Evaluación de posibles dianas terapéuticas para el cáncer de colon aplicando Pipeline Bioinformático como base para el diseño de fármacos asistido por computador

Abstract

Colon cancer is a common type of malignant tumor in the gastrointestinal tract, accounting for about 13 percent of all tumors. Its development is influenced by epigenetic changes, genetic and environmental factors. However, current methods for diagnosing and treating this disease are often expensive, making access to treatment difficult for many patients. To identify the genes that are expressed or inhibited in colon cancer, differential expression analysis was performed using R. These genes were contrasted with databases such as: OMIM, Malacards, Harmonizome, and KEGG. The most relevant genes are grouped according to their biochemical alteration, with this information biological interaction networks are created through Cytoscape to identify proteins that are altered within the disease process. For the identification of the targets, the DrugBank database was used, through DoGSiteScorer the drugable sites were identified, virtual screening is performed through MTiopenScreen to find possible ligands that present high binding affinity. The interaction networks obtained from STITCH allow the identification of the drug that is linked to the metabolic pathways to analyze the protein-ligand interactions. The drug etoposide was identified, and its pharmacokinetic and toxicity properties are assessed by bioinformatics predictions using QSAR VEGA and pkCSM models. The toxicity and hepatotoxicity were found to be negative, suggesting that this could be a viable candidate for the development of drugs targeting the SMAD2 and CASP9 genes.