, is on the market
. Fig. 8.8 Closely related structures of active substances can have
very different qualitative activity. Chlorpromazine 8.30, a dopamine
antagonist with neuroleptic activity, and imipramine 8.31, adopamine
transporter inhibitor with antidepressant activity, are both derived
from promethazine 8.29, an H1-antagonist with antiallergic activity
receptor, it protects it from an excessive response upon
elevated adrenaline release, for instance, from exercise
or stress.
Analogously, the exchange of the imidazole ring of
histamine 8.26 for large hydrophobic groups led to the
rst H1-antagonists, for instance, diphenhydramine 8.27
(. Fig.8.7). Sedation is the most troublesome side effect
of the classic H1-antagonists, which are used to treat allergies. The nonsedating terfenadine 8.28 (R = H) can
cross the blood–brain barrier because of its high lipophilicity, but is immediately expelled by atransporter.
Because of its cardiotoxicity, terfenadine has been withdrawn from the market and replaced by its active metabolite fexofenadine 8.28 (R = COOH).
The sedating side effects of antihistamines also led
to neuroleptics and antidepressants (Sect.1.6). Here,
however, the limits of rational drug optimization are
apparent. Promethazine 8.29 is an antihistamine with
antiallergic action and sedating side effects. The neuroleptic chlorpromazine 8.30 is a central depressant and
therefore an antipsychotic; the extraordinarily similar
structure of imipramine 8.31 acts, on the other hand,
as astimulant and is an antidepressant (. Fig.8.8). All
three substances have different mechanisms of action.
The introduction of additional aromatic rings to other
receptor agonists, for instance, to the neurotransmitters
acetylcholine and dopamine, has led to antagonists.
onists to antagonists. The exchange of both phenolic
hydroxyl groups in isoprenaline 8.12 for two chlorine
atoms (DCI, 8.21) or additional aromatic rings (pronethalol, 8.22) delivered the rst β-adrenergic antagonists,
the so-called β-blockers. The introduction of an oxygen
atom in the side chain, and further structural optimization afforded the rst
ple, practolol 8.23 and metoprolol 8.24. The
β
-selective antagonists, for exam-
1
β
-selective
1
partial agonist xamoterol 8.25 is ablocker as well as an
agonist (. Fig.8.6). It occupies
β
-receptors and dis-
1
plays amoderately stimulating effect. By occupying the
8.6 Optimizing Bioavailability
and Duration of Action
The absorption of the majority of pharmaceuticals depends only on their lipophilicity. The more polar the
drug, the more poorly it can penetrate the lipid membrane, and the lower the absorption (Sect.19.6). Increasing the lipophilicity improves the absorption. Extremely
lipophilic compounds are insoluble in water, and their
absorption is too slow. Lipophilic acids and bases will
offer advantages here, if their acidity constant is not too
far away from the neutral point, pH7. In their ionized
. • Variations of the Spatial Pharmacophore
form, they are highly water soluble, while in their neutral
form, with which they are in equilibrium, they are lipophilic and membrane permeable. These correlations are
discussed in Sect.19.5. The molecular size inuences the
bioavailability insofar that substances with amolecular
weight above 500–600 Da are captured by the liver solely
because of their molecular size, and they are quickly excreted with the bile. Aside from this, there are substances
that penetrate the membrane regardless of their polarity.
These are taken up into the cell or are eliminated from
the cell by transporters (Sect.30.10). Among these are
structural analogues of amino acids and nucleosides.
Classical strategies to extend the duration of action
are the conversion of free hydroxyl groups to ethers (see
Sect.9.2), the replacement of esters with amides, and the
replacement of metabolically labile amide groups with
isosteres. In afew cases, such structural changes are associated with areduction in potency, which is more than
compensated for by alonger duration of action. In the
case of peptides, the replacement of l-amino acids with
d-amino acids, the reversal of the direction of amide
groups, and the replacement of larger structural elements
with peptidomimetic groups (Sect.10.4) have all proven
successful.
The metabolism of aliphatic amino groups can be
suppressed with alkyl substitution or branching at the
α
-carbon. Secondary alcohols can be converted to the
more bioavailable tertiary alcohols by introducing an
ethinyl group at the same carbon atom (Sect.28.5).
The introduction of an isosteric uorine atom in the
para-position as areplacement for hydrogen atoms prevents hydroxylation in this position. If steric considerations do not play arole, the para-position can also be
blocked with alarger group, such as achlorine atom
or amethoxy group. In the hydroxylated 3- and 4-position of the neurotransmitters dopamine, adrenaline,
and noradrenaline, the conversion to the monohydroxylated analogues 3,5-dihydroxy compounds or to the
NH-isosteric indole group (. Fig.8.1, Sect.8.2) led to
metabolically more stable and, therefore, longer-acting
compounds.
8.7 Variations of the Spatial
Pharmacophore
are changed to maintain the principle function, while arriving at higher potency or better selectivity. Many computer methods have been developed to generate ideas for
the spatial isomorphic replacement of ligand scaffolds.
By considering the conformational aspects of the molecules (Chap.16), they scan databases to nd possible candidates that, despite adifferent parent scaffold, can place
the side chains and interacting groups in the same spatial
orientation. Examples of such approaches are presented
in Sect.10.8 and Chap.17. However, a more indirect
route via the protein structure has also been explored.
Starting from the spatial structure of aprotein–ligand
complex, the part of the binding pocket for which anew
building block in aligand is sought is cut out. The shape
and interaction properties of the extracted pocket are
then compared with the database of all known protein–
ligand complexes (Sect.20.4). If apocket section similar
to the search pocket is found, the ligand binding to this
pocket is of interest. The structure of the building block
occupying the discovered pocket may provide anew idea
for isosteric replacement of the ligand to be modied.
Adifferent strategy that also considers the pharmacophore can be successful. In this approach, the pharmacophore is retained and only those groups that affect
the pharmacokinetic properties (i.e., the transport, dis-
tribution, metabolism, and excretion of amolecule) are
modied. An efcient and pragmatic strategy is important. For this, it is essential that not too many changes are
made at the same time, and the changes should not be
too biased. With little synthetic effort, abroad spectrum
of physicochemical properties and spatial arrangements
should be covered.
In the meantime, it has been established that binding
to human plasma proteins such as serum albumin and
the acidic k1-glycoprotein is of decisive importance for
the transport and pharmacokinetic properties of adrug.
Therefore, binding to these proteins is considered even in
the early phase of drug development (Chap.19). On the
other hand, binding to the hERG ion channels (so-called
“antitarget”) is avoided because blocking these channels
can lead to arrhythmias (Sect.30.3). Drug metabolism is
in itself avery important theme and must be considered
in earlier phases of development. Cytochrome P450 en-
Rational design is characterized by the fact that the common feature of all active compounds and the differences
to less potent or inactive analogues can be derived from
the spatial structure of the pharmacophore. Apharmaco-
phore (. Fig.8.9) is dened as aspecial arrangement of
particular functionalities that are common to more than
one drug and form the basis of the biological activity
(Sect.17.1).
During the course of rational optimization, the mo-
lecular scaffold and the substituents at apharmacophore
. Fig. 8.9 The active substance histamine 8.26 and the correspond-
ing pharmacophore assigned to it (Aacceptor, Ddonor, P positively
charged group)
Chapter • Optimization of Lead Structures
8
zymes are responsible for the vast majority of chemical
transformations that occur on xenobiotics (Sect.27.6).
To be able to predict the behavior of drug candidates at
this stage of the development process, the expected interactions with these metabolic enzymes are evaluated in an
early phase of optimization. The expression of P450 enzymes can also be induced by xenobiotics. The trigger for
this could be the binding to atranscription factor like the
pregnaneX receptor (PXR; Sect.28.7). Drug candidates
binding to this transcription factor can be evaluated early
in their development to avoid this undesirable enhanced
metabolism.
8.8 Optimizing Affinity, Enthalpy, and
Entropy of Binding and Binding
Kinetics
Generally, the binding afnity to atarget protein is primarily improved during the course of optimization. If
multiple candidates are available, the ligand efciency
(Sect.7.1) in addition to the synthetic accessibility will
lead the way. Small, potent lead structures offer legitimate hope that they can be well optimized. Very small
compounds that have nanomolar afnity, despite their
low molecular weight, can be problematic. Most of the
time in such amolecule an optimal interaction pattern
is already established. It is then almost impossible to
transfer this pattern to another molecular scaffold. Medicinal chemists have established aset of empirical rules
for standard functional group contributions to binding
afnity (Sect.4.10). According to these rules, it is possible to estimate how much aparticular group, if correctly
placed, will contribute to the binding afnity. It should
be noted, however, that the application of these rules assumes additivity of the group contributions. However,
this assumption is often too simplistic and cooperative
effects determine the actual afnity gain to be achieved.
It was shown in Sect.4.10 that the afnity is acombination of the enthalpic and entropic contributions.
Usually one starts with alead structure that has abinding afnity in the micromolar range. Expressed as the
Gibbs free energy ∆G, this is usually about 30 kJ/mol. An
increase in the binding afnity of 4–5 orders of magnitude causes an improvement in ∆G of another 20–30 kJ/
mol. In order to optimize the most appropriate property
of alead structure, where and how should the screw be
turned? Does it make more sense to improve the binding
enthalpy, or is one better advised to improve the binding entropy? Given the enthalpy/entropy compensation
described in Sect.4.10, is it even possible to attempt optimization of both values independently? The prerequisite for using such aconcept in the optimization is the
determination of both values of alead structure. Does
this help in the choice of the right candidate for optimization? In the case that the thermodynamic binding proles of multiple alternative lead candidates are known,
should enthalpically or entropically driven binders be cho-
sen for optimization? It is very interesting to compare
the thermodynamic signatures of multiple generations
of marketed products. The binding proles for HIV protease inhibitors (Sect.24.3) and HMG-CoA inhibitors
(Sect.27.3) are displayed in . Fig.8.10. Notably, it has
been successful to shift the prole from initially strongly
entropically driven binders to enthalpically driven ones.
This observation suggests that it is initially simpler to
optimize a substance’s entropic binding contribution
than its enthalpic contribution. Most of the time this
. Fig. 8.10 Between 1995 and 2006, the prole of multiple develop-
ment generations of HIV protease inhibitors (left; for formulas see
. Fig.24.15) and statins as HMG-CoA inhibitors (right; for formulas
see . Fig.27.13) could be optimized for their thermodynamic signatures, that is, the extent to which they are driven by entropy or enthalpy. The free energy ∆G is shown in blue, the enthalpy ∆H in green, and
the entropic contribution −T∆S in red. The more negative the column
becomes, the stronger the binding afnity and the more the prole
is determined by enthalpy or entropy. The initially developed compounds such as indinavir, saquinavir, nelnavir, and pravastatin were
predominantly entropic binders; in contrast, the newer derivatives
such as darunavir or rosuvastatin have an improved enthalpic prole
. • Optimizing Anity, Enthalpy, and Entropy of Binding and Binding Kinetics
of an enthalpic binder. Aresistance prole for inhibitors
against mutants of the viral HIV protease was investigated in the research group of Ernesto Freire at Johns
Hopkins University in Baltimore, USA (Sect.24.5). Interestingly, the result was that resistance to the entropically favored inhibitors could be developed much faster
than to inhibitors with enthalpic advantages. This observation indicates that it is worthwhile to concentrate on
enthalpically favored binders in cases in which resistance
can be expected to develop. In the investigated example,
the enthalpically driven binder 8.33 has aless-rigid scaffold (. Fig.8.11). This would allow 8.33 to more easily
elude changes that are caused by resistance mutations.
. Fig. 8.11 The rigid thrombin inhibitor 8.32 only exhibits asmall
number of rotatable bonds. It has an optimal shape complementarity
to the binding pocket of thrombin. Its binding is, for the most part,
entropically driven. On the other hand, the considerably more exible
ligand8.33 has ahigher enthalpic binding contribution
It is much more difcult for rigid ligands that bind for
entropic reasons to adapt to such steric modications.
On the other hand, an entropic binder may also experience an advantage in escaping resistance. If aligand is
entropically favored when binding in multiple binding
modes, perhaps even with high residual mobility in the
can be seen in the rst lead structure upon which an enlargement of the hydrophobic surface area leads to better
binding. The afnity that is gained is mostly explained
by the displacement of ordered water molecules from the
binding site (Sect.4.6). Such contributions are assumed
to be entropically favorable. A strategy of introducing
rigid rings can also be pursued. In doing so, the compound loses degrees of freedom. If the geometry of the
bound state is correctly frozen and if this state is also
populated in solution prior to protein binding, the afnity will improve for entropic reasons. An example of this
is the binding of the largely rigid thrombin inhibitor 8.32,
which binds in an almost exclusively entropically driven
manner to the protein (. Fig.8.11). In contrast, the decidedly more exible ligand8.33 displays alarge enthalpic binding contribution. Compound 8.32 represents the
result of an optimization that led to asubstance with
single-digit nanomolar binding and an optimal shape
complementarity for the binding pocket of thrombin.
As it seems, in general there are applicable concepts
for the entropy-driven optimization. If one can “always
win entropically,” then for pragmatic reasons enthalpically favored lead structures should be preferred as
astarting point for optimization.
However, caution is called for here. Why aligand has
aparticular thermodynamic prole must be claried rst.
The inhibitors 8.34 and 8.35 were discovered in avirtual screen as aldose reductase inhibitors (. Fig.8.12).
The chemical structures of both ligands are very similar.
Nevertheless, one is an enthalpically driven binder, and
the other is an entropically driven binder. The crystal
structures of both ligands with the protein delivered the
reason: the enthalpically preferred inhibitor 8.34 traps
awater molecule, which mediates binding between the
ligand and the protein, whereas the other one does not.
The incorporation of a water molecule is entropically
disfavored, and therefore the prole appears to be that
binding pocket, this may prove to be advantageous! If
the protein tries to restrict the shape of its binding pocket
against agiven inhibitor by resistance mutation, aexible
ligand interacting with multiple binding modes will still
nd other orientations to continue to bind well (cf. example in . Fig.32.12). Again, it becomes apparent that
such aconcept can only be applied in ameaningful way
if it is exactly understood why acertain binding prole
prevails.
If it is clear that alead structure is an enthalpically
driven binder, and superimposed effects such as the
entrapment of water molecules have not distorted the
prole, how will the binding of an enthalpically driven
binder be optimized? Let us remember from Sects. 4.5
and4.8: hydrogen bonds, electrostatic interactions, and
van der Waals contacts determine the contributions to
binding enthalpy. However, achange in such an interaction property of amolecule is often coupled with acom-
pensation of enthalpy and entropy. In the worst case scenario, it could well be that ∆G and, thus, binding afnity
do not change at all! The optimization process can be
compared to the challenge of repeatedly getting around
the inherent enthalpy/entropy compensation. Enthalpically favorable hydrogen bonds should have an optimal geometry and should not induce severe structural
changes in the protein environment. Otherwise this can
lead to an entropic compensation by causing ashift in
the degrees of freedom of the dynamic system. It seems
to be more favorable to strengthen the hydrogen bonds
in structurally rigid regions of the binding pocket. There,
enthalpy is more likely to be gained because the compensatory shift in dynamic parameters is less likely. Furthermore, introduced hydrogen bonds should not reduce
the degree of desolvation of abound ligand by exposing
aportion of its hydrophobic groups to the surrounding
solvent as aresult of small distortions in the binding
geometry. It is also important that the local water struc-
8
Chapter • Optimization of Lead Structures
. Fig. 8.12 Compounds 8.34 and 8.35 were discov-
ered in avirtual screening as lead structure for the
inhibition of aldose reductase. Although they are
structurally similar, 8.34 is astronger enthalpic binder
and 8.35 is amore entropic binder. The subsequent
crystal structure analyses of the complexes with the
reductase showed that 8.34 traps awater molecule
upon binding, whereas this was not observed with
8.35. Because the entrapment of awater molecule is
entropically unfavorable, the binding of 8.34 is overall
enthalpically preferred
ture in the binding pocket is not unnecessarily modied
to alarge extent.
Another essential question concerns the binding ki-
netics that an optimal ligand should have. This aspect
can only be answered with regard to the properties of the
target structure to be modulated by adrug. In principle,
it must be taken into account that the lifetimes of various
proteins in humans vary considerably. The rate of resynthesis after degradation of aprotein varies greatly from
protein to protein. This is even further complicated by
the fact that between individuals of our species, even the
resynthesis rates of the same protein can vary.
The binding kinetics determine how quickly or slowly
adrug binds to its target, how long it remains there in
abound state (so-called residence time RT = 1/k
off
) and
how quickly it dissociates from there again. Along resi-
dence time can be advantageous for therapeutic interventions where prolonged drug binding to the target protein
is desired. It guarantees that binding persists over alonger period of time and, thus, ensures amore sustained
pharmacological effect. It can even extend beyond the
time window in which, due to much faster pharmacokinetics, the local drug concentration has already decreased
below the Kd for the target, since the drug is still effective
as it remains in the bound state. For example, among the
antihypertensive sartans (Sect.29.5, . Fig.29.7), cande-
sartan (29.25), which has a30-fold longer residence time,
appears to have aclinically proven better protective effect
than losartan (29.20), which has ashorter residence time.
Conversely, if there is arisk of drug-related toxicity,
it may be desirable not to set the target binding too long.
On the one hand, the residence time should be maximized to achieve the therapeutic effect as efciently as
possible, while on the other hand, sufciently rapid elimination must minimize unwanted side effects and off-target binding. If the latter aspect does not play adecisive
role, as will be the case with most anti-infectives, the drug
should hit the target as hard and as long as possible (e.g.,
by irreversible inhibition), because then alower dose may
be sufcient for efcacy. In contrast, if there is arisk of
target-based toxicity, the mechanism of action should
be tailored so that toxicity is minimized but efcacy is
still maintained. In this case, faster dissociation of the
. Fig. 8.13 The chemically similar inhibitors 8.36 and 8.37 bind
with the same Gibbs free energy to carbonic anhydraseII, the second
one binding slightly more enthalpically, and the rst slightly more entropically. In terms of kinetics, 8.36 binds more rapidly to the enzyme,
whereas 8.37 dissociates more slowly
drug may be advantageous (compare COX inhibitors
(Sect. 27.9, . Fig. 27.40) acetylsalicylic acid (27.94),
which is an irreversible binder, or ibuprofen (27.95) and
indomethacin (27.98), which are both reversible inhibitors with rapid dissociation kinetics).
Such optimized efcacy adapted to the therapeutic
indication cannot be achieved by considering afnity
alone. Arapid deactivation of atarget by accelerated
on kinetics can also be essential, e.g., in acute medicine.
In Sect.7.7, methods for determining binding kinetics
have been presented. In the case of 1:1 binding, the
thermodynamic equilibrium quantity “binding afnity”
is expressed by the relative ratio of the binding kinetic
dissociation rate (k
) divided by the association rate
off
(kon). When discussing kinetic phenomena, however, it
should be borne in mind that the binding of aligand to
its protein usually does not occur in asingle step, but
instead proceeds via many intermediate steps. However,
only one of these steps on the way to the binding pocket
is rate-determining, and in most cases, it is not the same
step for the association as for the dissociation. We are
ing detailed structure–kinetics relationships. Preliminary
evidence suggests that electrostatics or conformational
adaptations of the ligand or the protein are important for
-
Bibliography and Further Reading
the kinetics. Also, how quickly the local concentration
of aligand increases at the site of the target protein can
determine the association rate. Furthermore, the dehydration of the previously uncomplexed binding pocket
or the shedding of the ligand’s solvation shell may be important. Conversely, the rewetting of functional groups
of aligand with water molecules can become atime-determining step for dissociation.
It has been observed that structurally highly similar
ligands may well have strongly divergent kinetic binding proles. . Fig. 8.13 shows two carbonic anhydrase
inhibitors with the same afnity, 8.36 and 8.37, which
have different on- and off-kinetics despite similar chain
lengths of their substituents. 8.36 binds faster than 8.37
to human carbonic anhydrase, whereas 8.37 dissociates
again more slowly.
Helena Danielson’s group in Uppsala, Sweden,
showed that therapeutically used HIV protease inhibitors have different binding proles with respect to the
development of resistance to mutated variants of the
protease. It became clear that increased resistance to an
active compound occurs when it is found to dissociate at
an increased rate. This is acrucial criterion for guiding
drug optimization in the desired direction.
8.9 Synopsis
Alead structure is only the starting point on the way
-
to adrug; potency, specicity, and duration of action
have to be optimized concurrently to minimize side
effects and toxicity.
The structure of an active substance is determined
-
by its pharmacophore, which is responsible for target
binding. Its adhesion groups enhance potency and
biological activity, its lipophilicity is responsible for
transport and distribution, and groups to be cleaved
or modied release the active form.
Multiple concepts to modify the chemical structure
-
of alead can be planned; however, optimization is
multifactorial due to highly correlated inuences of
the attempted changes.
Bioisosteric functional group replacement attempts
-
the exchange of groups on agiven scaffold for steri-
cally and electronically related groups that maintain
activity but improve other drug properties.
Me-too research follows the goal of modifying the
-
competitor’s lead structures to arrive at patent-free
analogues with improved properties.
Assuming unchanged activity, enlarging amolecule,
-
adding chiral centers, and rigidication usually im-
prove selectivity, whereas removing chiral centers,
allowing more exibility, and reducing the size make
adrug less selective.
The activity spectrum of asubstance can be tailored
-
even by the smallest structural changes that modulate
afnity, transportation, distribution, or metabolism.
Therefore, aparticular compound class can show activity in very different therapeutic indications.
Transforming agonists to antagonists does not follow
-
clear-cut rules; however, increasing the size and the
attachment of hydrophobic groups such as aromatic
rings often shift the prole.
The more polar adrug, the more poorly it can pene-
-
trate lipid membranes, and the lower the absorption
is. On the other hand, special transporters can assist
penetration.
Extension of the duration of action is mostly
-
achieved by replacement of metabolically labile
groups with more stable isosteres, the introduction
of more branching groups, blockage of metabolically
labile positions at aromatic rings byF or Cl, or by
exchanging l- for d-amino acids concurrently with
the inversion of amide groups.
Molecular databases can be screened to detect other
-
scaffolds or substitution patterns that represent
agiven pharmacophore in an alternative fashion.
In the early phase of drug development, undesired
-
binding to plasma proteins, antitargets such as the
hERG ion channel or preferred binding, inhibition,
or activation of transcription factors or metabolizing
cytochrome P450 enzymes are examined and possibly
avoided.
Proper adjustment of the thermodynamic binding
-
prole can be essential for the optimization of binding afnity and to endow adrug with the required
target-specic properties. Similarly, the interaction
kinetics determining binding on and off rates or residence times are of decisive importance to develop
drugs with, for example, an optimal resistance prole.
Bibliography and Further Reading
General Literature
W. Sneader, Drug Discovery: The Evolution of Modern Medicines,
John Wiley & Sons, New York (1985)
J. B. Taylor and D. J. Triggle, Eds., Comprehensive Medicinal Chemis-
try II, Elsevier, Oxford (2007)
C. G. Wermuth, Ed., “The Practice of Medicinal Chemistry”, 3rd Edi-
tion, Elsevier-Academic Press, New York (2008)
M. A. M. Subbaiah, N. A. Meanwell, Bioisosteres of the Phenyl Ring:
Recent Strategic Applications in Lead Optimization and Drug Design, J. Med. Chem., 64, 14046–14128 (2021)
Special Literature
C. Hansch, Bioisosterism, Intra-Science Chem. Rept., 8, 17–25 (1974)
C. W. Thornber, Isosterism and Molecular Modication in Drug De-
sign, Chem. Soc. Rev., 8, 563–580 (1979)
C. A. Lipinski, Bioisosterism in Drug Design, Ann. Rep. Med. Chem.,
21, 283–291 (1986)
A. Burger, Isosterism and Bioisosterism in Drug Design, Fortschr.
Arzneimittelforsch., 37, 287–371 (1991)
8
Chapter • Optimization of Lead Structures
H. Steuber, A. Heine and G. Klebe, Structural and Thermodynamic
Study on Aldose Reductase: Nitro-substituted Inhibitors with
Strong Enthalpic Binding Contribution, J. Mol. Biol., 368, 618–638
(2007)
H. Ohtaka and E. Freire, Adaptive Inhibitors of the HIV-1 Protease,
Prog. Biophys. and Mol. Biol., 88, 193–208 (2005)
G. Klebe, Broad-scale analysis of thermodynamic signatures in medici-
nal chemistry: are enthalpy-favored binders the better development
option? Drug Discov. Today, 24, 943–948 (2019)
C. F. Shuman, P-O. Markgren, M. Hämäläinen, U. H. Danielson,
Elucidation of HIV-1 Protease Resistance by Characterization of
Interaction Kinetics between Inhibitors and Enzyme Variants, An-
tiviral Research, 58, 235–242 (2003)
R. A. Copeland, D. L. Pompliano and T. D. Meek, Drug–target Resi-
dence Time and its Implications for Lead Optimization, Nat. Rev.
Drug Discov., 5, 730–740 (2006)
G. Klebe, The Use of Thermodynamic and Kinetic Data in Drug Dis-
covery: Decisive Insight or Increasing the Puzzlement? ChemMed-
Chem, 10, 229–231 (2015)
D. C. Swinney, Opportunities to minimise risk in drug discovery and
development, Expert Opin. Drug Discov., 1, 627–633 (2006)
S. Glöckner, K. Ngo et al, Conformational changes in alkyl chains
determine the thermodynamic and kinetic binding proles of Car-
bonic Anhydrase Inhibitors, ACS Chem. Biol., 15, 675–685 (2020)
A. Alsadhan, J. Cheung, et al, Variable Bruton Tyrosine Kinase (BTK)
Resynthesis across Patients with Chronic Lymphocytic Leukemia
(CLL) on Acalabrutinib Therapy Affect Target Occupancy and
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4401–4401 (2018)
Designing Prodrugs
Contents
9.1 Foundations of Drug Metabolism – 128
9.2 Esters Are Ideal Prodrugs – 129
9.3 Chemically Well Wrapped: Multiple Prodrug Strategies – 131
9.4
9.5 Drug Targeting, Trojan Horses, and Pro-prodrugs – 133
9.6 Synopsis – 135
l-DOPA Therapy: AClever Prodrug Concept – 132
Bibliography and Further Reading – 136
© The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature 2024
G. Klebe, Drug Design, https://doi.org/10.1007/978-3-662-68998-1_9