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Intrinsically Disordered Proteins

Intrinsically Disordered Proteins

Intrinsically disordered proteins are a group of proteins that do not fold into specific three-dimensional structures. Their structural flexibility allows them to complement ordered proteins to perform functions that are inaccessible to rigid structures. They are more common in eukaryotes than prokaryotes and may either be exclusively intrinsically disordered or hybrid proteins, consisting of a mix of ordered and disordered regions. The absence of a rigid structure in these proteins can be...

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Mapping Dysfunctional Protein-Protein Interactions in Disease

Mapping Dysfunctional Protein-Protein Interactions in Disease

Published on: October 24, 2025

Quantitative proteome-based guidelines for intrinsic disorder characterization.

Michael Vincent¹, Mark Whidden¹, Santiago Schnell²

¹Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA.

Biophysical Chemistry

|April 17, 2016

Summary

This summary is machine-generated.

This study establishes crucial statistical guidelines for assessing intrinsically disordered proteins (IDPs). It provides expected values and cutoffs for disorder features across eukaryotic proteomes, aiding in objective disorder analysis.

Keywords:

Bioinformatics Computational biology Intrinsically disordered protein Protein sequence Protein structure Proteomics

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Published on: November 15, 2017

Area of Science:

Biochemistry
Computational Biology
Proteomics

Background:

Intrinsically disordered proteins (IDPs) lack stable structures but are vital for cellular signaling and regulation.
Computational prediction algorithms are used to characterize protein disorder from amino acid sequences.
Existing large-scale studies lack standardized proteome-based guidelines for objective disorder assessment.

Purpose of the Study:

To develop quantitative, statistically rigorous guidelines for characterizing intrinsic disorder in proteins.
To establish expected values and percentile cutoffs for various disorder features in eukaryotic proteomes.
To define novel algorithm- and proteome-specific thresholds for evaluating disordered regions based on sequence length.

Main Methods:

Employed a rigorous non-parametric statistical approach for quantitative disorder feature characterization.
Utilized multiple ab initio disorder prediction algorithms based on physicochemical principles.
Analyzed ten eukaryotic proteomes to derive descriptive statistical guidelines.

Main Results:

Provided expected values and percentile cutoffs for numerous disorder features across ten eukaryotic proteomes.
Established novel threshold values for assessing the significance of continuous disordered regions by sequence length.
Developed guidelines specific to prediction algorithms and proteomes for improved disorder interpretation.

Conclusions:

The presented guidelines enhance the objective assessment of intrinsic disorder in proteins.
These findings facilitate more accurate interpretation of disorder content and predictions from a proteomic perspective.
The study offers a robust framework for understanding the prevalence and characteristics of protein disorder.