QSAR Analysis for ADA upon Interaction with a Series of Adenine Derivatives as Inhibitors

Article abstract of DOI:10.1081/NCN-120030719

The kinetic parameters of adenosine deaminase such as K_m and K_i were determined in the absence and presence of adenine derivatives (R₁- R₂₄) in sodium phosphate buffer (50 mM; pH 7.5) solution at 27°C. These kinetic parameters were used for QSAR analysis. As such, we found some theoretical descriptors to which the binding affinity of adenosine deaminase (ADA) towards several adenine nucleosides as inhibitors is correlated. QSAR analysis has revealed that binding affinity of the adenine nucleosides upon interaction with ADA depends on the molecular volume, dipole moment of the molecule, electric charge around the N1 atom, and the highest of positive charge for the related molecules.

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QSAR Analysis for ADA upon Interaction with a Series
of Adenine Derivatives as Inhibitors
A. A. Moosavi‐Movahedi a , S. Safarian a b , G. H. Hakimelahi c , G. Ataei a d , D. Ajloo
a e , S. Panjehpour a , S. Riahi f , M. F. Mousavi f , S. Mardanyan g , N. Soltani h , A.
Khalafi‐Nezhad h , H. Sharghi h , H. Moghadamnia h & A. A. Saboury a
a Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
b Department of Biology, Faculty of Science, University of Tehran, Tehran, Iran
c Institute of Chemistry, Academia Sinica Taipei, Taipei, Taiwan, ROC
d Department of Chemistry, Faculty of Paramedical Science, Shahid Beheshti University
of Medical Science, Tehran, Iran
e Department of Chemistry, University of Damghan, Damghan, Iran
f Department of Chemistry, Faculty of Science, Tarbiat‐Modares University, Tehran, Iran
g H.Ch. Buniatyan Institute of Biochemistry of the Armenia, NAS, 5/1 P. Sevak St.,
Yerevan, 375014, Armenia
h Department of Chemistry, Faculty of Science, University of Shiraz, Shiraz, Iran
Version of record first published: 07 Feb 2007.
To cite this article: A. A. Moosavi‐Movahedi , S. Safarian , G. H. Hakimelahi , G. Ataei , D. Ajloo , S. Panjehpour , S.
Riahi , M. F. Mousavi , S. Mardanyan , N. Soltani , A. Khalafi‐Nezhad , H. Sharghi , H. Moghadamnia & A. A. Saboury (2004):
QSAR Analysis for ADA upon Interaction with a Series of Adenine Derivatives as Inhibitors, Nucleosides, Nucleotides and
Nucleic Acids, 23:3, 613-624
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NUCLEOSIDES, NUCLEOTIDES & NUCLEIC ACIDS
Vol. 23, No. 3, pp. 613–624, 2004
QSAR Analysis for ADA upon Interaction with a Series of
Adenine Derivatives as Inhibitors
A. A. Moosavi-Movahedi,1, S. Safarian,1,2 G. H. Hakimelahi,3 G. Ataei,1,4
*
D. Ajloo,1,5 S. Panjehpour,1 S. Riahi,6 M. F. Mousavi,6 S. Mardanyan,7
N. Soltani,8 A. Khalafi-Nezhad,8 H. Sharghi,8 H. Moghadamnia,4
and A. A. Saboury1
2
1Institute of Biochemistry and Biophysics, and Department of Biology, Faculty of
Science, University of Tehran, Tehran, Iran
3Institute of Chemistry, Academia Sinica Taipei, Taipei, Taiwan, ROC
4Department of Chemistry, Faculty of Paramedical Science, Shahid Beheshti
University of Medical Science, Tehran, Iran
5Department of Chemistry, University of Damghan, Damghan, Iran
6Department of Chemistry, Faculty of Science, Tarbiat-Modares University,
Tehran, Iran
7H.Ch. Buniatyan Institute of Biochemistry of the Armenia, Yerevan, Armenia
8Department of Chemistry, Faculty of Science, University of Shiraz, Shiraz, Iran
ABSTRACT
The kinetic parameters of adenosine deaminase such as Km and Ki were determined in
the absence and presence of adenine derivatives (R1–R24) in sodium phosphate buffer
(50 mM; pH 7.5) solution at 27°C. These kinetic parameters were used for QSAR
analysis. As such, we found some theoretical descriptors to which the binding affinity
of adenosine deaminase (ADA) towards several adenine nucleosides as inhibitors is
correlated. QSAR analysis has revealed that binding affinity of the adenine
nucleosides upon interaction with ADA depends on the molecular volume, dipole
*
Correspondence: A. A. Moosavi-Movahedi, Institute of Biochemistry and Biophysics, University
of Tehran, Tehran, Iran; Fax: +9821-6404680; E-mail: moosavi@ibb.ut.ac.ir.
613
DOI: 10.1081/NCN-120030719
1525-7770 (Print); 1532-2335 (Online)
www.dekker.com
Copyright D 2004 by Marcel Dekker, Inc.

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Moosavi-Movahedi et al.
moment of the molecule, electric charge around the N1 atom, and the highest of
positive charge for the related molecules.
Key Words: Adenosine deaminase; Adenine nucleosides; QSAR analysis; Cyclic
and acyclic adenosine derivatives.
INTRODUCTION
Adenosine deaminase (ADA EC 3.5.4.4) is an important enzyme of the purine
salvage pathway catalyzes the irreversible hydrolytic deamination of adenosine or
deoxyadenosine to their respective inosine product and ammonia. It is present in
virtually all mammalian cells and has a central role in maintaining immune
competence. Lack of the enzyme is associated with severe combined immunodeficiency
disease (SCID) that is a genetically inherited disease fatal to newly born children if not
properly diagnosed and treated.[1,2] Higher levels of ADA in the alimentary tract and
decidual cells of developing fetal–maternal interface put ADA among those enzyme
performing a unique role in the growth rate of cells, embryo implantation, and
undetermined functions.[3,4]
Understanding the interaction of ADA with its inhibitors and substrates at the
molecular level will be important in the development of the next generation of
pharmaceutical agents that act as inhibitors or substrates.[5] Computer simulations can
examine these interactions at the molecular level and describe features important for
ADA–substrate and ADA–inhibitor recognition.[5–8] For example, molecular dynamics
and free energy simulations of coformycin and deoxycoformycin (two potent inhibitors
of adenosine deaminase) and their complexes with ADA can be used to obtain
structural and dynamic insights into the behavior of these molecules, which help to
understand the differences in the strength of binding of these inhibitors.[5] On the other
hand, performing the analysis of quantitative structure activity relationship (QSAR
analysis as a potent computational method) for several series of drugs, enzymes and
biologically active compounds is now well appreciated. The basic assumption of QSAR
is that there are some quantitative relationships between the microscopic (molecular
structure) and the macroscopic (empirical) properties (particularly biological activity)
of a molecule.[9] The term structure does not necessarily mean the spatial arrangement
of atoms in a molecule itself, but rather the chemical and physicochemical properties
inherent in that arrangement. In fact, the first logic confirming QSAR based predictions
is that the physicochemical properties of a chemical compound can be attributed to the
molecular structure via the mathematical functions. As such, we can write molecular
properties = f(structure). Most of the QSAR studies have frequently used empirical
parameters, i.e., lipophilicity (expressed by logarithm of partition coefficient or log P),
solubility, cavity surface area (CSA) and Hammetts constant.[10–13] But, it will be quite
meaningful to seek the other theoretical parameters, which may replace the common
experimental parameters. In the biological world, such empirical parameters may be
found through ascertaining some kinetic parameters of the enzymes (such as Km and
Ki) to elucidate the amount of enzyme’s affinity for binding to the substrate or
inhibitor molecules.

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QSAR Analysis for ADA
615
Our main objectives in the present study are to find some theoretical descriptors to
which the binding affinity of adenosine deaminase (ADA) for attachment of several
adenine nucleoside inhibitors is well correlated. Then, it would be possible to determine
those molecular characteristics, which are necessary for increasing the binding affinity
of the adenine nucleoside molecules to inhibit ADA.
MATERIALS AND METHODS
Materials
Adenosine deaminase from calf intestinal mucosa (type IV) and adenosine were
obtained from Sigma. Reagents were of analytical grade and buffer solutions were
made in double distilled water.
Methods
Enzyme Assay and Kinetic Analysis
Enzymatic activities were assayed on a Shimadzu UV-3100 spectrophotometer by
a measuring the rate of ADA-dependent decrease of adenosine absorption was
measured at 265 nm at 27°C using an extinction coefficient of 8.4 mMꢀ1 cmꢀ1. One
unit of ADA activity is defined as the amount of enzyme that produces 1 mole of
inosine per minute. Cuvettes of 1 cm path length were used. Assays were carried out in
50 mM sodium phosphate buffer, pH 7.5. Activities were measured over at least seven
different concentrations of adenosine and the assays were repeated at least three times.
Adenosine concentration range is between 0.5 to 3.5 Km. The concentration of enzyme
in the assay mixture was 1.0 nM. Km was determined by Lineweaver–Burk plots with a
fourth power weighting function using the enzyme kinetics (Trinity Software) program.
For measuring Ki using mixture of substrate and inhibitor prior addition of enzyme.
The quantity of Ki was ascertained regarding to the reciprocal plot of the apparent Km
values plotted against the different inhibitor concentrations.[14] Ki or Km were measured
for ADA in the presence of nucleosides R2–R10 in our laboratory.
Data Set and Computational Methods
Data set was made for the literature selected compounds. This set was divided into
two groups, the cyclic and acyclic nucleosides. QSAR analysis was performed on the
two cited groups regarding to the following steps: 1) entry of the molecular structures
into the adequate software to perform the structural optimization, 2) generation of the
molecular descriptors, 3) statistical analysis through the multiple linear regression
method (MLR), 4) defining of the model validation. In the first step, molecular
structure of each adenosine derivative was constructed in the Hyperchem-5.0 medium
and the three-dimensional optimized structure was generated using molecular modeling
calculations. The MOPAC-7.0 was also utilized to generate the final three-dimensional
coordinates. At the second step, quantum mechanical descriptors were generated using

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Moosavi-Movahedi et al.
the MOPAC program. These obtained numerical descriptors encode the structural
features (e.g. topological, geometrical, physicochemical and electronic properties) for
each adenosine derivatives. For example, geometrical descriptors (which were
calculated through the optimized Cartesian as well as van der Waals radii of each
participating atom in the molecule) encode valuable information about the three-
dimensional features (such as molecular size and shape) for the related molecules.
Electronic descriptors are another types of informative descriptors, which contained
partial atomic charge, electron density and dipole moment. In the third step, our main
goal was checking each descriptor to eliminate those descriptors which had not shown
any desirable correlation upper than R = 0.931. This selection of descriptors was
performed by MLR method based on the construction of a linear mathematical model
regarding to the observed binding affinities of the nucleosides (which has been
quantified by the Km and Ki values) with the numerical descriptors. The final linear
equation was formed by stepwise deletion of terms (backward procedure). In the fourth
step, model validation was defined through randomly dividing of the data-set into two
groups, a training set and a prediction set. The training set was used for model
Table 1. Quantitative values for the experimental (Km and Ki) and calculated parameters
(molecular volume, Vol; electronic charge around the N1 atom, ECN1, dipole moment of the
molecule, DIPM; the highest of positive charge on the molecule, HPOST).
Compound
log (Km or Ki) (mM)
Vol
ECN1
DIPM
HPOST
Ref.
R1
R2
1.9494
1.1139
0.5051
1.8921
1.9395
2.2148
2.2788
0.5051
1.3979
1.3222
1.1139
0.5051
2.2148
2.2788
ꢀ 0.7423
2.3424
1.8751
1.6532
2.1139
ꢀ 0.8539
1.0792
1.1471
1.5563
2.1461
708
986
1231
754
689
704
672
729
794
711
986
1231
704
672
843
824
896
966
705
1292
975
706
936
775
ꢀ0.2245
ꢀ0.2254
ꢀ0.2254
ꢀ0.2244
ꢀ0.2236
ꢀ0.2249
ꢀ0.2249
ꢀ0.2252
ꢀ0.2240
ꢀ0.2241
ꢀ0.2254
ꢀ0.2254
ꢀ0.2249
ꢀ0.2249
ꢀ0.2233
ꢀ0.2244
ꢀ0.2239
ꢀ0.2242
ꢀ0.2283
ꢀ0.2226
ꢀ0.2242
ꢀ0.2257
ꢀ0.2254
ꢀ0.2257
2.213
5.372
7.14
0.2001
0.4112
0.4381
0.2036
0.2057
0.2223
0.1990
0.1861
0.2170
0.2177
0.4112
0.4381
0.2223
0.1990
0.2149
1.3189
1.3227
1.3438
0.2378
0.4543
0.4130
0.1847
0.4455
0.3941
[22,23]
[19]
[20]
R3
R4
3.839
3.349
4.558
4.337
1.945
3.930
4.068
5.372
7.140
4.558
4.337
1.487
1.140
2.732
2.320
1.053
7.378
5.284
1.667
2.661
2.156
[18,19]
[20]
[18]
R5
R6
R7
R8
[19]
[22,23]
[22,23]
[22,23]
[21]
R9
R10
R11
R12
R13
R14
R15
R16
R17
R18
R19
R20
R21
R22
R23
R24
[21]
[20]
[20]
[21]
[20]
[20]
[20]
[20]
[20]
[20]
[20]
[20]
[20]
The R2–R10 compounds are synthesized in our lab or their kinetic parameters have been
ascertained directly by us. Kinetic information of the other compounds is obtained from
the literature.

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617
Scheme 1. Molecular structures of adenine derivatives.

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Moosavi-Movahedi et al.
Scheme 2. Molecular structures of adenine derivatives.
generation and prediction set used for evaluation of the model. Generally, the good
linear agreement between the predicted and experimental values can be used as an
adequate parameter for testing the validity of the model. It should be noted here that, in
our statistical analysis the total number of selected compounds is equal to 24. In the
literature, there are many QSAR reports in which a lower set of compounds is utilized
for statistical studies.[15–17] So, it can be deduced that here, an acceptable accuracy is
existed for the accomplished statistical work. In the QSAR analysis it has been
commonly accepted that the data set should be contained of five times as many
compounds as descriptors. The reason for this is that too few compounds relative to the
number of descriptors will give a falsely high correlation. This subject has been also
considered in our QSAR study.

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QSAR Analysis for ADA
619
Scheme 3. Molecular structures of adenine derivatives.
RESULTS AND DISCUSSION
To gain insight into the structure–activity relationship of the nucleoside
compounds, QSAR analysis has been performed through ascertaining of several
suitable descriptors that is followed by defining of any linear correlation between the
cited descriptors and the parameters of binding affinity for the enzyme. Thus, a number
of molecular descriptors have been primarily determined for a set of cyclic as well as
acyclic adenine–nucleoside derivatives. The interested common feature in some
nucleosides was the presence of adenine base as a consensus part of the molecules and
the availability of the kinetic parameters in the same environmental condition
(especially Km and Ki values) for the selected nucleosides among the interaction with
ADA. Fortunately, in the literature,[18–23] there were several adenine nucleosides which
their kinetic parameters were reported during their interactions with ADA at those
environmental conditions that is similar to the exerted conditions of our studies. Among

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Moosavi-Movahedi et al.
Table 2. Specification of the multiple linear regression model for cyclic and acylic nucleosides.
Descriptor
Coefficient
Mean effect
Dipole moment
Volume
1.869 ( 0.369)
ꢀ 15.557 ( 1.446)
ꢀ 0.560 ( 0.068)
13.165 ( 3.508)
0.893
43.298
1.973
The highest positive of charge
Charge of N1
Constant
55.743
106.421 ( 16.156)
R = 0.931; F = 34.302; n = the total number of nucleoside compounds (n = 24).
the total studied nucleosides, herein, the numerical information of R2–R10 are tabulated
in the first part of the Table 1 because all of these compounds were synthesized in our
laboratory or their kinetic parameters were obtained directly through our kinetic
investigations (see also Schemes 1–3). It should be mentioned that utilizing of the
Figure 1. The good linear correlation between the empirical values of Km or Ki and the related
values of the prediction set (r = 0.931). Inset: Symmetrical distribution of the residual values
confirming the goodness of the performed calculations.

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QSAR Analysis for ADA
621
kinetic parameters of Km and Ki as the quantified amounts for quantifying the
enzyme’s binding affinity is permissive because, these both parameters are dissociation
constants with the identical thermodynamic dimension of mole/liter. Interestingly,
regarding to the kinetic studies all of the selected nucleosides manifested the similar
type of inhibition which was the competitive inhibition. Therefore, it can be concluded
that the specific binding site for settling of the total nucleoside derivatives should be
the enzyme’s catalytic site.
In pharmacology ascertaining of the molecular properties of the chemical
compounds that is interfered with the molecular binding affinity is very important
because, the obtained data can be finally used for improving the general insight for
designing the new potent drug inhibitors to suppress the over activated enzymes. Here,
the QSAR analysis has revealed that binding affinity (BA) of the adenine nucleosides in
interaction with ADA depends on the molecular volume (Vol), dipole moment of the
molecule (Dipm), electric charge around the N1 atom (ECN1) and the highest of
positive charge (HPOST), see Eq. 1.
logðBAÞ ¼ ꢀ15:557 logðVolÞ þ 13:165ðECN1Þꢀ1 þ 1:69 logðDipmÞ
ꢀ0:560ðHPOSTÞꢀ1 þ 106:42
ð1Þ
Generally in the QSAR studies the algebraic sign before each term of the resulted
equation elucidates the essence of the existent correlation between each of the related
descriptor and the mathematical function, e.g. log(BA). For example when the algebraic
sign before the first term of Eq. 1 is negative it means that a negative correlation
between the molecular volume of the adenine nucleosides and the enzyme’s binding
affinity should be existed. Therefore, whatever the molecular volume of the adenine
nucleosides are largely growing the affinity for settling into the ADA catalytic site will
be decreased. Consequently, regarding to the cited logic, binding affinity of the adenine
nucleosides will be increased if the molecular volume as well as electric charge around
the N1 atom are both diminished. It should be mentioned here that log(BA) is related
with the reciprocal amounts of ECN1 so, the positive sign before the second term of
Eq. 1 shows the positive correlation of log(BA) with (ECN1)ꢀ1. Therefore, it can be
deduced that increasing of (ECN1)ꢀ1 (or decreasing of ECN1) will be followed by
increment of the enzyme’s affinity. Subsequently increment of dipole moment for the
adenine nucleosides will be resulted the increment of the binding affinity for the ADA
catalytic site. The highest of positive charge (HPOST) is the last descriptor which
shown acceptable linear correlation with log(BA) but, regarding to its delocalized
position in the molecular structure of the adenine nucleosides this descriptor is not an
informative parameter and is set aside in our presented discussion. If we want to
compare the degree of importance of the cited descriptors for evaluation of the
enzyme’s binding affinity it would be better to utilize the statistical factor of the mean
effect. Regarding to this valuable parameter the validity order of (Vol), (ECN1), (Dipm)
is distinguished (Table 2). Figure 1 shows the good linear correlation between the
empirical values of Km or Ki and the related values of the prediction set (r = 0.931).
The inset of the figure indicates the symmetrical distribution of the residual values
confirming the goodness of our performed calculations.
In conclusion, there is no doubt that N1 atom must contain the higher negative
charge density this was due to delocalization of electron (resonance effect) through the

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Moosavi-Movahedi et al.
electron demanding pyrimidine structure (see the following scheme). In state (I) the
electron is injected to highly electron-withdrawal pyrimidine ring which bring the
electrons on the N1 atom (state II). On the other hand, the sequence of electron motion
in this manner will bring electron to N3 (state III). The state II must have lower energy
with regard that it posses of minimum charge separation respect to the other allowed
representative states (states I or III). Here, using quantum mechanic calculations it has
been shown that for the optimized geometry related to the nucleoside structures there is
considerable electron density around the N1 atom (see Table 1). But, it is also
determined here that whenever the electronic charge around the N1 atom is decreased
then the binding affinity for the catalytic site of ADA will be increased. In fact,
regarding to the state III and the possibility for repletion of electron around the N3
atom (decrement of electron density around N1), establishment of hydrogen bond
between N3 and one of the free hydroxyl groups in the sugar moiety is probable. In this
manner, it can be deduced that however the strength of the established secondary
binding (hydrogen bond) is increased then formation of the state III as a suitable
enzyme-bound structure (with a low electron density around N1) will be more probable.
Evidently, in this structure (state III) the N1 atom is free and it can better interacted to
the enzyme’s surface.
ACKNOWLEDGMENT
Financial support of the Research Council of the University of Tehran is
gratefully appreciated.
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23. Khorshidi, A. Doctoral thesis; Faculty of Pharmacy, Isfahan University, Iran.
Received March 13, 2003
Accepted November 26, 2003

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