Luyang Shi and Hongzong Si* Pages 1 - 19 ( 19 )
Background: Recent studies have found that Phosphodiesterase-4 (PDE4) is closely related to the pathogenesis of depression, cognitive impairment and neurological impairment.
Objective: Our objective is to develop potent inhibitors of the high-affinity phosphodiesterase 4D isoform (PDE4D) that can serve as radioligands for Positron Emission Tomography (PET) imaging, thereby advancing research in the field of neurological diseases.
Methods: We employed a multi-step approach combining three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, molecular docking, classification techniques, and CoMSIA analysis to investigate the conformational relationship of highaffinity PDE4D inhibitors as PET ligands. ADMET and Drug-likeness predictions were also conducted. By utilizing these methods, our aim was to identify more potent PDE4D inhibitors.
Results: The results showed that the CoMSIA model with the best principal component scores (n=7) had a cross-validated Q2 value of 0.602 and a non-cross-validated R2 value of 0.976. These results affirmed the excellent predictive capability of the established CoMSIA model. Analysis of the generated 3D-QSAR contour plots highlighted specific regions in the molecular structure of the compounds that can be further optimized and modified. Guided by the contour plots, we designed 100 novel PDE4D inhibitors, and molecular docking was performed for the top 4 compounds with high activity. The molecular docking scores were promising, and ADMET and drug similarity predictions yielded satisfactory results. Taking into consideration these factors, compound 51c was determined to be the optimal compound, laying a solid foundation for further research.
Conclusion: For the continued development of PDE4D PET radioligand, these models and new compounds' developing methodology offer a theoretical foundation and crucial references.
3D-QSAR, CoMSIA, molecular docking, phosphodiesterase-4D (PDE4D) inhibitor, radioligand, PET, ADMET.