Unveiling the Selectivity Mechanism of Type-I LRRK2 Inhibitors by Computational Methods: Insights from Binding Thermodynamics and Kinetics Simulation

Shuoyan Tan, Jun Wang, Peng Gao, Guotong Xie, Qianqian Zhang, Huanxiang Liu, Xiaojun Yao

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding the selectivity mechanisms of inhibitors toward highly similar proteins is very important in new drug discovery. Developing highly selective targeting of leucine-rich repeat kinase 2 (LRRK2) kinases for the treatment of Parkinson’s disease (PD) is challenging because of the similarity of the kinase ATP binding pocket. During the development of LRRK2 inhibitors, off-target effects on other kinases, especially TTK and JAK2 kinases, have been observed. As a result, significant time and resources have been devoted to improving the selectivity for the LRRK2 target. DNL201 is an LRRK2 kinase inhibitor entering phase I clinical studies. The experiments have shown that DNL201 significantly inhibits LRRK2 kinase activity, with >167-fold selectivity over JAK2 and TTK kinases. However, the potential mechanisms of inhibitor preferential binding to LRRK2 kinase are still not well elucidated. In this work, to reveal the underlying general selectivity mechanism, we carried out several computational methods and comprehensive analyses from both the binding thermodynamics and kinetics on two representative LRRK2 inhibitors (DNL201 and GNE7915) to LRRK2. Our results suggest that the structural and kinetic differences between the proteins may play a key role in determining the activity of the selective small-molecule inhibitor. The selectivity mechanisms proposed in this work could be helpful for the rational design of novel selective LRRK2 kinase inhibitors against PD.

Original languageEnglish
Pages (from-to)3472-3486
Number of pages15
JournalACS Chemical Neuroscience
Volume14
Issue number18
DOIs
Publication statusPublished - 20 Sept 2023

Keywords

  • LRRK2 kinase inhibitor
  • Parkinson’s disease
  • drug dissociation
  • molecular dynamics simulation
  • residence time

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