Artículos de revistas
Pockets as structural descriptors of EGFR kinase conformations
Fecha
2017-12Registro en:
Hasenahuer, Marcia Anahí; Barletta Roldan, Patricio German; Fernández Alberti, Sebastián; Parisi, Gustavo Daniel; Fornasari, Maria Silvina; Pockets as structural descriptors of EGFR kinase conformations; Public Library of Science; Plos One; 12; 12; 12-2017; 1-17; e0189147
1932-6203
CONICET Digital
CONICET
Autor
Hasenahuer, Marcia Anahí
Barletta Roldan, Patricio German
Fernández Alberti, Sebastián
Parisi, Gustavo Daniel
Fornasari, Maria Silvina
Resumen
Epidermal Growth Factor Receptor (EGFR), a tyrosine kinase receptor, is one of the main tumor markers in different types of cancers. The kinase native state is mainly composed of two populations of conformers: active and inactive. Several sequence variations in EGFR kinase region promote the differential enrichment of conformers with higher activity. Some structural characteristics have been proposed to differentiate kinase conformations, but these considerations could lead to ambiguous classifications. We present a structural characterisation of EGFR kinase conformers, focused on active site pocket comparisons, and the mapping of known pathological sequence variations. A structural based clustering of this pocket accurately discriminates active from inactive, well-characterised conformations. Furthermore, this main pocket contains, or is in close contact with, ≈65% of cancer-related variation positions. Although the relevance of protein dynamics to explain biological function has been extensively recognised, the usage of the ensemble of conformations in dynamic equilibrium to represent the functional state of proteins and the importance of pockets, cavities and/or tunnels was often neglected in previous studies. These functional structures and the equilibrium between them could be structurally analysed in wild type as well as in sequence variants. Our results indicate that biologically important pockets, as well as their shape and dynamics, are central to understanding protein function in wild-type, polymorphic or disease-related variations.