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Predicting Protein Conformational Disorder and Disordered Binding Sites

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2449))

Abstract

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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  1. Ketty C. Tamburrini and Giulia Pesce contributed equally to this work.

Authors and Affiliations

  1. Aix Marseille Univ, CNRS, Architecture et Fonction des Macromolécules Biologiques, AFMB, UMR 7257, Marseille, France

    Ketty C. Tamburrini, Giulia Pesce, Juliet Nilsson, Frank Gondelaud & Sonia Longhi

  2. Centre de Recherche en Biologie cellulaire de Montpellier, UMR 5237, CNRS, Université Montpellier, Montpellier, France

    Andrey V. Kajava

  3. INRAE, Aix Marseille Univ, Biodiversité et Biotechnologie Fongiques (BBF), UMR 1163, Marseille, France

    Ketty C. Tamburrini & Jean-Guy Berrin

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  1. University of Pavia, Pavia, Italy

    Oliviero Carugo

  2. Genome Institute and Bioinformatics Institute, Singapore, Singapore

    Frank Eisenhaber

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Tamburrini, K.C. et al. (2022). Predicting Protein Conformational Disorder and Disordered Binding Sites. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 2449. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2095-3_4

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