Integrated molecular modeling techniques to reveal selective mechanisms of inhibitors to PI3Kδ with marketed Idelalisib

Abstract

Phosphatidylinositol‐3‐kinase (PI3K) is important for cell proliferation, differentiation, and apoptosis, and the diverse physiological roles of different PI3K isoforms have highlighted the significance of the development of PI3Kδ inhibitors. A large number of PI3Kδ inhibitors have been reported after the FDA approval of Idelalisib, but the clinical use of Idelalisib was limited because of its serious side effects. Therefore, great efforts have been made on the development of PI3Kδ inhibitors with higher selectivity and lower toxicity, but there is no new PI3Kδ inhibitor coming into the market so far. Even so, as the first listed PI3K inhibitor, Idelalisib could be used as an effective tool to investigate the selective inhibition mechanism of PI3Kδ. Thus, in this study, a modeling strategy integrated 3D‐QSAR, pharmacophore model, and molecular dynamics simulation was employed to reveal the key chemical characteristics of Idelalisib analogs and the binding pattern between the inhibitors and PI3Kδ. First, the CoMFA model with high statistical significance was built to reveal the general structure–activity relationships. And then, a reliable pharmacophore model with a robust discrimination capability was constructed to expound the main chemical characteristics of the PI3Kδ inhibitors. Finally, molecular dynamics simulation was conducted to explore the binding modes and some key residues refer to δ‐selective binding were highlighted with binding‐free energy calculation. In summary, these models and results would provide some effective help for the discovery or the rational design of novel PI3Kδ inhibitors.

Molecular docking, 3D-QASR and molecular dynamics simulations of benzimidazole Pin1 inhibitors

“…Then, the best principal component N value was used in the non-cross validation analysis in order to calculate the non-cross validation correlation coefficients ( r ncv 2 ), standard deviation (SEE) and F -test values of the model as well as the energy contribution of each force field to the model, 32 which are parameters that allow for the evaluation of the model's fitting ability. q 2 is not necessary to evaluate the goodness of 3D-QSAR models.…”