SCUBIDOO: A Large yet Screenable and Easily Searchable Database of Computationally Created Chemical Compounds Optimized toward High Likelihood of Synthetic Tractability

De novo drug design
is widely assisted by computational approaches
that enable the generation of a tremendous amount of new virtual molecules
within a short time frame. While the novelty of the computationally
generated compounds can easily be assessed, such approaches often
neglect the synthetic feasibility of the molecules, thus creating
a potential hurdle that can be a barrier to further investigation.
Therefore, we have developed SCUBIDOO, a freely accessible database
concept that currently holds 21 million virtual products originating
from a small library of building blocks and a collection of robust
organic reactions. This large data set was reduced to three representative
and computationally tractable samples denoted as S, M, and L, containing
9994, 99 977, and 999 794 products, respectively. These
small sets are useful as starting points for ligand identification
and optimization projects. The generated products come with synthesis
instructions and alerts of possible side reactions, and we show that
they exhibit drug-like properties while still extending into unexplored
quadrants of chemical space, thus suggesting novelty. We show multiple
examples that demonstrate how SCUBIDOO can facilitate the search around
initial hits. This database might be a useful idea generator for early
ligand discovery projects since it allows a focus on those molecules
that are likely to be synthetically feasible and can therefore be
studied further. Together with its modular building block construction
principle, this database is also suitable for structure–activity
relationship studies or fragment-growing strategies.