Pharmacoinformatic Analysis of Drug Leads for Alzheimer’s Disease from FDA-Approved Dataset Through Drug Repositioning Studies

Abstract

Drug design is highly priced and time-consuming procedure. Therefore, to overcome this problem, in silico drug design methods, particularly drug repositioning have been developed to assess therapeutic effects of known drugs against other diseases. In this study, computational drug repositioning method is used to explore the alternative therapeutic effects of FDA approved drugs to treat Alzheimer’s disease. The chemical shape-based screening was employed to fetch some potential new drugs based on the structure of standard drugs. The screened drugs were further evaluated through pharmacogenomics, molecular docking, and molecular dynamics simulation studies. The best lead drugs, such as darifenacin, astemizole, tubocurarine, elacridar, sertindole and tariquidar displayed promising repositioned effects in the treatment of Alzheimer’s disease and may be used as potential medicines after thorough experimental and clinical studies.