1 Integrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, TN, 632014, India.
2 Department of Biotechnology, Indian Institute of Technology (Madras), Chennai, TN, 600036, India.
3 Department of Biotechnology, Dwaraka Doss Goverdhan Doss Vaishnav College, Chennai, TN, 600106, India.
4 Jindal Institute of Behavioral Sciences, O.P Jindal Global University, Sonipat, Haryana, 131001, India.
5 Centre for Research in Molecular Modeling (CERMM), Department of Chemistry and Biochemistry, Concordia University, Loyola Campus, Montreal, QC, H4B 1R6, Canada.
6 Centre for Research in Molecular Modeling (CERMM), Department of Chemistry and Biochemistry, Concordia University, Loyola Campus, Montreal, QC, H4B 1R6, Canada; Bioinformatics Unit, Department of Biomaterials, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS) University, Chennai, TN, 600077, India. Electronic address: gurudeeban.selvaraj@concordia.ca.
7 Integrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, TN, 632014, India. Electronic address: ssajithalulu@vit.ac.in.

Parkinson's disease (PD) is a complex neurological disease associated with the degeneration of dopaminergic neurons. Oxidative stress is a key player in instigating apoptosis in dopaminergic neurons. To improve the survival of neurons many dietary phytochemicals have gathered significant attention recently. Thus, the present study implements a comprehensive network pharmacology approach to unravel the mechanisms of action of dietary phytochemicals that benefit disease management. A literature search was performed to identify ligands (i.e., comprising dietary phytochemicals and Food and Drug Administration pre-approved PD drugs) in the PubMed database. Targets associated with selected ligands were extracted from the search tool for interactions of chemicals (STITCH) database. Then, the construction of a gene-gene interaction (GGI) network, analysis of hub-gene, functional and pathway enrichment, associated transcription factors, miRNAs, ligand-target interaction network, docking were performed using various bioinformatics tools together with molecular dynamics (MD) simulations. The database search resulted in 69 ligands and 144 unique targets. GGI and subsequent topological measures indicate histone acetyltransferase p300 (EP300), mitogen-activated protein kinase 1 (MAPK1) or extracellular signal-regulated kinase (ERK)2, and CREB-binding protein (CREBBP) as hub genes. Neurodegeneration, MAPK signaling, apoptosis, and zinc binding are key pathways and gene ontology terms. hsa-miR-5692a and SCNA gene-associated transcription factors interact with all the 3 hub genes. Ligand-target interaction (LTI) network analysis suggest rasagiline and baicalein as candidate ligands targeting MAPK1. Rasagiline and baicalein form stable complexes with the Y205, K330, and V173 residues of MAPK1. Computational molecular insights suggest that baicalein and rasagiline are promising preclinical candidates for PD management.