Journal
ADVANCED SCIENCE
Volume 7, Issue 8, Pages -Publisher
WILEY
DOI: 10.1002/advs.201903337
Keywords
calcium oxalate crystallization inhibitors; chronic kidney disease; image-based drug screening; kidney calcification; kidney stones
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Funding
- Functional Genomics Center Zurich (FGCZ)
- Small molecule Crystallography Center (SMoCC, ETH Zurich)
- ETH Zurich Postdoctoral Fellowship programme
- Ministry of Social Justice and Empowerment (Government of India)
- Deutsche Forschungsgemeinschaft [AN372/16-2, AN372/24-1]
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Calcium oxalate (CaOx) crystal-induced nephropathies comprise a range of kidney disorders, for which there are no efficient pharmacological treatments. Although CaOx crystallization inhibitors have been suggested as a therapeutic modality already decades ago, limited progress has been made in the discovery of potent molecules with efficacy in animal disease models. Herein, an image-based machine learning approach to systematically screen chemically modified myo-inositol hexakisphosphate (IP6) analogues is utilized, which enables the identification of a highly active divalent inositol phosphate molecule. To date, this is the first molecule shown to completely inhibit the crystallization process in the nanomolar range, reduce crystal-cell interactions, thereby preventing CaOx-induced transcriptomic changes, and decrease renal CaOx deposition and kidney injury in a mouse model of hyperoxaluria. In conclusion, IP6 analogues based on such a scaffold may represent a new treatment option for CaOx nephropathies.
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