Advanced Molecular Modeling Techniques Applied to Ion Channels Blockers - Ion Channels and Their Inhibitors - page 66

with known drug class warning, predicted of target activities of drug and specific
subset of clinical indication for which the drug may have been prescribed [ 88 ] such
as QT-prolonging drug [ 89 ], antidepressant [ 90 ], antiarrhythmic drugs [ 91 ], and
chloroquine groups [ 92 ]. The advantages of QSAR are that they can reduce research
time, cost and the numbers of animals required to study the properties and toxicity
of chemicals. QSAR is useful for assessing the properties of that are experimentally
very difficult to determine as well as being relatively easy to interpret, thereby
allowing the decomposition of the terms involved to allow the design and prediction
of novel chemicals. However, a disadvantage of all QSAR models are that an
accurate prediction may not be possible if there are not enough compounds in the
training datasets used to build the initial model. The advantages and disadvantages
of 2D- and 3D-QSAR studies have been critically analyzed by comparing statistics
[ 93 ]. For the prediction of the hERG-channel blockers affinities, 2D-QSAR seems
to be more robust than 3D-QSAR [ 94 ].

4.1 Principle of QSAR Methodology

The QSAR models have been widely used in the field of pharmaceutical chemistry,
toxicology, and agro chemistry. A QSAR is the mathematical model that describes
the relationship between structure and physical properties of chemical and its
activity. The general formula of QSAR model is shown in (2):

A or P ¼ f ð molecule structure Þ (2)

where A is Activity, P is Properties and f ( ) is a function, which depend on the
structure of chemical or molecular descriptors.
The QSAR technique has been described in the context of the development of
the model to predict hERG inhibition [ 85 ]. Fragment-based QSAR descriptor
methods such as support vector regression, partial least squares, and random forests
[ 95 ] have been used. The alignment of molecules and active conformation selection
were the successful 3D-QSAR model by CoMFA approach such as the develop-
ment of antiarrhythmic drugs, the blockade of the rapidly and slowly activating/
delayed rectifier K + currents has been specifically studied [ 91 ]. However, QSAR
analysis was successfully performed using the lipophilicity adjusted hERG
potency, pIC 50 hERG Log D , to identify moieties [ 96 ].

4.2 2D-QSAR of Ion Channels Blockers

We have reviewed two-dimensional quantitative structure-activity relationship
(2D-QSAR) models reported in the literature and discuss the nature of the models
and the descriptors involved. The descriptors for 2D-QSAR [ 97 ] can also be