Classifying kinase conformations using a machine learning approach.

ABSTRACT:

Background

Signaling proteins such as protein kinases adopt a diverse array of conformations to respond to regulatory signals in signaling pathways. Perhaps the most fundamental conformational change of a kinase is the transition between active and inactive states, and defining the conformational features associated with kinase activation is critical for selectively targeting abnormally regulated kinases in diseases. While manual examination of crystal structures have led to the identification of key structural features associated with kinase activation, the large number of kinase crystal structures (~3,500) and extensive conformational diversity displayed by the protein kinase superfamily poses unique challenges in fully defining the conformational features associated with kinase

SUBMITTER: McSkimming DI 

PROVIDER: S-EPMC5290640 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature