The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Discovery of Highly Potent, Selective, and Brain-Penetrable Leucine-Rich Repeat Kinase 2 (LRRK2) Small Molecule Inhibitors
Open accessAbstract
There is a high demand for potent, selective, and brain-penetrant small molecule inhibitors of leucine-rich repeat kinase 2 (LRRK2) to test whether inhibition of LRRK2 kinase activity is a potentially viable treatment option for Parkinson's disease patients. Herein we disclose the use of property and structure-based drug design for the optimization of highly ligand efficient aminopyrimidine lead compounds. High throughput in vivo rodent cassette pharmacokinetic studies enabled rapid validation of in vitro-in vivo correlations. Guided by this data, optimal design parameters were established. Effective incorporation of these guidelines into our molecular design process resulted in the discovery of small molecule inhibitors such as GNE-7915 (18) and 19, which possess an ideal balance of LRRK2 cellular potency, broad kinase selectivity, metabolic stability, and brain penetration across multiple species. Advancement of GNE-7915 into rodent and higher species toxicity studies enabled risk assessment for early development.
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Cites
The influence of drug-like concepts on decision-making in medicinal chemistry
Leeson, P. D., & Springthorpe, B. (2007) · Nature Reviews Drug Discovery · doi:10.1038/nrd2445 · Cited by 2,403
Lees, A. J., Hardy, J., & Revesz, T. (2009) · The Lancet · doi:10.1016/s0140-6736(09)60492-x · Cited by 1,956
Matched Molecular Pairs as a Medicinal Chemistry Tool: Miniperspective
Griffen, E., Leach, A. G., Robb, G. R., & Warner, D. J. (2011) · Journal of Medicinal Chemistry · doi:10.1021/jm200452d · Cited by 282
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Kinase Drug Discovery – What’s Next in the Field?
Cohen, P., & Alessi, D. R. (2013) · ACS Chemical Biology · doi:10.1021/cb300610s · Cited by 377
Matikainen-Ankney, B. A., Kezunovic, N., Mesias, R. E., Tian, Y., Williams, F. M., Huntley, G. W., & Benson, D. L. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.3314-15.2016 · Cited by 139
Small-Molecule Inhibitors of LRRK2
Hatcher, J. M., Choi, H. G., Alessi, D. R., & Gray, N. S. (2017) · Advances in Neurobiology · doi:10.1007/978-3-319-49969-7_13 · Cited by 39
Metadata
- Authors
- Estrada, A. A., Liu, X., Baker-Glenn, C., Beresford, A., Burdick, D. J., Chambers, M., Chan, B. K., Chen, H., Ding, X., DiPasquale, A. G., Dominguez, S. L., Dotson, J., Drummond, J., Flagella, M., Flynn, S., Fuji, R., Gill, A., Gunzner-Toste, J., Harris, S. F., Heffron, T. P., Kleinheinz, T., Lee, D. W., Le Pichon, C. E., Lyssikatos, J. P., Medhurst, A. D., Moffat, J. G., Mukund, S., Nash, K., Scearce-Levie, K., Sheng, Z., Shore, D. G., Tran, T., Trivedi, N., Wang, S., Zhang, S., Zhang, X., Zhao, G., Zhu, H., & Sweeney, Z. K.
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-10-15
- Volume
- 55
- Issue
- 22
- Pages
- 9416-9433
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W1991732882
- Cited by
- 162
- References
- 3
- FWCI
- 15.27
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Discovery of Highly Potent, Selective, and Brain-Penetrable Leucine-Rich Repeat Kinase 2 (LRRK2) Small Molecule Inhibitors. https://app.cochat.ai/papers/10.1021/jm301020q
- The paper
- Estrada, A. A., Liu, X., Baker-Glenn, C., Beresford, A., Burdick, D. J., Chambers, M., Chan, B. K., Chen, H., Ding, X., DiPasquale, A. G., Dominguez, S. L., Dotson, J., Drummond, J., Flagella, M., Flynn, S., Fuji, R., Gill, A., Gunzner-Toste, J., Harris, S. F., . . . Sweeney, Z. K. (2012). Discovery of Highly Potent, Selective, and Brain-Penetrable Leucine-Rich Repeat Kinase 2 (LRRK2) Small Molecule Inhibitors. Journal of Medicinal Chemistry. https://doi.org/10.1021/jm301020q
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
