INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, VOL. XXXV, 205-214 (1989)
Interaction Model for the Antiinflammatory Action
of Benzoic and Salicylic Acids and Phenols
E. L. MEHLER AND J. GERHARDS"
Department of Structural Biology, Biocenter, University of Basel, CH-4056 Basel, Switzerland
Abstract
Ab initio, quantum chemical methods have been used to develop an interaction model for the binding of
benzoic and salicylic acids and phenols to cyclooxygenase, leading to their antiinflammatory action. The
model is based on a regression analysis of the energy of the highest occupied molecular orbital with the
potency of the active substances to inhibit prostaglandin production in mouse macrophages and on an
analysis of the frontier orbital charge distributions and electrostatic potentials of active and inactive compounds. The model suggests that binding is controlled by an electrostatic orientational factor and a charge
transfer or polarization contribution. The observed relative potencies of the phenols and acids can be rationalized with the help of the proposed interaction model.
Introduction
No other disease syndrome has been researched so persistently as the inflammatory
symptoms of pain and swelling, and it is not surprising that some of the earliest medicinal-chemical investigations were directed at the nonsteroidal antiinflammatory
drugs (NSAID). Among them was salicylic acid (0-OH benzoic acid) found in the oil
of gualtheria in 1844 and first used in rheumatic fever in 1875 and maintaining its supremacy for this condition to the present day [ l ] . Derivatives such as aspirin also
have not been replaced, and 5-(2,4-difluorophenyl) salicylic acid (diflunisal) is a recent entry to the salicylate drug field, chosen from 500 candidate compounds by
screening [2].
Many biochemical mechanisms of action were suggested when it was demonstrated
that salicylate, aspirin, and indomethacin inhibit the cyclooxygenase-catalyzed biosynthesis of prostaglandins (FG)[3]. Since then a large body of experimental evidence
has accumulated, but nevertheless the structural requirements of NSAID activity or
even reliable quantitative structure-activity relationships (QSAR) are still lacking [4].
A complicating factor is the observation that the locus of competitive binding is not
only the catalytic site of cyclooxygenase, but also a supplementary site distinct from,
but related to, the catalytic site [5]. An understanding of structure-activity relationships at the molecular level are most naturally obtained through an explicit consideration of inhibitor-enzyme interactions. However, the three-dimensional structure of
*Present Address: Hoffmann-La Roche & Cie. AG, Grenzacherstr. 124, CH-4002 Basel, Switzerland.
0 1989 John Wiley & Sons, Inc.
CCC 0020-76081891010205- 10$04.00
206
MEHLER AND GERHARDS
the target enzyme, prostaglandin synthase (PGS),is unknown, eliminating this approach. An alternative approach is one which concentrates on identifying those electronic interactions which may contribute to stabilizing the inhibitor-enzyme complex
without specifying explicit structural parameters of the receptor's binding sites.
The pharmacological data employed for the studies reported below were obtained
for about 80 monosubstituted congeners of benzoic and salicylic acid and phenol [ 6 ] .
This data is based on the in vitro inhibition of prostaglandin production in mouse macrophages 171 and is expressed as PIC,,, where IC,, is the 50% inhibitory concentration.
In this paper we first review the results for the acidic [8] and the phenolic [9]
NSAID. It is shown how linear regression analysis of electronic reactivity indices was
combined with an analysis of the frontier orbital charge distributions and the electrostatic potentials (ESP) to identify the relevant reactivity indices and propose a mechanism for complex formation. This analysis suggests that the binding site for the two
classes partially overlaps, and on this basis an electrostatic potential interaction
model is formulated which can rationalize most of the observed differences in activity
between the benzoic (BZA)and salicylic acids (SAA) and the phenols.
Details of the Calculations
Ab initio molecular orbital calculations were carried out on 34 active compounds
with general formulas
"\o
I
I1
and which are listed in Table I. In addition to these molecules, molecular orbital
wave functions were determined for several inactive substituted benzoic acids (6,8)
and for a large number of benzoates and salicylates. Thus, a total of about 80
molecules were calculated. To help reduce the computational effort for this number
of larger molecules, two simplifying assumptions were made: first, all calculations
were performed at the minimum basis (MB) set level, and, second, standard geometries were used throughout with the exceptions described in Ref. 8.
To exploit the use of standard geometries to the maximum, the integral program
was modified to allow for the recalculation of two-electron integrals involving an arbitrary subset of the contractions, and programs were developed to manipulate the integral lists. Using these programs the two-electron integrals calculated for a given
molecule, which do not change when the structure is modified, can be reused and do
not have to be recalculated. Thus the two-electron integrals required for a substituted
phenol, i-R-C,H,OH, can be obtained from the integral list of the analogous SAA,
(i + 1)-R-C,H,COOHOH, by deleting all the integrals involving the carboxyl and
only recalculating those for the H which replaces the COOH group. In the present
INTERACTION MODEL FOR ANTIINFLAMMATORY ACTION
207
TABLE
I. HOMO energies and in vitro activities of monosubstituted acids and phenols.
R"
-E"OMOb
PICSO
PICSO'
(calcd.)
Error
Salicylic acids
3-OH
4-OH
5-OH
H
3-F
5-F
3-C1
4-C1
5-C1
3-IPR
4-IPR
5-IPR
223.0
235.9
218.1
233.2
238.2
236.0
234.5
242.6
232.1
223.0
227.5
220.4
4.43
3.02
4.61
3.33
3.82
3.82
3.89
3.31
4.06
3.92
3.29
4.12
4.54
3.55
4.92
3.16
3.38
3.54
3.66
3.05
3.80
4.54
4.19
4.14
-0.11
-0.53
-0.31
-0.43
0.44
0.28
0.23
0.26
0.26
-0.62
-0.90
-0.62
Benzoic acids
3S-(OW2
3-IPR
4-IPR
4-NPR
230.9
238.8
241.5
243.6
3.61
3.01
2.93
2.98
3.93
3.33
3.12
2.96
-0.32
-0.32
-0.19
0.02
Phenols
2-OH
3-OH
2-CH3
3-CH3
4-CH3
2-ETH
3-ETH
4-ETH
2-IPR
3-IPR
4-IPR
2-F
3-F
4-F
2-c1
3-C1
4-C1
H
216.3
221.7
218.0
219.7
214.9
216.1
218.5
214.0
215.6
217.9
211.9
232.6
234.0
227.6
231.8
231.6
224.8
224.1
5.34
5.15
5.16
4.74
5.26
5.88
5.26
5.61
4.81
4.41
5.48
3.51
4.05
3.98
4.62
4.61
4.86
3.54
5.05
4.64
4.93
4.80
5.16
5.07
4.89
5.23
5.11
4.93
5.39
3.80
3.69
4.19
3.87
3.88
4.40
4.46
0.29
0.51
0.23
-0.06
0.10
0.81
0.37
0.38
-0.30
-0.52
0.09
-0.23
0.36
-0.21
0.75
0.73
0.46
-0.92
*ETH; Ethyl; IPR; isopropyl; NPR; n-propyl.
b ~ H O M Ois given in kiIocalories/moIe.
'Calculated pICso from Eq. (1).
case, where minimum basis sets are used, this means that only integrals involving a
single contraction have to be recalculated. Since these molecules require from 41
to 87 contractions for the MB wave functions, this procedure yields substantial
savings of computing time. The same idea can also be used to replace a group by
a larger one. Here the old integral list is expanded to provide storage for the addi-
208
MEHLER AND GEFSIARDS
tional integrals, and only the new ones have to be calculated. Finally, Ahlrichs’
method [ 111 was implemented in the integral program to avoid calculating small twoelectron integrals.
The MBS used in this work were contracted from (5s, 2p) and ( 7 s , 3 p ) atomic bases
for second and third row atoms, respectively, and Huzinaga’s (3s) basis for hydrogen
[ 121. These bases were specially constructed to mimic the valence shell representation of larger bases [13], and the parameters have been given elsewhere [14]. Calculations were carried out on a large number of monosubstituted benzenes and phenols
to test the reliability of these small bases, and for properties such as orbital energies,
dipole moments, charge distributions, etc., it was shown that qualitatively reliable results were obtained. Moreover, there was little change in reliability between using
optimized or experimental geometries and standard geometries [ 151. The programs
for calculating the electrostatic potentials and densities over Gaussian lobe functions,
as well as the SCF programs, were developed in this laboratory.
Results and Discussion
Sulicylutes and Benzoutes
The detailed formulation of the interaction model for the acidic inhibitors with PGS
has been reported elsewhere [a], and here we review only those aspects which are
relevant for the present discussion. In Ref. 8 an interaction model was proposed
which involved a two-step process leading to complex formation: first, an alignment
of the inhibitor in the binding site controlled by stabilizing interactions between the
ESP of the enzyme’s binding site and that of the drug molecule; second, in favorable
orientations the inhibitor’s frontier orbitals overlap with complementary orbitals in
the binding site, leading to a two-way charge-transfer or mutual polarization of the
interacting charge distributions.
The above model was formulated on the basis of a regression analysis of electronic
reactivity indices and an analysis of the frontier orbital charge distributions and structure of the ESPS of active and inactive molecules. It was found that the reactivity index DE = cHoMo
- qUMo
correlated strongly with activity, which suggests directly a
two-way interaction where charge moves or polarizes from the HOMO of the inhibitor
to a low-lying virtual orbital of the receptor and from a high-lying occupied orbital in
the active site to the LUMO of the drug molecule.
Such a complementary interaction could be achieved through interactions of fragments of the inhibitor with local sites on the receptor. This idea is supported by HOMO
and LUMO charge distributions of SAA which are plotted in Figures l a and c. It is seen
that in the HOMO, charge is concentrated on the ring and OH group, whereas the
LUMO’S
virtual charge is concentrated on the ring and carboxylic group. Thus the carboxylic moiety and the OH group represent two fragments which could be involved
in the interactions. It was also found that increasing frontier orbital charge on the
OH + R groups and decreasing T charge on the carboxylic group correlated with activity. These correlations together with the HOMO and LUMO charge distributions then
suggest an interaction where charge moves from the inhibitor’s OH and substituent
groups to the receptor and from the receptor to the carboxylic moiety of the drug
molecule.
INTERACTION MODEL FOR ANTIINFLAMMATORY ACTION
209
d
Figure 1. Frontier orbital charge distributions of salicylic acid and phenol: (a) HOMO of
SAA, (b) HOMO of phenol, (c) LUMO of SAA, and (d) LUMO of phenol. The contours are drawn
in a plane 0.53 8, above the ring; contour values: 0.054 e/8,’, 0.027 e/A’, 0.0135 e / R .
Although D E provides a reasonable quantitative description of the active acidic
congeners, it was not as reliable in predicting inactive substances, implying that additional factors not described by DE are operative in the process, leading to complex
formation. The molecular ESPS were able to resolve the active and inactive compounds and also provided further insight to help rationalize some of the other observed differences in potency. The structure of the ESPS allowed orientation vectors to
be drawn as shown in Figure 2. It appeared that the vector connecting the minimum
above the ring to the minimum near the hydroxy oxygen was crucial for activity and
was therefore termed an “activating” orientation vector. The (dashed) vector shown in
Figure 2b connecting the minimum near the carboxylic oxygen to the minimum
above the ring appeared to weaken activity, and when only this latter vector can be
drawn (Fig. 2a), the compound was usually inactive. This latter orientation vector
was therefore termed “inactivating.” A more detailed discussion of orientation vectors is given by Weinstein et al. [16].
Phenols
As for the acidic compounds, complex formation of the phenols with the receptor
appears to be controlled by the ESP of the inhibitors and a frontier orbital interaction.
The charge densities of the frontier orbitals given in Figures l b and d show that the
phenol’s HOMO charge density distribution is quite similar to that of SAA, which is
also true for the substituted congeners [17]. Due to the absence of the carboxylic
group, the LUMO virtual density distribution is completely different. However, as for
the acids there is essentially no virtual density on the phenolic oxygen.
210
MEHLER AND GERHARDS
Figure 2 . ESP maps 2 8, above ring plane of (a) BZA, (b) SAA, and (c) phenol. Contour valPositive potentials, (- .-) negative potential,
ues (kcal/rnol) are 0, 1 , 2, 4, 8, and 16. (-1
(- . .-) zero potential. Arrows indicate orientation vectors.
The similarity of the HOMO charge distributions of the phenols to the SAAS is also
reflected in cHOMO,
since a correlation with activity is also observed for the phenols.
However, no correlation is found with D s or .cLUMO,
but since there is no fragment
which could act as an electron acceptor, this is not surprising. The observed relationand activity suggests an interaction where charge moves from the
ship between
inhibitor to the receptor. The origin of the charge transfer seems to be somewhat different than for the SAAS because activity correlates with qT on the OH group. Moreover, we also found that activity correlates with oxidation-reduction potentials [ 181
which presumably only involves the phenolic group. The latter two relationships suggest that for the phenols the interaction more closely resembles charge transfer stabilization, whereas for the acids a mutual polarization takes place.
The activating orientation vector found for the active acidic compounds is also
present in the phenols as shown in Fig. 2c, but the inactivating vector is absent. The
ESPS of the alkyl-substituted phenols are qualitatively similar to phenol, exhibiting a
strong activating orientation vector and a large positive region in the upper half of
INTERACTION MODEL FOR ANTIINFLAMMATORY ACTION
211
the diagram. This latter feature may lead to less stringent orientational requirements
than for the SAAS which would make an additional contribution to the free energy of
binding. The electron-withdrawing substitutents exhibit additional negative regions of
potential, which do not seem to appreciably affect activity.
Interaction Model
It was reported earlier that
of combined samples of acidic and phenolic inhibitors correlated with activity [ 171. The complete sample of 34 substances listed in
Table I yields the regression
PIC,,, = 0.0767~,,,,
r = 0.84
F
=
76
+ 21.64
SD =
0.46
where r is the correlation coefficient, F is the F test, SD is the standard deviation, and
E is in kilocalories/mol. The regression is plotted in Figure 3, and it is seen that the
phenols concentrate primarily in the upper right and the acids in the lower left of the
diagram. The separation of the acids and phenols into less and more active groups,
respectively, is in full agreement with the observed potencies, since the mean PIC,,
of the latter is more than one unit greater than the former.
The slope of the above regression is not very different from the slopes obtained
from the regression of
with pIC5,, of the separate groups. Combining this observation with the similarities of the HOMO density distributions (Fig. l a and b) led to
the suggestion that the binding sites of the acids and phenols partially overlap [ 171.
1
h
A
5 -
0
0
.A A
u7
.--
u
Q
4-
x
u
c
aJ
-
c
a0
3 -
2-1
-245
I
'
-235
-225
HOMO Energy ( K c a l I m o l l
-215
Figure 3. Linear regression of PIC= with E~~~~ of 34 BUS, SAAS, and phenols. Open symbols
are acids and solid symbols are phenols: (A)alkyls, (V) -OH, (0)
-H, (0)
halogens.
2 12
MEHLER AND GERHARDS
We now consider the plausibility of this proposal with the help of the ESP of BZA,
SAA, and phenol.
The ordering of potency between the different groups has been remarked upon
above and (on the average) is phenols > SAAS > BZAS. The orientation vectors which
can be drawn for the different groups are shown in Figure 2: for BZA only an inactivating vector can be drawn, for SAA both inactivating and activating vectors are present, and for phenol only the activating vector is found. Thus the orientation vectors
directly suggest the ordering of potency which is observed. Naturally, this relationship in the ordering of the potencies and the types of orientation vectors present in
each species also supports an overlapping binding site.
It was observed that in the SAAS the increase in strength and extent of the positive
region of ESP located around the carboxyl moiety appeared to contribute to activity
[8]. In the phenols this positive region is further enhanced, and the negative bump
due to the hydroxy oxygen of the carboxyl group has disappeared.
On the basis of these considerations a schematic diagram of the ESP of the receptor’s binding site is presented in Figure 4.The model has been slightly modified from
the one proposed for the acidic substances in that the negative region has been somewhat expanded to accomodate the additonal information obtained from the phenols.
The region within the inner contour is assumed to be more strongly negative than the
outer region, and phenol and SAA are placed in their assumed optimal positions to interact with the binding site. Phenol has been shifted about 0.5 8, parallel to the orientation vector and can no longer interact with the receptor’s occupied and unoccupied
orbitals in the same way as was assumed for SAA (see Fig. 6, Ref. 8).
Figure 4.
Schematic presentation of proposed binding site ESP and orientation vectors.
and phenol are positioned in their assumed binding orientations.
SAA
INTERACTION MODEL FOR ANTIINFLAMMATORY ACTION
213
It can now be seen how this common interaction model helps rationalize the observed differences in activity of the three classes of substances. The SAAS orientation
vector aligns with the receptor’s orientation vector, and the positive region of ESP near
the carboxy moiety interacts with the inner negative region of ESP in the receptor,
leading to favorable interactions. In this alignment the frontier orbitals of the SAAS
overlap optimally with occupied and unoccupied orbitals in the receptor to affect the
charge transfer interaction (see Fig. 6, Ref. 8). However, to bring the BZAS’and the
receptor’s orientation vectors into alignment, the molecule has to be rotated, causing
the negative ESP to the right of the carboxyl fragment’s hydroxy oxygen to overlap
with the deeper negative region of the receptor’s ESP and also reducing the overlap
between the frontier orbitals and the complementary orbitals in the receptor. Both of
these interactions lead to loss of stabilization and hence to the observed inactivity of
most BZA congeners.
The phenol’s ESP enhances stability relative to SAA:the inactivating orientation vector is no longer present and therefore there is no competition in phenol between two
potential alignments, one of which is favorable whereas the other destabilizes the
complex. In addition, the upper region of negative ESP in SAA (Fig. 2b) overlaps with
a region of weak negative ESP in the model’s interaction site, leading to some destabilization. In the phenols all negative ESP regions due to the carboxylic oxygens have
disappeared, leaving an extensive positive region of ESP (Fig. 2c, upper third of the
diagram) which can interact favorably with the model receptor’s negative ESP in this
of the phenols is on the averregion. Combining these effects with the fact that
age about 11 kcal/mol less negative than for the acidic substances seems to account
for the observed greater potency of the phenol congeners.
Conclusions
For the acidic and phenolic substances considered in this paper a two-step model
has been formulated leading to complex formation. First, there is an alignment of the
active molecule in the receptor’s binding site controlled by the molecular ESP,and
second a charge transfer or polarization is affected which leads to further stabilization. Furthermore, the two aspects are complementary since the former provides a
qualitative relation between structure and activity whereas the latter is quantitative.
The analysis also suggests that the binding sites of the two classes overlap. The basis
of this conclusion is found in the similarities of the ESP, HOMO charge density distributions and the relationship between
and potency and allows the observed differences in activity to be rationalized.
Acknowledgments
The authors express their gratitude to Prof. A. Cerletti and Prof. U. Meyer for their
support in carrying out part of this research. We also thank the University of Base1
Computing Center for generous grants of computing time. The support of the Swiss
National Foundation for the Advancement of Scientific Research (grant No. 3.5230.83) is gratefully acknowledged.
214
MEHLER AND GERHARDS
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Received May 5, 1988
Accepted for publication July 7, 1988