Tolcapone

Alzheimer's disease affects 6.9 million Americans aged 65 and older, a number expected to double by 2060. Eight FDA-approved drugs target Alzheimer's, but no cure is available, and most treatments are symptomatic. Drug repurposing, the use of FDA-approved drugs for new indications, is a promising strategy to address this lack of effective therapies. However, despite prior safety approval, repurposable drugs may still trigger unexpected side-effects in new contexts. This study introduces a network-based approach to minimize side-effect risk in drug repositioning, focusing on QT interval prolongation, a cardiac side-effect observed in Alzheimer's patients treated with acetylcholinesterase inhibitors. The method integrates Mode-of-Action and Random Walk with Restart analyses to identify repositioning candidates while assessing QT-related risk. This strategy identified promising compounds including acamprosate, tolcapone, sitagliptin, and diazoxide, with potential to mitigate disease pathology. Gene set enrichment analysis was used to computationally assess the compounds' ability to reverse disease-related gene expression signatures.

The dengue virus (DENV) infects approximately 400 million people annually worldwide causing significant morbidity and mortality. Despite advances in understanding the virus life cycle and infectivity, no specific treatment for this disease exists due to the lack of therapeutic drugs. In addition, vaccines available currently are ineffective with severe side effects. Therefore, there is an urgent need for developing therapeutics suitable for effective management of DENV infection. In this study, we adopted a drug repurposing strategy to identify new therapeutic use of existing FDA approved drug molecules to target DENV2 non-structural proteins NS3 and NS5 using computational approaches. We used Drugbank database molecules for virtual screening and multiple docking analysis against a total of four domains, the NS3 protease and helicase domains and NS5 MTase and RdRp domains. Subsequently, MD simulations and MM-PBSA analysis were performed to validate the intrinsic atomic interactions and the binding affinities. Furthermore, the internal dynamics in all four protein domains, in presence of drug molecule binding were assessed using essential dynamics and free energy landscape analyses, which were further coupled with conformational dynamics-based clustering studies and cross-correlation analysis to map the regions that exhibit these structural variations. Our comprehensive analysis identified tolcapone, cefprozil, delavirdine and indinavir as potential inhibitors of NS5 MTase, NS5 RdRp, NS3 protease and NS3 helicase functions, respectively. These high-confidence candidate molecules will be useful for developing effective anti-DENV therapy to combat dengue infection.