“development and optimization of high-performance computational tools for protein-protein docking

  1. JIMÉNEZ GARCÍA, BRIAN
Dirigée par:
  1. Juan Fernández Recio Directeur

Université de défendre: Universitat de Barcelona

Fecha de defensa: 21 juillet 2016

Jury:
  1. Pablo Chacon Montes President
  2. Josep Lluis Gelpi Buchaca Secrétaire
  3. Raphael Guerois Rapporteur

Type: Thèses

Teseo: 428494 DIALNET lock_openTDX editor

Résumé

Development and optimization of high-performance computational tools for protein-protein docking Computing has pushed a paradigm shift in many disciplines, including structural biology and chemistry. This change has been mainly driven by the increase in performance of computers, the capacity of dealing with huge amounts of experimental and analysis data and the development of new algorithms. Thanks to these advances, our understanding on the chemistry that supports life has increased and it is even more sophisticated that we had never imagined before. Proteins play a major role in nature and are often described as the factories of the cell as they are involved in virtually all important function in living organisms. Unfortunately, our understanding of the function of many proteins is still very poor due to the actual limitations in experimental techniques which, at the moment, they can not provide crystal structure for many protein complexes. The development of computational tools as protein-protein docking methods could help to fill this gap. In this thesis, we have presented a new protein-protein docking method, LightDock, which supports the use of different custom scoring functions and it includes anisotropic normal analysis to model backbone flexibility upon binding process. Second, several interesting web-based tools for the scientific community have been developed, including a web server for protein-protein docking, a web tool for the characterization of protein-protein interfaces and a web server for including SAXS experimental data for a better prediction of protein complexes. Moreover, the optimizations made in the pyDock protocol and the increase in performance helped our group to score in the 5th position among more than 60 participants in the past two CAPRI editions. Finally, we have designed and compiled the Protein-Protein (version 5.0) and Protein-RNA (version 1.0) docking benchmarks, which are important resources for the community to test and to develop new methods against a reference set of curated cases.