Chronic sleep deprivation can lead to cognitive impairment which makes it difficult to think, focus, and make comprehensive decisions. This in turn leads to the progression and increased risk of several diseases. This study aimed to explore potential drug targets and biomarkers underlying the increased disease risk due to sleep deprivation, including stress responses, immune dysfunction, and metabolic dysregulation. Four datasets namely GSE40562, GSE98566, GSE98582 for sleep deprivation, and GSE26576 normal brain cells were utilized to understand the molecular basis and potential drug targets associated with sleep deprivation. The GEO2R tool, Robust rank aggregations, and Venny were used to retrieve the common DEGs. Functional gene and pathway analyses were carried out via GO and the KEGG analyses. The STRING and CytoHuba plugins were utilized to identify the protein-protein interactions (PPIs) as well as the hub genes in the main PPI subnetworks following the drug interaction of the hub genes and GEPIA-based survival analysis of the DEGs. A total of 160 common DEGs were retrieved from all four datasets. Among them, 65 were down-regulated and 95 were up-regulated. TOP2A, AURKB, NEFL, CDC42, ASPM, GAP43, PVALB, NUF2, CALM1, TPR, KIF5B, KIF15, TROAP, NDC80, PBK, MKI67, SST, AHSP, ALAS2, and NEFH were retrieved as hub genes. While based on drug interaction, survival analysis and gene expression profile eight hub gene named TOP2A, AURKB, PVALB, CALM1, KIF5B, PBK, MKI67, and SST were found to be potential drug candidates and significantly correlated with infiltration levels of CD8 + T cells, B cells, macrophages, CD4 + T cells, neutrophils, and dendritic cells. These genes might play a role in sleep disorders via various pathways associated with neurodegeneration and diseases, potentially serving as biomarkers to support treatment and diagnosis.