Biomedical Engineering Reference
In-Depth Information
or protonation states [
101
]. The resultant 4D-QSAR models can be graphically
displayed and used to virtually screen libraries of compounds [
102
]. 4D-QSAR
methods were shown to perform better than CoMSIA and CoMFA in the past [
103
]
because the CoMFA and CoMSIA models do not generalize beyond the molecules in
the training set. This study was done to explore the relationships of molecular level
physicochemical properties to in vivo antiarrhythmic activity [
104
]. These results
suggested that the log
P
descriptor was of particular importance in the 4D-QSAR
model, which was developed on a set of analogs ability to displace adsorbed Ca
2+
ions.
5 ADMET Prediction of Ion Channels Blockers
Absorption, Distribution, Metabolism, Excretion and Toxicity is an acronym for
key biological properties in the fields of pharmacokinetics, pharmacodynamics and
pharmacology. An understanding of the relationships between important ADMET
parameters and molecular structure and properties has been used to develop in silico
models [
105
,
106
]. This includes issues such as high plasma protein binding
requiring extra studies for FDA approval [
107
]. The Meta-Drug system represents
a prototype for integrative or ADMET systems that builds on the database- and
network-building tools such as MetaCore [
108
,
109
]. Studies reported the use of
Gaussian process methods for the prediction of ADMET properties associated with
the
human ether-a-go-go
related gene (hERG) channel inhibition [
110
].
The accumulated data make it possible to construct models for predicting the
ADMET properties of compounds before structural modifications are made [
111
].
ADMET modeling was used to derive a quantitative relationship between channel
blockers and physicochemical properties [
112
]. The computational models based
on antiarrhythmics could have helped prevent some companies from selecting
noncardiovascular drugs with hERG inhibitory activity [
113
] and is a cheaper
alternative approach to in vitro and in vivo testing [
114
].
Thermodynamic descriptors describe the important features associated with
hERG potassium channel blockers are hydrophobic groups, the number of aromatic
rings and hydrogen bond acceptor [
110
]. Others also suggest that hERG inhibition
increases with increasing molecular weight, log
P
, or both, with ionization state
playing a beneficial or detrimental affect depending on the parameter in question
[
107
]. Oprea et al. (2004) expected advances in this area, as more tailored ADMET
prediction software that gives proper treatment to charge functional groups will
yield improved predictivity [
115
]. An understanding of the profile of drug metabo-
lism has increasingly become an important consideration in early stages of drug
development and the profound effect of metabolism has been important drug
properties as metabolic stability, toxicity, and drug-drug interactions [
116
]. Simi-
larly, the prediction of molecules hERG channel activity is becoming increasingly
important in the drug discovery process because blockade of the hERG channel
may lead to life-threatening cardiac arrhythmias [
117
]. To identify ADMET
properties, data relating to molecular structures tested in animal or human tissues
in vitro or in vivo [
103
].
