Comparison of Large Chemical Spaces

Chemical
libraries are commonplace in computer-aided drug discovery, and assessing
their overlap/complementarity is a routine task. For this purpose,
different techniques are applied, ranging from exact matching to comparing
physicochemical properties. However, these techniques are applicable
only if the compound sets are not too big. Particularly for chemical
spaces, containing billions of compounds, alternative ways of assessment
are required. Random subsets could be enumerated and compared one-to-one,
but given the vast sizes of the chemical spaces assessed here, such
samples can at best provide a rough estimate of any overlap. Here
we describe a novel way to compare chemical spaces utilizing a panel
of query compounds. We applied this technique to three different types
of spaces and obtained insight into their structural overlap, their
coverage of the chemical universe, and their density. As chemical
feasibility of virtual compounds is particularly important, we included
related in silico predictions in our assessment.