Exploring the functional impact of mutational drift in LRRK2 gene and identification of specific inhibitors for the treatment of Parkinson disease

• Published in: Journal of cellular biochemistry 2018-06, Vol.119 (6), p.4878-4889
• Main Authors: Nagarajan, Nagasundaram, Chellam, Jaynthy, Kannan, Rajaretinam Rajesh
• Format: Article
• Language: English
• Subjects: Brain; Central nervous system; Chemical bonds; Computational neuroscience; Computer simulation; Dopamine receptors; Drug resistance; G2019S; Hydrogen bonding; Hydrogen bonds; I2020T; Identification; Inhibitors; Kinases; Levodopa; LRRK2; LRRK2 protein; Medical treatment; Molecular docking; Molecular dynamics; Movement disorders; Mutants; Mutation; Neurodegenerative diseases; Parkinson disease; Parkinson's disease; Precision medicine; Resistance factors; Structure-function relationships; Substantia nigra
• ISSN: 0730-2312; 1097-4644
• DOI: 10.1002/jcb.26703

Parkinson's disease (PD) is a disorder of the central nervous system that is caused due to the death of the dopaminergic neurons in the region of the brain called substantia nigra. Mutations in LRRK2 genes are associated with disease condition and it's been reported as crucial factor for drug resistance. Identification of deleterious mutations and studying the structural and functional impact of such mutations may lead to the identification of potential selective inhibitors. In this study, we analyzed 52 PD associated mutations, among that 20 were identified as highly deleterious. The deleterious mutations G2019S and I2020T in the kinase domain were playing a key role in causing resistance to drug levedopa. Molecular docking analyses have been performed to understand the binding affinity of levodapa with LRRK2 in wild and mutant condition. Molecular docking results show that levedopa binds differentially and obtained less number of hydrogen bonds in compared with wild type LRRK2. In addition, molecular dynamics simulations were performed to study the efficacy of docked complexes and it was observed that the efficacy of the mutant complexes (G2019S‐Levodopa and I2020T‐Levodopa) affected in the presence of mutation. Finally, through virtual screening approach specific inhibitors SCHEMBL6473053 and SCHEMBL1278779 have been identified that could potentially inhibit LLRK2 mutants G2019S and I2020T respectively. Over all this computational investigation correlates the impact of genotypic modulation in structure and function of drug target which enhanced in the identification of precision medicine to treat PD. The emerging of resistance to chemotherapy is the major hurdle faced by clinicians and researchers. Most of the drugs are responding well initially, but stared to relapse gradually, despite many improvements in chemotherapy, and their use over several decades. Now the clinician required to be at least one step ahead of the neurodegenerative disorders, the diagnosis, and treatment that can be associated to “molecular level investigation”. Thus, as well as an increasing role for targeted therapy to clinically stratify patients, it is becoming clear that personalized treatments are required to obtain better results.