Identificación de posibles dianas terapéuticas para la Enfermedad de Parkinson mediante la aplicación de métodos in silico

Abstract

In the exploration of possible therapeutic targets to treat Parkinson's disease through computational chemistry, drug design using docking tools is employed. This process is based on the analysis of genes such as LRRK2, where the main objective is to identify the most optimal binding sites in terms of energetic stability, considering them as possible ideal locations for protein action. In this context, virtual screening makes it possible to verify whether the complexes formed between the protein and the ligand represent a potential avenue for the investigation of a disease-specific drug. The analysis of several disease databases, such as MalaCards, Harmonizome, KEGG, OMIM, Unitpro, Disgenet, GeneReviews and Orphanet, has allowed the identification of key genes in Parkinson's disease. These genes are of great importance since, among numerous candidates, those with similarities in molecular processes and common dysfunctions were selected. The grouping and categorization of these genes facilitated the creation of a biological network of interactions using Cytoscape, accompanied by a bibliographic investigation of the metabolic pathways and the relationships between them, thanks to this approach, mutations in the LRRK2 gene were identified to then search for possible druggable sites in this molecule, with the aim of forming protein-ligand complexes. Thus, existing drugs or ligands can be analyzed by screening and evaluation of toxicological properties. In this bioinformatics study of therapeutic targets, I point out that the main ligand Losulazine presents a higher affinity of pharmacological interaction with the LRRK2 gene.