Chemical-Space-Based de Novo Design Method To Generate Drug-Like Molecules

To discover drug
compounds in chemical space containing an enormous
number of compounds, a structure generator is required to produce
virtual drug-like chemical structures. The de novo design algorithm
for exploring chemical space (DAECS) visualizes the activity distribution
on a two-dimensional plane corresponding to chemical space and generates
structures in a target area on a plane selected by the user. In this
study, we modify the DAECS to enable the user to select a target area
to consider properties other than activity and improve the diversity
of the generated structures by visualizing the drug-likeness distribution
and the activity distribution, generating structures by substructure-based
structural changes, including addition, deletion, and substitution
of substructures, as well as the slight structural changes used in
the DAECS. Through case studies using ligand data for the human adrenergic
alpha2A receptor and the human histamine H1 receptor, the modified
DAECS can generate high diversity drug-like structures, and the usefulness
of the modification of the DAECS is verified.