Biomedical Engineering Reference
In-Depth Information
In summary, the pharmacophore models suggest that the hERG blockers
are characterized by the presence of a protonated nitrogen linked with two or three
hydrophobic and/or aromatic moieties. The only exception is the pharmacophore
model obtained by Aronov et al., which was generated solely by uncharged
molecules. This indicated that the development of uncharged compounds is not a
safe way to avoid unwanted inhibition of the hERG channel. The charged nitrogen
atom, the hydrophobic and the aromatic features might interact with the amino acids
Tyr652 and Phe656. Some pharmacophore models suggest also that hydrogen-bond
donor and/or acceptor groups might play an important role for hERG inhibition,
probably by interaction with Thr623, Ser624, or Ser649.
4.2
3D-QSAR
The first 3D-QSAR model for prediction of hERG blockers was developed by Ekins
et al. [
29
] through the analysis of 15 molecules with Catalyst. These compounds are
characterized by the presence of one ionizable feature and four hydrophobic
moieties. The pharmacophore shows the presence of one ionizable feature
surrounded by four hydrophobic features. The 3D-QSAR model shows a high
correlation with an
r
2
of 0.90, and also a good performance in the prediction of
the activity of the external test set, with an
r
2
of 0.83. The ability of the model to
correctly rank the hERG blockers according to their IC
50
values achieved a
Spearman's rank coefficient of 0.76 and 0.77 for the training and the test set,
respectively. The excellent performance of the model for both qualitative prediction
and quantitative ranking of hERG inhibitors indicates that it is a suitable tool to
discover potential hERG blockers.
Cavalli et al. [
30
] developed a 3D-QSAR model through the analysis of 31
hERG blockers using the CoMFA technique. For most of the molecules, the 3D
structure was retrieved from the Cambridge Structural Database (CSD) or by
adding substituents to the crystallographic structure. Three-dimensional structures
of additional molecules were generated with SYBYL. The alignment of the
molecules was performed using the previously generated pharmacophore. The
model shows a good predictive performance with
r
2
0.95 and
q
2
0.74. In a
further validation using a test set of compounds not involved in the model genera-
tion, an
r
2
of 0.74 was achieved. The comparison of the pharmacophore and the
CoMFA models shows that the pharmacophoric features C1 and C2 are sterically
favorable regions, while C0 is influenced by the steric and electrostatic properties of
the compounds. In particular an increased volume in C0 will decrease the activity,
while an opposite effect is predicted for charged groups.
Through the application of the CoMSiA technique, 22 sertindole analogues and
a set of 10 structurally different hERG blockers were analyzed by Pearlstein et al.
[
21
]. The best model reached a
q
2
of 0.571. Docking studies performed in a
homology model of the hERG channel
¼
¼
in the open state could explain the
pharmacophore and the CoMSiA models.
