Mathematical modeling of oligomerization and biased signaling of g-protein-coupled receptors

• Autores: Bin Zhou
• Directores de la Tesis: Jesus Giraldo Arjonilla (dir. tes.)
• Lectura: En la Universitat Autònoma de Barcelona ( España ) en 2018
• Idioma: español
• Tribunal Calificador de la Tesis: Francisco Ciruela Alférez (presid.), Josefa Sabriá i Pau (secret.), Francisco Javier Luque Garriga (voc.)
• Programa de doctorado: Programa de Doctorado en Neurociencias por la Universidad Autónoma de Barcelona
• Materias:
  • Química
    • Bioquímica
      • Farmacología molecular
• Enlaces
  • Tesis en acceso abierto en:  TESEO  TDX 
• Resumen

  • G-protein-coupled receptors (GPCRs) play very important roles in a great variety of biological processes. They are located in the membrane and mediate the signaling pathways in the cell. It is widely accepted that these receptors often form oligomers which may have significant physiological functions. In addition, one GPCR may act at several downstream signaling pathways, and these pathways can be differentially activated by the ligand of the receptor. The present thesis tries to provide new mathematical tools for the understanding of these phenomena. There are two new mathematical models for GPCR oligomerization and one novel framework for biased signaling in the present thesis.

    Firstly, a new mathematical model is proposed for the receptor heterodimer. This heterodimer model can be employed to dissect the impact of the two ligands which are respectively bound to the two protomers in the heterodimer on the downstream signaling pathways of the heterodimer. Secondly, a new mathematical model is presented for the receptor homodimer. This homodimer model can be utilized to analyze a wide range of dose-response curves of the ligands binding to the receptor homodimer and the biased signaling which is dependent on ligand concentration. Thirdly, a novel conceptual framework is put forward for the dissection of biased signaling. This framework provides new insights on biased signaling and novel quantitative scales for system bias, ligand bias, and signaling bias.

    To sum up, the new mathematical models and framework are based on some existing operational models for GPCR signaling which have been widely applied to the study of drug action. Therefore, it is feasible to use the rationale and computational tools shown in the present thesis to overcome the difficulties in data analysis which are caused by GPCR oligomerization and biased signaling.