Discovery of novel and highly selective PI3Kδ inhibitors based on the p110δ crystal structure

In Silico Discovery of a Novel PI3Kδ Inhibitor Incorporating 3,5,7-Trihydroxychroman-4-one Targeting Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma, and it is highly aggressive and heterogeneous. Targeted therapy is still the main treatment method used in clinic due to its lower risk of side effects and personalized medication. Excessive activation of PI3Kδ in DLBCL leads to abnormal activation of the PI3K/Akt pathway, promoting the occurrence and development of DLBCL. The side effects of existing PI3Kδ inhibitors limit their clinical application. The discovery of PI3Kδ inhibitors with novel structures and minimal side effects is urgently needed. This study constructed a PI3Kδ inhibitor screening model to screen natural product libraries. Revealing the mechanism of natural product therapy for DLBCL through network pharmacology, kinase assays, and molecular dynamics. The results of molecular docking indicated that Silibinin had a high docking score and a good binding mode with PI3Kδ. The results of network pharmacology indicated that Silibinin could exert therapeutic effects on DLBCL by inhibiting PI3Kδ activity and affecting the PI3K/Akt pathway. The kinase assays indicated that Silibinin concentration dependently inhibited the activity of PI3Kδ. The results of molecular dynamics indicated that Silibinin could stably bind to PI3Kδ. Silibinin was a structurally novel 3,5,7-trihydroxychroman-4-one PI3Kδ inhibitor, providing valuable information for the subsequent discovery of PI3Kδ inhibitors.

Identification of Novel Src Inhibitors: Pharmacophore-Based Virtual Screening, Molecular Docking and Molecular Dynamics Simulations

Src plays a crucial role in many signaling pathways and contributes to a variety of cancers. Therefore, Src has long been considered an attractive drug target in oncology. However, the development of Src inhibitors with selectivity and novelty has been challenging. In the present study, pharmacophore-based virtual screening and molecular docking were carried out to identify potential Src inhibitors. A total of 891 molecules were obtained after pharmacophore-based virtual screening, and 10 molecules with high docking scores and strong interactions were selected as potential active molecules for further study. Absorption, distribution, metabolism, elimination and toxicity (ADMET) property evaluation was used to ascertain the drug-like properties of the obtained molecules. The proposed inhibitor–protein complexes were further subjected to molecular dynamics (MD) simulations involving root-mean-square deviation and root-mean-square fluctuation to explore the binding mode stability inside active pockets. Finally, two molecules (ZINC3214460 and ZINC1380384) were obtained as potential lead compounds against Src kinase. All these analyses provide a reference for the further development of novel Src inhibitors.