High-throughput screens for agonists of bone morphogenetic protein (BMP) signaling identify potent benzoxazole compounds

Abstract

Bone morphogenetic protein (BMP) signaling is critical in renal development and disease. In animal models of chronic kidney disease (CKD), re-activation of BMP signaling is reported to be protective by promoting renal repair and regeneration. Clinical use of recombinant BMPs, however, requires harmful doses to achieve efficacy and is costly because of BMPs' complex synthesis. Therefore, alternative strategies are needed to harness the beneficial effects of BMP signaling in CKD. Key aspects of the BMP signaling pathway can be regulated by both extracellular and intracellular molecules. In particular, secreted proteins like noggin and chordin inhibit BMP activity, whereas kielin/chordin-like proteins (KCP) enhance it and attenuate kidney fibrosis or CKD. Clinical development of KCP, however, is precluded by its size and complexity. Therefore, we propose an alternative strategy to enhance BMP signaling by using small molecules, which are simpler to synthesize and more cost-effective. To address our objective, here we developed a small-molecule high-throughput screen (HTS) with human renal cells having an integrated luciferase construct highly responsive to BMPs. We demonstrate the activity of a potent benzoxazole compound, sb4, that rapidly stimulated BMP signaling in these cells. Activation of BMP signaling by sb4 increased the phosphorylation of key second messengers (SMAD-1/5/9) and also increased expression of direct target genes (inhibitors of DNA binding, Id1 and Id3) in canonical BMP signaling. Our results underscore the feasibility of utilizing HTS to identify compounds that mimic key downstream events of BMP signaling in renal cells and have yielded a lead BMP agonist. Figure 3. Dose responses of the top 12 potential BMP agonists.A, 12 compounds were tested for BRE-Luc responses at 2-fold increasing concentrations from 0.5 nM to 10 M in triplicate. B, effective concentrations at 50% maximum response (EC 50 ), and the Hill slopes were calculated for each compound. Maximum -fold induction (FI) above DMSO controls is reported. C, chemical structures of the 12 candidate BMP agonists are shown schematically.

Non-coding RNA-Associated ceRNA Networks in a New Contrast-Induced Acute Kidney Injury Rat Model

“…lncRNA_000343 were ceRNAs of rno-miR-1956-5p targeting KCP. KCP transgenic mice were significantly more resistant to interstitial fibrosis and renal injury via inhibiting both transforming growth factor β (TGF-β) and activin signals while enhancing bone morphogenetic protein signaling, which can attenuate both acute and chronic renal injury 54, 55, 56. The circRNA- or lncRNA-associated ceRNA networks in CI-AKI are highly complex and diverse.…”

The Interactivity between TGFβ and BMP Signaling in Organogenesis, Fibrosis, and Cancer

“…Due to limited clinical use of BMPs related to costly production or hazardous doses required to achieve efficacy, some synthetic BMP agonists or inducers are being tested in preclinical models. Following small-molecule high-throughput screening for synthetic compounds, the benzoxazole compound BMP agonist, sb4, has shown in vitro efficacy in stimulating BMP signaling and is thus a promising prospect for the treatment of chronic kidney disease [102]. Peritoneal dialysis offers an option in the treatment of this illness but this practice causes mesothelial cells to lose MBP7 expression and undergo EMT conversion which in turn leads to inflammation, fibrosis, angiogenesis and ultimately peritoneal membrane damage.…”

Ligand-receptor promiscuity enables cellular addressing

“…To systematically identify parameters that generate orthogonal channels, we used an optimization approach ( Figure 3B). We considered discrete ligand concentrations, allowing each ligand to take on one of three logarithmically spaced concentrations, 10 0 = 1, 10 1.5 ≈ 32, and 10 3 = 1000 arbitrary units (AU), reflecting the experimentally observed input dynamic range for BMP signaling (Antebi et al, 2017;Bradford et al, 2019;Hatsell et al, 2015). This discretization defines a finite set of 3 possible ligand words.…”