Estudios bioinformáticos para la identificación de posibles dianas terapéuticas en la enfermedad de la Diabetes Mellitus tipo 2 (T2DM)

Abstract

The search for therapeutic targets for the disease type 2 diabetes mellitus is based on computer-aided drug development through molecular concentration analysis and virtual screening in disease databases. The identification of the study gene requires analysis in different databases such as MalaCards, OMIM, Harmonizome and KEGG to validate the information on the genes involved in the disease. Thus, the genes with the greatest connections are chosen and grouped according to their genetic dysfunction to create biological networks and validated in the DrugBank database. Subsequently, an analysis of the metabolic pathway taken from KEGG that connect the target genes that maintain the identified mutation is performed and the three-dimensional structures are used to evaluate the domains plus drugs. Molecular coupling and screening simulations are then carried out, considering the compounds with the highest affinity for IRS-1, and finally the toxicity of the drugs is analyzed. QSAR models show that Zosuquidar, Rimacalib, Uk432097, Mosapramine, Devazepide and Setipiprant are the safest ligand compounds in toxicity analyses. The present study is based on the identification of the genes most associated with T2DM and the search for possible therapeutic targets through bioinformatics applied to computer-assisted drug design. The results obtained can be used for subsequent research studies to increase the therapeutic spectrum for T2DM or other metabolic degenerations.