Identificación de posibles dianas terapéuticas en Alzheimer utilizando pipeline bioinformático combinado para aplicarlas al diseño de fármacos asistidos por computadora

Abstract

Bioinformatics has a potential biotechnological use because it allows the study of genetically complex diseases using different tools. The aim of this project was to analyze transcriptomic data related to Alzheimer's disease (AD) for the identification of potential therapeutic targets and computer-aided drug design. This was done through the application of a multilevel analysis of biological interaction networks, molecular docking, and evaluation of the pharmacokinetic properties of selected drugs. The analyses indicated a total of 507 and 478 genes with high and low expression, respectively, present in brains with different stages of AD. The results of the protein-protein interaction and miRNA-miRNA network analysis identified only one biomarker, hsa-mir-34a-5p, for the diagnosis of AD and asymptomatic AD in cancer patients. Survival analysis revealed that CDK6 and CD44 are potential therapeutic targets for AD. Additionally, the established pipeline also identified CCND1 as another potential therapeutic target. The drug-gene interaction networks reflected four potential drug candidates for repurposing in the treatment of AD: Estradiol, Trichostatin A, Doxorubicin, and Dorsomorphin. Molecular docking demonstrated that Estradiol and Trichostatin A can inhibit the CCND1 protein, while Dorsomorphin induces inhibition of CDK6, because of their free energy of binding is lower than the reference. The evaluation of pharmacokinetic properties indicated that only Trichostatin A can be used for the treatment of AD in humans.