COMPUTATIONAL IDENTIFICATION OF BIOMARKER AND THERAPEUTIC TARGETS IN NEURODEGENERATIVE AND BRAIN DISORDERS

Abstract

Aim: The objective of the current study was to identify candidate sets of differentially expressed and hub genes related to Multiple Sclerosis (MS) using bioinformatics methods, and to identify potential phytochemical inhibitors targeting the BUB1B protein in Glioblastoma (GBM) through molecular docking analysis.

Background: Neurological diseases like Multiple Sclerosis (MS) and Glioblastoma (GBM) are highly complex diseases, characterised by impairment of the nervous system and few therapeutic choices. Multiple Sclerosis involves immune-mediated demyelination and degeneration of the nervous system, while Glioblastoma is a rapidly growing, aggressive malignant brain tumour that is resistant to treatment. The identification of molecular Therapeutic targets and biomarkers is key to the advancement of diagnosis and therapeutic approaches to the disease. Increased knowledge about disease mechanisms and potential therapeutics using recent bioinformatics and computational drug discovery advances. Effective tools for understanding disease mechanisms and identifying potential therapeutics using bioinformatics and computational advances in drug discovery.

Methodology: Gene expression data (GSE21942) were downloaded from the Gene Expression Omnibus (GEO) database and analysed with GEO2R to generate a list of differentially expressed genes. The STRING database was used to conduct functional enrichment analysis, Gene Ontology (GO) pathway analysis, KEGG pathway analysis and protein–protein interaction (PPI) network construction. Degree centrality analysis was used to determine hub genes. For molecular docking studies, the three-dimensional structure of the BUB1B protein was obtained from the Data Bank on Proteins. Phytochemicals were selected and screened using EasyDock Vina. Protein–ligand interaction analysis was performed using LigPlot+, and the structural visualisation was performed using PyMOL.

Results: A total of 1276 genes were identified as being DE (697 up-regulated and 579 down regulated). Multiple Sclerosis was found to be regulated by hub genes: RPS6, RPS28, RPS18, CD79A, and CD79B. Functional enrichment analysis showed ribosomal activity, protein translation, inflammatory pathways, and immune response were enriched pathways. Based on the molecular docking study, α-peltatin had the highest binding affinity towards the BUB1 B protein with a docking score of — 10.6 kcal/mol, indicating that it has therapeutic potential against Glioblastoma.