Order in Disorder: Context-dependent strategies fo.. (ORDER IN DISORDER)
Order in Disorder: Context-dependent strategies for integrating peptide-mediated interactions
(ORDER IN DISORDER)
Start date: Dec 1, 2012,
End date: Nov 30, 2017
Peptide-mediated protein interactions are emerging as key regulators of many important regulatory processes in the cell. Short motifs, usually embedded into disordered regions of the protein, interact with specific sets of protein partners in a transient way and allow efficient and malleable propagation of signals towards their targets. While regular protein interactions have been intensively studied, many aspects of peptide-mediated interactions have not yet been elucidated.The aim of this proposal is to improve our understanding of the basic strategies that are employed by peptide-mediated interactions to achieve different types of outcomes in different settings, and how the context of the peptide influences this outcome. Towards this aim, we will establish two complementary strategies, namely (1) a significant extension of our modeling tools for peptide-protein complex structures that will allow modeling of effects of the surrounding flexible linker, and (2) the establishment of an experimental lab that will allow us to independently validate and complement our modeling results. Targeted modulation of peptide affinity, specificity, and linker length and sequence, using both computational design as well as experimental in vitro evolution, will dissect different contributions to the functional outcome of a peptide-mediated interaction within its context. We can thus study in detail the interplay of the interaction with additional features in the linker sequence, such as posttranslational modification sites, as well as additional peptide binding motifs and interactions.Interactions mediated by intrinsically disordered regions are omnipresent. Their accurate characterization, modeling and manipulation holds therefore many promises towards applications for the development of better drugs and basic insights for better fundamental understanding of the underlying basis of regulatory interactions.
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