Anàlisi bioinformàtic de les interaccions i selectivitat d’inhibidors dels receptors Sigma 1 i Sigma 2

Abstract

Sigma 1 (S1R) and Sigma 2 (S2R) receptors are proteins involved in various functions such as intracellular calcium regulation, oxidative stress regulation, and cellular signalling, which are associated with pathologies where these biological processes are altered, such as neurodegenerative diseases and cancer. For this reason, Sigma 1 and Sigma 2 receptors are the main focus of many studies and biological assays aimed at better understanding the molecular functioning of these potential therapeutic targets to develop new treatments. Additionally, the study and design of new ligands that can regulate these receptors and therefore be used in the treatment of pathologies are of great importance. One key aspect is the design of selective inhibitors for each of the receptors. Despite the advances in recent years, there are still no sufficiently selective inhibitors for S1R and S2R. The objective of this work is to use and validate bioinformatics tools such as molecular docking to study Sigma 1 and Sigma 2 receptors both for their structural characteristics and their binding capacity and selectivity for ligands, providing a solid knowledge base from an emerging perspective like bioinformatics. To do this, 10 compounds with known inhibitory activity for each of the receptors have been selected and docking has been performed with the crystallographic structures obtained from the PDB database, with codes 5HK1 for Sigma 1 and 7M95 for Sigma 2. This way, the interactions and affinity values that allowed the study of the receptors and ligands from the bioinformatics program Chimera and the Dock6 program for docking are predicted. The results have reaffirmed the information already known at the experimental level and the importance of residues Asp 126 and Glu 172 of Sigma 1 and residue Asp 29 in Sigma 2 for hydrogen bond formation with ligands. Additionally, they have indicated that most compounds show higher selectivity for Sigma 2 compared to Sigma 1. However, more advanced analysis is needed to determine the chemical and structural particularities that cause this preference. These bioinformatics tools can be used in the future for the design of new selective inhibitors for these receptors