| Literature DB >> 29968758 |
Elisabeth Rexen Ulven1, Mette Trauelsen2, Matjaz Brvar3, Michael Lückmann4, Line Ø Bielefeldt3, Lisa K I Jensen3, Thue W Schwartz2,4, Thomas M Frimurer2.
Abstract
The succinate receptor 1 (SUCNR1) is a receptor for the metabolite succinate, which functions as a metabolic stress signal in the liver, kidney, adipose tissue and the retina. However, potent non-metabolite tool compounds are needed to reveal the physiological role and pharmacological potential of SUCNR1. Recently, we published the discovery of a computationally receptor-structure derived non-metabolite SUCNR1 agonist series with high target selectivity. We here report our structure-activity exploration and optimisation that has resulted in the development of agonists with nanomolar potency and excellent solubility and stability properties in a number of in vitro assays. Ligand-guided receptor models with high discriminative power between binding of active and inactive compounds were developed for design of novel chemotypes.Entities:
Mesh:
Substances:
Year: 2018 PMID: 29968758 PMCID: PMC6030209 DOI: 10.1038/s41598-018-28263-7
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1General synthetic route. Reagents and conditions: (a) SOCl2, MeOH, 0 °C → reflux. (b) BTFFH, DIPEA, ArCOOH, DCM, 80 °C. (c) ArB(OH)2, Pd-XPhos-G4, 0.5 M K3PO4aq, THF, room temp. (d) For R” = OH: K2CO3, alkylhalide/tosylate, MeCN, 50–55 °C. (e) 0.6 M LiOHaq, THF, room temp.
Investigation of miscellaneous amide analogues.
|
| ||||
|---|---|---|---|---|
| R | hSUCNR1 | mSUCNR1 | ClogPb | |
| pEC50 (efficacy, %)a | ||||
| 3 |
| 5.75 ± 0.08 (72.8 ± 2.6) | 6.46 ± 0.06 (79.3 ± 1.6) | 1.66 |
| 4 |
| 4.53 ± 0.13 (78.1 ± 7.5) | 4.93 ± 0.05 (95.8 ± 2.9) | 0.44 |
| 5 |
| 22% @10−4M | 13% @10−4M | 0.28 |
| 6 |
| 50% @10−4M | 64% @10−4M | 1.52 |
| 7 |
| 8% @10−4M | 15% @10−4M | 1.26 |
| 8 |
| 5% @10−4M | 11% @10−4M | 1.28 |
| 9 |
| 25% @10−4M | 15% @10−4M | 2.44 |
apEC50 values were determined from dose-response curves of induction of IP3 turnover in SUCNR1 transfected HEK cells (N = 3), efficacy is determined relative to succinate (100%). bCalculated by BioByte’s algorithm as implemented in ChemDraw Professional 16.0.1.4 (ClogP option).
Investigation of ring A.
|
| ||||
|---|---|---|---|---|
| Ring A | hSUCNR1 | mSUCNR1 | ClogPb | |
| pEC50 (efficacy, %)a | ||||
| 3 |
| 5.75 ± 0.08 (72.8 ± 2.6) | 6.46 ± 0.06 (79.3 ± 1.6) | 1.66 |
| 10 |
| 5.29 ± 0.19 (81.6 ± 8.4) | 6.16 ± 0.11 (81.3 ± 3.6) | 1.47 |
| 11 |
| 5.27 ± 0.18 (94.7 ± 8.7) | 6.13 ± 0.10 (76.7 ± 3.1) | 1.67 |
| 12 |
| 5.02 ± 0.10 (91.9 ± 5.3) | 6.07 ± 0.09 (81.6 ± 3.0) | 1.97 |
| 13 |
| 6.33 ± 0.14 (69.1 ± 3.9) | 6.83 ± 0.11 (73.2 ± 2.7) | 1.97 |
| 14 |
| 4.81 ± 0.20 (74.2 ± 11.8) | 5.71 ± 0.09 (79.6 ± 3.7) | 0.43 |
| 15 |
| 6.13 ± 0.14 (71.1 ± 4.2) | 6.82 ± 0.08 (74.8 ± 2.0) | 0.87 |
| 16 |
| 5.29 ± 0.15 (103.8 ± 7.9) | 6.14 ± 0.10 (78.1 ± 3.1) | 0.89 |
| 17 |
| 6.41 ± 0.14 (85.3 ± 4.5) | 7.39 ± 0.07 (84.2 ± 1.8) | 1.45 |
| 18 |
| 6.55 ± 0.25 (81.0 ± 7.2) | 6.81 ± 0.17 (80.6 ± 4.6) | 2.43 |
| 19 |
| 6.39 ± 0.11 (72.1 ± 3.2) | 6.79 ± 0.06 (76.0 ± 1.5) | 1.00 |
apEC50 values were determined from dose-response curves of induction of IP3 turnover in SUCNR1 transfected HEK cells (N = 3), efficacy is determined relative to succinate (100%). bCalculated by BioByte’s algorithm as implemented in ChemDraw Professional 16.0.1.4 (ClogP option). cDuplication of data from Table 1.
Alkoxy analogues.
|
| ||||
|---|---|---|---|---|
| R | hSUCNR1 | mSUCNR1 | ClogPb | |
| pEC50 (efficacy, %)a | ||||
| 17 | Me | 6.41 ± 0.14 (85.3 ± 4.5) | 7.39 ± 0.07 (84.2 ± 1.8) | 1.45 |
| 20 | F3C | 6.99 ± 0.15 (61.7 ± 3.6) | 6.72 ± 0.11 (69.7 ± 2.8) | 3.17 |
| 21 | Et | 6.59 ± 0.14 (56.3 ± 3.1) | 7.44 ± 0.09 (70.2 ± 2.0) | 1.98 |
| 22 | 6.84 ± 0.14 (69.6 ± 4.3) | 7.29 ± 0.07 (75.6 ± 1.7) | 2.29 | |
| 23 |
| 6.27 ± 0.11 (76.5 ± 3.1) | 6.97 ± 0.07 (82.4 ± 1.9) | 1.81 |
| 24 |
| 6.10 ± 0.09 (63.9 ± 2.4) | 7.33 ± 0.09 (74.6 ± 2.1) | 0.53 |
apEC50 values were determined from dose-response curves of induction of IP3 turnover in SUCNR1 transfected HEK cells (N = 3), efficacy is determined relative to succinate (100%). bCalculated by BioByte’s algorithm as implemented in ChemDraw Professional 16.0.1.4 (ClogP option). cDuplication of data from Table 2.
Investigation of ring B.
|
| ||||
|---|---|---|---|---|
| Ring B | hSUCNR1 | mSUCNR1 | ClogPb | |
| pEC50 (efficacy, %)a | ||||
| 3 |
| 5.75 ± 0.08 (72.8 ± 2.6) | 6.46 ± 0.06 (79.3 ± 1.6) | 1.66 |
| 25 |
| 5.91 ± 0.11 (49.7 ± 3.9) | 5.40 ± 0.13 (58.0 ± 4.5) | 2.27 |
| 26 |
| 4% @10−4M | 7% @10−4M | 2.27 |
| 27 |
| 6.03 ± 0.25 (78.2 ± 8.0) | 6.10 ± 0.17 (89.3 ± 6.1) | 2.05 |
apEC50 values were determined from dose-response curves of induction of IP3 turnover in SUCNR1 transfected HEK cells (N = 3), efficacy is determined relative to succinate (100%). bCalculated by BioByte’s algorithm as implemented in ChemDraw Professional 16.0.1.4 (ClogP option). Duplication of data from Table 1.
Combined analogues.
|
| |||||
|---|---|---|---|---|---|
| Ring A | Ring B | hSUCNR1 | mSUCNR1 | ClogPb | |
| pEC50 (efficacy, %)a | |||||
| 28 |
|
| 6.79 ± 0.12 (58.0 ± 2.7) | 5.92 ± 0.09 (64.0 ± 2.5) | 2.01 |
| 29 |
|
| 6.85 ± 0.19 (52.6 ± 3.9) | 6.74 ± 0.13 (71.2 ± 3.2) | 1.07 |
| 30 |
|
| 7.23 ± 0.14 (49.2 ± 2.7) | 5.84 ± 0.16 (45.3 ± 3.4) | 3.11 |
| 31 |
|
| 7.64 ± 0.13 (61.7 ± 2.5) | 6.75 ± 0.09 (69.9 ± 2.2) | 2.18 |
| 32 |
|
| 7.23 ± 0.23 (88.7 ± 6.1) | 7.00 ± 0.09 (68.1 ± 2.5) | 1.86 |
| 33 |
|
| 7.23 ± 0.37 (66.4 ± 7.2) | 7.29 ± 0.18 (61.5 ± 3.8) | 2.13 |
apEC50 values were determined from dose-response curves of induction of IP3 turnover in SUCNR1 transfected HEK cells (N = 3), efficacy is determined relative to succinate (100%). bCalculated by BioByte’s algorithm as implemented in ChemDraw Professional 16.0.1.4 (ClogP option).
Figure 2Summary of in vitro agonist potencies. (a) Scatterplot of in vitro agonist potencies by IP3 accumulation in SUCNR1 transfected HEK-293 cells of the compounds in Tables 1–5 on the hSUCNR1 and mSUCNR1 receptor. (b,c) Dose-response curves for succinate and selected compounds (3, 21 and 31) on hSUCNR1 and mSUCNR1.
Figure 3Iterative SUCNR1 receptor optimisation based on ligand information gained in this study. (a) Small-scale virtual ligand screening (VLS) results at different stages of the optimisation process (generations GEN_1 - GEN_4). Receiver operating characteristic (ROC) curves and normalised square root area under the curve (NSQ_AUC) values are shown for each generation of receptor pockets. The diagonal corresponds to a random VLS performance. (b) Best-performing receptor pocket ensemble (GEN_4), consisting of three receptor structures shown with the best-scored docking poses of all 25 active compounds investigated in this study (dark green lines). Best-scored docking poses of compound 24 (b), 31 (c), 3 (d) and 21 (e) are shown in green sticks. Polar receptor-ligand interactions are indicated by yellow spheres. Homology models are based on the x-ray crystal structure of the P2Y1 receptor (PDB 4XNW) which shares several key side-chains in the binding site with SUCNR1, i.e. Y79:2.64, D174 and R276:7.39. Figure was made using PyMol.