ABSTRACT
ALS (Amyotrophic Lateral Sclerosis) is a rare type of neurodegenerative disease. It shows progressive degradation of motor neurons in the brain and spinal cord. At present, there is no treatment available that can completely cure ALS. The available treatments can only increase a patient's life span by a few months. Recently, microRNAs (miRNAs), a sub-class of small non-coding RNAs have been shown to play an essential role in the diagnosis, prognosis, and therapy of ALS. Our study focuses on analyzing differential miRNA profiles and predicting drug targets in ALS using bioinformatics and computational approach. The study identifies eight highly differentially expressed miRNAs in ALS patients, four of which are novel. We identified 42 hub genes for these eight highly expressed miRNAs with Amyloid Precursor Protein (APP) as a candidate gene among them for highly expressed down-regulated miRNA, hsa-miR-455-3p using protein-protein interaction network and Cytoscape analysis. A novel association has been found between hsa-miR-455-3p/APP/serotonergic pathway using KEGG pathway analysis. Also, molecular docking studies have revealed curcumin as a potential drug target that may be used for the treatment of ALS. Thus, the present study has identified four novel miRNA biomarkers: hsa-miR-3613-5p, hsa-miR-24, hsa-miR-3064-5p, and hsa-miR-4455. There is a formation of a novel axis, hsa-miR-455-3p/APP/serotonergic pathway, and curcumin is predicted as a potential drug target for ALS.