Identifyingnovel Leucine-Rich Repeat Serine/Threonine-Protein Kinase 2 (LRRK2) Inhibitors Usingmolecular Modelingapproaches

Abstract

The etiology of the Parkinson’s disease (PD) is one of the world’s most common age-related neurodegenerative disorders. The leucine-rich repeat kinase 2 (LRRK2)is an important target in designing drugs against PD.The R1441C mutation in the Ras-like GTPase domain (ROC) of LRRK2 havereduced GTPase activity.It changes the strength of ROC whichinturn enhanced kinase activity and caused PD.Hence, we target ROC of LRRK2 as a therapeutics strategy to mitigate brain damage in PD patients. Thus, we performed an atom based3D-QSAR studieson LRRK2 inhibitors, using a series of derivatives such as 4-alkylamino-7-aryl-3-cyanoquinoline,cinnoline-3-carboxamides, and triazolopyridazine. The statistical parameters generated by 3D-QSAR model revealed the strength of predictabilitywith the highest score.The reliability of the generated model was confirmed by internal and external validation parameters.The validated hypothesis was usedfor performing virtual screening for extraction of the potential leads from commercial databases (Maybridge, NCI, and ZINC).Further, the pharmacokinetic properties (Lipinski’s, ADME) wereanalyzed for the selected hits to make more drug-likeness.Themost suitable binding orientation of selected hit compounds wasanalyzed by the docking studies. Finally,four hits were selected on the basis of Glide score, GOLD fitness score and hydrogen bonding interactions with critical residues.