Abstract
![]()
RNA is an emerging
target for drug discovery. However, like for
proteins, not all RNA binding sites are equally suited to be addressed
with conventional drug-like ligands. To this end, we have developed
the structure-based druggability predictor DrugPred_RNA to identify
druggable RNA binding sites. Due to the paucity of annotated RNA binding
sites, the predictor was trained on protein pockets, albeit using
only descriptors that can be calculated for both RNA and protein binding
sites. DrugPred_RNA performed well in discriminating druggable from
less druggable binding sites for the protein set and delivered predictions
for selected RNA binding sites that agreed with manual assignment.
In addition, most drug-like ligands contained in an RNA test set were
found in pockets predicted to be druggable, further adding confidence
to the performance of DrugPred_RNA. The method is robust against conformational
and sequence changes in the binding sites and can contribute to direct
drug discovery efforts for RNA targets.
Collapse