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Library design may be considered as the
initial step in a combinatorial chemistry experiment. Often,
the huge number of compounds which could theoretically comprise
the library is too large to be practically synthesisable. The
use of library subsetting may be of value to decrease the size
of the library to a more manageable number of compounds. One
approach to this technique is to subset the library on the basis
of a diversity function, thereby selecting a diverse subset of
molecules to be synthesised.
In order to describe the diversity of a
dataset, a number of molecular descriptors can be calculated.
The use of 1D descriptors, and 2D topological descriptors is
widespread. Recently, the use of 3D descriptors has been incorporated
into some studies, however, the additional benefits of these 3D
descriptors have yet to be quantified.
This study uses a dataset of around 70 compounds,
from 14 different activity classes. An ideal diversity selection
method should select one molecule from each activity class. Diversity
selection was conducted on the dataset on the basis of various
combinations of descriptors to determine the impact of the inclusion
of 3D descriptors on the selection of diverse molecules. Selections
were assessed on their coverage of the compound activity classes
within the dataset.