Topliss Decision Tree Method.This method is quicker and easier to use than the
Hansch method. The Topliss schemeis an empirical method in which each compound
is tested before an analog is planned, and is compared in terms of its physical proper-
ties with analogs already planned. Like the Free–Wilson method, the Topliss decision
tree is no longer extensively used. The 2D- and 3D-QSAR methods are gradually sup-
planting the 1D methods.
3.4.2.2 2D-QSAR — Pattern Recognition Analysis
2D-QSAR is a somewhat more advanced method for correlating activity and struc-
ture. The first step in performing a 2D-QSAR is to select the training set. This is a
subset of molecules that are diverse in terms of both structure and bioactivity. Ideally,
the compounds that are available cover the full spectrum of bioactivity, ranging from
active (fully and partially, covering a 10^3 -fold range in receptor binding affinities) to
inactive. It is difficult to determine what makes a molecule bioactive (or conversely
what makes a molecule bioinactive) if all of the compounds tested have similar bioac-
tivities. The more molecules the better, but a reasonable start can be made with as
few as ten compounds. It is important not to use all available molecules, since
another subset is held back and retained as a test set.This test set will ultimately be
used to validate any prediction algorithm that is developed through the study of the
training set.
Next, every molecule in the training set, regardless of its pharmacological activity, is
characterized by a series of descriptors:
- Geometric descriptors
Bond lengths
Bond angles
Torsional angles
Interatomic distances - Electronic descriptors
Charge densities on individual atoms
Energy of the highest occupied molecular orbital
Energy of the lowest unoccupied molecular orbital
Molecular dipole - Topological descriptors
Graph theory indices
Randic indices
Kier–Hall indices
Ad hoc indices
Number of rings in the molecule
Number of aromatic rings in the molecule - Physicochemical descriptors
Octanol–water partition coefficients
LogP
(LogP)^2
Hydrogen bonding number
Number of hydrogen bonding donor sites
Number of hydrogen bonding acceptor sites
DESIGNING DRUG MOLECULES TO FIT RECEPTORS 143