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Updated: May 9, 2026

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
Published on: April 3, 2026
From IPI-549 to Novel Compounds: A Novel Strategy Integrating 3D-QSAR, Scaffold Growth, Molecular Docking, and
Jingyu Zhu1, Xiaolian Yu1, Lei Jia1
1School of Life Sciences and Health Engineering, Jiangnan University, Wuxi, Jiangsu, 214122, China.
Introduction:
Phosphoinositide-3-kinase gamma (PI3Kγ) has emerged as a valuable therapeutic target for various diseases. However, there is a notable scarcity of inhibitors that have advanced to clinical studies, highlighting the urgent need for the development of novel PI3Kγ inhibitors.
Methods:
A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was conducted to investigate the structure-activity relationships of PI3Kγ inhibitors. A scaffold growth strategy was employed to design novel compounds. Furthermore, a virtual screening workflow integrating drug-likeness filtering, 3D-QSAR predictions, and molecular docking was established.
Results:
An optimal CoMFA model was developed with q² = 0.752, r² = 0.995, and r²pred = 0.736, revealing key structural features and interactions crucial for selective PI3Kγ inhibition. Using the N-phenyl isoquinolinone core of IPI-549 as a template, new compounds were generated via a reaction-based scaffold growth approach. Following drug-likeness evaluation, 3DQSAR predictions, and molecular docking, nine compounds demonstrated superior predicted activity compared to IPI-549. Three top-ranked hits were subsequently subjected to molecular dynamics simulations and binding free energy calculations, providing insights into the PI3Kγ/Hit binding mechanism and identifying critical residues governing selectivity, including MET804, TRP812, ILE831, VAL882, and MET953.
Discussion:
Developing selective PI3Kγ inhibitors is challenging due to the high homology among kinase structures. IPI-549, the first PI3Kγ inhibitor to enter clinical trials, served as a suitable template for designing novel selective inhibitors. This study applied computer-aided drug design strategies to formulate promising new PI3Kγ inhibitors.
Conclusion:
The present workflow provides an effective and precise approach for identifying novel PI3Kγ inhibitors and offers valuable guidance for the rational design of selective PI3Kγ- targeted therapeutics.
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