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. 2018 Jul 3;8(1):10010.
doi: 10.1038/s41598-018-28263-7.

Structure-Activity Investigations and Optimisations of Non-metabolite Agonists for the Succinate Receptor 1

Affiliations

Structure-Activity Investigations and Optimisations of Non-metabolite Agonists for the Succinate Receptor 1

Elisabeth Rexen Ulven et al. Sci Rep. .

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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
General 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.
Figure 2
Figure 2
Summary 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 3
Figure 3
Iterative 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.

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