AI Article Synopsis
- PI3Kδ, mostly found in immune cells, plays a key role in activating leukocytes and is targeted for treatments of inflammatory diseases and blood cancers.
- The study analyzed 17 crystallographic complexes to create 94 pharmacophore models, using QSAR modeling to identify the best predictors of bioactivity from a diverse set of 79 inhibitors.
- The top QSAR model demonstrated strong predictive capabilities and was used to search the NCI database, which led to the identification of two potential new PI3Kδ inhibitors with promising activity.
Article Abstract
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 physicochemical descriptors).
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.
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| http://dx.doi.org/10.2174/1573406415666190222125333 | DOI Listing |
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