Structural binding site comparisons reveal Crizotinib as a novel LRRK2 inhibitor

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung



Mutations in leucine-rich repeat kinase 2 (LRRK2) are a frequent cause of autosomal dominant Parkinson's disease (PD) and have been associated with familial and sporadic PD. Reducing the kinase activity of LRRK2 is a promising therapeutic strategy since pathogenic mutations increase the kinase activity. Several small-molecule LRRK2 inhibitors are currently under investigation for the treatment of PD. However, drug discovery and development are always accompanied by high costs and a risk of late failure. The use of already approved drugs for a new indication, which is known as drug repositioning, can reduce the cost and risk. In this study, we applied a structure-based drug repositioning approach to identify new LRRK2 inhibitors that are already approved for a different indication. In a large-scale structure-based screening, we compared the protein–ligand interaction patterns of known LRRK2 inhibitors with protein–ligand complexes in the PDB. The screening yielded 6 drug repositioning candidates. Two of these candidates, Sunitinib and Crizotinib, demonstrated an inhibition potency (IC50) and binding affinity (Kd) in the nanomolar to micromolar range. While Sunitinib has already been known to inhibit LRRK2, Crizotinib is a novel LRRK2 binder. Our results underscore the potential of structure-based methods for drug discovery and development. In light of the recent breakthroughs in cryo-electron microscopy and structure prediction, we believe that structure-based approaches like ours will grow in importance.


Seiten (von - bis)3674-3681
FachzeitschriftComputational and Structural Biotechnology Journal
PublikationsstatusVeröffentlicht - Jan. 2021

Externe IDs

PubMed 34285770
PubMedCentral PMC8258795
ORCID /0000-0003-2848-6949/work/141543337
ORCID /0000-0002-7688-3124/work/142250011



  • Binding site, Crizotinib, Drug repositioning, LRRK2, Protein–ligand interactions, Structure-based screening