Background: PI3Kδ is predominantly expressed in hematopoietic cells and participates
in the activation of leukocytes. PI3Kδ inhibition is a promising approach for treating inflammatory
diseases and leukocyte malignancies. Accordingly, we decided to model PI3Kδ binding.
Methods: Seventeen PI3Kδ crystallographic complexes were used to extract 94 pharmacophore
models. QSAR modelling was subsequently used to select the superior pharmacophore(s) that best
explain bioactivity variation within a list of 79 diverse inhibitors (i.e., upon combination with other
Results: The best QSAR model (r2 = 0.71, r2
LOO = 0.70, r2
press against external testing list of 15
compounds = 0.80) included a single crystallographic pharmacophore of optimal explanatory
qualities. The resulting pharmacophore and QSAR model were used to screen the National Cancer
Institute (NCI) database for new PI3Kδ inhibitors. Two hits showed low micromolar IC50 values.
Conclusion: Crystallography-based pharmacophores were successfully combined with QSAR
analysis for the identification of novel PI3Kδ inhibitors.