학술논문

Network metrics, structural dynamics and density functional theory calculations identified a novel Ursodeoxycholic Acid derivative against therapeutic target Parkin for Parkinson's disease
Document Type
article
Source
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 4271-4287 (2022)
Subject
Biomarker
Docking
Ligand optimization
Neurodegenerative disorder
Simulation
Systems biology
Biotechnology
TP248.13-248.65
Language
English
ISSN
2001-0370
Abstract
Parkinson's disease (PD) has been designated as one of the priority neurodegenerative disorders worldwide. Although diagnostic biomarkers have been identified, early onset detection and targeted therapy are still limited. An integrated systems and structural biology approach were adopted to identify therapeutic targets for PD. From a set of 49 PD associated genes, a densely connected interactome was constructed. Based on centrality indices, degree of interaction and functional enrichments, LRRK2, PARK2, PARK7, PINK1 and SNCA were identified as the hub-genes. PARK2 (Parkin) was finalized as a potent theranostic candidate marker due to its strong association (score > 0.99) with α-synuclein (SNCA), which directly regulates PD progression. Besides, modeling and validation of Parkin structure, an extensive virtual-screening revealed small (commercially available) inhibitors against Parkin. Molecule-258 (ZINC5022267) was selected as a potent candidate based on pharmacokinetic profiles, Density Functional Theory (DFT) energy calculations (ΔE = 6.93 eV) and high binding affinity (Binding energy = -6.57 ± 0.1 kcal/mol; Inhibition constant = 15.35 µM) against Parkin. Molecular dynamics simulation of protein-inhibitor complexes further strengthened the therapeutic propositions with stable trajectories (low structural fluctuations), hydrogen bonding patterns and interactive energies (>0kJ/mol). Our study encourages experimental validations of the novel drug candidate to prevent the auto-inhibition of Parkin mediated ubiquitination in PD.