Accelerated Discovery of Novel Ponatinib Analogs with Improved Properties for the Treatment of Parkinson's Disease.
ACS Med Chem Lett 2020;
11:491-496. [PMID:
32292555 DOI:
10.1021/acsmedchemlett.9b00612]
[Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 03/12/2020] [Indexed: 11/30/2022] Open
Abstract
Parkinson's disease (PD) is a debilitating and common neurodegenerative disease. New insights implicating c-Abl activation as a driving force in PD have opened a new drug development avenue for PD treatment beyond the symptomatic relief by L-DOPA. BCR-Abl inhibitors, which include nilotinib and ponatinib, have been found to inhibit this process, and nilotinib has shown improvement in outcomes in a 12-patient, nonrandomized trial. However, nilotinib is a potent inhibitor of hERG, a cardiac K+ channel whose inhibition increases risk of sudden death. We used our machine learning approach to predict novel molecules that would inhibit c-Abl while also having minimal liability against hERG. Of our six novel compounds tested, we identified two that had c-Abl potencies comparable to nilotinib, but with significantly improved profiles regarding the hERG channel. Our best compound exhibited a hERG IC50 of 12.1 μM (compared to nilotinib with an IC50 of 0.45 μM and ponatinib with IC50 of 0.767 μM). This work is a step forward for a machine learning enabled, multiparameter optimization of a chemical space and represents a significant advance in the development of novel Parkinson's therapies.
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