Protein dynamics studied by coarse-grained and atomistic theoretical approaches

• Autores: Laura Orellana Ramírez
• Directores de la Tesis: Matteo Palassini (dir. tes.), Modesto Orozco López (dir. tes.)
• Lectura: En la Universitat de Barcelona ( España ) en 2014
• Idioma: inglés
• Tribunal Calificador de la Tesis: Richard Lavery (presid.), Ugo Bastolla (secret.), Francesco Luigi Gervasio (voc.)
• Materias:
  • Física
    • Química física
  • Química
    • Bioquímica
      • Biología molecular
      • Bioquímica física
  • Ciencias de la vida
    • Biofísica
• Enlaces
  • Tesis en acceso abierto en: Dipòsit Digital de la UB
• Resumen

  • BACKGROUND: Protein structure, dynamics and function, are inseparable in order to understand the mechanisms of Life at the molecular level. From the structure comes dynamics, and from dynamics many, if not all, protein functions. Usually functional motions operate at timescales and conditions that are far beyond the limits of current experimental techniques. GOALS AND METHODOLOGY: In order to address rationally the complex interplay between these three aspects of proteins, we will deepen into and compare both coarse-grained and atomistic simulation methods. RESULTS: In the first part of this thesis, coarse-grained Elastic Network Models are compared with Molecular Dynamics and experimental results in order to obtain a more accurate representation of protein dynamics. We propose a novel ENM algorithm rendering results close to atomistic simulation methods. In the second part of the thesis, the novel method is applied to detect dynamical hot spots in a relevant biological system, the tyrosine kinase receptor HER1, revealing why mutations are accumulated at discrete structural regions. Near-microsecond long simulations of the mutant hot spots are presented which unravel a long-sought intermediate in a large-scale functional transition. Finally, we explore more widely the validity of the ENMs potentials, and its relations with complex networks approaches, using a fast internal coordinates algorithm. The analysis of the parameter space for ENMs demonstrate that the performance of these methods is closely related to network properties of the protein structures, which also highlights how evolution might have selected certain folds to display particular collective motions, and why deleterious mutations hit the residues transferring most information. CONCLUSIONS: The main conclusions of this thesis are the following: 1) The local topology of proteins, not only determines shapes but dynamics,; 2) Long-range contact dictate the equilibrium between different motions; 3) Perturbations such as mutations can shift this equilibrium and affect protein functions, causing disease