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Book Sections Year : 2022

Predicting Protein Conformational Disorder and Disordered Binding Sites

Ketty Tamburrini
  • Function : Author
Giulia Pesce
  • Function : Author
Juliet Nilsson
  • Function : Author
Frank Gondelaud
  • Function : Author
Andrey Kajava
  • Function : Author
Jean-Guy Berrin
  • Function : Author


In the last two decades it has become increasingly evident that a large number of proteins adopt either a fully or a partially disordered conformation. Intrinsically disordered proteins are ubiquitous proteins that fulfill essential biological functions while lacking a stable 3D structure. Their conformational heterogeneity is encoded by the amino acid sequence, thereby allowing intrinsically disordered proteins or regions to be recognized based on their sequence properties. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental for delineating boundaries of protein domains amenable to crystallization. This chapter focuses on the methods currently employed for predicting protein disorder and identifying intrinsically disordered binding sites.
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hal-03834097 , version 1 (28-10-2022)



Ketty Tamburrini, Giulia Pesce, Juliet Nilsson, Frank Gondelaud, Andrey Kajava, et al.. Predicting Protein Conformational Disorder and Disordered Binding Sites. Data Mining Techniques for the Life Sciences, 2449, Springer US, pp.95-147, 2022, Methods in Molecular Biology, ⟨10.1007/978-1-0716-2095-3_4⟩. ⟨hal-03834097⟩
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