Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/133729
Title: Análisis bioinformático de la expresión proteica en la COVID-19: interacción entre las células huésped infectadas, el SARS-COV2 y posibles dianas terapéuticas
Author: Tordera Mora, José María
Tutor: Franco Serrano, Luis  
Others: Maceira, Marc  
Abstract: The COVID-19 pandemic has deeply impacted the sociosanitary healthcare systems as well as becoming a new challenge for the scientific community in terms of research about SARS-CoV2 and its interplay with the human host. The existance of previous viral infectious models like SARS-CoV1 and MERS has enabled making comparisons from a protein level, mainly with some components of the Spike S protein, a protein capable of establishing communication with host cell membrane receptors and activating the viral infective cycle. The encountered homology in the sequence of some S protein subunits among the SARS-CoV as well as the prediction of similar potential epitope regions in the three viruses has focused the physiopathological research of the disease in the interaction between the virus and host cells. Not only ACE2 receptor but other alternative ways of interaction such as CD147 and CD26/DPP-4 have been described. Also has been analyzed the host cell ability to activate the S protein through different proteases, making possible the viral entry. It is noteworthy the description of multifunctional proteins in the virus and host cells that may enhance immune responses according to the function being adopted. The different proportion and combination in the protein expression of the receptors and proteases in the epithelial airway cells and in the immune system, as noted in the protein expression studies from in vitro cellular models, could be detrimental to better define the endotypes and phenotypes of patients, with potential clinical and therapeutic repercussions.
Keywords: coronavirus
proteomics
type 2 pneumocyte
innate immunity
T lymphocyte
Document type: info:eu-repo/semantics/masterThesis
Issue Date: 18-Jul-2021
Publication license: http://creativecommons.org/licenses/by-nc-nd/3.0/es/  
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