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http://hdl.handle.net/10609/146366
Title: | Búsqueda de compuestos moduladores de STAU1 mediante herramientas computacionales para su aplicación en la distrofia miotónica tipo I |
Author: | López Martínez, Andrea |
Tutor: | Fajardo, Emmanuel |
Others: | Calvet Liñán, Laura |
Abstract: | Myotonic dystrophy type I is a neurodegenerative disease that affects 1 in 8000 people. It is currently untreatable and although the most appropriate therapeutic strategies for its cure would be gene editing techniques, these are not yet ready to reach the clinic. This makes molecules from pharmaceutical repositioning attractive therapies for their short-term applications. The aim of this work is to search for compounds that can bind to the STAU1 protein, overexpressed in DM1 patient samples, to restore the signaling pathways altered by its deregulation. At the methodological level, protein modeling servers have been used, binding sites have been identified and two virtual screens have been performed, one based on the structure and the other based on a known ligand. In this work we have obtained two models of the STAU1 structure, we have checked the binding of a ligand defined in one of the partial structures and we have obtained two different databases on which to perform a docking process. From the docking, we have obtained three different lists in which we have more than 1500 compounds to study in future studies. In conclusion, we can confirm that the described methodology has allowed us to perform a structure-based and a ligand-based screening and to obtain a set of compounds that are expected to bind with high affinity to STAU1. |
Keywords: | structural modeling virtual screening |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | 21-Jun-2022 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Trabajos finales de carrera, trabajos de investigación, etc. |
Files in This Item:
File | Description | Size | Format | |
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andrealopezmar29TFM0622memoria.pdf | Memoria del TFM | 4,04 MB | Adobe PDF | View/Open |
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