<i>In Silico</i> Enabled Discovery of KAI-11101, a Preclinical DLK Inhibitor for the Treatment of Neurodegenerative Disease and Neuronal Injury
Dual leucine zipper kinase (DLK), expressed primarily in neuronal cells, is a regulator of neuronal degeneration in response to cellular stress from chronic disease or neuronal injury. This makes it an attractive target for the treatment of neurodegenerative diseases such as Alzheimer's, Parkinson's, and amyotrophic lateral sclerosis, and neuronal injury, such as chemotherapy-induced peripheral neuropathy. Here, we describe the discovery of a potent, selective, brain-penetrant DLK inhibitor, KAI-11101 (<b>59</b>). Throughout the program's progression, medicinal chemistry challenges such as potency, hERG inhibition, CNS penetration, CYP3A time-dependent inhibition, and kinase selectivity were overcome through the implementation of cutting-edge <i>in silico</i> tools. KAI-11101 displayed an excellent <i>in vitro</i> safety profile and showed neuroprotective properties in an <i>ex vivo</i> axon fragmentation assay as well as dose-dependent activity in a mouse PD model.
Authors
- Éric Therrien (ORCID: https://orcid.org/0000-0003-3306-9162)
- R.J. Skene (ORCID: https://orcid.org/0000-0002-1482-6546)
- Robert Pelletier (ORCID: https://orcid.org/0000-0003-2112-1461)
- Felicia Gray
- Yuansong Jiang
- Mats Svensson
- Karen H. Dingley
- Hua Zhou
- Morgan Lawrenz (ORCID: https://orcid.org/0000-0002-4798-6423)
- Mitsunori Kato (ORCID: https://orcid.org/0000-0002-8426-2504)
- Hideyuki Igawa (ORCID: https://orcid.org/0009-0007-3802-6344)
- Jeffrey A. Bell (ORCID: https://orcid.org/0000-0002-8310-0183)
- Zhe Nie (ORCID: https://orcid.org/0009-0009-5125-8929)
- Markus K. Dahlgren
- H. Rachel Lagiakos (ORCID: https://orcid.org/0000-0001-5737-2495)
- Zhijian Liu (ORCID: https://orcid.org/0000-0003-1841-2671)
- Yefen Zou
- Kristian Jensen
Institutions
- Schrodinger (United States) (US)
- Takeda (United States) (US)
Publication Details
- Journal
- Journal of Medicinal Chemistry
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1021/acs.jmedchem.4c02074
- Citations
- 6
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 2.17