FuzPred: a web server for the sequence-based prediction of the context-dependent binding modes of proteins

Author:

Hatos Andras12345ORCID,Teixeira João M C1,Barrera-Vilarmau Susana1,Horvath Attila6,Tosatto Silvio C E1ORCID,Vendruscolo Michele7ORCID,Fuxreiter Monika18ORCID

Affiliation:

1. Department of Biomedical Sciences, University of Padova , Padova , Italy

2. Department of Oncology, Lausanne University Hospital , Lausanne 1011 , Switzerland

3. Department of Computational Biology, University of Lausanne , Lausanne 1015 , Switzerland

4. Swiss Institute of Bioinformatics , Lausanne1015 , Switzerland

5. Swiss Cancer Center Leman , Lausanne 1011 , Switzerland

6. John Curtin School of Medical Research, The Australian National University , Acton , Australia

7. Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge , UK

8. Department of Physics and Astronomy, University of Padova , Padova , Italy

Abstract

Abstract Proteins form complex interactions in the cellular environment to carry out their functions. They exhibit a wide range of binding modes depending on the cellular conditions, which result in a variety of ordered or disordered assemblies. To help rationalise the binding behavior of proteins, the FuzPred server predicts their sequence-based binding modes without specifying their binding partners. The binding mode defines whether the bound state is formed through a disorder-to-order transition resulting in a well-defined conformation, or through a disorder-to-disorder transition where the binding partners remain conformationally heterogeneous. To account for the context-dependent nature of the binding modes, the FuzPred method also estimates the multiplicity of binding modes, the likelihood of sampling multiple binding modes. Protein regions with a high multiplicity of binding modes may serve as regulatory sites or hot-spots for structural transitions in the assembly. To facilitate the interpretation of the predictions, protein regions with different interaction behaviors can be visualised on protein structures generated by AlphaFold. The FuzPred web server (https://fuzpred.bio.unipd.it) thus offers insights into the structural and dynamical changes of proteins upon interactions and contributes to development of structure-function relationships under a variety of cellular conditions.

Funder

AIRC

Publisher

Oxford University Press (OUP)

Subject

Genetics

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