Network metrics, structural dynamics and density functional theory calculations identified a novel Ursodeoxycholic Acid derivative against therapeutic target Parkin for Parkinson's disease

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.

Keywords: ADMET, Absorption, Distribution, Metabolism, Excretion, Toxicity; AI, Artificial Intelligence; BBB, Blood Brain Barrier; Biomarker; CS, Confidence Scores; DFT, Density Functional Theory; DL, Deep Learning; Docking; FEA, Functional Enrichment Analysis; GI, Gasto-Intestinal; GIN, Gene Interaction Network; GO, Gene Ontology; HOMO, Highest Occupied Molecular Orbital; IC, Inhibition Constant; LB, Lewy Bodies; LD, Lethal Dose; LUMO, Lowest Unoccupied Molecular Orbital; Ligand optimization; MDS, Molecular Dynamics Simulation; ML, Machine Learning; MMP, Mitochondrial Membrane Potential; Neurodegenerative disorder; PD, Parkinson's Disease; RMSD, Root Means Square Deviation; RMSF, Root Means Square Fluctuation; Rg, Radius of Gyration; SNpc, Substantia Nigra pars compacta; Simulation; Systems biology; TPSA, Total Polar Surface Area; UDCA, Ursodeoxycholic Acid.

Graphical abstract

Fig. 1

Gene Interaction Network Analysis: (a) MCODE clustering analysis of 49 PD associated genes (b) Hub genes and associated genes involved in apoptosis [GO:0042981; GO:2001233] (c) Hub genes and associated genes involved in oxidative stress [GO:2000377; GO:0006979; GO:0034599] (d) Hub genes and associated genes involved in mitophagy [GO:0010821; GO:1903599; GO:0051881; GO:1903146].

Fig. 2

Structural Analysis of Parkin: (a) Optimized modeled structure (b) Global model quality (c) Local model quality (d) Atomic-level fluctuations (normalized B-factor), solvent accessibility and secondary structural analysis (e) Propensity plot (f) ProTSAV heat-map (g) Extent of disorderness.

Fig. 3

Stability Analysis of Parkin: (a) Global folding free energy of thermodynamic and kinetic constraints of Parkin (b) Backbone stability profile of Parkin (c) Residue-level fluctuation profile of Parkin.

Fig. 4

MDS analysis of unbound Parkin: (a) RMSD curve (b) Residue-level RMSF plot (c) Rg trajectory (d) Minimum distance amongst proximal backbone residues (e) Number of intermolecular (protein-solvent) hydrogen bonds (f) SASA trajectory (g) Potential energy curve (h) Total energy curve.

Fig. 5

DFT simulations highlighting frontier molecular orbital (HOMO-LUMO) and electron density map of: (a) UDCA (b) Molecule-258 (c) Molecule-297 (d) Molecule-371.

Fig. 6

Molecular Docking Profiles: (a) 3D conformer of Parkin highlighting its RING domains (b) Binding energies and Inhibition Constants of docked complexes (c) Intermolecular interaction profile of UDCA (d) Intermolecular interaction profile of Molecule-258 (e) Intermolecular interaction profile of Molecule-297 (f) Intermolecular interaction profile of Molecule-371.

Fig. 7

MDS analysis of Parkin-Inhibitor Complexes: (a) RMSD curve (b) Residue-level RMSF plot (c) Rg trajectory (d) Number of intermolecular (protein-inhibitor) hydrogen bonds (e) SASA trajectory (f) Free energy of solvation (g) Interaction energy profile (h) Total energy curve.