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Introduction
Camptothecin (CPT) is an alkaloid isolated from the Chinese tree
Camptotheca acuminate (Figure 1) by Wall Me and
co-workers in 1966[1]. The molecule has a pentacyclic ring structure embodying pyrrolo[3,4-b]-quinoline moiety (rings A, B and
C), conjugated pyridone moiety (ring D) and a chiral centre within a 6 membered
a-hydroxy lactone (ring E). Although showing impressive activity in a number of experimental
tumors[2,3] including the human colon, lung and mammary tumor
lines, its clinical development was halted in the early 1970s owing to negligible water solubility and
unpredictable and formidable toxicities, such as myelo-suppression, diarrhoea and hemorrhagic
cystitis[4].
The renewed interest in CPT relies mainly on the
recognition of its novel and unique mechanism of action. It was
not until 1985[5] that the nuclear enzyme topoisomerase I
(TOP I) was identified as its molecular target reported by Liu
and co-workers. The enzyme has been implicated in various
DNA transactions such as replication, transcription and
recombination. CPT and its analogs bind to a complex formed
by DNA with the Top I enzyme, which inhibit tumor growth.
Because of the unique mechanism of action, the research
interests in CPT have become manifold and lead to the
production of several hundreds of synthetic and semi-synthetic
analogs to date. Now, 2 compounds in this class, topotecan
(hycamptin) and irinotecan (camptosar), have been approved
for clinical use as anticancer drugs in the United States by
the Food and Drug Administration (FDA). Topotecan is
presently indicated as a second-line therapy for advanced
ovarian cancer and small-cell lung cancer. Irinotecan is approved
for use in the treatment of advanced colorectal cancer, both
as first-line therapy in combination with 5-FU and as salvage
treatment in 5-FU refractory disease. There are more than 10
other CPT analogs in various stages of clinical
evaluation[6], including 9-AC, 9-NC, GI-147211, exatecan mesylate, and
karenitecin.
As a lot of CPT analogs have been synthesized and
evaluated, several 3D QSAR studies of CPT were reported
from laboratories[10,18,19] . Among them, Yoon and colleges
developed the QSAR model with CPT-11 and other prodrugs
with their hydrolysis percent of serum esterase activity to
design a new, easily activated SN-38
prodrug[18]. In two other
papers[10,19], the authors built the QSAR models with
little CPT dataset and few substitutes. Furthermore, due to
lack of crystal structure, they all align the compounds with
the partial least squares (PLS) fit, and have no detailed
interpretation of crystal structure. In this paper, in order to
further understand the inhibition mechanism of CPT and to guide
structural modification and rational drug design of CPT
analog, a 3D QSAR study of CPT analogs with larger dataset
using CoMFA was implemented. The final 3-D contour maps
were compared with the available X-ray crystal structure (PDB
entry 1K4T)[8] from the Protein Databank (PDB,
http://www.rcsb.org).
Materials and methods
Computational methods All computations are supported
by corresponding modeling suite in
SYBYL6.8[7], operated on a SGI Octane-2 graphic workstation (Mountain View, CA,
USA ).
Structure preparation The 53 compounds for this study
and their bioactive data are listed in Figures 2_6 and Tables
1_5. The potency data (IC50) was assessed by the minimum
concentration (mol/L) that inhibited the cleavable complex
formation by 50%.
Because the TOP I/DNA/topotecan ternary complex
(1K4T)[8] with CPT analog (topotecan) was resolved,
topotecan was selected as the starting structure; its starting
geometry was extracted from the available X-ray crystal
structure (PDB entry 1K4T)[8] from the PDB. After correcting the
atom type and bond type by using SYBYL6.8, it was
minimized with the TRIPOS force field after being charged with
the Gasteiger-Hückel charge . Then the prepared topotecan
was used as the template compound to construct other
molecules by modifying and assembling fragments from the
SYBYL standard library. Other molecules also constructed
were charged by the Gasteiger-Hückel charge and further
minimized by the minimize 2 module in SYBYL6.8. As for
CPT analog, 20S-isomer is much more potent than
20R form and is approximately twice as potent as the
20RS form, so only 20S-isomer CPT analogs with bioactivity were selected.
All structures remained 20S configurated after minimization.
Alignment rules The molecular alignment is another
critical factor in the CoMFA calculation. Based on the known
ternary complex, the docked structure was used for CoMFA
study after the above-mentioned compounds were
docked into the complex model using molecular simulation program
Dock4.0 (Department of Pharmaceutical Chemistry,
University of California, San Francisco, USA). The
enzyme/DNA/topotecan complex, 1K4T[8], was used to generate the
receptor site and the energetic grid for the following docking
calculations for molecule alignment. The docking procedure
was applied as follows: the sphere centers (a set of
overlapping spheres) of the topotecan binding site at a radius of 8 Å
were identified by the sphgen program; then a box was
created to enclose the spheres to be used for docking. Afterward,
the energetic grid was created by a grid program using an
all-atom model and a distance-dependent dielectric function with
a 10 Å cutoff; an anchor fragment orientation method was
performed subsequently, and 50 conformations were
produced per cycle. Finally, the dock energy score was used as
the scoring function in the docking runs. Only the best
scoring pose from each docking run was considered.
CoMFA[20] CoMFA interaction potential energy fields
were evaluated on a region (lattice) extending 4 Å in the X, Y
and Z axes beyond the volume defined by the union of all
molecules with a grid spacing of 2 Å. Standard CoMFA
steric and electrostatic fields were calculated using
distance-dependent dielectric constant with energy truncation
values of 30 kcal/mol. The minimum-sigma (column filtering)
was set to 2.0 kcal/mol to improve the signal-to-noise ratio
by omitting those lattice points whose energy variation was
below this threshold. PLS was carried out for compounds in
the training set, except 10 compounds randomly selected as
the test set, cross-validated with leave-one-out.
Results and discussion
The CoMFA model was constructed with 43 compounds
in the training set, which was validated by the remaining
molecules in the test set.
PLS model The PLS
technique[21_23] was employed to generate a linear relationship that correlates changes in the
computed steric and electrostatic potential fields with
changes in the corresponding experimental values of the
bioactivity (PIC50) for the data set of ligands. Employing the
CoMFA potential energy fields for each molecule as the independent variable and the corresponding
PIC50 values as the dependent variable, PLS converts the steric and
electrostatic field descriptors to so-called latent variables or
principle components (PC) that consist of linear combinations of
the original independent variables.
To assess the internal predictive ability of the CoMFA
models, we employed a `leave-one-out' cross-validation
procedure. In this procedure, each compound is excluded
one at a time, after which its bioactivity is predicted by the
model constructed from the remaining compounds in the data
set. Cross-validation determines the optimum number of PC,
corresponding to the smallest error of prediction and the
highest cross-validated q2 (or
r2cv). PLS analysis was
repeated without validation using the optimum number of PC
to generate a final CoMFA model from which the
conventional r2, a measure of the internal consistency of the model,
was derived. The result using this procedure is described as
follows.
After cross-validated PLS analysis was carried out for
the training set, the number of optimal PC at 6 was obtained
with cross-validated q2 of 0.495 (Table 6). The
non-cross-validated PLS analysis with the optimum PC revealed a
conventional r2 value of 0.935,
F=86.748, and an estimated standard error of 0.176. Furthermore, the obtained model showed
high predictability. As illustrated in Table 7, the predicted
values were very close to the observed values. Nine of 10
compounds in the test set were predicted well in terms of
activity, except compound 7. The predicted
r2 of 9 compounds was 0.58, which showed good correlation. So the
3D QSAR model is predictable, and results of the obtained
model are summarized in Tables 6 and 7.
The QSAR model also gave the relative electrostatic
contribution and relative steric contribution. In this model, the
steric contribution was much higher than the electrostatic
contribution in which the steric field descriptors explained
65.1% of the variance, while the electrostatic descriptors
explained 34.9%. These are in accordance with the
`drug-stacking' hypothesis.
Visualization of 3-D contour maps To visualize the
information content of the derived 3D QSAR models, CoMFA
contour maps were generated by interpolating the products
between the 3D QSAR coefficients and their associated
standard deviations. The green contours represented the
regions of high steric tolerance, while the yellow contours
represented regions of unfavorable steric effects. The blue
contours described regions where a positively charged group
enhanced activity, while the red contours described regions
where a negatively charged group enhanced activity. To aid
in visualization, topotecan was displayed in the maps. 3-D
contours were mostly found around 7, 9, 10, and 11
positions of CPT analogs, because most substituents of CPT
analogs are focused on this position. However, there was a
contour at the southeast region in Figure 7A, where there
was no substituent near the 14-position. Because of
docking CPT analogs into complexes according to the alignment
rule, the compounds with methylenedioxy and
enthylene-dioxy substituents with high activity rotated a little to right
down. It seemed that there was a substitute in the vicinity of
the 14-position. So it is an artifact in which more bulky
substituents in the 14-position will improve activity. The steric
CoMFA map (Figure 7 A) illustrates a favorable region of
steric interaction at the 10 and 11 positions, but much more
bulky substitutes will decrease
activity[15]. The compounds with methylenedioxy and enthylenedioxy substituents
(compounds 32_52) exhibit considerable increase of activity,
while compounds 3, 8 and 21 decrease their activity. At the
same time, there is another favorable steric region at the
7-position, indicating that more bulky substituents are needed
in this position to improve the inhibitive activity, which is
consistent with the fact that silyl-substituted compounds
display more strong potency[14]. The prediction is confirmed
by the molecular surface of the binding pocket which is big
enough to accommodate more bulky substituents which will
conflict with Lys425 if they are too large. More negative
substituents will increase inhibitive activity at positions 9,
10, and 11, which is in agreement with previous
observations[9,10,16]. It is also in agreement with the mapped
enzyme/DNA/topotecan complex because positively-charged residue
Lys425 is in the direction of positions 9 and 10. The
hydrogen bond between 10-hydroxyl of topotecan and a water
molecule[8] also contributed to the negative contour map.
Furthermore, CPT analogues were stacked into base pairs,
like C112 (Figure 7B) and A113 (not shown in Figure for
clarity) and other base pairs (not shown) in this ternary
complex, which might show slight positive charge. In
addition, more positive substituents at position 7 would
strengthen the binding of the inhibitors to top the I-DNA
complex, so alkyl-substitutes at position 7 possess
considerable activity, and silyl-substitutes show more inhibitive
activity[14], which should be correlative with the hydroxyl of
base T10. There is a green contour on the left because of the
negative charged phosphodiester. The CoMFA contour
maps are illustrated in Figure 7.
Furthermore, the steric interaction at positions 7, 9, 10,
and 11 can be interpreted using the enzyme/DNA/topotecan
ternary complex with CPT analogs
(topotecan)[8] in Figure 8. The topotecan molecule is oriented with the E ring near the
DNA break, and the concave portion of the drug molecule
faces the DNA major groove[17]. The structural model
demonstrates that 7, 9, 10, and 11 positions face the major groove
of the DNA, and the substituents on these positions point
toward the sugar backbone. So the model suggests that
electron-rich groups of moderate or large size would be
favored for these positions.
Conclusion
A study on the quantitative structure_activity
relationship with CoMFA for a series of CPT analogs was performed
successfully, and a good cross-validated correlation was
obtained with q2 of 0.495. Then the PLS model
non-cross-validated was built and permitted demonstrations of high
predictability for the activities of the CPT analogs in the test
set selected randomly. The CoMFA contour maps illustrated
that more negative-charged large group at positions 9, 10,
and 11 would increase activity, but excessively increasing
the bulky group at position 10 would decrease activity;
substituents that occupy position 7 with the bulky
positively-charged group will enhance inhibitive activity.
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