Disrupting the protein-protein recognition in cancer pathways by molecular modeling.

• Autores: Cristian Obiol Pardo
• Directores de la Tesis: Jaime Rubio Martínez (dir. tes.)
• Lectura: En la Universitat de Barcelona ( España ) en 2008
• Idioma: inglés
• Tribunal Calificador de la Tesis: Juan Jesús Pérez González (presid.), Miguel González Perez (secret.), Fernando Albericio Palomera (voc.), Marta Cascante Serratosa (voc.), Carme Rovira Virgili (voc.)
• Materias:
  • Física
    • Química física
  • Química
    • Bioquímica
      • Farmacología molecular
• Enlaces
  • Tesis en acceso abierto en:  TDX  Dipòsit Digital de la UB 
• Resumen

  • Cancer is the second disease leading cause of death in industrialized countries. Although early detection and more efficient drugs are responsible of the reduction of mortality, several cancers still present difficult treatments and low survival rates. Conventional drugs only exhibit moderate therapeutic index between cancer and normal tissues but recent advances are focused to improve lesstoxic treatments. Hence, new drugs must target specific signaling pathways involved in cell growth and proliferation. Concerning this aim, two mechanism involved in cancer disease, named apoptosis (or programmed cell death) and pentose phosphate pathway, have been selected in this work to search new inhibitors to target crucial proteins of both cell routes.Overexpression of antiapoptotic genes has been correlated with tumor growth and resistance tochemotherapy, thus many efforts have been done to block the activity of XIAP and Survivin, central proteins acting in apoptosis and studied in the present work. Moreover, the two most active proteins detected in both the oxidative and nonoxidative branches of the pentose phosphate pathway, Glucose-6-Phosphate Dehydrogenase (G6PDH) and Transketolase (TKT), have been also selected in this thesis.Molecular Modeling methods, covering topics in protein and peptide recognition, molecular dynamics, pharmacophore generation, database searching, docking and scoring in virtual screening and binding free energy prediction, have been applied with success to discover new active molecules inhibitors of XIAP, Survivin, G6PDH and TKT proteins.