INTEGRATED BIOINFORMATICS ANALYSIS TO IDENTIFY CRITICAL GENES AND POTENTIAL DRUG CANDIDATE DISCOVERY

Abstract

Alzheimer's disease is one of the world's leading causes of dementia. It is one of the most deadly and irreversible neurodegenerative diseases. There is a limited supply of novel drugs introducing in the market because of safety reasons or lower pharmacokinetic properties. Drug repurposing offers the potential to avoid the slow speed of the drug discovery and it’s commercialization after clinical trials. Hence, reducing the cost of drug production. The main advantage of adopting the drug repurposing strategy is that the clinical trials have previously been done and safety issues have already been inspected and the drugs have been commercialized and in the market. As this way helps to speed up providing the alternate drugs for AD, this study shows the interaction of the known four cancer drugs (Selinexor, Entrectinib, Lenvatinib, BIIBO21) with two target (FN1 and E1F4A3) involved in AD using in-silico techniques. A computational method was adopted to find the dysregulated genes involved in the disease. The microarray analyses were done on the GSE28146 dataset, which was extracted from the Gene Expression Omnibus (GEO) database, out of all the expressed genes in the array 59 were upregulated and 68 were downregulated. These genes were used to generate a viable gene networks and hub gene network of the top 10 dysregulated genes. Top 4 genes were used as a target for the selected drugs and their interaction was investigated by molecular docking. In this study the best drug was chosen based on the best docking score for both the targets. The current study discloses the potential of Selinexor as a new drug against two targets associated with AD.