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This research aims to develop and evaluate novel thienopyrimidine PI3Kδ inhibitors for DLBCL using computational methods.

Computational Design and Evaluation of Novel Thienopyrimidine PI3Kδ Inhibitors for Diffuse Large B-Cell Lymphoma: QSAR, Docking, Molecular Dynamics, and Density Functional Theory Studies

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This research aims to develop and evaluate novel thienopyrimidine PI3Kδ inhibitors for DLBCL using computational methods.
Utilized a curated dataset of thienopyrimidine derivatives with pIC₅₀ values.
Developed a QSAR model through multiple linear regression and genetic algorithms.
Conducted molecular docking and molecular dynamics simulations to assess inhibitor stability.
Performed ADMET profiling and MM-GBSA binding free-energy estimation.
Applied DFT calculations for electronic stability analysis.
The QSAR model showed strong internal and external validation with R² values indicating predictive reliability.
Compound 14D3 demonstrated the highest predicted activity with pIC₅₀ of 8.387 and strong docking affinity.
Molecular dynamics simulations confirmed stable binding and interactions at the PI3Kδ active site.
Density functional theory provided insights into the stability of the optimized compound relative to copanlisib.

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Computational methods identify potent PI3Kδ inhibitors in diffuse large B-cell lymphoma, suggesting effective drug development strategies.

Isah et al. (2026) studied this question.

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Computational methods identify potent PI3Kδ inhibitors in diffuse large B-cell lymphoma, suggesting effective drug development strategies.