Advances in Computational Biology of Intrinsically Disordered Proteins

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 453

Special Issue Editor


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Guest Editor
Department of Biology, McGill University, Montreal, QC, Canada
Interests: protein evolution; intrinsic disorder; compositional bias; prions; protein function

Special Issue Information

Dear Colleagues,

Bioinformatical and simulational analysis has been a key component of efforts to understand the functional and biophysical characteristics of intrinsic disorder in proteins. This Special Issue aims to bring together diverse research focuses in the computational analysis of intrinsic disorder in proteins, that produce insights and hypotheses that are actionable for future research. It is not limited to purely computational work, but may include research involving laboratory experiment.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

  • Prediction of intrinsic disorder and its subtypes
  • Analysis of the evolution of intrinsic disorder
  • Insights into the role of compositional bias and ‘low-complexity’ sequence
  • Analysis of the function of intrinsically-disordered regions
  • Simulational analysis of intrinsic disorder
  • Computational analysis of prions
  • Computational case studies of proteins and protein families with intrinsic disorder

In this Special Issue, original research articles and reviews are welcome. I look forward to receiving your contributions.

Dr. Paul Harrison
Guest Editor

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Keywords

  • intrinsic disorder
  • compositional bias
  • prions
  • protein annotation
  • protein simulation

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Published Papers (1 paper)

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Research

14 pages, 2453 KB  
Article
Patterny: A Troupe of Decipherment Helpers for Intrinsic Disorder, Low Complexity and Compositional Bias in Proteins
by Paul M. Harrison
Biomolecules 2025, 15(9), 1332; https://doi.org/10.3390/biom15091332 - 18 Sep 2025
Viewed by 155
Abstract
Intrinsically disordered regions (IDRs) are sometimes considered parts of the ‘dark proteomes’, i.e., protein parts that have been largely under-appreciated, as are the overlapping phenomena of low-complexity or compositionally biased regions (LCRs/CBRs). Experimentalists and computationalists alike are still learning how to decrypt the [...] Read more.
Intrinsically disordered regions (IDRs) are sometimes considered parts of the ‘dark proteomes’, i.e., protein parts that have been largely under-appreciated, as are the overlapping phenomena of low-complexity or compositionally biased regions (LCRs/CBRs). Experimentalists and computationalists alike are still learning how to decrypt the functionally meaningful features of such regions. Here, I report the creation of the support troupe Patterny to aid such protein cryptanalysis. The current troupe members are named Blocky, Bandy, Moduley, Repeaty, and Runny. To discern important features, protein regions are compared to ideal assortments wherein everything is sampled proportionally and dispersed randomly. Blocky discerns the segregation of amino-acids by type, and scores them for it. Bandy is focused on picking out compositional bands and calculating their evenness. Moduley labels the boundaries of optimized compositional modules (‘CModules’) and other possible boundary sets for compositionally biased regions. Repeaty concisely summarizes repetitiveness using an information entropy of amino-acid interval diversity. Runny enumerates homopeptide content and assesses its significance. Both original whole sequences and CModules from Moduley, are fed into the other Patterny members. Patterny is applied to some illustrative sample data from yeast proteome and the DISPROT database. It is available at Github, and might aid those aiming to intensify light-shedding and hypothesis generation for protein regions with function encoded in a distributed manner, such as IDRs and LCRs/CBRs more generally. Full article
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