Image_1_Pharmacogenetic Aspects of the Interaction of AT1 Receptor Antagonists With ATP-Binding Cassette Transporter ABCG2.PDF

<p>The ATP-binding cassette transporter ABCG2 (BCRP and MXR) is involved in the absorption, distribution, and elimination of numerous drugs. Thus, drugs that are able to reduce the activity of ABCG2, e.g., antihypertensive AT1 receptor antagonists (ARBs), may cause drug-drug interactions and compromise drug safety and efficacy. In addition, genetic variability within the ABCG2 gene may influence the ability of the transporter to interact with ARBs. Thus, the aim of this study was to characterize the ARB-ABCG2 interaction in the light of naturally occurring variations (F489L, R482G) or amino acid substitutions with in silico-predicted relevance for the ARB-ABCG2 interaction (Y469A; M483F; Y570A). For this purpose, ABCG2 variants were expressed in HEK293 cells and the impact of ARBs on ABCG2 activity was studied in vitro using the pheophorbide A (PhA) efflux assay. First, we demonstrated that both the F489L and the Y469A substitution, respectively, reduced ABCG2 protein levels in these cells. Moreover, both substitutions enhanced the inhibitory effect of candesartan cilexetil, irbesartan, losartan, and telmisartan on ABCG2-mediated PhA efflux, whereas the R482G substitution blunted the inhibitory effect of candesartan cilexetil and telmisartan in this regard. In contrast, the ARB-ABCG2 interaction was not altered in cells expressing either the M483F or the Y570A variant, respectively. In conclusion, our data indicate that the third transmembrane helix and adjacent regions of ABCG2 may be of major importance for the interaction of ARBs with the ABC transporter. Moreover, we conclude from our data that individuals carrying the F489L polymorphism may be at increased risk of developing ABCG2-related drug-drug interactions in multi-drug regimens involving ARBs.</p

Inhibition of SEPT4 and tau phosphorylation by DYRK1A.

<p><b>A</b>, HeLa cells transiently expressing FLAG-SEPT4 were treated with AnnH31 or AnnH75 for 5 h before cells were lysed and analysed by immunoblotting with a FLAG-tag antibody. 5-iodotubercidin (IoT) served as positive control. Relative SEPT4 phosphorylation was calculated as the ratio of the intensities of the phosphorylated upper band and the lower band. <b>B</b>, HEK293 cells with constitutive expression of GFP-tau and regulatable expression of GFP-DYRK1A were treated with doxycyclin and the indicated inhibitors for 18 h. Phosphorylation of tau on Thr212 was detected with a phosphospecific antibody. Expression levels of GFP-tau and GFP-DYRK1A were assessed with a GFP antibody. For quantitative evaluation of DYRK1A inhibition, the basal pT212 signal in control cells not treated with doxycyclin (Ctrl) was subtracted from all values. <b>C</b>, Quantitative evaluation of three experiments each for SEPT4 and tau. All data were standardized to the level of phosphorylation in cells untreated with inhibitors. Error bars indicate SEM.</p

Selectivity profile of AnnH75.

<p>AnnH75 was profiled at a concentration of 1 μM against a panel of 300 protein kinases (see Table A in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132453#pone.0132453.s001" target="_blank">S1 File</a> for the complete results). <b>A</b>, Target kinases inhibited by more than 50% are indicated. The kinome dendrogram was adapted and is reproduced courtesy of Cell Signaling Technology. <b>B</b>, Calculation of the Gini coefficient as a measure of kinase selectivity. The Lorenz curve illustrates the degree to which the total inhibitory activity of a compound (i.e. the sum of inhibition of all tested kinases) is equally distributed among all tested kinases (bisector line, Gini coefficient of 0) or directed towards a single kinase (maximal selectivity, a Gini coefficient of 1).</p

Analysis of kinase inhibitor interactions.

<p><b>A-D</b>, Predicted binding modes of AnnH75 at DYRK1A and related kinases. The inhibitor is colored cyan and kinases are depicted as ribbon structures. Only relevant amino acid residues in the ATP binding pocket are shown for clarity. In B-D, residues different from DYRK1A are colored green and labeled. The distances of the two hydrogen bonds (red line) and the distance between the cyano group and the glycine of the P-loop (G166 in DYRK1A) are given in Angstrom. (DYRK1A, PDB ID 3ANR; DYRK2 PDB ID 4AZF; HIPK2, homology model, CLK1, PDB ID 2VAG). <b>E</b>, Comparison of amino acid residues relevant for AnnH75 binding. In the left, the relationship of the kinases is illustrated by the sequence identity of their catalytic domains. Residues generally conserved in protein kinases (G166, K188, D307) and the gatekeeper residue (F238) are highlighted by bold print. Residues different from DYRK1A are shown with their position in the sequence. Differences correlating with kinase resistance to AnnH75 are highlighted in red.</p

AnnH75 inhibits both threonine and tyrosine kinase activity of DYRK1A.

<p>A DYRK1A construct with an N-terminal StrepTag 2 (ST2-DYRK1Acat) was expressed in a cell-free <i>E</i>. <i>coli</i>-derived expression system. Coupled <i>in vitro</i> transcription and translation reactions were incubated for 1 h in the presence of recombinant SF3B1-NT-His₆ and AnnH75. Phosphorylation of tyrosines in DYRK1A and of Thr434 in SF3B1 was determined by immunoblotting with a phosphotyrosine-specific antibody (pTyr) and a pThr434-specific antibody. <b>A</b>, Representative western blots. The asterisks mark unidentified bands. <b>B</b>, Quantitative evaluation. Results were normalized to the total amount of DYRK1A or SF3B1, respectively, and are plotted relative to the phosphorylation in the untreated control samples (means +/- SEM, n = 3).</p

Inhibition of SF3B1 phosphorylation by DYRK1A in HeLa cells.

<p>HeLa cells expressing GFP-SF3B1-NT were treated with the indicated compounds for 18 h. The phosphorylation state of SF3B1 was determined by immunoblotting with pT434 antibody, and the results were normalized to the total amount of SF3B1 immunoreactivity. <b>A</b>, Representative western blots. AnnH79 is a harmine analogue that does not inhibit DYRK1A and was used as negative control. The vertical line indicates where irrelevant lanes were deleted from the final image. <b>B,</b> The column diagram summarizes the quantitative evaluation of 3–6 experiments for each compound (means + SD).</p

Kinome selectivity of AnnH75 and published DYRK1A inhibitors.^a

<p>^a Structures are shown in Fig. D in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132453#pone.0132453.s001" target="_blank">S1 File</a>.</p><p>^b IC₅₀ values are given because %-activity values are not given in the reference.</p><p>^c IC₅₀ value taken from Cuny et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132453#pone.0132453.ref038" target="_blank">38</a>]</p><p>Kinome selectivity of AnnH75 and published DYRK1A inhibitors.<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132453#t002fn001" target="_blank">^a</a></p

Inhibition of DYRK1A and related kinases by selected β-carbolines.

<p>Kinase activities are given as the means of at least 3 measurements in the presence of 1 μM of the compounds (10 μM in HIPK2 assays) and are expressed as the percentage of the uninhibited control (Kinase-GLO assay). 5-iodotubercidin (IoT) served as a structurally unrelated control compound that inhibits all tested kinases.</p

Application of Docking and QM/MM-GBSA Rescoring to Screen for Novel Myt1 Kinase Inhibitors

Identification of compounds that can bind to a target protein with high affinity is a nontrivial task in structure-based drug design. Several approaches ranging from simple scoring methods to more computationally demanding methods are usually applied for this purpose. In the current work, we used ligand docking in combination with QM/MM-GBSA, MM-GBSA, and MM-PBSA rescoring to discriminate between active and inactive Myt1 kinase inhibitors. Results show that QM/MM-GBSA rescoring performs better than normal docking scores or MM-GBSA rescoring in classifying active and inactive inhibitors. We also applied QM/MM-GBSA rescoring to estimate the binding affinities of compounds from different virtual screening runs. To prove our approach and to confirm its predictive power, a few compounds which were predicted to be active were purchased and experimentally tested. Among the five selected compounds, three showed significant inhibition of recombinant Myt1. PD-173952, which yielded a favorable QM/MM-GBSA binding free energy, showed a <i>K</i>_i value of 8.1 nM. In addition, two compounds, PD-180970 and saracatinib, showed inhibition at the low micromolar level. Thus, the developed protocol might be useful for further virtual screening experiments to better discriminate between active and inactive compounds and to further optimize the identified hits

Differential response of cancers to 9c and 9d.

<p><b>A</b>, GI50 values across the NCI-60 cell line panel in response to <b>9c</b>. <b>B</b>, GI50 values across the NCI-60 cell line panel in response to <b>9d.</b></p