Human PDE4B blocking peptide

To identify amino acid residues involved in PDE3-selective inhibitor binding, we selected eight presumed interacting residues in the substrate-binding pocket of PDE3A using a model created on basis of homology to the PDE4B crystal structure. We changed the residues to alanine using site-directed mutagenesis technique, expressed the mutants in a baculovirus/ Sf9 cell system, and analyzed the kinetic characteristics of inhibition of the mutant enzymes by milrinone and cilostazol, specific inhibitors of PDE3. The mutants displayed differential sensitivity to the inhibitors. Mutants Y751A, D950A, and F1004A had reduced sensitivity to milrinone (K-i changed from 0.66 muM for the recombinant PDE3A to 7.5 to 156 muM for the mutants), and diminished sensitivity to cilostazol (K-i of the mutants were 18- to 371-fold higher than that of the recombinant PDE3A). In contrast, the mutants T844A, F972A and Q975A showed increased K-i for cilostazol but no difference for milrinone from the recombinant PDE3A. Molecular models show that the PDE3 inhibitors cilostazol and milrinone share some of common residues but interact with distinct residues at the active site, suggesting that selective inhibitors can be designed with flexible size against PDE3 active site. Our study implies that highly conserved residuals Y751, D950 and F1004 in the PDE families are key residues for binding of both substrate and inhibitors, and nonconserved T844 may be responsible for the cilostazol selectivity of PDE3A. Detailed knowledge of the structure of inhibitory sites should contribute to development of more potent and specific inhibitory drugs.

Pharmacophore modeling, molecular docking, and molecular dynamics (MD) simulation studies have been performed, to explore the putative binding modes of 2-phenylpyrimidine series as PDE4B selective inhibitors. A five point pharmacophore model was developed using 87 molecules having pIC(50) ranging from 8.52 to 5.07. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a high correlation coefficient (R-2=0.918), cross validation coefficient (Q(2)=0.852), and F value (175) at 4 component PLS factor. The external validation indicated that our QSAR model possessed high predictive power (R-2=0.70). The generated model was further validated by enrichment studies using the decoy test. To evaluate the effectiveness of docking protocol in flexible docking, we have selected crystallographic bound compound to validate our docking procedure as evident from root mean square deviation. A 10 ns molecular dynamics simulation confirmed the docking results of both stability of the 1XMU-ligand complex and the presumed active conformation. Further, similar orientation was observed between the superposition of the conformations of 85 after MD simulation and best XP-docking pose; MD simulation and 3D-QSAR pose; best XP-docking and 3D-QSAR poses. Outcomes of the present study provide insight in designing novel molecules with better PDE4B selective inhibitory activity. (C) 2016 Elsevier Ltd. All rights reserved.