doi:10.1016/j.jmb.2010.02.007
J. Mol. Biol. (2010) 397, 1042–1054
Available online at www.sciencedirect.com
Non-additivity of Functional Group Contributions in
Protein–Ligand Binding: A Comprehensive Study by
Crystallography and Isothermal Titration Calorimetry
Bernhard Baum 1 †, Laveena Muley 2 ‡, Michael Smolinski 2 ‡,
Andreas Heine 1 †, David Hangauer 2 ⁎‡ and Gerhard Klebe 1 ⁎†
1
Department of Pharmaceutical
Chemistry, Philipps-University
Marburg, Marbacher Weg 6,
35032 Marburg, Germany
2
Department of Chemistry,
University at Buffalo, The State
University of New York,
Buffalo, NY 14260, USA
Received 9 November 2009;
received in revised form
21 January 2010;
accepted 1 February 2010
Available online
12 February 2010
Additivity of functional group contributions to protein–ligand binding is a
very popular concept in medicinal chemistry as the basis of rational design
and optimized lead structures. Most of the currently applied scoring
functions for docking build on such additivity models. Even though the
limitation of this concept is well known, case studies examining in detail
why additivity fails at the molecular level are still very scarce. The present
study shows, by use of crystal structure analysis and isothermal titration
calorimetry for a congeneric series of thrombin inhibitors, that extensive
cooperative effects between hydrophobic contacts and hydrogen bond
formation are intimately coupled via dynamic properties of the formed
complexes. The formation of optimal lipophilic contacts with the surface of
the thrombin S3 pocket and the full desolvation of this pocket can conflict
with the formation of an optimal hydrogen bond between ligand and
protein. The mutual contributions of the competing interactions depend on
the size of the ligand hydrophobic substituent and influence the residual
mobility of ligand portions at the binding site. Analysis of the individual
crystal structures and factorizing the free energy into enthalpy and entropy
demonstrates that binding affinity of the ligands results from a mixture of
enthalpic contributions from hydrogen bonding and hydrophobic contacts,
and entropic considerations involving an increasing loss of residual
mobility of the bound ligands. This complex picture of mutually competing
and partially compensating enthalpic and entropic effects determines the
non-additivity of free energy contributions to ligand binding at the
molecular level.
© 2010 Elsevier Ltd. All rights reserved.
Edited by J. E. Ladbury
Keywords: non-additivity of functional group contributions; ligand–protein
interactions; crystal structure analysis; isothermal titration calorimetry;
thrombin
Introduction
*Corresponding authors. E-mail addresses:
[email protected]; [email protected].
† Contributed to the kinetic and microcalorimetric
characterization of the compounds, the crystal structure
determination and analysis and the collaborative
interpretation of the data.
‡ Contributed the design and synthesis of the
compounds (correspondence regarding the design and
synthesis should be addressed to D.H.) as well as
collaborative interpretation of the data.
Usually, the interactions experienced between a
protein and a bound small molecule ligand are noncovalent in nature. Deeper insights, which allow
better quantification of the energetics of the
involved molecular recognition phenomena, would
significantly enhance the ability to predict and
rationally design small-molecule ligands that bind
to specific sites on macromolecules, such as
proteins.1 In recent years, substantial advances in
the structural determination of protein–ligand complexes have been achieved by crystallography and
NMR spectroscopy. Despite this impressive body of
0022-2836/$ - see front matter © 2010 Elsevier Ltd. All rights reserved.
1043
Non-additivity of Functional Group Contributions
structural information, it is still a significant challenge
to deduce binding affinity from structure. A plethora
of computational methods have been developed to
predict affinity; however, the performance and
reliability of such scoring methods, e.g. as used in
docking, is still in need of major improvement.2
What is the reason for this still unmet challenge?
The reliable prediction of binding affinity has proven
to be very difficult because the protein–ligand
binding affinity is not simply a summation of
collective weak non-covalent interactions such as
multiple hydrogen bonds, burial of hydrophobic
surface area, van der Waals interactions or the
fixation of molecular degrees of freedom. The
binding affinity also involves solvation/desolvation
terms and various entropy contributions originating
from the protein, ligand and solvent molecules.3,4
Experimental techniques such as isothermal titration
calorimetry (ITC) provide the overall thermodynamic profile of protein–ligand interactions, but these
data can be difficult to interpret, since they cover the
binding event globally. Hence deconvolution of the
binding affinity into the individual contributions
arising from the interacting partners and the solvent
is a very challenging task.5
A significant limitation of many current computational approaches is the assumption that binding
affinity, as contributed by each individual interactions
to the total binding affinity, is additive and does not
depend on the surrounding interactions.6 This rather
pragmatic oversimplification ignores the fact that the
binding affinity is a Gibbs free energy and hence
includes an important entropy term. Even though
separation of energy terms into (pairwise) individual
contributions is a popular approximation, e.g. usually
done in force-fields, this is, in principle, not valid for
free energy and thus also for entropy or enthalpy.7,8
Instead, we have to deal with non-additivity or
cooperativity, as coined by Williams.9,10 Two ligand
fragments mutually linked together into one entity
can result in a ligand with a binding affinity greater
than the sum of its parts. The latter situation has been
defined as positively cooperative for protein–ligand
interactions by Williams et al.11,12 and should be
distinguished from the original definition given by
Monod et al.,13 who used “cooperativity” to describe
the cross-talk between multiple binding sites in
protein complexes. Conversely, a binding event can
be negatively cooperative when the affinity is
decreased while two ligand parts experience simultaneous interactions with the protein.11,12 This fundamental phenomenon has thus far been
pragmatically ignored in favor of the simpler additivity approach, well in line with frequently applied
concepts in chemistry on the basis of simple and
convenient additive models.
Here, a series of thrombin inhibitors are evaluated in
depth in order to probe the non-additivity of noncovalent interactions. In order to unravel the individual interaction contributions, a series of closely related
ligands was analyzed systematically so that their
properties can be correlated with structural changes.
Thrombin was selected as a model system because its
binding site is well structured into three aligned subpockets and was used by us earlier for evaluating the
binding properties of other systematically varied
ligands.14,15 Thrombin is readily accessible in significant quantities, crystal structure analysis is well
established, and ITC yields reliable measurements.
Furthermore, thrombin has been a prominent drug
target for many years and it is therefore well known to
many medicinal chemists, modelers and structural
biologists. It is suggested that the conclusions drawn
from this protein are quite representative for protein–
ligand binding in general.
Target binding site and compound series
As shown in Fig. 1, the designed series 1–4 of
ligands firstly differ only in the presence or absence
of a terminal amino group (X = H, NH2) competent
to form a hydrogen bond with the carbonyl oxygen
of Gly216. A second modification concerns the
identity of the group that anchors the ligand in the
S1 pocket. Either a meta-chlorobenzyl or a benzamidine moiety has been attached to the central L-prolyl
portion, linked via an amide bond. The pivotal
proline moiety fits well under Tyr60A and Trp60D
of the 60-loop, similar to the natural substrate.16
Across the m-chlorobenzyl and the benzamidine
series, the P2 portion was kept constant, whereas the
third, and most interesting, variation is the increasing size of the hydrophobic side-chains R attached to
occupy the virtually hydrophobic S3 pocket.
The synthesis and the kinetic characterization of
the different series in a photometric assay have
been described.17 Overall, the binding data spread
from two-digit micromolar to nanomolar binding.
As expected, the P1-benzamidine analogs exhibit
higher affinity compared to the m-chlorobenzyl
derivatives. Furthermore, the attached terminal
amino group increases binding affinity by a factor
of 10–100, once similarly substituted derivatives
are compared directly. In both P1 series (benzamidine and m-chlorobenzyl), increasing the size of
the hydrophobic occupant for the S3 pocket from
methyl to benzyl enhances the binding constant
significantly. To understand the structure–activity
relationship observed, we generated putative
binding modes by molecular modeling17 and
analyzed the hydrophobic surface shared between
protein and ligands. The size of the hydrophobic
contact surface was plotted against the free energy
of binding (ΔGbind) as derived from the measured
Ki values.17 Linear correlations were obtained for
both the benzamidine and m-chlorobenzyl series
with and without a terminal amino group (X = H,
NH2), but with significantly different slopes (Fig. 1,
data shown for the m-chlorobenzyl series with
X = H, NH2). Well beyond experimental error, the
series with the amino group exhibited a correlation with a slope almost twice as large as that of
the series lacking the NH2 group.17 Undoubtedly,
one would expect a significant contribution from
the charge-assisted hydrogen bond formed by the
most likely positively charged amino group in the
1044
Non-additivity of Functional Group Contributions
Fig. 1. Compound series 1–4 studied as thrombin inhibitors. R1, substituent placed into the S1 pocket metachlorobenzyl or para-benzamidine; X = H or NH2; R2, substituent (a-l) placed into the S3 pocket; schematic binding mode
and neighboring active site residues (S1, blue; S2, brown; S3/S4, red, non-specific peptide recognition, gray) are indicated.
On the lower left the correlation of hydrophobic ligand surface area (in Å2) in contact with the protein as indicated by the
model-built protein–ligand complexes is plotted against the Gibbs free energy of binding (in kJ/mol) as derived from the
photometrically recorded binding constant Ki. A linear correlation is obtained for both inhibitor series 1 (X = H) and 2
(X = NH2) but the slopes of the lines are different.
latter series to the carbonyl group of Gly 216.
Assuming independence of the contributions
added by the different interactions, one might have
expected this to result in a parallel translated shift of
the linear correlation towards better binding but not
in a different slope. However, as shown in Fig. 1 the
slope with X = NH2 is changed significantly, indicating cooperativity between the hydrogen bond and
hydrophobic binding in the S3 subsite. This observation of non-additivity of functional group contributions becomes even more apparent when
analyzing the binding data of the following four
inhibitors from the m-chlorobenzyl series. Replacement of the terminal methyl group at the n-propyl
chain (1c) by a phenyl ring (1l) results in an affinity
increase of – 3.1 kJ/mol. Attachment of the amino
group to the n-propyl derivative (2c) leads to an
enhancement of – 9.6 kJ/mol. Surprisingly, the
compound exhibiting both modifications (2l) features a binding enhancement of – 18.6 kJ/mol. This
value is –5.9 kJ/mol larger than the ΔG value
expected from a pure summation of the individual
contributions described above. This remarkable
contribution of non-additivity can be explained
only by a pronounced influence of cooperative
effects. These findings stimulated us to embark on
a detailed crystal structure analysis and ITC of the
structural and thermodynamic features that govern
binding of these ligands to thrombin.
Results and Discussion
Here, we want to discuss the properties of the
12 compounds of the series (1c, 1e, 1l; 2c, 2e, 2l;
3c, 3e, 3l; 4c, 4e, 4l) shown in Fig. 2. All
attempts to co-crystallize the ligands 1c, 1e and 1l
from the m-chlorobenzyl series lacking the terminal amino group were unsuccessful. This observation is likely to be due to the limited solubility
of these inhibitors along with their low binding
affinity. Also, successful soaking into thrombin
crystals would require rather high concentrations
of solvated ligand in aqueous solution. Nevertheless, for nine of these inhibitors (series 2, 3, 4),
crystal structure analysis and ITC data could be
recorded, and for those of series 1 we will focus
on the kinetically determined binding affinities.
The data for 2c, 2l, 4c, and 4l were presented
earlier.14
Kinetic data
The free energy of binding ΔG0 as derived from
the kinetic inhibition constants (Table 1) was also
analyzed through a thermodynamic cycle (Figure
2). The thermodynamic cycle for the benzamidines
(series 3, 4) also shows non-additivity, similar to
the m-chlorobenzyl series non-additivity described
earlier, though somewhat less pronounced.17
1045
Non-additivity of Functional Group Contributions
Fig. 2. Thermodynamic cycle for 12 compounds (1-4, b, d, l) as discussed in this study. All free energies of binding
ΔG0 (italics in kJ/mol) to thrombin are derived from the kinetically determined Ki values. The ΔΔG differences between
compounds, adjacent in the diagram, are indicated along the connecting arrows. The m-chlorobenzyl series is shown in
the back (light blue), and the p-benzamidine series is shown in front (orange).
Crystal structures, B-factor analysis
An indication of the residual dynamic properties
of the inhibitors, while bound to the active site, can
be obtained by considering the temperature factors
determined for the different thrombin-inhibitor
complexes (Table 1). The crystallographically observed temperature or B-factors (closely related to
the so-called atomic displacement parameter u; B = 8
π2 u2) reflect the fluctuation of the atoms about their
average positions and provide at least qualitative
information about the residual mobility of molecular portions in a crystal structure. Their magnitude is
reflected in structure refinement. The more an atom,
and thus its electron density, is scattered as a result
of increased vibrations or scattering over multiple
static arrangements, the more out-of-phase, and
thus attenuated, are the X-rays from different parts
of an atom diffracted. Therefore, at higher diffraction angles, the diffracted intensity falls off more
than that calculated for a point atom of given
diffraction power. This fall-off is approximated by
an exponential function that includes the abovementioned B-factor. As they relate to the electron
density in a particular region of a crystal, they will
correlate significantly with the population parameters assigned to, for example, a hosted ligand.
Furthermore, it is hardly possible to distinguish
static from dynamic disorder. Usually, protein
crystals are studied at 100 K where motions are
reduced significantly. However, it is assumed that
flash cooling applied to protein crystals still
Table 1. Compilation of Ki values (photometric assay), thermodynamic data from microcalorimetry (ITC, ΔG, ΔH, –TΔS)
in Tris buffer, PDB codes, mean B-factor as observed in the different crystal structures (for inhibitor and binding site
residues) and the B-factor ratio of inhibitor versus binding site residues
Inhibitor
2c
2e
2l
3c
3e
3l
4c
4e
4l
Ki
(μM)
ΔG
(kJ/mol)
ΔH
(kJ/mol)
–TΔS
(kJ/mol)
PDB code
Resolution
(Å)
B Inhibitor
(Å2)
B Binding site
(Å2)
B Inhibitor/
B Binding site
6.8 ± 1.6
0.54 ± 0.19
0.18 ± 0.15
5.70 ± 1.20
1.28 ± 0.27
0.75 ± 0.19
0.18 ± 0.03
0.02 ± 0.01
0.004 ± 0.001
- 31.3 ± 1.9
- 35.1 ± 0.3
- 35.4 ± 0.2
- 32.8 ± 0.3
- 37.4 ± 1.2
- 37.8 ± 0.8
- 40.1 ± 0.2
- 42.9 ± 0.2
- 46.1 ± 0.6
- 33.5 ± 0.3
- 42.7 ± 2.9
- 37.1 ± 1.1
- 27.0 ± 1.4
- 22.7 ± 1.7
- 28.6 ± 0.5
- 38.7 ± 0.7
- 34.5 ± 0.1
- 40.1 ± 2.9
2.2 ± 1.9
7.5 ± 3.0
1.7 ± 0.3
- 5.8 ± 1.7
- 14.7 ± 2.9
- 9.3 ± 0.8
- 1.4 ± 0.6
- 8.4 ± 0.3
- 6.1 ± 3.4
2ZFP
2ZGB
2ZC9
2ZI2
2ZIQ
2ZHQ
2ZGX
2ZNK
2ZDA
2.25
1.60
1.58
1.65
1.65
1.96
1.80
1.80
1.73
35.1
21.4
15.7
23.6
21.9
18.5
18.2
17.2
11.4
18.5
19.5
14.5
14.9
16.1
14.7
16.3
14.6
10.9
1.90
1.10
1.08
1.58
1.36
1.26
1.12
1.18
1.06
1046
provides a most likely frozen static picture of
protein dynamics at ambient temperature.
Nevertheless, some special care is needed in the
interpretation of B-factors. We analyzed the Bfactors separately for each inhibitor relative to the
neighboring amino acids exposed to the binding
site. This calibration was done as an approximate
normalization to correct for any superimposed
quality difference in the diffraction properties of
the various crystal structures being compared.
Furthermore, if the ratio of B-factors of ligand
atoms relative to those of the binding pocket
residues is close to 1, equal thermal motion of
ligand and the binding cavity is assumed and full
occupancy of the inhibitors in the crystal is
suggested. Deviations from this ratio indicate higher
or lower mobility, often experienced by parts of a
ligand, provided full occupancy is given for the
considered ligand. As there might be some concerns
about the inherent correlation of B-factors with
partial/full occupancy, we studied this aspect in
great detail, as described.15 With this analysis we
can rule out concerns about partial population of the
highly soluble and tightly binding benzamidines.
Consequently, we are confident in our interpretation
of a high ratio of the B-factors of ligand portions
relative to the binding pocket residues as an
indicator for enhanced residual mobility of the
ligand or its fragments in the active site.
Non-additivity of Functional Group Contributions
In order to illustrate the magnitude of the thermal
parameters determined, a color-coding with respect
to the B-factors of active site residues and ligand
atoms has been assigned and is shown in Figs. 3 to 6
(blue, low; green, medium; and red, high thermal
motion). The protein residues are indicated by the
colored solvent-accessible surface and the ligand by
a color-coded stick representation. Fig. 3 shows
clearly that the benzamidine moiety is firmly fixed
in the S1 pocket (low temperature factors) and the
proline ring bound below the 60's loop shows rather
low thermal motion in the crystal. Much higher Bfactors are observed for the lipophilic side-chain
binding in the S3 subpocket of the enzyme, though
the difference electron density allows unambiguous
location of all ligand atoms during refinement of the
structure.
The derived crystallographic and thermodynamic
data enable us to compare individual inhibitors and
to find possible explanations for the phenomenon of
cooperativity.
ITC data, protonation correction
Before the comparison of thermodynamic data it
has to be determined if any putatively overlaid
protonation effects upon inhibitor binding are
occurring. To detect potential changes in protonation states, titration experiments were performed
Fig. 3. The crystallographically determined binding mode of 3e in complex with thrombin. Colors are assigned to all
atoms according to their temperature factors, from blue (low B-factor) to green to yellow and to red (high B-factor).
Protein residues are shown by solvent-accessible surface, ligand atoms in stick representation. The ligand is shown with
the Fo – Fc difference electron density (green mesh) at a contour level of 1.5 σ.
Non-additivity of Functional Group Contributions
1047
Fig. 4. The crystallographically determined binding mode of 3c and 4c in complex with thrombin. Colors are assigned
to all atoms as described for Fig. 3. The ratio of the mean B-factor of ligands with respect to the active-site residues is
indicated and the difference in the thermodynamic data, as recorded by ITC, is given. The lengths of the hydrogen bonds
between the ligands and Gly216 are given in Å.
from different buffer solutions. A negligible heat of
protonation has been observed experimentally for
4l.14 As discussed in detail elsewhere,14 this finding
results from a rather complex protonation inventory
that covers mutually compensating effects arising
from deprotonation of His57 and protonation of the
primary amino function of the ligand. Because a
very similar pattern, and thus very similar pKa
values are given with respect to titratable groups,
we assume similar behavior, also resulting in buffer
independence for the analogous inhibitors 4c and
4e. With some care, similar arguments can be used
for 2c, 2e and 2l from the m-chlorobenzyl series
because here the mutually compensating functionalities (His57 and amino group) are also present.
However, a similar mutual protonation inventory is
impossible for the inhibitors 3c, 3e and 3l because
they do not feature the primary amino group. In an
earlier study, we showed by a direct comparison of
2j and its N-acetylated analog that the release of
0.6 mol protons (most likely originating from His57)
occurs upon ligand binding. Therefore, we assume
similar heat effects to be superimposed to the heat of
binding of 3c, 3e and 3l, as these ligands do not
Fig. 5. The crystallographically determined binding mode of 3e and 4e in complex with thrombin. Colors are assigned
to all atoms as described for Fig. 3. The ratio of the mean B-factor of ligands with respect to the active site residues is
indicated and the difference in the thermodynamic data, as recorded by ITC, is given. The lengths of the hydrogen bonds
between the ligands and Gly216 are indicated in Å.
1048
Non-additivity of Functional Group Contributions
Fig. 6. The crystallographically determined binding mode of 3l and 4l in complex with thrombin. Colors are assigned
to all atoms as described for Fig. 3. The ratio of the mean B-factor of ligands with respect to the active site residues is
indicated and the difference in the thermodynamic data, as recorded by ITC, is given. The lengths of the hydrogen bonds
between the ligands and Gly216 are indicated in Å.
feature a titratable primary amino group that can
pick up the protons released from His57. As this
release will give rise to an additional heat signal, the
experimentally observed heat of binding of 3c, 3e
and 3l has to be corrected for the heat of ionization
associated with the release of 0.6 mol of protons by
His57 and the uptake of the same amount by the
buffer (Table 2). The heat of ionization for a histidyl
moiety accounts for 30 kJ/mol.18 If His57 releases
0.6 mol of protons upon complex formation, this
release should be endothermic and involve about
18 kJ/mol. The experimentally measured heat signal
is lowered by this value, and thus the authentic
0
is more enthalpic. In addition, the released
ΔHbind
protons are picked up by the buffer. Therefore, a
correction for an uptake of 0.6 mol of protons with a
heat of ionization for Tris buffer of 48 kJ/mol is
necessary.19 Consequently, the exothermic proton
uptake by the buffer contributes 28.8 kJ/mol to the
observed enthalpy. Accordingly, for 3c, 3e and 3l
0
is in total
the corrected enthalpy of binding ΔHbind
balance 10.8 kJ/mol lower than the experimentally
0
for
observed heat signal in Tris buffer. Thus, ΔHbind
3c appears to be – 16.2 kJ/mol, for 3e it accounts for
0
= – 17.8 kJ/
– 11.9 kJ/mol and 3l binds with ΔHbind
mol. The entropic contribution to binding –TΔS0
can be calculated as the difference from the observed
ΔG0 (Table 2).
(indicated by an arrow), which is observed also in
the complexes with 3c and 4c. Refinement results in
a low temperature factor for this water molecule.
With respect to the ligands, the introduction of the
amino group (from 3c to 4c) leads to a significant
decrease in the B-factor ratio from 1.58 to 1.12.
Obviously, 4c loses some part of its mobility
indicated by thermal motion compared to 3c. It
can be assumed that an entropically beneficial
binding event correlates with high residual mobility
of the inhibitor in the binding site. This residual
mobility has a significant influence on the entropy
component reflected in the total free energy of
binding.
The observed fixation of 4c compared to 3c
corresponds to an entropic disadvantage of
–TΔΔS = 15.2 kJ/mol of the binding process. It is
overcompensated by an enthalpic gain of
ΔΔH = –22.5 kJ/mol occurring upon the formation
of an additional, possibly charge-assisted hydrogen
bond between the amino function of 4c and the
carbonyl group of Gly216. The second hydrogen
bond, already present in 3c which lacks the amino
group, is formed between the ligand carbonyl
group and the amide NH of Gly216. Its length is
shortened only slightly by the additional charge-
Correlation of structural and thermodynamic
data of 3c/4c
Table 2. Thermodynamic data as corrected for
superimposed protonation steps for 3c, 3e and 3l
The inhibitors 3c and 4c with a small hydrophobic alkyl R2 side-chain exhibit virtually the same
binding mode (Figure 4). As detected in the highresolution crystal structure of uncomplexed
thrombin,15 the S3 pocket hosts one water molecule
Inhibitor
3c
3e
3l
a
ΔG0 (kJ / mol)
ΔH0bind (kJ/mol)
– TΔS0 (kJ/mol)
-32.8 ± 0.3 a
-37.4 ± 1.2
-37.8 ± 0.8
- 16.2 ± 1.4
- 11.9 ± 1.7
- 17.8 ± 0.5
-16.6 ± 2.9
-25.5 ± 2.9
-20.0 ± 0.8
Standard deviations as for the uncorrected values.
Non-additivity of Functional Group Contributions
assisted hydrogen bond. In summary, the data for
3c and 4c provide an example of a classical
enthalpy/entropy compensation.20,21 Furthermore,
differences in the solvation/desolvation properties
of 3c and 4c will also have an impact on the
observed thermodynamic profiles.
Correlation of structural and thermodynamic
data of 3e/4e
A similar comparison performed for the ligand
pair 3e and 4e with a branched medium-size alkyl
R2-side-chain shows a slightly different picture (Fig.
5). In the case of 3e, the aliphatic side-chain seems to
experience some kind of “conflict of interest”. In
order to form an optimal lipophilic contact with the
surface of the S3 pocket, and to fully displace the
hosted water from the S3 pocket, which is observed
in uncomplexed thrombin and the complexes with
3c and 4c, a rupture of an optimal hydrogen bond
formed between the ligand carbonyl group and the
amide nitrogen of Gly216 is required. This contact is
expanded in the complex with 3e to a distance of
3.6 Å (Fig. 5, left). Upon introduction of the amino
group in 4e, the complete dual ladder β-sheet-like
hydrogen bond network between inhibitor and
Gly216 is formed with two shorter distances (3.0 Å
and 3.2 Å). However, they prevent the isopropyl
side-chain from experiencing optimal lipophilic
contacts with the hydrophobic binding pocket.
Also in the present case of 3e/4e, the B-factor
ratio decreases from 1.36 to 1.18, which most likely
results from tighter fixation of 4e in the active site.
This results in an entropic disadvantage for the
binding of 4e. It is suggested that this effect is
slightly more pronounced for the branched medium
size than for the short chain alkyl R2 side-chain
(–TΔΔS: 3e/4e = 17.1 versus 3c/4c = 15.2 kJ/mol).
Possibly, the larger branched group has to abandon
more degrees of freedom than the smaller alkyl
substituent.
Correlation of structural and thermodynamic
data of 3l/4l
A third ligand pair that was evaluated is 3l and 4l
exhibiting a large aromatic R 2 side-chain. The
strongest cooperative effects have been observed
for this pair. In the present case, the introduction of
the amino group results in hardly any differences of
the crystallographically observed binding modes,
except the additionally formed charge-assisted
hydrogen bond (3.1 Å) and a slight reduction of
the adjacent hydrogen bond (distance 3.3 Å versus
2.8 Å) between the ligand carbonyl and the nitrogen
of Gly216. Again, we observe a significant decrease
in the B-factor ratio from 1.26 to 1.06 (Figure 6),
indicating that an enthalpy-/entropy compensation
is in operation in the present complexes.
Interestingly enough, the entropic penalty of
– TΔΔS = 13.9 kJ/mol for the ligand pair 3l/4l is
slightly lower than in the examples with the aliphatic
side-chains (3c/4c and 3e/4e). Presumably, the
1049
large benzyl side-chain is already rather tightly fixed
via hydrophobic contacts to the S3 pocket in 3l, even
in the absence of the additional amino group of 4l.
This view is supported by an almost identical
binding mode exhibited by both ligands, which
suggests that the introduced charge-assisted hydrogen bond has less of an influence on the differences in
the residual mobility of the respective complexes.
Thermodynamic cycle of the benzamidine series
3 and 4
Figure 7 shows the thermodynamic cycle for the
benzamidine derivatives with and without a terminal amino group. In all examples the introduction of
the NH2-group (3c/4c, 3e/4e, 3l/4l) enhances
binding affinity by about – 7 kJ/mol. The introduced
hydrogen bond reveals a strong enthalpic signal
(– 22 kJ/mol) which is largely compensated by an
entropic disadvantage of about – 15 kJ/mol. Interestingly, the enthalpic contribution remains virtually unchanged across the series, whereas the entropic
contribution changes appear to be less uniform. As
discussed, this observation is presumably explained
by the deviating residual mobility and number of
degrees of freedom experienced by the P3 substituents of different size in the ligands.
In both series replacing short-chain by branched
medium-size alkyl and large aromatic R2 side-chain
reveals small increases in ΔG of varying amounts
(– 4.6/– 2.8 and – 0.4/– 3.2 kJ/mol; Fig. 7). More
interesting is the fact that these ΔΔG changes
factorize into much larger absolute contributions of
enthalpy and entropy across the series, which
indicates pronounced mutual enthalpy/entropy
compensation. Remarkably, this enthalpy/entropy
compensation occurs with reversed sign going from
short-chain to branched medium-size alkyl R2 sidechain and from branched medium-size alkyl to large
aromatic R2 side-chain. This observation finds an
explanation by considering the molecular detail of
the binding mechanism. The short chain to branched
medium-size alkyl replacement (3c→3e and
4c→4e) involves the release of a water molecule
from the S3 pocket, an entropically favorable and
enthalpically disfavorable process. 22 Subsequent
substitution of the branched alkyl group by the
larger aromatic moiety (3e→3l and 4e→4l) is
enthalpically beneficial but entropically disfavored.
The larger substituent experiences much better van
der Waals contacts with the protein, however, at a
cost of a significant loss of its residual mobility.
From an entropic point of view the latter effect is
disfavorable. The stepwise optimizing of interaction
geometry by increasingly sacrificing ligand mobility
is best seen in the case of 3e. The branched alkyl
group experiences elevated mobility. Presumably,
this ligand tries to find a compromise between
satisfactory burial of its hydrophobic surface and
formation of a reasonably short hydrogen bond. MD
simulations performed on 1d, 2d, 1l and 2l,
described elsewhere,17 are in full agreement with
this hypothesis. Furthermore, in an earlier study we
1050
Non-additivity of Functional Group Contributions
Fig. 7. The thermodynamic cycle for six p-benzamidine derivatives 3c, 3e, 3l and 4c, 4e, 4l. All binding data are taken
from ITC experiments, ΔG0 (in italics), the relative differences (ΔΔ) between compounds, adjacent in the diagram, are
indicated along the connecting arrows: ΔΔG0, black; ΔΔH0, blue;–TΔΔS0, red. All values are given in kJ/mol.
experienced a similar behavior for a ligand with the
same scaffold bearing a P3 cyclohexylamino
group.23 The binding of this ligand is also governed
by a dynamic balance between formation of a
hydrogen bond to Gly216CO or, upon rupture of
this bond, efficient occupation of the S3 pocket. The
inventory between residual mobility, optimization
of intermolecular contact geometry and partial
desolvation is responsible for the observed cooperativity or non-additivity of different functional group
contributions in the present compound series.
To a substantial degree, the various contributions
are leveled out by enthalpy/entropy compensation.
Obviously, a ligand that is already firmly fixed to its
receptor site has fewer degrees of freedom (and thus
less residual entropy) to lose upon introduction of
additional functional groups that will further amplify the attractive interactions to the host protein. In
the present case, the mutual affinity-enhancing
interactions are of different natures (hydrogen
bonding or lipophilic contacts), but we can expect
that they reveal an equivalent influence once they
constrain the ligand degrees of freedom. This effect,
in another context, has been described as the zippertype mechanism, and can be traced in detail in our
example. It provides instructive insights into the fine
details of molecular recognition.
Summary and Conclusions
The present systematic study of ligand binding to
thrombin gives a structural and thermodynamic
explanation for the phenomenon of cooperativity or
non-additivity of functional group contributions.
Four series of closely related ligands (1-4, Fig. 1)
have been investigated. These series exhibit at P1 a
m-chlorobenzyl or benzamidine moiety. Next to the
P3 position, they either present an amino group
capable of forming a charge-assisted hydrogen bond
to Gly216CO or this group is lacking. For the S3
pocket, a broad range of hydrophobic substituents
of significant size difference has been tested. A
convincing linear relationship is obtained by correlation of hydrophobic surface areas buried in the
model-built complexes upon binding with free
energy changes. This finding supports the idea
that most of the currently used scoring functions
evaluate such a burial term by awarding a constant
amount of binding affinity per Å2 of hydrophobic
contact area. A derived adjustable parameter is
utilized to correlate hydrophobic contact surface
area to ΔG changes either to transfer scoring
functions among different protein targets or similarly in setting up a QSAR analysis. However, most
striking in the present case is the fact that hydrophobic contact surface contributions differ depending upon the presence or the absence of the amino
group.
Considered in detail, this observation contradicts
simple additivity of functional group contributions
and supports pronounced cooperative effects. Analysis of the individual crystal structures and factorizing the free energy into enthalpy and entropy
demonstrates that the binding affinity of the ligands
results from a mixture of enthalpic contributions
from hydrogen bonding and hydrophobic contacts,
and entropic considerations involving an increasing
loss of residual mobility of the bound ligands. These
conclusions match with a recent comprehensive
1051
Non-additivity of Functional Group Contributions
database survey.24 However, even within a series of
ligands that agrees well with the above-mentioned
linear burial versus free energy correlation, the
derived additivity can be artificial. This fact finds
an explanation in differences in the residual mobility
of bound ligand portions. Therefore, a property such
as the degree of surface burial calculated for the
static picture of a protein–ligand complex must be
misleading and does not consider dynamic properties. This fact becomes obvious regarding the
reversal enthalpy/entropy compensation and the
pronounced cooperative effects within the series.
As a matter of fact, many molecular phenomena
determining ligand binding are governed by pronounced enthalpy/entropy compensation. Thus,
they do not become transparent in ΔG and will
not be reflected in a free energy correlation.
Therefore, even incorrectly modeled binding
modes can lead to correct estimations of binding
affinity from structure. Supposedly, this is the
explanation of why empirical scoring functions still
work reasonably well. However, if the properties of
one member of the series deviate significantly from
pronounced enthalpy/entropy compensation, this
complex will fall out of the correlation based on a
too simply modeled (static) geometry. In conclusion,
if we want to have scoring functions of greater
reliability we have to incorporate descriptors that
model residual mobility and cooperative effects (or
appropriate entropic terms) correctly, apart from
correct solvation/desolvation phenomena.
Materials and Methods
Kinetic inhibition
The kinetic inhibition of human α-thrombin (isolated
from Beriplast®, CSL Behring, Marburg, Germany) was
determined by monitoring absorbance at 405 nm using the
chromogenic substrate Pefachrom tPa (LoxoGmbH, Dossenheim, Germany) as described,25 and applying the
following conditions: 50 mM Tris–HCl, pH 7.4, 154 mM
NaCl, 5% (v/v) DMSO, 0.1% (w/v) PEG 8000 at 25 °C
using different concentrations of substrate (182, 91, and
45 μM) and inhibitor (36.4, 27.3, 18.2, and 9.1 μM for the
weakest inhibitor and 3.6, 2.7, 1.8, and 0.9 nM for the
tightest binder). The activity of thrombin was adjusted by
diluting (∼ 1:300) 50 μg/ml thrombin solution with
154 mM NaCl until linear conversion of the substrate
could be detected over 5 min in an appropriate absorption
window (0.2∼0.8). The assay was stopped after 3 min by
the addition of concentrated acetic acid and absorption in
each well was corrected for the blank value. The Ki values
(n ≥ 3) were determined as described.26
was freshly prepared for each experiment by dialysis of a
thrombin sample in the buffer used for titration experiments and adjustment of DMSO final concentration to
2.5%. ITC measurements were routinely done at 25 °C in
50 mM Tris–HCl, pH 7.8, 100 mM NaCl, 2.5% DMSO, 0.1%
PEG 8000. Inhibitor solutions (0.03–0.25 mM, depending
on the individual ligand) were degassed for ∼ 10 min
immediately before use and titrated into the stirred cell
(1.3513 ml) containing a thrombin solution (0.006–
0.02 mM) once the baseline was stable. The injection
sequence consisted of an initial injection of 1.5 μl of ligand
solution to prevent artifacts arising from the filling of the
syringe (not used in data fitting), followed by injection of
7–12 μL each at 300 s intervals until complete saturation of
the enzyme binding sites was achieved. Raw data were
collected and the area under each peak was integrated,
followed by correction for heats of dilution and mixing by
subtracting the final baseline consisting of small peaks of
the same size to zero. The data were analyzed with
ORIGIN Software (Microcal Inc.) by fitting a single-site
binding isotherm,27 which yields ΔH0bind (enthalpy of
binding) and KD (dissociation constant). Measurements
were done in at least triplicate; KD was reproducible to
within 10% and ΔH0bind was reproducible to within 5%.
The buffer dependence of ΔH0bind was tested earlier for the
present compound series.14
Crystallisation and soaking
Human α-thrombin was dissolved in crystallisation
buffer (100 mM sodium phosphate, 350 mM NaCl,
10 mM benzamidine, pH 7.5) and dialyzed against the
same buffer overnight. The sample was concentrated to
5 mg/mL and 200 μL of this solution were mixed with
20 μL of an aqueous solution (500 mg/mL) of Hirugen
(Bachem, Bubendorf, Switzerland). After incubation for
10 h at 4 °C, crystallisation was carried out at 4 °C by
the vapour-diffusion, hanging-drop method using 28%
PEG 8000 and 100 mM sodium phosphate (pH 7.5).
Microseeding was done after equilibration for 16 h. For
soaking, a 1:3 (v/v) mixture of 10–40 mM inhibitors in
DMSO and crystallisation buffer was prepared, in
which medium-sized crystals without visible imperfections were soaked for 6–24 h.
Data collection and processing
Crystals were prepared for data collection at 110 K using
20% (w/v) glycerol in crystallisation buffer as a cryoprotectant solution. The datasets for 2e, 3c, 3e, 4e and 4l were
collected with synchrotron radiation at BESSY (Berlin,
Germany) beamlines 14.1 on the Marmosaic 225 mm CCD
and 14.2 on the Mar CCD 165 mm detector. Diffraction data
for 2l were collected at DESY (Hamburg, Germany) beamline X13 on the Mar CCD 165 mm detector. Diffraction data
for 2c, 3l and 4c were collected on RIGAKU copper rotating
anode (RU300) at 50 kV, 90 mA using an R-AXIS IV++ image
plate system. Data processing and scaling were performed
using the HKL2000 package.28
ITC experiments
Structure determination and refinement
The ITC experiments were done with an MCS titration
calorimeter (Microcal, Inc., Northampton, MA).27 Concentrations of inhibitor stock solutions in DMSO were
determined by the weight of the corresponding hydrochlorides. The final concentration was achieved by
diluting 1:40 in the experimental buffer. Protein solution
The coordinates of human thrombin (PDB code 1H8D)29
were used for initial rigid body refinement of the protein
molecules followed by repeated cycles of conjugate
gradient energy minimization, simulated annealing and
B-factor refinement using the CNS program package.30
1052
Table 3. Data collection and refinement statistics for the nine complex structures determined in this study
Complex
PDB entry
A. Data collection and processing
No. crystals used
Wavelength (Å)
Space group
Unit cell parameters
a, b, c (Å)
β (°)
Matthews coefficient (Å3/Da)
Solvent content (%)
B. Diffraction dataa
Resolution range (Å)
a
THR-2e
2ZGB
THR-2l
2ZC9
THR-3c
2ZI2
THR-3e
2ZIQ
THR-3l
2ZHQ
THR-4c
2ZGX
THR-4e
2ZNK
THR-4l
2ZDA
1
1.54178
C2
1
0.91841
C2
1
0.97803
C2
1
0.91841
C2
1
0.91841
C2
1
1.54178
C2
1
1.54178
C2
1
0.91841
C2
1
0.91841
C2
70.5, 71.3, 72.9
100.6
2.3
48
69.8, 71.4, 72.6
100.3
2.3
46
70.4, 71.3, 72.9
100.7
2.3
47
70.5, 71.6, 72.6
100.6
2.3
47
70.2, 71.6, 72.3
100.3
2.3
46
70.1, 71.4, 72.9
100.8
2.3
47
70.4, 71.5, 72.5
100.7
2.3
47
70.2, 71.6, 72.5
100.5
2.3
46
70.3, 71.5, 72.4
100.5
2.3
46
20 – 2.25
(2.29 – 2.25)
15,884 (786)
8.2 (31.7)
93.8 (90.3)
2.2 (2.0)
12.1 (2.8)
20 – 1.60
(1.63 – 1.60)
45,709 (2273)
3.5 (31.9)
99.5 (100)
3.2 (3.1)
29.5 (3.9)
30 – 1.58
(1.61 – 1.58)
46,641 (1725)
3.4 (23.5)
95.9 (71.1)
2.2 (1.7)
24.9 (3.4)
20 – 1.65
(1.68 – 1.65)
41,212 (1681)
3.2 (23.8)
96.5 (77.8)
2.0 (1.7)
20.8 (2.5)
20 – 1.65
(1.68 – 1.65)
41,871 (1963)
4.2 (23.3)
98.6 (91.0)
2.8 (2.3)
24.2 (3.5)
20 – 1.96
(2.01 – 1.96)
24,126 (1668)
7.2 (25.7)
93.7 (96.7)
2.8 (2.7)
12.6 (2.8)
20 – 1.80
(1.83 – 1.80)
32,453 (1558)
4.8 (32.6)
99.1 (96.2)
2.5 (2.4)
20.7 (2.5)
20 – 1.80
(1.83 – 1.80)
32,354 (1535)
2.8 (9.1)
98.8 (95.1)
2.7 (2.4)
29.4 (6.0)
20 – 1.73
(1.76 – 1.73)
35,607 (1692)
9.0 (25.2)
97.6 (93.1)
2.9 (2.2)
14.8 (3.3)
10–2.25
14 832/709
10–1.60
43 780/2187
10–1.58
42 070/2197
10–1.65
39 496/1 973
10–1.65
40 527/2 022
10–1.96
22,286/1070
10–1.80
31,065/1536
10–1.80
31,481/1536
10–1.73
32,402/1691
17.6/29.8
19.3/23.1
18.0/23.3
18.2/22.5
18.1/22.5
19.3/27.2
17.8/22.9
17.9/22.9
17.2/22.8
15.4/26.3
18.6/22.2
17.1/22.0
17.1/21.2
17.3/21.3
17.7/25.4
16.6/21.5
17.4/21.9
16.9/21.4
251
2
22
142
251
2
24
185
251
2
27
271
252
2
23
192
252
2
25
179
251
2
28
154
250
2
24
194
251
2
26
220
252
2
29
268
0.005
2.0
0.009
2.5
0.010
2.6
0.009
2.6
0.009
2.5
0.006
2.1
0.008
2.4
0.008
2.5
0.008
2.5
86.0
84.6
86.1
85.5
84.0
85.2
86.5
85.2
86.6
13.0
14.9
13.4
14.0
15.6
14.8
13.0
14.3
13.4
1.0
0.5
0.5
0.5
0.4
-
0.5
0.4
-
23.8
23.0
28.1
23.2
21.4
29.9
20.7
15.7
31.2
19.5
23.6
27.7
21.7
21.9
28.6
20.1
18.5
25.7
21.6
18.2
27.9
19.6
17.2
27.4
17.1
11.4
26.7
Numbers in parentheses characterize the highest resolution shell.
Non-additivity of Functional Group Contributions
Unique reflections
R(I)sym (%)
Completeness (%)
Redundancy
I/σ(I)
C. Refinement
Resolution range (Å)
Reflections used in
refinement (work/free)
Final R value for all reflections
(work/free) [%]
Final R value for reflections
with F N 4 σ F (work/free) (%)
Protein residues
Sodium ions
Inhibitor atoms
Water molecules
RMSD from ideal
Bond lengths (Å)
Bond angles (°)
Ramachandran plot
Residues in most-favoured
regions (%)
Residues in additionally
allowed regions (%)
Residues in generously
allowed regions (%)
Mean B-factor
Protein (Å2)
Inhibitor (Å2)
Water molecules (Å2)
THR-2c
2ZFP
Non-additivity of Functional Group Contributions
Refinement at later stages was done with the program
SHELXL.31 Here, at least 20 cycles of conjugate gradient
minimization were done with default restraints on
bonding geometry and B-values; 5% of all data were
used for the Rfree calculation. Amino acid side-chains were
fitted into σ-weighted 2Fo – Fc and Fo – Fc difference
electron density maps using Coot.32 After the first
refinement cycle, water molecules and subsequently ions
and ligand were located in the electron density and added
to the model. Restraints were applied to bond lengths and
angles, chiral volume, planarity of aromatic rings and van
der Waals contacts. Multiple side-chain conformations
were built in case an appropriate electron density was
observed and maintained during the refinement, and if the
minor populated side-chain showed at least 10% occupancy. During the last refinement cycles, riding hydrogen
atoms were introduced without additional parameters.
The final models were validated using PROCHECK.33
Data collection, unit cell parameters and refinement
statistics are given in Table 3. Analysis of temperature
factors was done with Moleman, 34 distances were
measured using SYBYL 8.0 (Tripos Inc., St. Louis, MO).
Figures were prepared using Isis Draw (MDL, San
Leandro, CA) and Pymol 0.99 (DeLano Scientific, Palo
Alto, CA). Coordinates and structure factors of all X-ray
structures have been deposited in the Protein Data Bank
and the accession codes are given in Table 3.
Protein Data Bank accession numbers
Coordinates and structure factors have been deposited
in the Protein Data Bank with the following accession
numbers: THR-2d complex 2ZGB; THR-3c complex 2ZI2;
THR-3l complex 2ZHQ; THR-4e complex 2ZNK.
Acknowledgements
We kindly acknowledge CSL Behring, Marburg,
for supplying us with generous amounts of human
thrombin from the production of Beriplast®. We
thank the beamline support staff at DESY (Hamburg, Germany) and BESSY (Berlin, Germany) for
their advice during data collection and the BMBF
(support code 05ES3XBA/5) for generously supporting travel to BESSY/Berlin.
Author Contributions. L.M., M.S. and D.H.
contributed the design and synthesis of the compounds (correspondence regarding the design and
synthesis should be addressed to D.H.) as well as
collaborative interpretation of the data. B.B., A.H. and
G.K. contributed to the kinetic and microcalorimetric
characterization of the compounds, the crystal structure determination and analysis and the collaborative
interpretation of the data. Correspondence regarding
these aspects should be addressed to G.K.
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