1. Computational drug discovery approaches identify mebendazole as a candidate treatment for autosomal dominant polycystic kidney disease.
- Author
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Brownjohn PW, Zoufir A, O'Donovan DJ, Sudhahar S, Syme A, Huckvale R, Porter JR, Bange H, Brennan J, and Thompson NT
- Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is a rare genetic disorder characterised by numerous renal cysts, the progressive expansion of which can impact kidney function and lead eventually to renal failure. Tolvaptan is the only disease-modifying drug approved for the treatment of ADPKD, however its poor side effect and safety profile necessitates the need for the development of new therapeutics in this area. Using a combination of transcriptomic and machine learning computational drug discovery tools, we predicted that a number of existing drugs could have utility in the treatment of ADPKD, and subsequently validated several of these drug predictions in established models of disease. We determined that the anthelmintic mebendazole was a potent anti-cystic agent in human cellular and in vivo models of ADPKD, and is likely acting through the inhibition of microtubule polymerisation and protein kinase activity. These findings demonstrate the utility of combining computational approaches to identify and understand potential new treatments for traditionally underserved rare diseases., Competing Interests: Authors PB, AZ, DO’D, SS, AS, RH, JP, JB, and NT were employed by Healx Ltd. Author HB was employed by Crown Bioscience Netherlands B.V. The authors declare that this study was funded by Healx Ltd. The funder was involved in the study designs, data analysis, data interpretation and writing and submission of the article., (Copyright © 2024 Brownjohn, Zoufir, O’Donovan, Sudhahar, Syme, Huckvale, Porter, Bange, Brennan and Thompson.)
- Published
- 2024
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