Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 May 1;85(9):1297-305.
doi: 10.1016/j.bcp.2013.02.026. Epub 2013 Mar 5.

Chemical Informatics Uncovers a New Role for Moexipril as a Novel Inhibitor of cAMP phosphodiesterase-4 (PDE4)

Affiliations
Free PMC article

Chemical Informatics Uncovers a New Role for Moexipril as a Novel Inhibitor of cAMP phosphodiesterase-4 (PDE4)

Ryan T Cameron et al. Biochem Pharmacol. .
Free PMC article

Abstract

PDE4 is one of eleven known cyclic nucleotide phosphodiesterase families and plays a pivotal role in mediating hydrolytic degradation of the important cyclic nucleotide second messenger, cyclic 3'5' adenosine monophosphate (cAMP). PDE4 inhibitors are known to have anti-inflammatory properties, but their use in the clinic has been hampered by mechanism-associated side effects that limit maximally tolerated doses. In an attempt to initiate the development of better-tolerated PDE4 inhibitors we have surveyed existing approved drugs for PDE4-inhibitory activity. With this objective, we utilised a high-throughput computational approach that identified moexipril, a well tolerated and safe angiotensin-converting enzyme (ACE) inhibitor, as a PDE4 inhibitor. Experimentally we showed that moexipril and two structurally related analogues acted in the micro molar range to inhibit PDE4 activity. Employing a FRET-based biosensor constructed from the nucleotide binding domain of the type 1 exchange protein activated by cAMP, EPAC1, we demonstrated that moexipril markedly potentiated the ability of forskolin to increase intracellular cAMP levels. Finally, we demonstrated that the PDE4 inhibitory effect of moexipril is functionally able to induce phosphorylation of the small heat shock protein, Hsp20, by cAMP dependent protein kinase A. Our data suggest that moexipril is a bona fide PDE4 inhibitor that may provide the starting point for development of novel PDE4 inhibitors with an improved therapeutic window.

Figures

None
Fig. 1
Fig. 1
Established PDE4 inhibitors (26) and newly identified PDE4-inhibitory 3-carboxy-6,7-dimethoxytetrahydroisoquinoline compounds: moexipril (1a), 7 and 8.
Fig. 2
Fig. 2
Docked models of newly identified 3-carboxy-6,7-dimethoxytetrahydroisoquinoline inhibitors [moexipril (1a), 7 and 8] fitted to the PDE4 catalytic pocket and comparison with papaverine (4). (A)–(C) Best scoring poses for moexipril, 7 and 8 docked into the PDE4 zardaverine co-crystal structure (PDE4: 1MKD). (D) Structure of papaverine (cyan stick) bound to PDE4D core catalytic domain (PDB: 3IAK). (E) and (F) models of inhibitor 8 (green stick) fitted to the PDE4 papaverine co-crystal structure showing poses with alternative conformations for the tetrahydroisoquinoline core. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of the article.)
Fig. 3
Fig. 3
Determination of the efficacy of established and novel PDE4 inhibitors. Activities for each PDE4 subtype were related to a non-drug treated sample (100% control) over an increasing dose of the indicated compounds (n = 3). IC50 values were calculated using Graphpad Prism 4.0. (A) Dose response curves of moexipril against 3 different PDE4 isoforms. (B) Dose response curves of four different PDE4 inhibitors against PDE4B2. (C) Dose response curves of moexipril against PDE8A1 and PDE5.
Fig. 4
Fig. 4
Utilisation of a cAMP reporter construct to visualise changes in cAMP concentration triggered by PDE4 inhibitors. (A) Diagram illustrating mode of action of a FRET-based biosensor constructed from the nucleotide binding domain of the type 1 exchange protein activated by cAMP, EPAC1. (B) Changes in FRET ratio triggered by a 5 μM application of forskolin (FSK), followed by treatment with PDE4 inhibitors (i) rolipram (Roli), (ii) moexipril (Moex), (iii) compound 7 (Cmp 7), and (iv) compound 8 (Cmp 8). Data is from a single cell and is representative of experiments carried out at least n = 15. (C) Quantification of mean change in FRET ratio for all of the treatments including in lane 6 a saturating dose of forskolin (25 μM) plus the general PDE inhibitor 3-isobutyl-1-methylxanthine (IBMX 100 μM). All other lanes forskolin (FSK) applied at 5 μM. Significance evaluated using Student's t-test, ***p < 0.001 when compared with FSK alone. Number of individual experiments denoted by white numbers within grey bars.
Fig. 5
Fig. 5
PDE4 inhibitors induce PKA phosphorylation of the small heat-shock protein Hsp20. Lysates from SH-SY5Y cells were blotted for the expression of endogenous (A) PDE4D and (B) PDE4B enzymes. SH-SY5Y cells were treated with (C) rolipram (10 μM), (D) moexipril (50 μM), (E) compound 7 (50 μM) and (F) compound 8 (50 μM) for the indicated times. Cell lysates subjected to SDS page and western blotting. Blots were probed for phospho-serine 16 on Hsp20 and a loading control (tubulin). Quantification (n = 3) of the relative amounts of phosphorylation on serine 16 vs loading control were calculated following densitometry. Results are plotted as a percentage of the maximal phosphorylation over time. Significance evaluated using Student's t-test, *p < 0.05, **p < 0.01, ***p < 0.001. (G) SH-SY5Y cells were treated with KT5720 (4 μM) 20 min before the addition of a sub-optimal dose of forskolin (FSK, 10 μM) or forskolin (FSK, 10 μM) with moexipril (Moex, 50 μM) for 5 min. Lysates were blotted for tubulin or phospho-serine 16 on Hsp20. Data representative of n = 3.

Similar articles

See all similar articles

Cited by 3 articles

References

    1. Ashburn T.T., Thor K.B. Drug repositioning: identifying and developing new uses for existing drugs. Nat Rev Drug Discov. 2004;3:673–683. - PubMed
    1. Paul S.M., Mytelka D.S., Dunwiddie C.T., Persinger C.C., Munos B.H., Lindborg S.R. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat Rev Drug Discov. 2010;9:203–214. - PubMed
    1. Vasudevan S.R., Moore J.B., Schymura Y., Churchill G.C. Shape-based reprofiling of FDA-approved drugs for the H(1) histamine receptor. J Med Chem. 2012;55:7054–7060. - PubMed
    1. Hert J., Keiser M.J., Irwin J.J., Oprea T.I., Shoichet B.K. Quantifying the relationships among drug classes. J Chem Inf Model. 2008;48:755–765. - PMC - PubMed
    1. Keiser M.J., Setola V., Irwin J.J., Laggner C., Abbas A.I., Hufeisen S.J. Predicting new molecular targets for known drugs. Nature. 2009;462:175–181. - PMC - PubMed

Publication types

MeSH terms

LinkOut - more resources

Feedback