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Title: Reposicionamiento de fármacos en enfermedades mitocondriales
Author: Serrano Lorenzo, Pablo
Director: Cánovas Izquierdo, Javier Luis  
Tutor: Enciso Carrasco, Marta
Keywords: drug repurposing
machine learning
mitochondrial diseases
Issue Date: 8-Jan-2020
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: Mitochondrial diseases (MD) are a group of genetic disorders characterized by defects in the oxidative phosphorylation system (OXPHOS) or other metabolic disorders involving mitochondria. Currently there is no treatment for the majority of these diseases, so drug repositioning is an interesting and promising way to discover new therapies. In the present work a methodology has been developed, using Machine Learning (ML) techniques, which allows the prioritization of drugs with potential effects in MD. Through a ML/ML tandem use of two models, one for searching drugs with chemical and structural properties similar to the drugs currently used in MD, and another model for the prediction of new mitochondrial drug-target interactions, a total of 68 drugs (not present in the original set of drugs for model training) were prioritized. After a review of the 68 prioritized drugs, research studies have been found about seven drugs (D-Cysteine, Malic Acid, L-Glutamine, Folic acid, Beta-Alanine, Glycine and Beta-Amino Isobutyrate) that supports their potential beneficial effect on mitochondrial function and one work has been found about one prioritized drug (D-Serine) in which a possible detrimental effect on mitochondrial activity is described. Overall we concluded that the set of 68 prioritized drugs could contain new drugs with a potential beneficial effect for the treatment of MD.
Language: Spanish
Appears in Collections:Bachelor thesis, research projects, etc.

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